Trying to Replicate Physical Experiments

Referring back to the concept of an analysis plan discussed in the previous article, it’s important to decide if you’re trying to analyze the in-situ performance of your product out in the wild or replicate a physical experiment, as these often have very different requirements.

A frequent source of error is due to users trying to match the results of some test or physical experiment by using boundary conditions that would be more appropriate for the performance of the product under typical usage.

Consider the aerodynamics of a car. Replicating a wind tunnel test may involve a stationary model in a chamber of known size. Replicating the real use case of the car driving down the road may require incorporating effects such as wheel rotation, the relative motion of the ground under the car in an infinitely large open environment.

Another example is for automotive intake accessories or cylinder head geometry as in the figure below. There is a significant difference between trying to simulate the in-situ performance which could require time-dependent flow conditions representing the various strokes of the engine cycle, versus replicating a steady-state “flow bench” test where a fixed amount of vacuum is pulled to determine the resulting flow rate.

Figure 1. Replicating a flow bench test for an intake manifold.

Physical experiments usually only output results at a few key locations, while CFD provides output everywhere. Instrumentation usually involves additional test fixtures and rigging that may influence the device’s performance. If you’re attempting to replicate a physical experiment, representations of these fixtures should likely be included in the analysis. Also ensure that you probe the virtual measurements or define goals in the exact location of any physical test sensors.

Steady State vs Transient Analysis

When developing an analysis plan for thermal problems, it’s important to consider the “thermal mass” of the device and the time period of its intended operation. When a device has a low thermal mass and a long period of intended operation, a steady-state analysis makes a lot of sense. But what if the device has a heavy mass and only operates for short bursts? A steady-state analysis may provide a too-conservative and unrealistic result.

Steady-state analyses don’t reveal how long it takes for peak temperatures to be achieved. The engineer may think temperatures have stabilized quickly but there is no way of knowing whether those temperatures took 30 seconds, 30 minutes or 30 hours to reach a steady state.

When the thermal mass of the part is significant compared to the heat powers and time scale, it can be worth running a transient or time-dependent analysis. While the solve times of a transient analysis are much greater, they can be reduced significantly by taking advantage of solver options such as nested iterations, which perform sub-iterations for each solver timestep and allow specification of a much larger manual timestep size.

Figure 2. Transient thermal natural convection analysis.

In the transient thermal analysis above, the device takes approximately two hours to reach a temperature within a few percent of the steady-state value.

If you run a steady-state analysis and observe fluctuating goals or residual values, it’s possible that your problem may be “unsteady” in nature. This can occur due to vortex shedding or other dynamic effects that can spontaneously appear in the fluid flow at certain Reynolds numbers.

The more unsteady a problem is, the less accurate a steady-state solution will be. Even if you are after an averaged value as an output, it’s best in this case to switch to a transient solver.

To extract a steady-state value from an unsteady transient problem, you can export results from your monitored goals/sensors into Excel or other software and average the results over some relatively steady period.

Figure 3. Configuring averaged results for a transient study.

Alternatively, you may be able to specify in Calculation Control Options “averaged” results for a specific time interval. This will allow viewing time-averaged contour plots and other outputs that should be similar visually to the results you would expect from a steady-state study but with the confidence that the physics are properly supported.

Choosing Internal vs External Analysis

We commonly think of “internal” analyses for problems like manifolds and pipe flow and “external” analyses for flow over a vehicle. But the reality for many products is that the choice is not so obvious and although limiting the calculation to the internal region will almost always solve faster, it may neglect important factors about the outside environment.

Figure 4. Venting of a firebox as internal (left) and external.

If working with a room-scale or larger product, it may be desirable to see flow patterns through inlets or outlets and how they can interact with other geometry such as the floor or other obstructions.

For enclosures, if the model is too difficult to prepare as “water-tight,” we can use an external analysis as a workaround which allows the simulation of leakage through any small openings.

Figure 5. External analysis of an electronics enclosure with leakage from uncapped openings.

For problems where an internal analysis makes sense but there are still important effects to represent around the inlet and outlet, a balance can be achieved by creating a more representative inlet geometry shape. An example would be a hemispherical cap, which helps approximate the inlet air flow direction for devices that feature a rounded opening or velocity stack.

Figure 6. Hemispherical inlet on an internal analysis.

Extending geometry away from inlets and outlets can also help minimize any artificial effects imposed by boundary conditions. Guidelines for CFD typically recommend the length of these extensions in some multiple of the pipe diameter (three times diameter, six times diameter, etc.)

Figure 7. Extended inlets and outlets on a pump.

If you intend to neglect the frictional losses from these extended inlets, then be sure to specify an ideal wall condition on the inner faces.

Unrealistically High Heat Powers

For electronics cooling analysis specifically, a common issue seen is improper definition of the heat powers of electronic components.

Avoid confusing the absolute power rating with dissipated heat power. This can apply to power supplies, inverters, DC converters, etc. The waste heat for these could be estimated by multiplying the power rating by the efficiency – for a 300 W rated power supply that is 90% efficient, we could estimate about 30 W of waste heat that could be applied as an equivalent heat source within the CFD analysis. Applying the 300 W condition would result in some very high temperatures. Light emitting devices like LEDs also emit a portion of their energy as visible light so it’s important to apply their efficiency as well.

A trickier issue is understanding the duty cycle of various components. For many electronics, it may be unlikely that every component on the board will be operating at its maximum rated thermal power continuously 100% of the time. Detailed simulation of duty cycle can be carried out by cycling heat power on and off in a transient analysis but it is more common in practice to overlook minor transient fluctuations in temperatures and instead, simply scale down the heat powers by an appropriate factor.

Neglecting Thermal Radiation

Before neglecting thermal radiation altogether, it’s important to determine whether radiation has only a limited influence on your device’s thermal performance. For forced convection (fan or liquid cooled) electronics devices, the heat transfer tends to be dominated by convection and it is common to neglect thermal radiation.

While conductive and convective heat transfer rates are both proportional to linear difference in temperature, the radiative heat transfer rate is dependent on the difference of each body’s absolute temperature raised to the fourth power. This means that at higher temperature differences and higher absolute temperatures the effects of radiative heat transfer become much more significant.

For passively-cooled electronic devices that rely on natural convection, radiation can be worth investigating. Incorporating radiative heat transfer into your analysis would also be a requirement to analyze effects of different surface finishes and coatings such as black anodize which are known to have high emissivity values.

A quick way to investigate the effects of thermal radiation would be to duplicate your study and enable radiation, observing both the changes in temperature and heat transfer rate due to these newly included effects.

Figure 8. A flux plot showing heat transferred by radiation and convection.

The Flux plot in SOLIDWORKS Flow Simulation is a method to quickly filter by high power components and see where the heat is going. It’s also a useful tool to catch setup issues like lack of contact between components that should be conducting heat to each other.

Alternatively, investigation of radiation can be performed by a quick hand calculation. Incorporating temperatures obtained from your original analysis and measurements of external surface area should give a good idea of whether or not the radiative heat transfer will be significant factor for your problem.

Unsupported Physics

For problems beyond simple thermal and fluid flow, it’s important to ensure your CFD package supports the relevant physics.

For example, consider problems that involve the coupled motion of bodies with fluid flow or other effects such as “free surface” liquid/gas boundaries.

SOLIDWORKS Flow Simulation has the “free surface” functionality which can be enabled which uses the volume of fluid approach to solve simple problems involving sloshing or other behaviors. It also supports rotating components through the definition of rotating regions but doesn’t support any other type of body motion such as reciprocating or oscillating components. It also doesn’t support surface tension or capillary action.

Figure 9. Coupled body motion in SIMULIA XFlow.

For arbitrary motion of bodies with multiple degrees of freedom, coupled two-way FSI and more powerful and varied free surface methods, SIMULIA XFlow and SIMULIA Fluid Dynamics Engineer each have unique advantages.

Figure 10. Mixing tank with headspace in SIMULIA XFlow.

If your problem hinges on chemical reactions, combustion or phase change, you will want to find a solver that can tackle those effects.

Conclusion

It’s easier than ever to use CAD-embedded CFD to predict the performance of your product, with tools like SOLIDWORKS Flow Simulation making the setup process very straightforward.

While it still may require significant research and investment to build a very high accuracy simulation model (the saying, “getting the last 10% takes 90% of the effort” comes to mind), avoiding the mistakes in this article should help you achieve a level of accuracy sufficient to make design decisions and avoid some of the most common pitfalls.

Start by planning out the analysis with defined assumptions, inputs and outputs, then carefully choose where you place your virtual sensors or goals. Ensure your parameters of interest are solved through to their convergence and check that your mesh is adequate. Step back and look at the problem you are trying to solve, and determine if there are any changes required to match a physical experiment or to make sure the proper physics are incorporated.

Lastly, if you aren’t sure if you should make a certain assumption, use a certain approach or just how to proceed in general – reach out to your colleagues or your software provider for assistance! Sharing what you’ve tried so far and any documentation you have for your analysis plan should give them the info they need to quickly advise.

However, the extra accessibility afforded by modern CFD software allows users to neglect common analysis fundamentals. This can lead to poor accuracy or misleading results. It won’t be possible to address every possible source of error in this article, but I’ll do my best to address the major setup mistakes I’ve seen often working with engineers using CFD.

The article will focus primarily on SOLIDWORKS Flow Simulation but the principles should apply to most CFD packages.

Mistake: Not Creating an Analysis Plan

Before jumping into any kind of simulation, it’s a great idea to come up with an analysis plan. This should include defining the main parameters of interest (the “outputs” or independent variables) and the main inputs to be used in the simulation.

While you’re at it, it’s a good idea to document the relevant assumptions you’ll be making and the level of simplifications you plan on making to the models.

A little bit of planning upfront can keep you on track and save a lot of time in the long run so you don’t lose sight of your end goals and assumptions. Perhaps more important is that having your plan documented allows you to easily reach out for help to colleagues or your software technical support team and clearly explain what you’re trying to achieve.

Figure 1. Simplified analysis plan for a Tesla valve.

If you’re having trouble coming up with a plan, I usually recommend thinking of the simulation setup like a virtual experiment. If you were conducting a real-life experiment, how would you set it up? Where would you place measurement sensors and what parameters would you want to measure? Would you run the test only for a short duration or an extended period? How large would the test chamber/environment need to be?

Answering these questions provides a great starting point for an analysis plan. This will directly translate into decisions on where to place virtual sensors to monitor the solution, choosing a steady-state vs transient analysis, sizing the computational domain, etc.

Mistake: Not Monitoring Goals and Solution Convergence

Whatever the parameters of interest for the simulation are, appropriate goals should be defined to track them throughout the course of the solution. Depending on the type of analysis this could include monitoring values such as pressure loss from inlet to outlet, flow rates, lift and drag forces on surfaces, temperatures of key components in a thermal analysis, or the concentrations of various species of fluids in a mixing problem.

Since computational fluid dynamics is an iterative process, failure to monitor these values can cause one of two problems: the peak values may not be captured due to the solution not developing long enough (causing major inaccuracy) or the solve time may be drastically increased by solving for much longer than required.

To avoid this, a good rule of thumb is to think of these result monitoring locations as virtual sensors, so wherever you would place a sensor in a physical experiment, place a goal or output request to track the parameter of interest in that location.

You can then plot values at these locations over the course of the solution (practically every CFD package will allow viewing results at these monitored locations in real-time) to manually assess convergence once the values have stabilized within a certain threshold, but a better idea is to take advantage of stopping criteria.

Figure 2. Goals defined in SOLIDWORKS Flow Simulation (left) and solver monitor goals plot.

When goals are defined in SOLIDWORKS Flow Simulation, automatic stopping criteria are placed to stop the solver once the goals are converged to within a tolerance. The user can manually specify the tolerance if they want more control. As soon as all the parameters of interest are stabilized to within this threshold, the solver will automatically terminate and save the results, often cutting minutes or hours off the solve time.

It is still important to double-check the solution convergence after the fact.

Adjusting Stopping Criteria

If you find that the monitored locations are still increasing in value when the solution stopped, it’s likely that some secondary stopping criteria, such as a limit on number of iterations or “travel” is kicking in. For problems where your monitored locations are taking a particularly long time to converge, it may be necessary to raise the limit for the number of iterations/travels or eliminate these secondary stopping criteria entirely.

Figure 3. Finishing criteria for SOLIDWORKS Flow Simulation with manual goal tolerance.

Aside from helping ensure accuracy of the solution, defining the goal or other result monitors in advance saves time when it comes to post-processing or interpreting the results later, as these values can easily be graphed and exported to reports. 

If you find you need to extend the solution after completing an analysis, most CFD programs allow you to continue or resume the calculation from where you left off. You don’t have to solve the whole problem all over.

Monitoring Residuals

SOLIDWORKS Flow Simulation doesn’t require the monitoring of residuals for typical problems including steady-state and transient problems with the default settings.

In other CFD packages like SIMULIA Fluid Dynamics Engineer, the residuals will automatically have associated output requests so that they can be plotted over the course of the solution. Residuals are typically provided for mass flow, energy and turbulence parameters. The residual value can be thought of as the imbalance that remains between iterations of the solver and, due to the iterative nature of the solution process, they are expected to decrease over the course of the analysis before plateauing at some infinitesimal value.

If you observe residuals increasing over the course of the solution or their absolute value is much larger than expected, it is likely there is a problem with the CFD setup and the program is producing an instability or “divergent” solution. The results in this case should not be trusted until whatever is causing the residuals to diverge is corrected.  

Note that monitoring residuals on their own isn’t a replacement for directly monitoring the convergence of your parameters of interest. In SIMULIA Fluid Dynamics Engineer, this can be done by placing additional output request for whatever your key parameters are, similar to the goals in SOLIDWORKS Flow Simulation.

If you happen to be running a SOLIDWORKS Flow Simulation time-dependent study with “nested iterations,” you will have access to residuals for normalized mass, momentum and energy as additional goal plots. If you are trying to speed up the solution process by forcing a large manual timestep with nested iterations, checking these residuals will let you know if the solution is stable or if you’ve pushed the timestep size too far.

Mistake: Resuming or Continuing an Analysis

When running the CFD any time after the initial solve, there should be an option to resume the previous simulation.

Figure 4. Dialog showing options for either new or continued calculation in SOLIDWORKS Flow Simulation.

As previously discussed, this option to resume can be helpful if the goals were not converged and you wanted to solve for more iterations. However, take note that if you made any changes to the simulation setup, you will most likely want to do a “New calculation.”

This comes up often: you are making changes to the simulation setup and wondering why they are not being reflected in your results. It’s very possible you’ve accidentally picked the “Continue calculation” option rather than starting a new one.

Performing model adjustments or geometry changes will flag the mesh as out-of-date and start the process from scratch but you must pay close attention to these options when you’re only modifying simulation parameters.

Mistake: Lack of Mesh Refinement

Automatic meshing done by many CFD packages makes it easy to do simulation but it is important to examine the mesh to ensure it fulfills a few general guidelines. If time allows, a mesh convergence study should be performed to examine the effects of increasing mesh refinement and determine a point of diminishing returns. These studies are commonly called “mesh dependence” or “grid dependence” studies and are carried out with the goal of proving the solution is mesh or grid independent.

SOLIDWORKS Flow Simulation uses a fairly unique meshing technology that combines a Cartesian grid or octree mesh with the immersed boundary method, a technique that allows capturing features that are smaller than the mesh cell size.

These cells (referred to as solid/fluid or partial cells in SOLIDWORKS Flow Simulation) provide a great deal of flexibility in controlling the amount of detail in a simulation.

In the image below you can see a draft mesh for a server rackmount unit featuring hundreds of components.

Figure 5. SOLIDWORKS Flow Simulation mesh for electronics cooling displaying partial solid/fluid cells.

Note that the mesh cells in the zoomed-in view are larger than and not aligned with the memory chips. Thanks to the support for partial or solid/fluid cells, SOLIDWORKS Flow Simulation can resolve this detail which greatly reduces the mesh cell count (and time) required to solve such a problem.

Avoiding Severe Mesh Issues

While the automatic mesh creation is impressive, it’s not a magic bullet for all situations.

By far the most common issue I see regarding meshing for SOLIDWORKS Flow Simulation is a mesh with cell sizes many orders of magnitude larger than the solid features they are trying to resolve. There is only so much the partial cells can do and when there is too much variation in the size of the cells will result in very inaccurate results or generated cryptic solver error messages.

Simply checking the mesh that the software generates by inserting a Mesh Plot command. This will ensure the cell sizes are roughly of the same order of magnitude as the feature sizes you expect to resolve and will prevent these worst errors.

To increase accuracy further, it’s recommended that you provide a few cells across any narrow channels. If you’re expecting to see detailed thermal gradients through a solid, then you’d be well advised to include a couple cells through the solid thickness as well. For the best quality results, you will want to place 10-15 cells across a narrow channel.

Proving Mesh Independence

None of the guidelines discussed are replacements for performing a mesh independence or mesh convergence study. Performing a series of studies with increasing mesh refinement to observe the sensitivity of your key results to the mesh is crucial if you are striving to eliminate all errors.

One area where additional effort for mesh refinement is important is aero and hydrodynamic effects on curved surfaces – for example, lift or drag calculations for a vehicle or the performance of a rotating impeller.

Figure 6. Mesh convergence study for a propeller thrust calculation.

The figure above shows a simple mesh convergence study conducted on a rotating propeller, with the thrust as the key output. Zooming in to the propeller cross section and hiding the propeller body shows that at coarse refinement levels the profile of the propeller cross section is not well defined – this is known as discretization or local truncation error. If you consider that that pressure is resolved into forces across each cell, it is clear why this can yield large differences in the predicted thrust.

However, with minor refinements the solution converges to a thrust value while still maintaining a reasonable number of cells. As one might expect, this is the level (Refinement 5 in figure above) at which the outline of the profile of the cells on the zoomed in view matches the geometry of the original propeller blade. Refinement 6, which more than triples the cell counts, does not change the thrust, so the results may be considered converged.

Note that ensuring the solution is mesh independent does not necessarily mean it is accurate – only that you have addressed one possible source of error.

Solution-Adaptive Meshing

If you don’t want to fool around with a mesh convergence study, you can also check whether your CFD software offers a solution-adaptive mesh approach.

Figure 7. Solution-adaptive mesh solve progression for wind loading.

SOLIDWORKS Flow Simulation’s solution-adaptive mesh allows setting targets for the maximum number of cells and a time period to wait between refinements. The software will then periodically refine areas of the model with high pressure gradients. If you are tracking your goals, this will give you a record of the goals converged values at each level of mesh refinement – essentially built-in proof that your solution is grid-independent.

Body-Fitted Mesh

The structured Cartesian mesh used by SOLIDWORKS Flow Simulation excels at applications like electronics cooling but can require significant amounts of refinement on smooth curved geometries. For classical aerodynamic and hydrodynamic problems, many CFD experts swear by “unstructured” or body-fitted mesh like that available in SIMULIA Fluid Dynamics Engineer and other standalone CFD packages.

Figure 8. Coarse and semi-refined body-fitted mesh in SIMULIA fluid dynamics engineer.

This mesh structure relies on special boundary-layer elements (commonly referred to as an “inflation layer”) near the walls to precisely resolve the mesh.

This meshing method tends to require additional geometry preparation and simplification as it is much less forgiving about any faults or imperfections in the CAD model quality compared to the immersed boundary method used by SOLIDWORKS Flow Simulation, which is capable of healing over small faults and geometry errors.

The payoff (especially when combined with advanced turbulence models like k-ω SST) can be higher accuracy for predictions of lift and drag, potentially at overall lower element counts.

Meshing guidelines for conformal mesh are mostly related to the thickness of the boundary layer elements, which can be determined in SIMULIA Fluid Dynamics engineer by placing an output request to track YPLUS (y+) the normalized wall-normal distance.

Each turbulence model will have recommended values for y+ to aim for depending on whether you plan to rely on wall functions which approximate the local effects of the near-wall boundary layer (possible with even a crude mesh) or directly resolving the viscous-sublayer.

That’s all…for now. There’s a few more mistakes to be avoided. Stay tuned.

In past articles we’ve explored use cases for nonlinear analysis, including hyperelastic materials such as rubbers or plasticity models for loadings beyond the yield point of a material.

Something all the materials discussed so far share is that they are generally thought of as homogenous in nature or made up of a single constituent material.

Composite materials, on the other hand, are made up of multiple constituent materials and can be engineered to possess qualities such as stiffness, strength or toughness that exceeds the performance of most of the material.

In this article, we’ll explore a high-level overview of analysis techniques for composite materials within SOLIDWORKS and SIMULIA products.

Composites Applications

The domain of composites is quite broad. This article will attempt to focus on the “macro” scale composites commonly chosen by engineers and product designers for their rated properties. The constituent components of a composite are often classified as the matrix or binding medium, and the reinforcement which is added for additional strength or other physical characteristics.

Wood products such as common plywood are an example of this. Laminated veneer lumber (LVL) beams and other glue laminated or “glulam” construction are used to achieve open-concept floorplans that would only otherwise be possible with steel members.

Sandwich composites make use of an inner core layer such as foam or aluminum honeycomb, with encapsulating thin outer skins to carry shear forces.

Figure 1. Glulam beams (left) and aluminum honeycomb sandwich composite (right).

Reinforced concrete with embedded steel or carbon-fiber reinforced polymer is a mainstay of commercial and residential construction.

Injection molded plastic parts are commonly reinforced with chopped fiberglass or carbon fiber, with such strength that they can often replace aluminum castings or stamped steel components.

Fiberglass composites are commonly used in all sorts of commercial and recreational products, from boats to storage tanks and FR-4 is a fiberglass composite that also happens to be the base material for most printed circuit boards in use today. 

Figure 2. Fiberglass FR-4 PCB (left) and fiber-filled injection molded part (right).

Of course, the image most of us probably arrive at in our minds when we hear the word “composites” is carbon fiber, more specifically glass-reinforced polymer (GRP) and carbon-fiber reinforced polymer (CFRP), with the classical case being a rigid structure made up of multiple layers of woven continuous-strand textile bound together by an epoxy resin.

Depending on the application, engineers may choose to incorporate or modify pre-purchased composites or go into depth designing their own custom lay-ups.

This article will attempt to examine both approaches and the levels of simulation software required for performing structural analysis at various levels of fidelity.

Orthotropic Materials with SOLIDWORKS Simulation Standard

A key behavior for many composite materials is that due to their heterogenous makeup, they often exhibit different behaviors depending on the direction of loading. This behavior can be crudely approximated using the linear elastic orthotropic material definition available in the most basic levels of SOLIDWORKS Simulation – including the simulation included with SOLIDWORKS Premium and the SOLIDWORKS Simulation Standard license.

Figure 3. Linear elastic orthotropic material properties for a glass-reinforced polymer with reference geometry selection.

This material model is in contrast to the default linear elastic isotropic used for homogenous materials and allows definition of elastic modulus and shear modulus in the X, Y and Z directions. These directions must be defined by some reference geometry selection – either a plane, planar face, coordinate system or axis. The reference geometry selection maps the material properties to the appropriate axes so if there are multiple bodies with different orientations they must have a relevant individual reference geometry selection.

This necessitates some limitations – the geometry must either be planar, cylindrical or spherical in nature, depending on the reference geometry selection. If the end part cannot be defined as a single body while satisfying these rules, then it must be broken up into multiple more primitive bodies. Such a procedure is described in the help article Defining Orthotropic Properties.

It should be noted that this approach generally allows adequately representing the stiffness of a composite material for a structural analysis, allowing accurate predictions of the total displacement and any reaction or free body forces. As the stress information is not available per-ply, caution must be taken from drawing conclusions about failure of the composite material itself. 

Another benefit of this approach is that it is available for all study types in SOLIDWORKS Simulation, including thermal analysis.

Transverse Isotropy

It should be noted that most layered composites exhibit the behavior of transverse isotropy, meaning their behavior can be simplified to in-plane and through-plane behaviors. For this reason, you may find material might often be provided with only two components of elastic modulus (such as E1 and E2) and one component of shear modulus (G12).

SOLIDWORKS Simulation has no transverse isotropic definition, so the missing properties for a full orthotropic material may be back-calculated (e.g., E1 = E3 assuming plane 1-3 is the plane of isotropy). Poisson’s ratio may also be back-calculated from the elastic modulus and shear modulus.

Materials may also behave differently based on the physics in question. For instance, PCBs are sometimes approximated as isotropic materials for structural analysis but generally must be represented as orthotropic materials for thermal analysis where the conductivity of the copper plays a more significant role.

Analysis of a Quadcopter Frame

For an example of using this approach, we’ll apply a linear orthotropic material to a frame for a quadcopter. This is an ideal case for these assumptions since the frame will be routed out of a pre-purchased CFRP sheet and the geometry is planar in nature.

Figure 4. Quadcopter CAD assembly (top) and same assembly prepared for analysis (bottom).

The analysis is a static study with a 5 g downward acceleration applied. Restraints are applied at the motor mounting locations using the Remote Load tool acting as a remote displacement and representing a ball joint style pivot.

It should be noted that this fixture scheme was arrived at after comparing against the naïve approach of “fixed geometry,” as visualized in the exaggerated displacement plot below.

Figure 5. Fixed geometry restraints (top) and remote load pivot fixture (bottom).

It can be seen from above that the response with the pivot restraints appears much more natural and represents the facts that the propellers will apply thrust force normal to their current direction, rather than the global vertical direction. The fixed geometry fixtures appear to have a severe and artificial stiffening effect which reduces the overall displacement. The lower image also shows that the quadcopter must be somewhat tail heavy with the rear end dipping down lower than the front. I’ll have to check with the designer to make sure the mass of the battery is correct.

A true-scale animation plot is presented in the following figure.

Figure 6. True scale displacement animation.

As no per-ply stress information is available, we really shouldn’t use stress components to predict factor-of-safety for the frame.

One potential alternative is to use strain as a predictor for failure.

Figure 7. Strain plot for CFRP sheet.

The figure above shows a strain plot for the frame, with the plot scaled for a strain design limit. This is about the best we can do without having access to more detailed composites information, but may suffice for many users looking to work with pre-purchased composite sheet or tube.

Composites Analysis with SOLIDWORKS Simulation Premium

The next step up in realism is to utilize the composites analysis available in SOLIDWORKS Simulation Premium. This requires using a shell mesh definition for the composite in question, and so requires a constant wall thickness region. This type of composite definition is possible in the linear static, frequency and buckling study types.

Material properties are defined in the same fashion as the linear orthotropic material, except there is no reference geometry selection and they can vary per ply. The ply orientation is mapped by default to the U-V coordinates of the surface, allowing truly orthotropic behavior for compound surfaces that is not restricted to specific geometry primitives.

Figure 8. Composite shell definition.

Composite shell definition for a fixed-wing drone fuselage is pictured above. To simplify the shell definition, a surface was extracted from solid body using the Offset Surface command. If you’re unfamiliar with shell definition in SOLIDWORKS Simulation, I’d recommend the tutorial on SOLIDWORKS Simulation Shell Definition.

The ability to align orthotropic material properties with arbitrary compound surfaces is really one of the biggest features of this composite shell definition. It allows analysis of things that aren’t just plates and tubes.

Note though that the orientation of the coordinate mapping should be verified and can be altered or corrected per face if there is an alignment discontinuity or mismatch. This can be a daunting process for geometry with many distinct faces/fillets as pictured above. For geometry with a low number of faces or with smooth continuous compound surfaces very little correction should be required.

Individual plies can be specified with their own thickness, angle and material properties during the shell definition allowing room for substantial experimentation from the designer.

As far as the simulation setup is concerned, the drone is subjected to a combination of torsion and gravitational acceleration that is intended to represent a very rough landing. Contact sets were defined to locally bond the composite shell to the other components in the load path, including the front and rear injection-molded housings and the tail boom.

Figure 9. Simulation setup with contact definitions.

The response is pictured below using Von Mises stress for the first ply, but note the additional options to plot stress for other plies, maximum across all plies and also interlaminar shear. 

Figure 10. Stress visualization.

Failure Theories

As mentioned, the composites functionality in SOLIDWORKS Simulation Premium adds the capability to track and interpret per -ply stresses as well as interlaminar shear stress.

This enables additional failure criteria in the factor of safety plot, including the Maximum Stress, Tsai-Hill and Tsai-Wu failure criterion.

Figure 11. Predicted factor of safety using Tsai-Wu criterion.

A helpful SOLIDWORKS article discusses selecting a composites failure criterion can be found here.

In short, Tsai-Hill and Tsai-Wu take into account the interactions between stress components and thus are capable of predicting failure of plies due interlaminar shear stresses (failure modes such as delamination) but aren’t intended for predicting failure in the matrix. Maximum stress criterion looks only at maximal values and can be useful for predicting failure in the composite matrix but isn’t intended for predicting failure due to delamination. 

It should be noted that the method used by SOLIDWORKS Simulation Premium is first ply failure (FPF) and will never show or describe delamination visually or allow simulating behavior past the initial failure. The “rule of mixtures” assumption utilized by SOLIDWORKS Simulation also approximates the bulk behavior of the composite from its makeup information, potentially neglecting localized failure modes.

Additionally, the way the ply information is mapped to the shell mesh means that we can’t easily analyze the relatively common case of composites with variable wall thickness or tapering sections.

Composites Analysis in SIMULIA

The desktop software package SIMULIA Abaqus/CAE and the cloud-connected equivalent 3DEXPERIENCE SIMULIA structural simulation roles both provide in-depth composites modeling and analysis, adding several major capabilities that span across many domains such as fatigue and durability, fracture mechanics and vibrations.

Composites in SIMULIA structural tools may be defined at various levels of detail and represented by either “composite shells” or “composite continuum shells” as in the case for many layups or with high-detail solid mesh. This means it is possible to analyze both the performance of something like a complex vehicle body or other large-scale structure or zoom in to analyze specific failure modes at connections or joints in very high detail.

Composite Ply Definitions

Composite shell sections function similarly to the composites functionality module in SOLIDWORKS Simulation Premium, mapping over ply stack information to surfaces, except that they support variable wall thickness and so can easily represent tapered or variable wall thickness.

Figure 12. Composite lay-up example from Abaqus CAE user guide.

Composite continuum shell sections combine many of the benefits of shell and solid mesh by incorporating a 3D nodal representation of the thickness. The user guide for Composite Continuum Shell describes in further detail:

“Like a shell section, a composite continuum section has one dimension (the thickness) that is significantly smaller than the other two dimensions. However, composite continuum shell sections are modeled in three dimensions; therefore, the model defines the thickness and stresses in the thickness direction are not negligible.”

Ply information can be defined directly in the analysis tool or, if product design is being performed in CATIA or the associated 3DEXPERIENCE roles, the ply information can be imported for analysis providing a tight coupling between design and analysis for faster iteration.

Delamination and Crack Propagation

The SIMULIA structural tools also support simulating behavior such as crack initiation and propagation. Cohesive elements within the software can be applied. These cohesive elements may be assigned to fail at certain magnitudes of strain or shear stress, allowing visualization of the beginning of crack formation or delamination. The virtual crack closure technique (VCCT) is an alternative approach that can be applied to further simulate crack propagation from some existing flaw or defect, as visible in the figure below from the Abaqus user guide example: Post buckling and growth of delamination in composite panels.

Figure 13. Composite panel in post-buckled state with SIMULIA Abaqus.

The two techniques utilized together can provide a robust overview of resistance of composites to delamination or failure of any bonded connections.

Additional damage models combined with the available Explicit solver also allow representing brittle fracture for modeling detailed behavior of impacts, crashes and other high speed dynamic events.

Figure 14. Ballistic impact of fiber composite.

Embedded Reinforcement Elements

In some cases, it makes sense to directly represent the reinforcing material rather than represent it by its bulk properties. A common example is reinforced concrete, where for concrete damage modeling the concrete aggregate serves as the matrix and is meshed with solid elements. The rebar is represented by 1D elements defined as an “embedded region” within the concrete.

As a thorough example, I would highly recommend checking out this tutorial on analysis of a reinforced concrete beam in Abaqus/CAE by Dr. Clayton Petit: 2D Concrete Beam (Concrete Damage Plasticity).

Figure 15. Reinforced concrete beam damage modeling in Abaqus/CAE.

Summary & Conclusion

Composites are increasingly common as manufacturing costs decrease and designers seek to optimize structures for weight and efficiency. This article examined several approaches to analysis at various levels of detail, beginning with analysis of simple orthotropic materials in any package of SOLIDWORKS Simulation, to analyzing composites with various ply stacks in SOLIDWORKS Simulation Premium and ultimately the possibilities for analyzing failure modes such as delamination in detail with either desktop SIMULIA Abaqus/CAE or the cloud-connected 3DEXPERIENCE SIMULIA structural simulation roles.

Once a Flow Simulation project is set up, the analysis is associated with the SOLIDWORKS part or assembly file, so managing design changes is simple – either changing a model dimension and re-running the analysis, or “cloning” the Flow Simulation project to various SOLIDWORKS configurations to preserve different variations of geometry.

Figure 1. Cloning an existing SOLIDWORKS Flow Simulation project.

This workflow is useful for small numbers of iterations. In other cases, where a designer wants to iterate over a wide range of operating conditions and generate some kind of performance curve, such as a pump curve for impellers, lift/drag curves for aircraft or thermal resistance curve for a heatsink, a parametric study can be used.

Creating a parametric study from an existing study allows access to three modes: “what if analysis,” “goal optimization” and “design of experiments.” Each of these has its own advantages which will be explored over the course of this article.

Figure 2. Creating a parametric study.

Case 1: Lift/Drag Ratio Curve Using “What If” Analysis

Lets discuss the case of lift and drag calculations for an airfoil. The baseline study is presented below at zero degrees angle of attack. Solution-adaptive mesh was enabled to dynamically place additional mesh refinements where needed.

Figure 3. Baseline analysis of airfoil with solution-adaptive mesh.

Once the initial project is set up, a parametric study is created using the “what if analysis” mode. Parametric studies allow varying simulation parameters (such as airspeed around the airfoil) or model geometry parameters such as SOLIDWORKS dimensions and mates.

In this case, the airfoil is placed in a SOLIDWORKS assembly with a mating scheme that allows control of pitch via an angle mate. The pitch angle is specified as a “dimension parameter” in the parametric study to allow varying the angle of attack iteratively. A range and step size is specified and a number of resulting scenarios are automatically created.

Figure 4. Angle mate input as a dimension parameter.

The “what if analysis” mode is great for “blind” analyses like this where you simply want to solve across a range of conditions, regardless of the outcome. Key results such as goals and cut plots are referenced as outputs and then the batch of scenarios can be solved.

Once the scenarios are solved, results become available and can be quickly compared across iterations, as visible in the image below:

Figure 5. Parametric study cut plots.

Numerical values can be automatically plotted against the scenarios using the built-in graphing functions. These curves can also be exported to Excel.

Figure 6. Parametric study goal charts.

To take a look at any particular scenario or “design point” in more detail, a right click allows creating a standalone Flow Simulation project from that iteration of the parametric study and opens up the capability to use the full set of results post-processing available.

Figure 7. Creating a project from a particular design point.

Note that many input variables can be specified for the “what if” analysis, but the number of scenarios will increase very rapidly and can easily get out of hand. This is something the “design of experiments” modes can help with, which we’ll look at later.

Case 2: Goal Optimization for CPU Water Cooling Block

The second mode parametric studies provide is “goal optimization.” This allows input of a specific target such as a target temperature, pressure drop and so on, and will automatically iterate the variable specified to try and achieve the target.

These studies are straightforward to setup and the results are easy to interpret. The biggest limitation is that only a single input variable can be included as part of the optimization.

Consider the case of the CPU water-cooling block depicted below. In the baseline study with 30 liters/hour of coolant flow, the predicted temperature of the chip mating surface is about 12°C above the coolant temperature.

Figure 8. Baseline study of CPU cooler.

Suppose we’d like to calculate the minimum coolant flow rate required to achieve a temperature rise of only 8°C? In this case, we’ll vary a simulation parameter (the coolant flow rate) between the range of 30 and 600 liters/hour and set a target of our maximum solid temperature to 8°C above our coolant input temperature.

Figure 9. Goal optimization input range.

Figure 10. Goal target criteria.

The goal optimization iterates until either the target tolerance or iteration limit is reached. In this case, after 10 iterations the solver indicated that a flow rate of about 75 liters/hour should produce a desired temperature rise of just under 8 degrees (visible as Design Point 10 in the figure below).

Figure 11. Tabular results for goal optimization.

Aside from the single-variable limitation of the goal optimization, there’s no way to predict in advance how many iterations it will require to converge on its target—or if it will at all—and it can be difficult to glean design trends when compared to a “what if” or “design of experiments” study.

Case 3: Design of Experiments for a CPU Water Cooling Block

While the “goal optimization” is only capable of varying a single parameter, the “design of experiments” study type comes in with multi-variable analysis. In this case, both the channel width and number of channels cut into the cooling block are varied across a pre-determined range, as depicted below.

Figure 12. Range of geometry variations for DoE study.

Whenever varying geometry (regardless of the type of parametric study) care must be taken to ensure the model geometry rebuilds properly across the range of variables specified. It’s also important that the topology of the model remains relatively consistent -- especially on any faces, bodies or edges where boundary conditions or other setup conditions are specified.

It’s recommended to test the model by manually adjusting it to the “min” and “max” conditions before running the parametric study to verify that it’s able to rebuild correctly so you don’t come back to a slew of failed analyses. Such testing was performed to determine the ranges and the extremes of the two ranges are depicted below.

Figure 13. Extremes of input variable range used in DoE study.

Unlike the other study types, scenarios for a design of experiments study are not automatically created. The user specifies how many experiments to create, and the input variables are varied across the ranges. Then, after each scenario is solved, the optimum design point is estimated after-the-fact by defining an objective function.

Figure 14. DoE scenario setup.

An additional output provided by the design of experiments study is a response surface viewer, to view trends between multiple variables and their outputs in 3D. The response surface depicted below indicates that changing either variable has a nonlinear effect on pressure drop, but a mostly linear one on the predicted maximum temperature for the given flow rate.

Figure 15. Response surface viewer.

An example of extracting an optimum design point is presented below, where the temperature and pressure are set to minimize with an additional constraint on the pressure to be below a certain value. 

Figure 16. Extraction of optimal design point.

One of the great benefits of this approach is that if objectives shift, it’s not necessary to rerun the entire DoE study to achieve some new target, simply create a new optimum design point with its own objective function.

It’s worth noting that the “optimum” design points are only estimates based on the trends detected, and should be run as their own analyses to confirm that the performance matches up to their estimated performance.

Conclusion

The nature of CAD-embedded analysis tools lends itself well to fast iteration and exploration of the design space available to engineers. While it’s possible to accomplish this by manually copying existing projects, at a certain point the capabilities of a table-based iterative tool such as design studies for SOLIDWORKS Simulation or the parametric studies covered here for SOLIDWORKS Flow Simulation really start to show their benefits—whether for varying the model geometry or simulation parameters.

The Insert Part feature provides a simple alternative to traditional assembly in-context editing and can be used for both simple and complex use cases.

This article will outline two case studies: the simple case of designing one part around another purchased or mating part and the more complex case of utilizing data from a master model.

Case Study 1: Designing Around Metal Insert

In this example, a metal threaded stud will be inserted into a molded plastic knob to allow subtracting the material necessary to produce the overmolded part.

The Insert Part command, visible in Figure 1 below, can be found on the “Insert” drop-down toolbar when an existing part file is already open.

Figure 1. Insert Part feature under the Insert pull down menu.

The part file to be inserted is browsed for and a particular configuration can be chosen.

One valuable feature of the Insert Part tool is the ability to specify which data gets transferred. This can include solid and surface bodies, sketches, planes and other reference geometry as well as material data and certain properties.

Choosing to transfer only the data that is needed will help keep the part model organized.

The Insert Part feature that gets added to the model tree can always be edited later to transfer more information or to update the configuration of the inserted part file.

Figure 2. Insert Part options and preview.

By default, the inserted part is linked to the original via an external file reference, unless the option “Break link to original part” is selected.

Positioning the Inserted Model

If the model to be inserted has the appropriate position about its origin, then no extra work is necessary. The checkmark can be clicked to insert the part with its origin aligned with the base part’s origin.

Most of the time, however, the inserted part will require positioning. There are two options to choose from if the “Locate part with Move/Copy feature” is selected. Enabling this option launches a prompt similar to the Move/Copy body feature which has two modes of operation.

Visible in Figure 3 below is the first mode which allows specifying either a translation or rotation in X/Y/Z coordinates allowing for a finite offset. In this mode, translation and rotation must be applied separately, which means it may be necessary to use a second manually defined Move/Copy body feature to achieve the desired result.

Figure 3. Locate Part with translate/rotate option.

The “Constraints” option in the Locate Part tool is visible in Figure 4 below. This option functions similarly to assembly-level mating and allows creation of multiple mates to locate the inserted part within a single prompt.

Figure 4. Locate Part with constraints option.

Referencing Inserted Bodies

A valuable addition in more recent versions of SOLIDWORKS is the ability to perform Interference Detection on multibody parts which can be seen in Figure 5 below:

Figure 5. Multibody interference detection.

Now that the interference is clearly visible, any part or multibody modeling techniques can be used to correct it.

Traditional sketch-based features such as extrude cut or revolved cut can be used along with Feature Scope to selectively target only the base model, as shown in Figure 6.

Figure 6. Sketch based features with feature scope.

One of the benefits of having both bodies in one file, however, is the ability to use Boolean-style modeling operations such as the Combine or Intersect features.

Figure 7 below shows the setup required for subtracting the insert from the base part using a Boolean-style modeling command.

Figure 7. Subtracting inserted body.

This approach should ensure the plastic part always updates correctly to subsequent model revisions. In comparison, the sketch-based methods may break or require editing if the profile is substantially altered in the inserted file.

Figure 8 shows the result of the subtract operation. Note that in the process of subtracting, the inserted body is consumed.

If it is desired to keep the inserted body in the final model, the body can be copied beforehand with a Move/Copy body feature and the “Copy” option enabled.

File References

It is important to be conscious of the file references occurring behind the scenes when using any form of in-context modeling.

File references can be viewed by right clicking the Insert part feature from the tree and selecting “External References…”

Figure 8. Final result and accessing file reference.

While the ability to have the part file automatically updated when the source inserted file changes can be of great value during the early stages in the design, there may be times when you need to lock the design to prevent further changes.

The “Lock All” option is useful in this case, as it will temporarily lock the reference until further notice, preventing the inserted file from changing unless it is unlocked.

If it is necessary to break the link from the inserted file permanently, the “Break All” option can be used combined with the checkbox to include original features, as shown in Figure 9 below.

Figure 9. Break All references and Insert features.

This action is irreversible, and in some cases the inserted features may have sketch or relation errors that need to be corrected, so it is best to create a backup of your file before performing this operation.

Figure 10. Inserted Features after using Break All option.

The results are the features from the inserted part being grouped in a folder neatly within the original part model with model intelligence allowing for straightforward edits.

This case study is also available in the form of the video tutorial SOLIDWORKS: Insert Part Feature for Multibody Part Modeling.

Case Study 2: Master Model Workflow with Insert Part

Product designs featuring complex shapes with multiple mating components, such as cast or molded enclosures, can also benefit from the Insert Part feature when used as part of a master model workflow.

Figure 11. Master model of enclosure – single solid body.

In this workflow the master model is constructed either as a set of solid bodies, surface bodies or a hybrid of the two. Figure 11 above shows a solid body that represents the drafted halves of a multi-piece enclosure as well as a surface to represent the parting line and some additional sketches that contain information that may need to be shared between pieces of the enclosure.

The goal of the master model is to capture only enough to define the overall form and the mating features of the split. New part files are created, and this base or “master” model is inserted into them using the Insert Part feature.

This first part file will represent the top of the enclosure, so a surface cut feature is used to discard the material below the parting line. Further detailing is performed on top of the inserted body until this part is complete.

Figure 12. Detailing top of enclosure – Insert Part feature is first in tree.

This process is repeated for other part splits. A new part file is created, the master model inserted, the part is cut down to the desired split piece and then detailed.

Splitting up a complex model using a master model workflow has two major benefits: reducing the feature complexity and rebuild time in any one file and allowing multiple designers to work on different portions of the design simultaneously.

As the Insert Part feature maintains an active reference to the base master model part, any changes to overall dimensions or the form of the enclosure will update and propagate through the “child” split parts.

The detailed parts are then put together in an assembly for final validation and accurate bill of materials.

Figure 13. Assembly of individual detailed parts.

Beware Out of Context

A final note of caution with file references: Be careful of loading the part out of context. In SOLIDWORKS, this is symbolized by a question mark ( ? ) next to the inserted file name.

The question mark is easy to overlook. Look hard for it because it indicates that the referenced file has not been loaded, meaning changes will not be reflected in the model. It can be resolved manually by opening the selected file or right clicking and choosing “Edit in context.”

Figure 14. Out of Context indicator in System Options.

To manage this in a more automated fashion, System Options for External References (visible in Figure 14 above) can enable automatically loading referenced documents or prompting on each load.

Insert Part Versus Other Methods

Insert Part has many strengths when only one other part file needs to be referenced, as in the case of the metal insert shown in the first example and in the master model workflow shown in the second.

If a part needs to draw references and information from multiple different part files, then in-context assembly references are a much more obvious choice.

Nesting inserted parts multiple layers deep should also generally be avoided due to the difficulty of diagnosing file reference issues if they were to occur.

For the master model workflow specifically, there are other methods available within SOLIDWORKS such as the Save Bodies feature that could also be explored. Most other methods require less initial work upfront but may also have less flexibility.

When compared to Save Bodies, a benefit of Insert Part for master models is the ability to carry over sketch and reference geometry information rather than just the body data, as well as the ability to insert features when breaking references.

Although Insert Part allows choosing the type of data to transfer, such as planes and bodies, it does not allow isolating specific data. This can be a potential benefit for assembly in-context relation, in the event there is an abundance of sketch or body information as only the data needed for a particular file can be referenced in.

Conclusion

This article outlined two case studies for use cases of the Insert Part feature in SOLIDWORKS. For simple multibody needs such as referencing geometry of another part file, the Insert Part feature can help avoid many of the pitfalls and complexities of assembly in-context references. For “master model” workflows, the Insert Part command differentiates itself by allowing propagation of reference geometry and sketches to derived or child models.

In general, SOLIDWORKS provides a variety of means of achieving the same end result and its important to explore them to find the one that works best for your application. Hopefully this article will inspire you to explore the Insert Part feature the next time you need to reference another part file.

Visit SOLIDWORKS to learn more, or check out this ebook to see all the new enhancements coming in SOLIDWORKS 2022.

Mold filling simulation allows for verifying part design before mold tool steel is ever cut—ensuring that major revisions will not be necessary to either the part or the molds. Incorporating a CAD-embedded molding simulation software enables designers to make decisions to improve moldability early on and throughout the design process.

Figure 1. Fill analysis in SOLIDWORKS Plastics.

SOLIDWORKS Plastics is an add-in product for SOLIDWORKS that enables simulations for plastic injection molding and is available in three levels: ranging from Plastics Standard for predicting single part mold filling and common defects; Plastics Professional which allows analysis of the pack or “pressure hold” cycle, more complex materials and multi-cavity molds; to Plastics Premium, which enables molders and tool designers to simulate cooling channel design and predict warpage.

This article will examine some of the common molding defects that can be predicted and avoided using SOLIDWORKS Plastics—as well as the setup process required to perform an analysis.

Creating a Plastics Fill Study

Creating a Plastics study is a straightforward process, beginning with loading the SOLIDWORKS Plastics add-in.

Geometry Preparation

Geometry preparation involves making sure you are working in the SOLIDWORKS Part environment. For single parts there is no work required, but multi-cavity layouts may require conversion from assemblies into multi-body parts.

Note that for Plastics analysis the “positive” volume of the net molded part is required, rather than the negative shape of the mold cavity. If you are working from mold tooling and do not have the shape of the target part, it can easily be extracted using the Intersect feature in SOLIDWORKS.

The last task before beginning analysis setup is to define areas for the gate or injection locations where polymer will be injected into the cavity. This is commonly defined as a simple sketch point coincident with an edge or face of the model.

Study Setup

At this point a new study can be created. For most studies, the only choice the user needs to make is Solid or Shell mesh. We will explain meshing later in detail but the short version is that a Shell mesh allows rapid analysis of relatively constant wall thickness in thin-walled parts, while Solid mesh has an increased solve time but offers more rich results with less assumptions.

Figure 2 below illustrates the Plastics Study feature tree after mesh generation. The injection location was specified under boundary conditions and a sketch point was specified. The polymer was chosen inside the Injection Unit options.

Figure 2. Plastics study tree.

Starting with the 2020 version of SOLIDWORKS Plastics the user-interface was re-structured to match other SOLIDWORKS Simulation products more closely.

Like SOLIDWORKS Simulation and Flow Simulation, the study setup is stored on the part file and can take advantage of multiple configurations for analyzing geometry variations. Results files are saved in the same folder as the CAD files by default. 

The Injection Units settings let you specify the polymer as well as fill settings such as injection pressure, mold temperature and fill time, if known. In the absence of user-specified parameters here, Plastics will use data from the material specifications for mold temperature as well as automatically calculated values for fill time.

For a more detailed guide on how to set up a study in SOLIDWORKS Plastics check out this video: SOLIDWORKS Plastics: Simulation Setup Guide.

Interpreting Results

A variety of part-level defects can be identified easily with Plastics Standard, which has automatic checks and visualization for short shots (incomplete fills), weld (knit) lines, sink marks and air traps in the model. Therefore, most severe molding problems can be identified and mitigated early with a quick first-pass analysis, often set up and run in just a few minutes.

Machine selection can also be considered by predicting the clamp tonnage and pressure required to mold the part.

Cooling time is estimated at this stage and part design changes can be made to reduce cooling time or minimize knit lines or sink marks.

Testing Geometry Variations

Once the initial analysis has been performed, analyzing different geometry variations or polymers is as simple as clicking the “Duplicate Study” button to create a new SOLIDWORKS configuration and copied Plastics study.

Alternatively multiple geometry variations that are prepared in advance can be set up and batch solved through the Batch Manager.

Runner Balancing

Plastics Professional adds the ability to represent multi-cavity molds. Especially troublesome for molders are “family molds” (where multiple different parts are grouped together to save on tooling cost) which can suffer from unbalanced fill times. Observe Figure 3 below, where due to their different volumes the smaller part fills much more quickly. In the pack cycle, this may result in excessive flashing and other issues.

Figure 3. Family mold prior to runner balancing.

The process of “runner balancing” or resizing the runners is normally a manual undertaking to attempt to even out the flow between disparate parts. SOLIDWORKS Plastics Professional automates this process using a runner balancing wizard which iterates and attempts to automatically optimize runner and gate sizes until equal fill rates are achieved.

Runner systems in general can be quickly prototyped using single line sketches and assigning profiles and sizes, or they may be modeled in more detail by creating a solid body to represent the runner system and flagging it as part of the runner domain.

Figure 4. Runner system: sketch lines (left) vs solid body (right).

Modeling a solid body to represent the gate and runner is the preferred method to accurately represent localized gate effects and test different gate designs such as submarine gate, cashew gate, etc.

Solid Mesh

The examples thus far have featured a shell mesh—which is appropriate for initial predictions of fill performance on thin-walled parts.

For parts that may feature thin and thick regions, or out of desire for more accuracy and rich results, it may be desirable to utilize a solid mesh.

Figure 5. Solid mesh and boundary layer element closeup.

The shell meshes only the interior and exterior faces and performs extra calculations to interpolate what the flow front is doing through the thickness of the cavity.

The solid mesh generates boundary layer elements on the inner and outer skins of the model and then fills in the inside with tetrahedral elements, which allows it to calculate the flow front explicitly.

This means that in addition to ensuring accuracy, solid mesh enables additional results outputs.

Isosurface plots allow visualizing the 3D flow front of polymer, as visible in Figure 6 below.

Figure 6. Isosurface display for fill time plot with solid mesh.

The presence of “through thickness” elements also means that accurate cut plots can be created and data can be probed at any location internal to the part, which is practically a requirement for parts that feature thick wall sections.

Solid mesh functionality is available even in Plastics Standard but only for single body parts.

Solid Mesh Performance

Despite requiring many more elements, solid mesh solvers are very well multi-threaded. Despite the speed advantage shell mesh may have in terms of solve time on lower-end hardware, the gap in solve time can be reduced on hardware taking advantage of a high number of cores in the CPU and GPUs.

Overmolding

Figure 5 and Figure 6 also show an example of insert overmolding, a feature which requires Plastics Professional. The ability to specify multiple different domains makes it easy to separate the runner body, the insert and the part cavity itself.

By including the insert in the analysis, the appropriate material can be applied and more accurately represent the thermal effects in the mold.

Plastics Professional also supports multi-shot injection molding for plastic-on-plastic parts, as well as materials such as TPU and TPE for soft-touch overmolding.

Mold-level Analysis: Cool & Warp

At the high end of SOLIDWORKS Plastics simulation in Plastics Premium, mold-level analysis can be performed by representing the runners, cooling channels and a mold body around the cavity.

Figure 7 below shows the cooling channels, defined in this case using simple sketch lines. Flow rates and a fluid are input to the cooling channels, which will perform a fluid dynamics calculation to determine their heat removal performance.

Figure 7. Cooling channel and runner system defined in Plastics Premium.

Cooling channels can also be modeled using solid bodies to represent more complex cooling, such as conformal cooling channels.

Figure 8. Virtual mold mesh cross section.

Figure 8 shows a cross section of the virtual mold—a volume of metal to represent the mold body. The mold could be represented as separate solid bodies and inserts for more complex scenarios.

Including the detail of the mold and cooling channels allows a molder or tool designer to simulate the cooling portion of the mold cycle using Plastics Premium.

Mold Temperature Assumptions & Cooling Analysis

Note that all the analyses possible in Plastics Standard & Professional are predicated on a “uniform mold temperature” assumption—meaning that the mold temperature specified is assumed to be uniform throughout. This is usually a reasonable assumption for parts with uniform wall thickness but the more non-standard the part design the higher the odds that assumption is invalid.

In any case, running the cool analysis provides much more detail. The cool analysis can be performed up front (even before Fill or Pack) which makes for a convenient workflow if the tooling designer is simply trying to optimize cooling channels.

Figure 9. Cool results - mold temperature.

Once the cooling results are available, as visible in Figure 9 above, they will automatically be incorporated into subsequent calculations such as Flow, Pack and Warp, increasing their accuracy.

Running Cool/Flow/Pack/Warp provides the most rich results the software is able to offer. Warpage is predicted and contribution of thermal versus viscous effects can be evaluated.

Figure 10. Warpage result (exaggerated deformation).

An exaggerated warp deformation is visible in Figure 10 above. If it is not possible to correct the warp by improving the part or tooling design, the inverted shape of the warpage may be exported using the Reverse Warp option when creating a deformed body. This allows exporting a shape with “windage” with the intent of cutting the reverse-warped shape into the mold to help improve accuracy of the final part.

Conclusion

SOLIDWORKS Plastics add-in allows a mold filling simulation from within SOLIDWORKS. For part designers, Plastics Standard represents a great value and will typically make moldability problems obvious with a quick “first pass” analysis.  

Overmolding, family molds and an expanded range of molding processes are available in Plastics Professional. Plastics Premium adds the ability to represent cooling system design and the mold itself, as well as performing warpage analysis.

Aside from helping avoid costly tooling challenges, having a plastics simulation tool on hand is especially helpful whenever the part design veers from normal or known, tried and true existing designs. Plastics simulation allows for design innovation, rather than playing it safe, giving engineers confidence and security that approaches that of “tried and true” designs.

For more about the benefits of simulation, check out the whitepaper Enhancing Data Management Workflows Through CAD-Integrated Simulation.

But what if a model has no features? Such is the case for imported models (such as .STEP and .IGES) which can benefit from Direct Editing techniques. The Direct Editing toolbar, visible in Figure 1 below, can be enabled by right clicking an existing tab of the SOLIDWORKS command manager (such as the Features tab) and choosing “Direct Editing.”

Figure 1. Direct Editing Command Manager toolbar.

Another great use case for direct edits is at the end of a feature tree to apply clearances to otherwise “nominal” dimensions.

In a pinch, direct edits can also be used to modify native SOLIDWORKS parts that suffer from poor structure or design intent. However, it should be noted that using direct edits in this way will only make the model structure more fragile and difficult to understand for other users. If you feel like you are relying on direct edits as a crutch, then it is likely that the proper solution is to put in the time to restructure the model with better design intent.

For users coming from traditional sketch-based features, direct editing can be a bit puzzling at first. The aim of this article is to demystify the time and place for each major feature. It is also worth noting that despite directly modifying faces of the geometry, these direct editing commands are still history-based, producing features in the feature tree that can be suppressed, rolled back or parametrically edited—they just pay no mind to existing sketch dimensions and constraints in the model.

Move Face

The Move Face feature enables “pushing” and “pulling” existing faces of the model—the first thing that often jumps to mind when thinking of direct edits. It features three options: Offset, Translate and Rotate.

In Figure 2 below, the Move Face feature with Translate can be seen being used to adjust the position of a slot on an imported model. Note that all faces of the slot must be selected.

Figure 2. Move Face: Translate.

In this case, a blind end condition is being used to move the slot a specific distance, but there are also other end conditions, such as “Up to Surface” and “Up to Vertex” to allow extending features up to another geometry reference.  

Note also that the Move Face command produces a feature in the feature tree. This means that features created by direct editing commands can still be suppressed, rolled back / reordered or have its dimensions accessed for editing or configuration.

It is only possible to perform one type of movement at a time, so if it is necessary to both translate and rotate geometry, this must be done with two consecutive Move Face features.

Rotation using the Move Face command is visible in Figure 3 below to change the bend angle of a flange on an imported sheet metal part. It may be necessary to define a rotation axis to perform the rotation about, which in this case was as simple as creating an axis referencing the bend arc.

Figure 3. Move Face: Rotate.

The offset option in Move Face allows shrinking and growing the size of existing features, in a direction normal to the existing faces, as visible in Figure 4 below.

Figure 4. Move Face: Offset.

The offset mode of Move Face can also be used to increase or decrease the thickness of models, such as the imported sheet metal file below in Figure 5.

Figure 5. Offsetting imported sheet metal.

Delete Face

The Delete Face command, particularly when used with the “Delete and Patch” option, is indispensable for removing features from imported geometry and simplifying models. As visible in Figure 6 below, selecting a group of chamfers with delete and patch will extend the surrounding faces and form the sharp corners that would have been present there before the chamfers were applied. The same can be done to remove fillets back to sharp corners.

Figure 6. Delete and Patch: Deleting fillets or chamfers.

Aside from removing fillets and chamfers, delete and patch can be used as an alternative to manual extrudes and extrude cuts to remove holes and unnecessary details such as engraved text and other small features.

Figure 7. Delete and Patch: Holes or slots.

For troublesome parts, delete and patch may be used as an intermediary step to simplify the geometry enough to allow a move face feature to execute.

Patterning Faces

For features of an imported part that needs to be arrayed or repeated, the face selection options inside the pattern types in SOLIDWORKS can be useful. Figure 8 below shows a linear pattern of an existing slot in a featureless file by selecting the slot faces.

Figure 8. Patterning faces.

Face-based patterns such as this are also useful in traditional modeling workflows if the intent is to pattern only some subsection of a feature.

Split & Move/Copy Body

The Split Feature and Move/Copy Bodies feature can be used together to accomplish complex model changes through a multistep process.

Figure 9. Split Feature.

Split requires selection of a cutting tool, which can be a plane, surface or sketch. Clicking the “Cut Part” button and checking the checkboxes under the scissor icon will produce separate solid bodies.

Figure 10. Splitting the model.

Once the bodies are separated, the Move/Copy bodies command allows for separating the two bodies. Similar to the Move Face command, translation and rotation can be performed in separate steps as separate features.

Figure 11. Bridging material.

Finally, traditional sketches and extrudes can be used to “bridge” the material back together into a single solid body part.

While the end result of the model change in Figure 11 above could have been accomplished by a Move Face command, the splitting and bridging technique opens up other possibilities such as rotating the separated body and Lofting or Sweeping the bridge between them.

For a more in-depth look at the Move Face, Delete Face and Split techniques consider the video guide Direct Editing for Imported Models.

Troubleshooting Direct Edits

When using the move face feature, it is crucial to select all the faces that need to move. This may sound obvious, but in practice is easy to overlook. Observe Figure 12 below, comparing two alternate selections in a move face translation.

In the image on the left, the chamfers are not included in the selection. In the resulting preview, a hint at how the move face command works can be seen: the surrounding chamfer faces are extended using the existing face data that is present in them. In this case, this is not the intended design change, and the image on the right shows that with the chamfers included in the selection the size of the entire ledge can be extended.

Figure 12. Move Face Troubleshooting: Incomplete selections.

More practically, missing a face or two in a direct edit selection can cause the feature to fail outright and give a puzzling rebuild error. There are a few things that may cause a direct edit feature to fail, but incomplete selections are one of the most common.

Thankfully, there are selection tools that help automate selection of faces, using the Select Connected Faces popup toolbar when initially making a selection in the move or delete face commands, visible in Figure 13 below.

Figure 13. Select Connected Faces toolbar.

Aside from incomplete selections, faulty faces in the model can prevent direct edits or any other type of modeling feature from successfully generating.

As faulty faces are more common on imported files, Import Diagnostics is a valuable tool to identify and repair them, as visible in Figure 14.

Figure 14. Import Diagnostics.

Note that if an import was performed with 3D Interconnect enabled, it will be necessary to “Dissolve Feature” on the imported model to break the external file reference before Import Diagnostics can be performed.

If no faulty faces are present or the model is SOLIDWORKS native, and all the proper selections are present, then it’s possible that there isn’t enough information in the surrounding faces for SOLIDWORKS to perform the move.

This is a common failure for situations such as offsetting a fillet inward, once the offset is great enough it exceeds the radius the offset will fail. These types of issues can be identified at least by testing smaller offsets and trying to identify the problem area.

Problem areas (such as fillets) may be removed with the Delete and Patch command and then added back on after the move is performed.

For complex surfaces and organic shape geometry, it is possible to run into outright limitations with the Move Face command. The performance will be related to how cleanly, and the manner in which, the surfaces were constructed and how much underlying data they contain. But if a failure occurs trying to move or delete and patch a complex surface, the only reliable fallback is to resort to manual surface modeling tools.

Direct Edits and Drawings

One reason direct edits may not be suitable for a production CAD file is their effect on drawings. When using Imported Annotations or the Model Items tool to import dimensions onto the drawing sheet, any dimensions in the base sketches will not represent the final state of the geometry.

If the drawing is detailed using manually created Smart Dimensions, then this is not of much concern.

Geometry Comparison

There are a couple of geometry comparison tools available in SOLIDWORKS, but the new Body Compare functionality added in all versions of SOLIDWORKS 2020 and newer has the most utility for comparing imported files.

Notably, it is capable of comparing solid bodies against surfaces and even mesh file types such as STL, making it a valuable tool for comparing revisions of imported bodies.

Figure 15. Body Comparison in SOLIDWORKS 2020.

Conclusion

Direct editing features such as the Move Face and Delete Face command can be useful to modify and simplify imported models or to perform final adjustments such as adding clearances to SOLIDWORKS native CAD files. The features themselves still produce a model history that can be edited, configured or suppressed.

Failing direct edits can be troubleshooted by ensuring proper face selection, testing a smaller offset and inspecting the base geometry for faults.  Understanding how and when to use each direct editing feature opens up a variety of possibilities not available in conventional modeling workflows. 

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One of the most common applications of Flow Simulation today though is thermal analysis for predicting cooling performance of electronics and other heat generating components. The ability to simulate heat conduction combined with convective heat transfer generated by airflow over heatsinks and chip packages offers a high degree of confidence in temperatures predicted, especially when compared to traditional hand calculations or FEA-based thermal analysis where assumptions about airflow must be input in the form of convection coefficients.

This article will examine the use cases of SOLIDWORKS Flow Simulation as it relates to thermal analysis, with a specific focus on predicting the performance of electronics cooling systems.

Background & Terminology

Flow Simulation is a computational fluid dynamics (CFD) analysis package using the finite volume method. The computational domain is broken up into a Cartesian mesh, a grid-like mesh made up of box-shaped cells, which will be discussed later in this article.

Key parameters of interest are tracked during the solution by the creation of user-defined goals. In the case of steady-state analysis, the convergence of goals is tracked and utilized as a stopping criteria for the solver. In other words, the solver continues to iterate until the values of the goals flatten off, indicating that the system has reached steady-state equilibrium. The appropriate definition of goals is thereby crucial to ensuring accuracy and reasonable computation time.

Steady-state and transient calculations can be performed. By default, new projects are treated as steady-state. Transient analysis is enabled via the time-dependent checkbox in the Project Wizard, which iterates over physical time steps and stores results over the time history of the solution, at the cost of extended solution time. Transient analysis makes it possible to input curves for conditions such as heat sources to represent duty cycle, or analyze problems which may be constantly fluctuating and have no steady-state solution at all.

Analysis can be internal or external. Internal analyses represent closed wall systems such as electronics enclosures, or a piping system or manifold. External analyses represent a larger computational domain, such as a room full of air around the product to be analyzed.

Mechanisms of Heat Transfer

By default when creating a new project, Flow Simulation simulates heat transfer in fluids and performs a steady-state analysis.

The Project Wizard allows selection of various physical effects at the time of project creation. Enabling the option for heat conduction in solids will open up a variety of new options in the project, namely: the ability to define materialswith thermal conductivity properties, heat sourceswith their own temperatures or heat generation rates and goals that track the temperature and  thermal properties of various solids.

Figure 1. Flow Simulation Project Wizard.

The ability to simulate heat transfer in fluids is maintained, so heat generating solids will automatically convect heat away to the surrounding fluid.

Enabling the radiation option in the Project Wizard allows definition of emissivity and performs simulation of radiative heat transfer.

Heat removal in the high-powered electronics manufactured today is typically accomplished by air or liquid cooling. As the thermal performance of such systems is often dominated by conduction and convection, radiative heat transfer is often assumed to be minor and neglected in the simulation to reduce solution time.

Radiation becomes crucial between components with very high temperatures, or those operating in near-vacuum conditions. Applications where radiative heat transfer is critical include: design of light bulbs and lamps, heating elements and furnace equipment, and spacecraft and satellites.

For the special case of problems that are dominated by conductive heat transfer and/or radiation, Flow Simulation has an option for “Heat conduction in solids only” which completely disables the fluid flow calculations—effectively removing the “flow” in Flow Simulation. This option is appropriate for drastically speeding up calculation of systems that operate in a vacuum.

Example 1: Natural Convection Analysis

The amplifier pictured in Figure 2 below is the subject of a natural convection thermal analysis, using an external analysis project type, as well as the options for heat conduction in solids and gravity (appropriately oriented). Solid materials with appropriate thermal conductivity are defined and heat sources are applied to any heat generating components.

As the option for Gravity is enabled in the Project Wizard, the heating of the surrounding fluid will cause convective currents to form as the heated fluid rises due to its lighter density and heavier cooler fluid descends to take its place—a process known as natural convection.

Figure 2. Example of Natural Convection Analysis of Amplifier.

Aside from setting up goals to track the temperatures of the solids of interest in the study, not much else is required from the user to quickly establish baseline results. Accuracy of the simulation can be improved by refining the mesh and establishing thermal contact resistances, as well as some specific considerations unique to external analyses.

Conjugate Heat Transfer

The convection coefficient, or “h” value, varies over a wide range based on fluid flow and geometry. It is calculated as an output from the Flow Simulation and can be extracted as a results parameter. This makes a CFD-based thermal analysis capable of solving coupled or “conjugate” solid/fluid heat transfer, which is a much more reliable tool for predicting cooling performance than hand calculations or analysis performed in thermal FEA, which require inputting a best guess at an h-value.

As a thought exercise, consider the case of a thermal FEA study for a heatsink. Without a way to accurately predict changes in h-value due to geometry, the results of the study will indicate that more fins on a heatsink is always superior due to the increased surface area they present. In reality, there will be an optimal point in terms of fin density that, once exceeded, will begin to impede the surrounding fluid flow and reduce the effective convection coefficient.

Thermal FEA will also fall short if the orientation of a heatsink is changed with respect to gravity direction, which can drastically affect thermal behavior for passive cooled systems.

SOLIDWORKS Flow Simulation is able to accurately predict these behaviors and allows for optimizing heat sink design, as well as predicting performance in alternate orientations.

Special Considerations for Natural Convection

Two considerations of note can affect results accuracy for natural convection problems and other external analyses. First is representing the geometry in its appropriate orientation and positioning. If a device is to be mounted flat on a table, the Gravity direction in the project must be oriented appropriately. Additionally, if the device is being mounted flat to some piece of equipment, the flow restriction from this should be modeled in.

The geometry used for analysis should match as closely as possible the geometry used in physical testing or production implementation, which may necessitate modeling a blocking surface in CAD.

The impact of such geometry is visible in the flow trajectories of Figure 3 below.

Figure 3. Flow Trajectories With and Without Blocking Surface.

The second consideration for external analyses is the sizing of the computational domain. Figure 4 below compares three different computational domain sizes.

Figure 4. Sizing of Computational Domain.

There is no exact rule for predicting adequate computational domain size. Rules of thumb can be found in the literature and typically will vary based on the velocities of fluid flow present in the analysis. Too small of a computational domain may negatively impact results, while an oversized computational domain will needlessly extend solution time.

Much like mesh cell refinement, a best practice would be to conduct a virtual experiment by cloning (duplicating) the Flow Simulation projects and iterating on computational domain size until an adequate balance of accuracy and solve time is determined. Such an experiment can determine guidelines that can be used for similar geometries and analyses moving forward.

Rapid iterations can be performed via the parametric study functionality, which is discussed later in the article.

A step-by-step tutorial covering set up of a simple natural convection problem and discussing these special considerations can be found in this video.

Example 2: Internal Analysis with Forced Convection

Electronics enclosures are often best represented by an internal analysis. Setup of an internal analysis requires capping off any openings of the enclosure. Flow Simulation offers a Lid Creation tool that can help speed up the process of creating lids to cap off the geometry. In order to conduct an internal analysis, the software must extract a “watertight” fluid body from the enclosed space.

Results from an internal analysis of a rackmount server are visible in Figure 5 below.

Figure 5. Internal Flow of Rackmount Server.

If it ends up being too difficult to create a watertight body, a fallback method is to approach the project as an external analysis. In this scenario, it could be thought of as a a pseudo-internal analysis within a slightly larger computational domain, as visible in Figure 6 below.

Figure 6. External Approach for an Enclosure.

Representing an enclosure within an external analysis in this way has a couple additional benefits: it can predict air leakage through any openings, as well as predict the convective cooling of the entire enclosure to the environment, with the trade-off of additional solve time required.

Forced convection from cooling fans is represented by definition of fan conditions. A handful of fan definitions are included with Flow Simulation by default, but additional representations of cooling fans (and even water pumps) can be user-defined by inputting a static-pressure curve. They can be placed as inlet or outlet fans at the edge of the computational domain, or internal fans in the middle of an enclsoure.

Figure 7 below shows a static pressure curve as input in the Flow Simulation Engineering Database, using data from the manufacturer’s specification sheet for a fan.

Figure 7. Fan Curve Definition.

The optional add-on module for SOLIDWORKS Flow Simulation known as the “Electronics Cooling” module greatly expands the built-in library of manufacturer’s fan definitions, as well as adding a variety of other useful features for electronics analysis such as enhanced materials for PCBs and IC packages, additional heating models such as two-resistor components, Joule heating and native support for heat pipes.

Aside from preparing the geometry for internal analysis and defining fans, the bulk of the setup work for this type of problem lies in defining the appropriate solid materials and heat sources. There are productivity tools that can help, such as importing setup conditions from child components and propagating definitions across all assembly instances.

Example 3: Liquid Cooling with Fluid Subdomain

It is increasingly common for high powered equipment such as computers in machine learning workloads to utilize liquid cooling. Liquid cooling may be used as a complete cooling solution, or in tandem with air cooling. An example analysis setup for combined liquid and air cooling is visible in Figure 8 below.

Figure 8. Open-Loop Liquid Cooling with Fluid Subdomain.

This liquid cooling within an air-cooled internal analysis is accomplished via a fluid subdomain. Fluid subdomains allow separating distinct fluid regions and applying unique conditions such as inlet temperature and flow rate to the distinct region. This process allows for simulation and prediction of liquid-air heat exchangers and radiators.

Parametric Studies

SOLIDWORKS Flow Simulation projects update automatically with changes to the CAD geometry. Another capability is to manually “clone” or duplicate projects to test and store the results of such variations.

Anytime there are many iterations required, such as when attempting to optimize a geometry, users can take advantage of the in-built parametric study functionality, which allows creating a virtual design of experiments (DoE). Such a DoE setup for optimization of the CPU cooling waterblock is visible in Figure 9 below.

Figure 9. Waterblock Optimization with Parametric Study.

Parametric studies allow varying multiple parameters (in this case, the thickness and number of fins), tracking results parameters and optionally calculating an optimal design point.

Meshing Technology in Flow Simulation

The Cartesian or grid-shaped mesh that SOLIDWORKS Flow Simulation utilizes is relatively unique among analysis tools. This meshing technology brings with it some distinct advantages, such as ease of generating the mesh and precise control over how much detail is included in the analysis.

Compared to a tetrahedral-based mesh which must start by resolving the solid geometry, the approach used in Flow Simulation begins by subdividing the computational domain. This means that it’s possible to force a coarser mesh density, which will effectively ignore tiny details in the model without actually performing extensive geometry simplification. This ability to “look past” tiny solid features means that Flow Simulation has a much easier time generating meshes for complex geometries.

This also comes with some additional responsibility for the user to ensure that areas of interest are being adequately resolved by the mesh. While the default mesh settings are often a good starting point to establish a baseline, manual adjustment of the global refinement settings, as well as a few carefully placed Local Mesh refinements, can go a long way toward ensuring accuracy of the solution.

Figure 10 below shows an example of mesh refinement around a CPU heatsink using a local mesh control, and a second lesser tier of local mesh refinement defined around the RAM modules.

Figure 10. Mesh Refinement around Heatsink.

Color-coded mesh refinement plots help the user to identify levels of refinement and the areas to which they apply throughout the meshing process.

Conclusion

This article presented the case that thermal analysis involving convection is best analyzed using a tool capable of natively solving conjugate heat transfer, such as the CFD-based approach presented by SOLIDWORKS Flow Simulation. Predicting thermal performance in this way prevents the need to estimate convection coefficients, as would be required to perform hand-calculations or an FEA-based thermal approach.

Several examples were showcased detailing setup of natural convection and forced convection problems for air-cooled electronics, as well as how combined liquid-to-air cooling can be analyzed.

Use of a CAD-integrated CFD tool also allows for rapidly analyzing geometry variations either through manual duplication of projects, or by conducting a virtual design of experiments utilizing the parametric study functionality in Flow Simulation. Lastly, a robust set of meshing defaults should make it easy to establish baseline analyses with limited geometry preparation required by the user.

Advances in software multithreading, combined with the rise of affordable many-core CPUs, has also drastically lowered the solution time requirements for CFD analysis on modern hardware—making it a viable tool to incorporate early on and throughout the design process.

To learn more, check out the whitepaper Design Through Analysis: Today's Designers Greatly Benefit from Simulation-Driven Product Development.

Custom Materials

There are many materials in the SOLIDWORKS Visualize library of materials, and more materials are available from the “cloud” library which can be toggled on at any point. But to add the final polish to a difficult rendering, it’s useful to understand how to define custom materials.

Visualize supports many different categories of material, from specialized gemstone materials to more commonplace metals, plastics and clearcoat paint. These appearances support varied texture channels such as bump, roughness and alpha, each of which have an impact on the resulting appearance.

An example of a customized brushed metal texture is visible in Figure 1 below:

Figure 1. Appearance texture channels.

Simply experimenting with modifying the textures and magnitudes for these channels can greatly improve the effect of the final rendering. Adding a mild bump map to almost any surface is a great way to prevent rendered surfaces from looking too smooth, which is a common giveaway of prerendered graphics. A bump map, for instance, can represent the grit of a textured plastic, or the spray pattern on a painted or powder coated part.

The fidelity of the texture becomes more important the closer the camera is to the model surface.

Multi-Layer Appearances

Complex materials and surface imperfections can be represented easily by taking advantage of multi-layer appearances. Like the name implies, these are stacks of up to four appearances that can be laid over each other in an adjustable order.

Straightforward applications include selectively adding scuff marks, texture or defects to an otherwise pristine surface to create a weathered or used look. See Figure 2 below, where multi-layer appearances were used to add fingerprint marks to the touchscreen.

Figure 2. Multi-layer appearances.

This appearance is combining the default Solid Glass material with a custom Fingerprints appearance created using free textures from poliigon.com.

To learn more about multi-layer appearances and textures setup in general, check out this video.

Custom Backplates & HDR Environments

Like materials, it’s easy to rely on built-in environments and backplates. Environments especially are crucial as they define the lighting in the scene—assuming you aren’t using custom defined lights in Visualize Professional.

If you ever want to convincingly fake overlaying your product onto an existing image, it’s a requirement to modify the environment. This is because in addition the lighting, the environment is the source of the reflections for the geometry. If you are using reflective or shiny appearances, simply swapping out the backplate without adjusting the environment will result in inaccurate reflections that will reveal your image is a rendering.

Figure 3 below shows the stock Camaro file with an 8k HDRI environment from HDRI Haven loaded. Note how the reflections of the sky and surrounding ground are reflected in the vehicle hood.

Enabling floor shadows and caustics can help improve the feeling that the object belongs in the environment.

Figure 3. Custom 8k HDRI environment.

High resolution HDR environments (8k and 16k) can replace the need for backplates all together for lower resolution outputs. For the best quality, though, it’s recommended to use an environment with matching backplate. If you are using your own backplate, try to find a matching HDR environment that will emulate the lightings and reflections.

It’s also quite easy to edit or create HDR environments yourself. Most newer Android smartphones have the capability of capturing a “photo sphere” or 360 degree photo, which can be brought into Visualize as an environment. iOS devices can use a similar function through the Google Maps app. HDR environments can be edited in a photo editor such as Photoshop or GIMP to make precise adjustments.

MDL Materials

Created by NVIDIA, MDL materials are a standard for physically-based materials that SOLIDWORKS Visualize now supports. These materials offer even more capability than the user defined materials in SOLIDWORKS Visualize, allowing them to accurately represent difficult materials such as textiles and liquids.

An extensive library of over 2,000 MDL materials, called the vMaterial library, can be downloaded directly from NVIDIA.

Since each MDL material is “physically based,” it will have unique adjustment properties for each class of material. In Figure 4 below, special properties for a metal weave material are displayed on the right. A sample rendering combining mahogany, hammered copper and floral carpet MDL materials is displayed on the left.

Figure 4. MDL materials in Visualize.

The materials in the AEC category are especially helpful. These include common building materials such as flooring, and commonly used interior/exterior materials as well as many different grades of metals.

To get the MDL materials into Visualize, you’ll have the best luck using the Windows File Explorer and clicking and dragging the relevant .mdl file from the vMaterial install location to the Visualize project.

Figure 5. Material library in File Explorer.

As visible in Figure 5 above, the .mdl files are accompanied by .png thumbnail previews of their different variants. This is useful to choose the .mdl to add to your project. Note that for many materials, adding one .mdl file will result in many appearance variants being imported.

For this reason, it is recommended that you do not batch import the .mdl materials, as this will inflate project size and reduce performance. It’s better to drag them in as needed per project.

Custom MDL materials can be created with 3^rd party tools such as the procedural texture generation program Substance Designer.

IES Light Profiles

Continuing the “physically based” theme, IES light profiles allow for definition of standardized custom light sources in Visualize Professional that represent real world lights. This can be very helpful for more accurately representing complex indoor lighting.

Figure 6. IES light profiles. (Image from SOLIDWORKS help files.)

You can learn more about IES light profiles in the What’s New section of the SOLIDWORKS Help Files.

Model Sets & Configuration Import

Model sets are a feature of SOLIDWORKS Visualize Professional that won’t make a rendering look better, but will make the process of batch rendering much easier.

Model sets themselves represent various states of the model inside a single .SVPJ file by increasing the polygon count active at any given time. This lets many different versions of the product be represented and stored efficiently.

As of SOLIDWORKS 2021, Visualize Professional can now batch import SOLIDWORKS configurations for parts and assemblies into corresponding model sets. All that is required is flagging the configurations you want to import with a Display Data Mark inside SOLIDWORKS beforehand, as seen in Figure 7below.

Figure 7. Adding display data mark.

Model sets are also useful to manually create an exploded view inside Visualize by translating and moving parts around, or to represent a product through different states of its range of motion.

Decals & Video Decals

Decals allow placement of externally sourced images such as labels, markings or in the case of LCD displays, the screen image. In additional to importing an image for the decal, Visualize allows applying an appearance to the decal.

This means that things like metallic labels and stickers can easily be represented by applying the appropriate material to the decal. For screen images, it makes it easy to apply an emissive appearance to the decal to create a more convincing render.

Visualize Professional also allows usage of video decals in animations. Rendering a screen image directly into the project adds realism that would be very difficult to accomplish in a video editor in post.

Figure 8. Video decal with emissive appearance.

To create the animation in Figure 8 above, a screen recording was performed on a smartphone, and this recording was inserted as a video decal beneath the glass of the virtual phone display in the Visualize project. Then an emissive appearance was applied.

This combination of layering of materials adds a significant amount of realism to the final rendering, which would be very difficult to achieve in a video editor—especially once camera motion is added.  To learn more about this process, consult this video.

Camera Properties

Adjusting the camera properties can add some artistic flair to any static rendering or animation.

Parameters such as depth of field focal distance and focus target can be adjusted between shots or keyframed in an animation to pull the viewers attention to a specific area. In cinematography, this is known as “rack focus” or “pulling focus” and the basic effect is illustrated in the animation in Figure 9 below.

Figure 9. Rack focus demonstration.

Another great parameter to explore is the perspective amount or focal length of the camera, which can also be animated. Combined with controlling the distance of the camera, this can recreate effects such as “dolly zoom.”

Denoiser

The Denoiser option can dramatically improve rendering performance, especially for accurate mode renders. With complex lighting, it can take multiple rendering passes to remove grain from the image due to the many light bounces that are required. Enabling the Denoiser option from the toolbar will remove noise from the rendering with an AI algorithm.

Figure 10. Denoiser toggle.

In many cases, this reduces the required number of rendering passes by a factor of 10x or more. Additional information on the denoiser is available here in SOLIDWORKS Help. In my experience, it works best whenever the camera is not very close to detailed rough surfaces, such as cast metal or frosted glass, as some of that detail may be artificially smoothed over.

Render Layers

While much of the focus of this article has been on physically correct or physically-based materials and settings, sometimes requiring the desired artistic effect involves faking things. When it comes to tweaking the final rendering, render layers are a valuable tool.

Figure 11. Render layers output imported to photo editor.

Figure 11 above shows the render layer output options available in Visualize Professional. For the 2021 version, this type of rendering output has dramatically improved performance.

It is recommended that you import the various render layers as layers into your photo editor of choice and experiment toggling the layers and trying various overlay modes such as multiply or lighten only. This is a great way to artificially increase or decrease the effect of shadows, or make the output appear more shiny/glossy than the original render.

You can learn more about the individual render layers here in SOLIDWORKS Help.

Conclusion

SOLIDWORKS Visualize makes it very easy to get convincing output out of the box with its built-in materials and environments, and it is a huge step up over the materials integrated with SOLIDWORKS and PhotoView 360.

This article outlined a number of methods to take your renders even further and create truly convincing product representations via custom material creation, custom HDR environments, physically based MDL materials, decals/video decals and artistic tricks such as overlaying render layers or modifying camera properties. Hopefully these tips give you some inspiration for your next photorealistic rendering project.

To learn more, check out the ebook SOLIDWORKS 2021 Enhancements.

This article will examine two case studies and describe techniques relevant for setting up any large assembly analysis, as well as some of the key relevant enhancements in SOLIDWORKS Simulation 2021 and other recent versions that make analyzing large assemblies much easier.

Example 1: Mold Base Solid Mesh Analysis

Consider the case of the injection mold in Figure 1 below. It’s important to establish a plan for the level of detail expected in an analysis before beginning study setup. In this analysis, the goal is to predict deflections and stresses around the mold cavities when subjected to the injection pressure and clamping forces.  

Figure 1. Case Study - Mold Base Analysis.

Contact interactions (formerly called “no penetration”) will be used sparingly at the interface between the mold halves. Contact significantly increases solve time, so the remaining plates will be assumed to be bonded. For loadings and restraints: one side of the mold is fixed, a clamping force is applied to the other side and a pressure is applied to the cavity faces exposed to the polymer.

Note: for this type of setup, it’s important that the clamping force is sufficiently large that it exceeds the clamp tonnage requirement, which can be estimated as the molding pressure multiplied by the 2D surface area of the cavities. Insufficient clamping force would cause the halves to separate and the solution would become unstable.

The pins and bolts in the assembly will be suppressed and replaced with the appropriate Virtual Connectors, a special type of simplified representation available in SOLIDWORKS Simulation to represent features such as pins, bolts, springs and welds.  

Geometry Preparation Tips

In an assembly with this many components, it’s worth creating a separate configuration just for analysis. SOLIDWORKS provides a variety of selection tools such as Select by Size to select small components or Select Toolbox to select all Toolbox components.

The most powerful method for identifying and suppressing small components is to use Assembly Visualization, pictured in Figure 2 below. This command is accessed on the Evaluate tab of the Command Manager and the column style display can be customized to sort by the volume of various components.

Figure 2. Assembly Visualization for small component suppression.

Shift-selecting components from the top selects the bulk of the small components that can be suppressed. If there are small components that are critical to the analysis, they can be Ctrl-selected to remove them from the selection before suppressing.

Calculating Mesh Sizes

The automatic defaults for mesh generation are often sufficient for creating a baseline mesh on many applications. But for a complex assembly, it may be necessary to manually determine mesh sizes. A foolproof workflow of determining the required mesh size is presented in Figure 3 below.

Figure 3. Simple Process for Meshing Success.

Open or isolate any parts that have small detailed features. Unnecessary detail can be suppressed or eliminated with extruded cuts or direct editing features such as Delete Face. Remaining detailed features must be resolved by the mesh. This means that, at minimum, the mesh size must be equal to or smaller than small edges and fillets.

Use the Measure Tool to size up the smallest features in the simplified model and use that measurement as an estimate for mesh element size. It’s best to apply a Mesh Control only in the areas where the refinement is necessary, then create the mesh.

Note that performing these steps at the part level has the benefit of fast mesh generation and the ability to quickly experiment with mesh sizes. Mesh controls and other features defined on “child” component studies like this can later be imported to the top level assembly using Import Study Features, described in more detail in Example 2 of this article.

These mesh controls can later be refined further for additional accuracy in prediction of local stresses. I would generally recommend waiting on any additional refinement until a baseline or “first pass” analysis is performed on the top level assembly to verify that the study setup is correct.

Mixing Mesh Quality

For solid mesh studies such as this one, SOLIDWORKS 2020 added the capability of mixed mesh quality.

Before this enhancement, it was necessary to choose on a global level between draft quality and high quality mesh. Draft quality mesh uses linear tetrahedrals that have many fewer nodes and degrees of freedom than high quality mesh, resulting in faster solution times with the tradeoff that it tends to underpredict stresses and displacements.

The global choice meant that draft quality was generally reserved exclusively for validating study setup on a crude first pass analysis.

Now that high quality mesh can be applied selectively to areas of interest, there is the possibility of carefully incorporating draft quality into regions that are sufficiently distant from the area of interest.  The two mesh qualities are color coded by default, and visible in Figure 4 below.

Figure 4. Completed Setup for First Pass Analysis.

Note that the presence of any shell or beam elements will remove the mixed mesh quality capability.  Care must still be exercised to ensure that the mesh refinement is adequate.

This study resulted in 1.5 million degrees of freedom and solved in under 30 minutes on an entry level workstation laptop. The results for stress and displacement, shown at an exaggerated deformation scale, are visible in Figure 5 below.

Figure 5. First Pass Results for Stress and Displacement.

The utilization of contact interactions between the mold halves is what is likely responsible for the solve time being as long as it is, but the 1.5 million degrees of freedom total leaves plenty of headroom for additional mesh refinement or reintroducing more high quality mesh later on.

The exaggerated deformation presented is useful to verify the loading setup conditions. In this case, it can be seen that the load and fixture scheme employed is probably not accurately representing the real life loading inside the injection mold machine.

This is because in reality the mold assembly will be squeezed between large and extremely stiff platens, which would greatly restrict the ability of the base plates to deform.  A more realistic analysis could be performed by using a new restraint scheme, or by modeling rigid bodies to represent the molding machine platens and squeezing the mold assembly between those.

Setup problems such as this can be more quickly determined using a “first pass” analysis rather than waiting hours for a very refined mesh study to solve. In fact, it probably could have been identified by running a globally bonded study, which would have solved in only a few minutes.

Example 2: Gantry Shell Mesh Analysis

Consider the example of the gantry crane pictured in Figure 6 below. While not inherently necessary for such an application, this model was purpose built with simulation in mind.

Figure 6. Case Study - Gantry Analysis.

In the case of the truss, geometry like this would often be represented as weldments in SOLIDWORKS, which would automatically convert into beam elements in the simulation. However, in this case, the truss was modeled using surface bodies, which will automatically convert into shell mesh.

The shell mesh provides greater detail and prediction of local stress concentrations than would be possible using a beam mesh. It also enables the use of contact interactions between the trolley, which will slide along the frame. Contact is also defined on the rollers at either end of the gantry. The remaining geometries such as the trolley and end rails were meshed with the default solid mesh. A Remote Load/Mass is used to represent the weight of the payload. These are useful to represent the effects of excluded components or other cantilevered loadings.

Simplification such as shell mesh definition requires additional setup compared to running an exclusively solid mesh study. Shell thickness, offset and orientation must be defined for the relevant surface bodies, and frequently it is necessary to manually define local contact interactions.

This process is expedited by using the Import Study Features command, which was added in SOLIDWORKS 2018 and is visible in Figure 7 below.

Figure 7. Import Study Features.

Import Study Features allows defining the simulation setup on a study of a child component, and then importing this setup up to the top level. Features to import, such as material/shell definition, mesh controls, loads and fixtures, can be selectively filtered.

Perhaps the most useful feature is “Propagate … to all instances” which will automatically pattern the imported features to the relevant component instances in the assembly.

Import Study Features also allows for rapid re-use of components which may need to be analyzed in different top level assemblies.

The heavy use of shell mesh on this study and the limited contact areas allowed it to solve quickly. It was easy to test alternate configurations with the trolley at various distances along the gantry.

Figure 8. Gantry Analysis Results.

The results of the analysis with an off-center trolley are depicted in Figure 8 above. The analysis totaled 850k degrees of freedom and solved in just a few minutes.

Productivity Shortcuts & Simulation API

Setting up simulations on larger projects often involves repetition of monotonous tasks such as defining many loads and fixtures. SOLIDWORKS Simulation allows for keyboard shortcuts, mouse gestures and shortcut bar customization for simulation to help speed up the process.

Pinning contact and connector menus so they remain persistent on the screen is another way to save time. Outside of the “Import Study Features” mentioned earlier, there are limited means to pattern loads or connectors.

One solution is to use the SOLIDWORKS Simulation API. The macro recorder is capable of recording simulation actions and outputting a VBA macro with the appropriate API calls. These can form the basis for automation to quickly generate simulation setups and perform detailed results post-processing.

Figure 9 below shows an example VBA macro integration with Microsoft Excel, which coordinates with SOLIDWORKS Simulation to setup and run a study and then extract the results.

Figure 9. Microsoft Excel Simulation API Example.

A variety of useful downloadable Simulation API examples are posted in a SOLIDWORKS blog article.

Simulation 2021 Enhancements

The examples portrayed throughout this article took advantage of a number of the performance enhancements in SOLIDWORKS 2021.

Performance Enhancements

The Blended Curvature Based mesher was rearchitected for the 2021 version, and now produces much better aspect ratios, as well as generating large meshes very efficiently. In SOLIDWORKS Simulation Professional and higher, the BCB mesher is multi-threaded very well. 

When meshing large assemblies, the 12-thread CPU in my laptop frequently maintained 100% utilization, as depicted in Figure 10 below, and the mesh generated much faster than in previous versions. 

Figure 10. BCB Mesher Multi-threading in Simulation Professional 2021.

There’s a similar story in terms of solver performance. The FFEPlus solver has substantially improved performance in 2021, primarily due to improvements in multithreading, as visible in Figure 11 below.

Performance increases have also extended to the Intel Direct Sparse solver and results post-processing which can both manage much larger data sets effectively.

Figure 11. FFEPlus Solver Performance in 2021. (Image from SOLIDWORKS Help Files.)

One of the great things about SOLIDWORKS Simulation is that even the base simulation packages are able to analyze large problems effectively – there are no hard restrictions on problem size in terms of components or node/element count.

Performance by Package Level

Up until 2021, all versions of SOLIDWORKS Simulation also offered similar performance in terms of mesh and solve time. With the 2021 version and the substantial rearchitecting of the meshers and solvers, for the first time there is a difference in performance gap between the different packages.

SOLIDWORKS Premium and the SOLIDWORKS Simulation Standard are limited to single-core meshing for the new Blended Curvature Based mesher. The solvers for SOLIDWORKS Premium and Simulation Standard are limited to 8 cores / 16 threads – admittedly still a generous limit that is unlikely to be bumped into on a run-of-the-mill system today.

SOLIDWORKS Simulation Professional and higher packages offer unrestricted multi-threading for both meshing and solving. With the advent of affordable many-core CPUs, this distinction will mean better quality of life for performing large assembly analysis with the higher level simulation packages in the future.

Interface Changes

Figure 12. New Settings for Mesh & Contact in 2021.

Interface changes also made their way into Simulation 2021. In the context of large assemblies, one of the most useful options is the ability to quickly toggle all part definitions to solid mesh, as visible in the left of Figure 12 above. This is a great diagnostic tool or fallback to troubleshoot faulty beam or shell conversion, or for cases where the additional detail of solid mesh is required.

Weldments can also then be batch converted to beams, and sheet metal parts to shells.

In the Simulation options, there are many more contact settings exposed that were previously inaccessible to the user – including a gap range for global bonding which can be adjusted to automatically bond over small gaps.

A new feature is stabilization for contact areas. This is said to produce much more accurate stress distributions for certain contact problems, as illustrated in the right of Figure 12 above.

For more detailed information on the Simulation 2021 enhancements, consider taking a look at these SOLIDWORKS Help files.

For an additional resource, consider viewing the associated live presentation this article was based on, which explores shortcuts and the setup process of these analyses.

Conclusion

This article examined two case studies of large assembly analysis in SOLIDWORKS Simulation, discussing the planning process as well as a number of useful simplification and setup techniques.

Enhancements to SOLIDWORKS Simulation for 2021 and recent years have greatly improved the viability of setting up large simulation studies.

Additional resources were presented to learn more about What’s New in 2021 and the Simulation API.

Check out the whitepaper Design Through Analysis: Simulation-Driven Design Speeds System Level Design and Transition to Manufacturing to learn more.

For manufacturers, FAI reports represent a way to show to a client that they are holding up their end of the bargain. Discerning customers buying parts from manufacturers can conduct their own FAI to verify the manufacturer’s work before putting those parts into service.

First Article Inspection and AS9102

The AS9102 template serves as one of the most widely used standards for First Article Inspection. Originally developed for the aerospace industry, variations on this template are used throughout all kinds of quality control departments around the world.

Most notably, it includes rows for each “characteristic” which represent every dimensional requirement or note of an engineering drawing, with columns for the tolerance limits established by the drawing and the results measured off the sample part(s).

Figure 1. Snippet of example AS9102 Form 3.

Accompanying the AS9102 form is a “tagged” or “ballooned” drawing that associates each characteristic with the callout on the drawing.

Figure 2. Example ballooned drawing view.

Generating a First Article Inspection form using a manual process means “ballooning” each characteristic and, at a minimum:

• Mapping over the nominal value of the characteristic and its location on the drawing.
• Noting the tolerances of the characteristic.
• Computing upper and lower limits based on tolerances and nominal dimensions.

This manual process may be manageable for simple drawings, but as the number of drawing sheets and dimensions per view grows, it quickly becomes unsustainable without an automated tool. With so much transcribing required, this manual process is also rife with the opportunity for error.

Statistical Process Control 

Statistical Process Control, or SPC is a term that should be familiar to any company employing or pursuing lean manufacturing, such as Lean Six Sigma. SPC involves performing inspections on a statistically significant number of sample parts during or after a production run. This is made feasible by inspecting a reduced set of characteristics—often only the most critical dimensions.

By sampling a significant number of samples, statistical analysis is performed to predict failure/rejection rates before the parts ever make it to FAI and understand how tightly the process is controlled. 

SPC employed in-process can even catch tool wear issues, a degrading piece of machinery and other problems before they happen.

The automotive industry relies on a part release program called PPAP (Production Part Approval Process) that combines first article inspection and SPC.

SOLIDWORKS Inspection Software

SOLIDWORKS Inspectionis a software package that automates inspection report creation for both First Article Inspection (FAI) and Statistical Process Control (SPC). It provides a variety of means for automatically extracting characteristics from a part or drawing, mapping the requirements into the appropriate form along with location callouts and automatically computing the upper and lower limits from tolerance information.

The tool can be used as a standalone software by Quality Control personnel who may not even have access to CAD, or as a SOLIDWORKS add-in to allow leveraging of SOLIDWORKS native data.

SOLIDWORKS Native Inspection Report Creation

Creating an inspection report based off SOLIDWORKS native data is a straightforward process with the SOLIDWORKS Inspection add-in. A prompt to create the Inspection report allows the user to select a template, establish the “default” tolerances for when no specific tolerance is specified, and reference SOLIDWORKS custom properties for information such as Part Name and Part Number.

Finally, Extraction Settings are adjusted to control which characteristics (dimensions, notes, hole callouts) will be automatically ballooned and extracted from the file.

Once the checkmark is clicked, SOLIDWORKS Inspection combs over the drawing and tags the relevant dimensions, while building a list of Characteristics visible in Figure 3 below.

Figure 3. Inspection project prompt and extracted characteristics.

This list of characteristics represents a preview of the data that will be exported to the relevant inspection form template. SOLIDWORKS Inspection ships with a number of templates including AS9102 variants and several templates for process control. The Microsoft Excel templates can be fully customized to inject company branding or make any other modifications required to formulas and data.

Figure 4. SOLIDWORKS Drawing set to extract only dimensions marked for Inspection.

In addition to the ability to extract data from 2D SOLIDWORKS drawings, the Inspection add-in can also extract data directly from SOLIDWORKS 3D CAD models prepared for Model Based Definition.

Figure 5. SOLIDWORKS MBD-enabled model with characteristics extracted.

Forward-looking organizations embracing MBD may find that the Product Manufacturing Information or PMI associated to the CAD model can also be used in other downstream software, such as by their CNC and CMM programming tools.

PDF-Based Inspection Report Creation

SOLIDWORKS Inspection Standalone is primarily used for inspection report generation using PDF versions of engineering drawings. This is useful for manufacturers and machine shops that may not be provided with the SOLIDWORKS native documents, or the worker in Quality Control who may not have access to a SOLIDWORKS CAD license.

While not fully automatic like the add-in, the standalone tool can extract any text data directly embedded in a PDF, as is common with many drawings created using “Save as PDF…” from a CAD system. If that doesn’t work, it will fall back to an OCR or Optical Character Recognition based extraction method.

Smart Extract functionality allows box selecting around batches of dimensions and automatically extracting their characteristics.

Figure 6. Smart Extract tool in SOLIDWORKS Inspection.

In the figure below, a selection box is dragged with Smart Extract around multiple ordinate dimensions. These dimensions are extracted with their nominal values and tolerances, and are populated into the characteristic list, ready for export.

Figure 7. Smart Extract being performed on a batch of dimensions.

Quality Control personnel often appreciate the extra control that this “semi-automatic” extraction process provides them. For example, they can easily split out hole callouts into multiple separate characteristics, or group them into one characteristic in the event they will be inspected with a Pass/Fail gauge.

Stubborn PDFs may necessitate more careful box selection around each individual characteristic for extraction. If necessary, a fallback option to improve performance is to develop a custom OCR dictionary, which involves training the software on a set of sample drawings.  This can be worth the effort if dealing with a large volume of drawings with a strange font, hand-drawn documents, or otherwise poor-quality scans—but should be a rare exception as the OCR choices built-in cover a wide range of common CAD software.

Inspection projects that were initially created in the add-in from SOLIDWORKS native data can also be exported to the SOLIDWORKS Inspection standalone tool. This means that engineers or designers may create a starting point for the inspection report based off the native SOLIDWORKS data, and the workers in quality control can make final adjustments.

Figure 8. PDF-based drawing comparison.

Also possible is the ability to perform a PDF-based change comparison of multiple drawings, where the new or modified characteristics will be automatically highlighted, and even swap out the underlying PDF for a new revision. This makes it possible to update an inspection project for new revisions of engineering drawings without starting from scratch.

External Measurement Input & QMS Export

The functionality covered so far pertains to generating an inspection report to be filled out with measurements later. The process can be taken a step further to enable measurement input directly into the SOLIDWORKS Inspection software—meaning a completed inspection report with measurement results and Pass/Fail status will be directly exported from the software.

Measurements can be input by manual typing, USB-based digital calipers or imported from external measuring device. Regardless of the approach, there is dynamic highlighting of the measured value and associated characteristic for color-coded and adjustable pass, fail and warning conditions.

Figure 9. Direct measurement input and results-based highlighting.

Most utilizing external measurement import take advantage of the CMM Data Import function, which allows importing raw measurements exported from a variety of digital measuring machines such as CMM, Faro arm or optical comparator. A variety of built-in templates are included for translation of common measurement formats and controller software, such as PC-DMIS.

Figure 10. CMM Data Import.

An important note is that the SOLIDWORKS Inspection software doesn’t replace software to program a CMM machine or other measurement device; instead, its capabilities lie solely in report generation and publishing.

Besides publishing a ballooned PDF and populated Excel report for first article inspection or process control, SOLIDWORKS Inspection can also export results directly into third-party Quality Management Systems(QMS) and inspection tools such as Net-Inspect and Verisurf to further streamline operations.

Figure 11. Publishing options.

Functionality Tiers

The Standard version of SOLIDWORKS Inspection includes the vast majority of functionality, including the ability to function as an add-in for automatic extraction of characteristics from SOLIDWORKS native drawings, or as a standalone software for inspection report generation from PDF drawings.

Features exclusive to the Professional version include:

• External measurement input and CMM data import.
• Graphical pass/fail status highlighting.
• 3D CAD or MBD-based inspection.

All versions include out of the box Excel export templates for AS9102, PPAP and process performance/SPC that can be further customized if needed.

Summary & Conclusion

First article inspection reports are a powerful and necessary tool for manufacturers and their clients alike, to ensure they hold each other accountable for the specifications presented by their engineering drawings. Historically these reports have been an extremely tedious type of documentation to produce, but it’s now possible to use a CAD-embedded solution that will virtually eliminate the grunt work of transcribing data and double-checking computed limits for dimensions to easily export reports.

Even for PDF-based drawing prints, advances in technology like Smart Extract and Optical Character Recognition have made semi-automatic extraction faster and more reliable than ever.

Organizations looking to be on the leading edge of technology can take advantage of rapid inspection report creation for their Statistical Process Control, or MBD-based inspection report generation for drawingless environments.

To learn more about SOLIDWORKS, check out the whitepaper Developing Better Products in the Cloud.

Example 1: Loadings Past Yield Stress

Loadings past the yield strength of a material may be the stereotypical application that comes to mind for nonlinear analysis. In certain industries and testing standards, it is acceptable for a part to undergo permanent deformations under overload conditions so long as the part continues to function and avoids catastrophic failure.

Consider the case of an alloy steel arm subject to a proof load of two tons representing an overload scenario.

Figure 1: Alloy steel arm mesh and loading.

Linear material models (the only option in a SOLIDWORKS Simulation Static analysis) only have a single stiffness parameter: elastic modulus, which represents the slope of the stress-strain curve within the linear region. Nonlinear study types available in SOLIDWORKS Simulation Premium can utilize plasticity material models, which contain extra information to describe post-yield changes in stiffness.

Figure 2: Example stress-strain curve (left), bilinear approximation (right).

Ideally, a stress-strain curve obtained from tensile test of the material would be input for most accurate plasticity model definition.

Alternatively, a parameter called tangent modulus can be added to approximate the slope of the stress-strain curve post-yield. Together with the elastic modulus and yield strength, this creates a bilinear material model as visible in Figure 2 above.

Figure 3: Linear material model (top) vs plasticity-Von Mises model (bottom).

Two simulation results from studies with identical setup and plot scales are visible in Figure 3 above. The top result utilizes a linear material model for alloy steel, and the bottom with a plasticity model driven by stress-strain curve. The linear material model predicts stresses approaching the ultimate strength of the material. The nonlinear material model shows substantially reduced peak stress values—only slightly above yield strength. How is such a difference possible?

As the material begins to enter the plastic region, its stiffness rapidly drops. This leads to a redistribution of stresses to surrounding material.

Strain plots in nonlinear studies are a valuable tool and allow displaying elastic or plastic strain. Plastic strain plots are useful to visualize regions of the model which have undergone permanent deformation, as seen in Figure 4 below.

Figure 4: Plastic strain plot.

These yielded regions have produced a redistribution of the locally high stresses around these fillets.

For these reasons, linear material models are generally an inaccurate predictor of stresses above yield. The only conclusion that can be drawn from stresses above yield in a linear static study is often that “yielding is likely to occur”—the values reported over yield must not be relied upon without first investigating a plasticity model in a nonlinear study.

It’s worth noting that finite element models in nonlinear studies will show distorted shapes but never damage like ruptures, cracks or tears. Predicting that kind of damage with SOLIDWORKS Simulation requires careful engineering determinations based on approaches such as comparing relevant stresses to the ultimate strength of material or observing strains.

If desirable, applied loads can be removed at the end of a nonlinear study to output residual stresses and deformations in an unloaded state.

Example 2: Snap Fit Connector

Design of snap fit connectors or clips are another great potential application for nonlinear analysis. In this example, a snap fit connector is pushed into the corresponding boss, and then pulled back out.

Quarter symmetry is employed to speed up solution time and provide a convenient cross-sectional view. Parameters of interest may include peak stresses in the snap fit connector and the insertion and pull-out forces required (if the clip is removable).

Figure 5: Nonlinear static stress results for a snap fit connector.

These studies are impractical in a linear static analysis due to changing contact conditions, and the desire to extract values over multiple load steps. As the linear static study solves in a single load application “step,” it is impossible to extract any time history.

Nonlinear static analyses (despite the name “static”) increment loadings using a parameter called time. However, dynamic effects such as inertia and damping are not taken into account in a nonlinear static analysis—such effects are incorporated in a nonlinear dynamics analysis if deemed necessary. Time in a nonlinear static analysis is sometimes referred to as pseudo-time to help reinforce this distinction.

This time parameter allows sequencing loadings that are not highly dynamic in nature and observing behavior at various steps. It is also the underlying mechanism that accounts for being able to solve large displacements, plastic deformation and other effects by incrementing load application and re-solving the stiffness matrix at each time step.

The loading in this example is a prescribed displacement on the top face of the male component, as visible in figure 6 below.

Figure 6: Prescribed displacement with corresponding time curve.

The loading is sequenced by ramping up the desired displacement amount from t = 0 to t = 0.5 seconds. From t = 0.5 seconds to t = 1, the displacement is reversed to pull back to its starting position. If desired, multiple loads/displacements may be varied or turned on and off during a study to represent different effects.

The default end time for a nonlinear static analysis is 1 second, but can be adjusted through the solver properties, as seen in figure 7 below.

Figure 7: Nonlinear static study properties.

Solution convergence is sometimes a concern for the implicit nonlinear solvers used in SOLIDWORKS Simulation Premium.

Time curves for loads and displacements must feature non-vertical slope in all areas to prevent solution convergence problems. It’s also necessary to provide a small enough time increment for the solution to converge.

The default “Automatic (autostepping)” option accomplishes this quite well by automatically reducing time step size when solution convergence issues are detected.

In this example, the time steps automatically reduce during the contact interactions between the two bodies. The mesh and contact pairs are defined as below:

Figure 8: Mesh and contact set definition.

Peak stresses are easily extracted by plotting relevant parameters such as Von Mises stress at various time steps or activating an envelope plot which will plot the maximum values across all steps. If stresses are in the elastic region then it’s not inherently necessary to use a nonlinear material model for these types of problems.

Another parameter of interest is the insertion and pull-out forces required. As force was not specified as an input to this analysis it is a variable being solved for that can be extracted.

This is accomplished by right clicking the Results folder and choosing Plot Result Force, then Reaction Force on the face defined as a fixture. This can then be plotted over the solution, as seen in the figure below.

Figure 9: Reaction force extraction.

Any graph plot can be exported as a .CSV through the File, Save As submenu for easier interpretation in an external plotting tool. In the figure below, the force in the Z direction was isolated on a plot in Microsoft Excel:

Figure 10: Reaction force in Z direction vs. time.

Note that the number of data points on the plot is controlled by the time steps in the nonlinear analysis. More data points may be desirable for plotting purposes, even if additional time steps aren’t necessary for solver convergence.

In these situations it’s recommended to reduce the “Max” time step size in the automatic time step parameters. For instance, setting the max time step to .02 would ensure the result features, at minimum, 50 data points—potentially more if the time step size needs to autostep down in any given area for convergence.

Example 3: Elastomers and Hyperelastic Materials

Elastomers such as rubber, TPE or EPDM are another common focus area for nonlinear analysis, utilizing a hyperelastic material model.

The Mooney-Rivlin model is the perhaps the most widely used in the area of hyperelastic material finite element analysis. It accepts inputs of either Mooney-Rivlin constants, or up to three material curves obtained through physical testing: simple tension, planar tension/pure shear, and biaxial tension.

A properly defined Mooney-Rivlin material model may allow examination of elongations of up to 300% or more. A common application for analysis of this type is gasket and O-ring design. In this example, a syringe plunger is presented modeled with a rubber-like material, as pictured in the figure below.

Figure 11: Cross section of syringe 3D Model.

The desired movement is to insert the plunger into the syringe barrel body. Parameters of interest here would include the insertion force required, the geometry of the seal that is generated and the contact pressure associated with the sealed surfaces.

Study setup for this example is similar to the Snap Fit Connector example in that a prescribed displacement is used to insert the plunger, and locally defined no penetration contact was employed. A Mooney-Rivlin material model was assigned to the black plunger body, and a linear elastic material model was used for the barrel body.

A key difference in this case is the use of 2D Simplification to analyze an axisymmetric slice of the model. This has many benefits in terms of solution time for a given mesh density, but also tends to have a much more favorable outcome in terms of solution convergence for the types of complex contact conditions that will occur once the hyperelastic material starts deforming.

Results at various timesteps are presented in Figure 12 below.

Figure 12: Results of 2D-simplified analysis with hyperelastic material model.

To get a sense of the sealing performance of the plunger to barrel interface, a Contact Pressure stress plot is created as visualized in Figure 13 below.

Figure 13: Contact Pressure stress plot with vector display.

The contact pressure values reported are used to make determinations about the amount of fluid pressure that can be resisted.

Sourcing Material Data

The more advanced material models provided in nonlinear study types are great, but they aren’t much use if a reliable source of material data can’t be established.

For the greatest accuracy, material model definitions should come from a material as close as possible to production parts. Ideally, material tests would be performed on a material sample from each lot of parts to derive the curves necessary.

There are some materials built into the default SOLIDWORKS Material library that feature more advanced material definitions. Any Material that says (SS) next to it includes a stress-strain curve that can be used with plasticity models.

Figure 14: Available material models in SOLIDWORKS Simulation Premium Nonlinear analysis.

Note in the figure above the text on the bottom of the material library window to “Click here” to access more materials. Through this link, SOLIDWORKS Simulation Professional or Premium customers on active subscription will have access to an additional material web portal called Matereality.

Matereality has many material definitions for fatigue, stress-strain curves and hyperelastic material models, as well as providing sources, references or certificates for material samples.

The raw test curves can be extracted from Matereality if desired, or each material can be conveniently downloaded as a SOLIDWORKS material.

Figure 15: Stress-strain curve for 7075-T6 aluminum from Matereality.

This makes Matereality a convenient fallback source for material models when they aren’t otherwise readily available.

Beyond SOLIDWORKS Simulation Premium

There are limits to what SOLIDWORKS Simulation Premium Nonlinear is capable of. Highly nonlinear systems with complex contact behavior or very large strains may be technically possible to solve but could require more simplification than desired or need frequent adjustments to time step size and mesh density.

Other offerings such as SIMULIA Abaqus employ state of the art nonlinear solvers particularly useful for resolving these difficulties. Some of the applications of Abaqus for nonlinear analysis include vehicle crash testing, buckling problems with many self-contacting faces (such as an imploding pressure vessel or a crumpling soda can) and drop tests for consumer product design.

Summary & Resources

This article presented a variety of use cases through three examples of nonlinear analysis.

There are many additional applications of nonlinear analysis in SOLIDWORKS Simulation Premium, including but not limited to nonlinear buckling studies, creep analysis, viscoelastic material model for foams and Nitinol (a nickel titanium alloy) shape-memory alloy material model.

Aside from these more exotic applications, it is also useful as a step-up from linear static analysis when complex contact conditions or large deformations arise.

Interested in trying out nonlinear FEA? There are a variety of built-in tutorials accessible from the pull-down menus. With the SOLIDWORKS Simulation add-in loaded, choose Help, SOLIDWORKS Simulation, Tutorials and click SOLIDWORKS Simulation Premium for a variety of step-by-step tutorials for various applications.

Figure 16: SOLIDWORKS Simulation Premium Tutorials.

Training courses should also be available locally from a SOLIDWORKS Value Added Reseller (VAR), or online.

SOLIDWORKS Simulation is also capable of copying a static study into a nonlinear study:

Figure 17: Copy static study into nonlinear study.

This means an existing static study can be used to quickly generate the basis of a nonlinear analysis. Once the static study is copied over, nonlinear-specific features such as the various material models can be applied to relevant components and forces can be modified with load curves to produce a functional nonlinear study.

For more information about SOLIDWORKS Simulation, check out the whitepaper Understanding Nonlinear Analysis.

Although they are SOLIDWORKS focused, the methodologies discussed here should be relevant to any feature-based CAD software. This article is a companion piece to a presentation given at SOLIDWORKS World 2019, which can be accessed here in both the PowerPoint and recorded presentation featuring live demonstrations of many of the techniques described.

Establishing a Model Plan

I’d like to present a simple workflow (see Figure 1) that, in the absence of a more sophisticated strategy, can serve as a basis for creating a robust CAD model.

As much as possible, features should reference back to the reference geometry and initial sketches that are planned out after a clear outline for the model has been established. The success of this process also hinges on performing checks during the modeling process—correcting and reorganizing as you go to make sure your work remains conformant to the plan.

Hand sketching an outline as shown in Figure 2 is a highly recommended prerequisite before you begin the modeling process. This sketch attempts to define the overall shape of your model and a few key parameters that will be driving the model’s design objective. It’s much better to figure this out at this stage rather than after you already have a lengthy feature tree.

To create your sketch, all you need is pen and paper (and, as you can clearly see from Figure 2, you don’t have to be an artist). A quick smartphone picture will digitize the sketch for your records. Unless you are completely confident that you have a clear mental picture of the end result in your head, don’t skip this step!

From the hand sketch, think ahead to what major features will make up your model. This will help guide the structure for sketches and reference geometry that will be created in the next steps.

Create reference geometry and initial sketches (see Figure 3)—these are the planes, axes and sketches that will be used to create the majority of the part features. Creating the appropriate geometry requires “thinking backwards” from the features you are planning to generate. Having more reference geometry than you need is fine, as extraneous or unused reference geometry or sketches can be deleted toward the end of the modeling process.

Primary features are features that make up the bulk of the overall shape of the model and would never be suppressed or removed from the design. These features must relate only to the reference geometry and initial sketches. Perhaps the most important rule for moving forward in the model is to never redefine anything that has already been defined in the initial sketches and reference geometry.

Primary features will typically consist of an initial base feature, plus up to a handful of other features that constitute the overall part profile of the model (see Figure 4).

Secondary features may relate to the initial reference geometry and base sketches, or to primary features (see Figure 5). To determine if a feature falls into the secondary feature category, ask yourself, “Would I ever want to suppress or remove from this from the design?” If the answer is yes, the feature is likely secondary. Secondary features typically include things like cutouts, pockets, holes and bosses.

Detail features are features that you could easily suppress or remove to make a low detail version of the model. This includes threads, small fillets, chamfers and text (see Figure 6).

Sticking to the Plan

It’s easy to have a plan—the real challenge is sticking to it when things get tough!

This modeling methodology hinges on two things: organization, and careful and selective use of references and relations.

I highly recommend the use of folders to help with organization.

Having the right type of features placed in their respective folders provides an inherent self-check to help ensure that you are conformant to the model plan. The folder structure also makes it manageable to navigate massive feature trees. Once you are comfortable with the standard process, you can deviate from such strict folder names to a method that works best for you.

While the shaft example has only 27 features (see Figure 7), a much longer feature tree doesn’t need to take up any more vertical space when using folders.

Some users may prefer to label individual sketches/features rather than use folders—another valid organization method.

Dynamic Reference Visualization can be enabled in SOLIDWORKS by right-clicking the top of the FeatureManager design tree as shown in Figure 8. This is a great tool to periodically check and ensure that your relations and dependencies are going according to plan.

Once the Dynamic Reference Visualization tool is enabled, features automatically highlight their references, so you can quickly validate whether the dependencies are correct. As you can see in Figure 8, the primary feature points back to only base reference geometry, whereas features further down the tree in the details folder may point back to both secondary and primary features.

Unfortunately, it’s easy to pick up relations by accident! To help myself focus on relating as much as possible to my base sketches and geometry, there are two tricks I like to use. Both methods revolve around hiding the part display, so that it’s only possible to reference the initial sketches and reference geometry—you can’t easily pick up a relation to something you can’t see!

My preferred method when trying to avoid accidental relations is to hide the underlying body—either by right-clicking and choosing the eye icon to hide the body, or by using a shortcut to hide bodies. To do this, hover the mouse over the part and press the Tab key on your keyboard. Then, show the initial sketches and reference geometry that you want to reference. Add your features and once you are done, hover over the area where the part was and press Shift+Tab to show the body again (see Figure 9).

Adding features using this method will result in features being placed at the end of the feature tree, which can be freely reordered upstream at will since they will only have dependencies to your early base sketches and reference geometry.

If you do need to pick up a reference to existing geometry, you can quickly show the body again while modeling. The objective is not to completely avoid using references—secondary and detail features will inevitably need some references to other features. The objective is to put careful thought into what relations you add, and, for me, hiding the body forces me to really consider each decision—and ask, “Do I really need to show the body to pick up a reference, or do I have enough information in the base sketches/reference geometry?”

The second approach is to simply roll back in the feature tree to how it was before the initial features were created as shown in Figure 10. Sketches or features you create at this stage can then be reordered down the tree if desired. If you are using the suggested folder structure, it may be necessary to toggle to Flat Tree View (CTRL+T keyboard shortcut), which organizes features in strict chronological order—temporarily ignoring folder display.

The downside of the rollback bar approach is that there is no fast toggle in the event that you do need to reference existing features.

Another thing to watch out for is accidental defining parameters that are already defined in your initial sketches or reference geometry. Unfortunately, SOLIDWORKS makes it very easy to do this! A common offender is the “blind” end condition on an extrude or extrude cut, which adds an additional feature dimension. If it is being used for a primary feature, the length of the extrude should already be defined somewhere in your initial sketches or reference geometry. Using an alternate end condition such as “Up to Vertex” or “Up to Surface” allows you to reference a sketch point or plane, respectively.

This way of thinking is what will help prevent having only portions of your design updating during a model change—and it is worth taking the time to correct issues like this immediately as they are encountered to stay conformant to the modeling plan.

In summary, I recommend creating a hand sketch or model outline in advance of creating your CAD model. Establish the key parameters that will be driving the design and use those to construct initial sketches and reference geometry. Reference back to these sketches and reference geometry exclusively to define your primary features—don’t redefine any parameters!

Once you have created secondary features and detail features, try to reference back to the initial sketches and reference geometry as much as possible —hiding the body and showing these sketches is a useful trick to force this. Expect that you will need to show the body again to reference primary features with certain relations and create new sketches for your smaller details. Periodically check the Dynamic Reference Visualization tool and make sure that features don’t have excessive amounts of dependencies.

Planning a Project

Everything discussed so far pertains to individual part modeling, but if you are tasked with planning out a full project or assembly model, it’s worth doing some additional high-level planning. Below are my major considerations when approaching a new project.

Design Inspiration/Research

Design inspiration and research is a crucial step whether you are brainstorming a new idea or working within strict specifications, and I believe it’s always worth doing some healthy research and trying to create a design inspiration collage (as shown in Figure 11). I always gravitate toward Microsoft OneNote, where I paste in pictures of various design ideas and annotate the aspects that interest me.

Hand Sketch and Preliminary Model

After choosing some parameters for my design, I return to paper to create hand sketches that will determine the overall structure of my assembly. Often it is also worth taking the time to build a preliminary concept CAD model, which can help you pick a winner from several competing designs (see Figure 12).

These preliminary models provide a bare-bones level of detail— enough to get the information needed to make a decision on how to move forward.

When creating the hand sketch and/or preliminary model, start to think of the logical splits for parts and subassemblies as you move into tree structure planning.

Tree Structure Plan

Developing a tree structure or “design tree” before you embark on your detailed modeling can reduce a host of issues. It should certainly be a requirement for working in a collaborative environment, as the separation between subassemblies is what enables concurrent design. Only one person can have write access to the top-level assembly at a time (or any other part/component), so breaking up the model into logical subassemblies enables multiple users to be working on separate regions as shown in Figure 13.

SOLIDWORKS Treehouse is a stand-alone application that allows you to plan new assembly tree structures, and even create the necessary assemblies, subassemblies and part files associated with them. Treehouse isalso usefulforretroactively viewing an assembly tree structure. If you don’t have access to Treehouse, using Microsoft PowerPoint, Visio, or another similar flowchart tool can produce effective plans.

Model Requirements

After defining a tree structure, it’s important to define the purpose of the models and what their “inputs and outputs” need to be. This means establishing design requirements for subcomponents as you would typically do for a full design—perhaps using specifications obtained from your preliminary model.

Although it’s not always possible, ideally requirements would be specific enough that each component becomes decoupled (effectively a “black box”),which is the best-case scenario for collaboration. Having enough data from the preliminary model to be able to set a detailed requirement like “Motor subassembly must fit into a 50 mm x 50 mm x 75 mm bounding box, and mate with standard 4 x 100 mm bolt pattern.” This reduces back-and-forth questions between designers and allows more progress to be made before integration into top-level assembly is required.

Level of detail is another important parameter that should be established—for example, what are the models being used for? Purchased vendor parts may be represented with a very low level of detail, while models for photorendering or CNC manufacturing need additional attention.

If you’ve followed along the modeling methodology presented previously, then you should have the best of both worlds—an easy way to vary the level of detail of your models by controlling the suppression of your “detail” features.

Part Numbering

There are many methods and systems for part numbering and entire books have been written on the subject. As it pertains to CAD, it’s important to have a system tohelp ensure that files have unique identifiers and won’tget overwritten by other parts (see Figure 14).

Here is one example system: use a descriptive part name during the preliminary design phase, and a reserved serialized number for release. This is useful because you may not be sure exactly how many parts are needed during the preliminary design phase, and is also an inherent way to differentiate prototype versus release files.

Sometime during the preliminary design phase and tree structure plan, reserve a sufficiently sized block of part numbers. This can be as simple as having a shared spreadsheet (shown in Figure 15) where users reserve ranges. It can be worth reserving some extra slots for parts that could be used for future revisions, upgrades or repairs.

Once the parts are ready to be released, rename the file with the reserved part number and convert the descriptive name into the part description. This is also a great time to fill out any other relevant file properties that may be useful on the bill of materials.

Note also that SOLIDWORKS PDM Professional supports automatically generated part numbering, which can streamline this manual process.

Project Timeline

The best laid plans won’t help if you don’t hit the deadline! For larger projects, it’s worth establishing a project timeline—usually as one of the first actions (see Figure 16). If you’re new to generating a timeline, you may not be sure what to realistically estimate. Thankfully, you can modify or “rebaseline” the timeline as you gain a more accurate picture of when you will likely be finished.

The best part of using a project timeline is that when you are tasked with a new project, you’ll have a historical basis that will help you to make a much better estimate of how long the next project should take. It’s also a great tool for proving that additional resources are required. One of the most popular tools for project planning is Microsoft Project (which produces Gantt charts as shown in Figure 16), but even marking down some critical estimated dates on a calendar can do the trick!

Summary

This article presented an example modeling methodology, relevant SOLIDWORKS tips, and basic project planning techniques. Every industry is different with their own unique requirements, so please consider this as simply one of many valid possible approaches.

I believe the most important thing is to adopt some form of system for modeling and project planning. By employing a system or methodology, you will be able to track your progress and make incremental refinements and improvements in the future.

I hope this article and the processes outlined will give you something to fall back on and allow you to take the complexity out of history-based CAD! If you enjoyed this article and would like more detail, then I recommend that you check out the recorded version of the associated presentation.