The pair dreamed of offering bikes to young racers using the Dell model, as Hilbert described at the 3DEXPERIENCE World 2023 conference. The idea is that people can customize the bike they want, before they buy it, so that it will fit their needs the day they get it. But there was a big roadblock to this dream. It was the 90s and the cost to get a seat of CAD software was about $30,000. Hilbert added that this didn’t even include the $30,000 computer needed to run the software in the first place.

Then, Hilbert went to a talk at his school that would change his life forever. The speaker was Jon Hirschtick—the card-counting founder of SOLIDWORKS. At this talk, Hilbert realized that by using this affordable CAD tool, he could compete with the big players.

“I tell you, the power we had by being able to design literally on a laptop in the late 90s—it completely changed the game for us,” he said.

How Cobra Moto uses SOLIDWORKS. (Image courtesy of Cobra Moto.)

Little did he know that as his dream evolved with that software, he would become CEO of Cobra MOTO and McDowell would become his Chief Engineer. And that their company would use the expanded features of SOLIDWORKS to change the world of motocross.

Motocross and the Start of Cobra MOTO

The sport of motocross consists of a group of racers navigating a course made up of different terrain, using a motorcycle. It became popular in Europe after WW2, with all the bikes that were left over. However, the sport didn’t really take off in the U.S. until the 60s. That delay explains the cookie-cutter market that Hilbert and McDowell found themselves in during the 90s.

When Cobra MOTO was created in 1993, it effectively built the marketplace of 50cc automatic bikes—as no one was serving that market. That’s because the audience was a niche of a niche: those interested in powersports, motorcycles, off-roading, motocross, youth products and competition-ready equipment.

“One of the really cool things about doing what we do is that we get to work with kids that are absolute phenoms,” said Hilbert. “They're some of the best athletes in the world and we get to see them grow up. If anybody happened to watch the Tampa Supercross … almost everybody that was at the very top of the field started out on a COBRA when they were kids.”

Cobra was first started by Bud Maimone, another motocross enthusiast who was attempting to address that market. He offered bikes that didn’t need self-modification, were race-ready and were therefore reliable. But Hilbert explained that Maimone was exhausted and looking for something new to do after running the company for so long. By 2003, Hilbert and McDowell took over.

They now had their dream to offer highly customized bikes to their target market, the software to make those designs and now the brand to make it all a reality. All they needed was the implementation.

The Cobra MOTO Design Strategy

To compete with the big boys, Hilbert and McDowell have implemented a design philosophy at Cobra MOTO that focuses on quality and speed—while keeping the workflow appropriate to the company’s small size. The crux of the philosophy centers around the 80/20 rule, using SOLIDWORKS for the hardware design and digital simulations and physical testing for final iterations and safety.

The design and development philosophy of Cobra MOTO. (Image courtesy of Cobra MOTO.)

“One of the things that works really well within the SOLIDWORKS platform is a lot of the built-ins: the built-in flow simulation, the built-in stress analysis and FEA. These aren't incredibly complex pieces of software. There aren’t high-end capabilities where you can adjust all kinds of boundary conditions, moving boundary conditions, multiphase and this-and-that. But they're good enough to get us the solution 80 percent of the time,” Hilbert said.

To ensure speed during the design and simulation side of this design philosophy, Cobra Moto uses HP Z4 workstations with NVIDIA GPUs. McDowell said after his presentation that “the biggest waste of time for my team is if they're waiting. Whether it's graphics or regeneration or just transferring files, if they're waiting...idle hands, idle minds. So the quicker the results, the more they can stay focused and the hardware is huge on that.”

Once the team is 80 percent certain on a design, they use tools such as additive manufacturing to speed up the physical testing/iteration part of the design process. Additive manufacturing enables the team to quickly build a prototype and test it for things such as rider grip or “getting a wrench where it needs to go” during maintenance, as Hilbert joked. He noted that if this was done with an outside organization, the iterations would take weeks, maybe months. But they can do it in days. He called it, “hardware at the speed of thought.”

Hilbert also reiterated that a design philosophy centered on speed and the 80/20 rule must keep safety as the highest priority. This is another reason why he believes in physical testing.

“You're putting a kid on a rocket ship. That’s what we do,” said Hilbert. “Safety becomes incredibly important. It informs almost every decision we make in terms of how we design and how we deal with our customers. As far as the testing goes, nothing surpasses testing. You can do a lot of work in the digital realm but until you get a product into a [test pilot’s] hands— and realistically multiple [test pilot’s] hands—you're never going to understand the use case fully until something's out there getting hammered-on in the field.”

How Cobra MOTO Offers Custom Made Bikes While Making a Profit

Now Hilbert and McDowell have a means of designing and testing parts. But how can they turn those parts into customized bikes and offer them to customers at a reasonable price while making a profit? After all, that target market is, by their own description, a niche of a niche. So, it would require small production lines that typically turn out expensive bikes. Cobra MOTO learned the solution to this problem during the Great Recession: when supply chains are tight, build it yourself.

“We kept our guys and gals working,” said Hilbert. “[This was a better] strategy versus trying to manage global supply chain in an incredibly uncertain time.” This verticalization strategy is especially efficient when you take into consideration the small production sizes. If they were to outsource production at 1,000 parts per run, then they wouldn’t have been able to keep the business profitable and few, if any, manufacturing outlets would go along for the ride.

Cobra MOTO makes its own tooling and fixtures. (Image courtesy of Cobra MOTO.)

Cobra MOTO produces its own tooling and fixtures using SOLIDWORKS. The challenge here is that as a small company they can only work on one injection mold at a time. To compensate for this, the company again uses additive manufacturing. They get to market with additive parts and slowly replace them with injection molded ones as they become available.

The build-it-yourself strategy of Cobra MOTO enabled the company to expand as a part supplier under the brand CARD and into the aerospace market with Cobra AERO—which even serves military drone customers. But that is another story.

This means that when companies such as XSun design drones like SolarXOne, they must perform multiphysics simulations to determine an optimal design based on weight, aerodynamics, structure, carrying capacity and much more.

Benjamin David, CEO and co-founder of XSun, said, “The idea of the drone is to be able to fly as long as possible and everywhere as simply as possible. The SolarXOne drone is a bundle of technologies—different sciences, different disciplines—that are not necessarily expected to work together. We had to find solutions to make it a harmonious product.”

To develop this drone, XSun opted to work with the 3DEXPEREIENCE Lab, which offered access to cloud-based development tools on the 3DEXPEREIENCE platform.

A rendering of the SolarXOne created by XSun. (Image courtesy of Dassault Systèmes).

The Design of the SolarXOne Autonomous Drone

David explained that the inspiration for SolarXOne was the concept of satellites at lower altitudes. In order to meet regulations for various countries, the drone needed to weigh less than 25 kg (55 lbs). If the design overshot this weight, the team wouldn’t be able to market the drone to all of their target markets.

The SolarXOne and its launching mechanism. (Image courtesy of Dassault Systèmes.)

The intended target audiences for the drone include:

• Scientific research, such as weather, ocean or geological monitoring.
• Business research, such as road monitoring, natural resource tracking or precision agriculture.
• Defense and security, such as search and rescue, telecommunication relays and surveillance.

“The ultimate goal would be to make [SolarXOne] available to various civil, scientific and military organizations as new autonomous data acquisition machines,” David explained.

As a result, the design team had to ensure that SolarXOne can operate for long periods of time, so that it could handle various types of treacherous, vast and/or remote terrain. XSun states that the current design is capable of a minimum of 12 hours of flight autonomy—with the ability to increase this time to 20 hours.

To achieve this, the drone needed to be light and to maintain an impressive wingspan. Not only does the wingspan help sustain lift, it also offers a large surface area for the solar panels. To accommodate this, XSun constructed the drone out of composite materials with a 4.5 m (14.7 ft) wingspan.

“The SolarXOne drone will enable much simpler, much cheaper and more autonomous data acquisition for different applications such as mapping, topography, agriculture and surveillance for different sectors,” said David.

XSun CEO and co-founder, Benjamin David, introduces SolarXone and the role that 3DXPERIENCE had in its design.

Design Engineering and the Effects of Working in a Single Cloud Platform

XSun’s development process lived completely on the cloud. This enabled them to work from anywhere with an internet connection—be it a hotel, home, company or temporary office.

An engineer works on SolarXOne within the 3DXPERIENCE platform. (Image courtesy of Dassault Systèmes.)

Denis Pitance, test engineer at XSun said, “Getting everyone’s updates in real-time enables us to save time with the integration of the elements. The Cloud was immediately obvious.”

David added, “It enables us to create things in a harmonized way. It also enables us to centralize all the information, all the data on a single platform and thus keep a unique clean and clear configuration.”

Employees could access the platform simultaneously, whenever they needed it. This enabled them to follow each other’s work and collaborate productively.

Andrea Viti, an aerodynamics engineer at XSun, said “The real challenge is to be able to work all together. More and more people are turning towards multidisciplinary design and the platform enables that. It’s really a question of acceleration; it enables us to do everything faster.”

Decisions made by one of the teams could have big ramifications for other teams. By having a single source of truth that updates automatically, it is easy to see how any changes affect the drone’s aerodynamic field.

In other words, XSun’s teams needed to keep track of the drone’s structure, loads, internal volume, equipment positions and much more. They also needed a cloud platform that could help them design and engineer the drone using composites, simulation and digital prototyping and testing.

That is where the 3DXPERIENCE platform came in. 3DEXPERIENCE consolidated all the data in a single repository of truth. It also helped XSun ensure subsystems such as landing gear, propellers, batteries and the fuselage were understood by the whole team.

How the 3DXPERIENCE Lab Streamlined the Development of the SolarXOne Drone

“We have to design a very secured machine—very reliable, very light—at a relevant cost. The 3DEXPEREIENCE platform has made these solutions a reality,” said David.

XSun had access to the 3DEXPEREIENCE Lab’s features and its community of experts, which enabled the team to improve their technical skills. In fact, some had no prior experience with the platform at all. However, within a few weeks they were up and running. In the end, the team was able to produce a preliminary design within a year.

“The use of the platform made it possible to develop several things in parallel,” said David. “For example, verification of the different internal subsystems, loads placement and checking, decentering, structural simulation and aerodynamics simulation. It has been a fundamental time saver for the project. This was made possible thanks to the 3DEXPERIENCE Lab and it has been an accelerator.”

Tools that offered XSun some of the highest levels of collaboration were CATIA and SIMULIA. Every time a CAD model was updated, it would reflect in the simulation. As a result, teams could virtually validate the aircraft before producing any physical products.

To learn how 3DEXPERIENCE helped XSun collaborate on the design of the circuit board’s cooling system and how it helped them avoid a design flaw between the propeller and the landing gear, read this case study or watch the video below:

XSun Engineers discuss the design process of SolarXOne.

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

Original part (left) compared to a topology-optimized part (right). (Image courtesy of Dassault Systèmes.)

Topology optimization is one of the biggest additions to SOLIDWORKS Simulation 2018. It takes minimal inputs from a user(loads, design space, constraints, boundary conditions and manufacturing methods) and then runs an iterative algorithm that supplies a near-optimized part.

No doubt a tool like this would be useful to many users from nearly any industry, so let’s dig deeper into how it works and what it does. For a quick overview, check out this video:

For more on what is new in SOLIDWORKS Simulation 2018, besides topology optimization that is, read this article on Engineers Rule (click here).

How SOLIDWORKS’ Topology Optimization Works?

Von Mises analysis of a topology-optimized part. (Image courtesy of Dassault Systèmes.)

So, topology optimization must sound magical to many design engineers. It seems to do most of the thinking for you.

Some topology optimization tools grow parts from scratch. Others chisels away at an old design until a new optimum is revealed.

In other words, topology optimization can be an additive or subtractive algorithm.

For SOLIDWORKS, they chose to focus on the subtractive method. To achieve this, they used the Tosca optimization engine under the hood to power the optimization.

“We felt the subtractive method was most attractive to our customers. It’s good with existing geometry you want to refine,” said Stephen Endersby, director of product portfolio management at SOLIDWORKS. “With Tosca, we also have the technology that has a track record in-house. So, it was a good, safe solution for our users.”

The software works by turning a design space into a mesh and then subjecting it to a simulation complete with user-defined loads, constraints and boundary conditions. The software then looks at the stiffness of each individual element and cuts out elements that appear to offer little to no structural or manufacturing benefit. This process is then iterated until the part meets all constraints and global compliance.

“Global compliance defines the stiffness of the component,” explained Endersby. “The software looks at the original shape and how the shape will deform under the loads. The software then compares these values to measure a deviation. You want to minimize the overall deflection.”

The cut-off point for each element can be user defined and altered at any time. This tells the software when to keep or eliminate an element. The system then recalculates the next iteration without these elements and sees if the part now exceeds or is within target of the global stiffness.

Users can also set manufacturing constraints that limit the changes to the geometry. For instance, engineers can define axes of symmetries, thickness controls, handedness, mold direction and more. These tools will help to ensure that your part will still be manufacturable despite its organic look.

As an example, the mold direction will notify the topology optimization tool of the direction the part will be pulled from. This will help to limit cavities, undercuts and parts that are impossible to extract from molds.

How to Use SOLIDWORKS Topology Optimization

To start the topology optimization process, a user defines the loads, constraints and boundary conditions of a part. From there, they must define the goals of the topology optimization.

Load manager compares how the part performs under various loads. (Image courtesy of Dassault Systèmes.)

Currently, the goals compatible with the topology optimize include optimizing:

• Stiffness to weight
• Minimal mass
• Maximum displacement

Constraints on the optimization process include:

• Required mechanical copies
• Percentage of mass removed
• Manufacturing process
• Maximum deflection

It should be noted that only one of these goals can be chosen at a time. Endersby suggests to start with stiffness to weight.

“It’s a good starting point,” said Endersby.“Everything will match up in a nice way with respect to the inputs, boundary conditions and strengths you apply. This is a benchmark. No analysis is a one-shot deal anyway. First, make assessments and see what happens when you change the topology optimization approach. Topology optimization can look at multiple criteria and loading conditions. The best thing is to create multiple studies with different goals to get what you want to do.”

Endersby suggests that engineers use the topology optimization tool to test out the extreme situations. You want to discover how far you can really push the design. To that end, the product comes with a load manager to keep track of the load inputs that will govern the outcome of the part’s topology optimization.

Endersby even hints that future versions of the topology optimization tool might keep track and manage your goals, constraints and manufacturing methods. This will help to speed up the development of your part and reduce any unnecessary rework. In theory, this could even streamline or automate the design space exploration. This tool would be similar in function to the load manager.

A constraints manager tool will be very useful to future iterations of the topology optimization tool. It will help engineers to optimize the trade-offs they will invariably find. Tools like this will help engineers see that “some constraints can be relaxed, while others can not—they will know the limits of their design,” said Endersby.

Users are also able to exclude regions of their part from their topology optimization. There are various reasons why this would make sense. Perhaps it is a region that holds onto a bolt? Perhaps it is a face that connects to another component? Perhaps it is a face that completes a seal with another component?

In this case, Endersby again suggests to run multiple runs to see what happens when you preserve the region and what happens when you don’t. This might inspire your team to better design the overall assembly.

“For all analysis, even topology optimization, you never hit run once,” said Endersby. “You look at the results and run it again with different assumptions and inputs to evaluate those inputs. Then you run it again. It’s an iterative process.”

How to Turn Your Topology Optimization Into CAD

SOLIDWORKS calculates a smoothed mesh and inputs it into the assembly. (Image courtesy of Dassault Systèmes.)

One advantage to SOLIDWORKS’ topology optimization tool is that it is designed to take these designs into a CAD environment.

Endersby explains that there are three methods to bring your optimization into CAD for further analysis and processing.

First, you can display the results on top of the original CAD model that spawned the optimization. The engineer can then use this overlay to guide the changes to the original geometry.

Simulation results of a topology-optimized part overlaid onto CAD geometry. (Image courtesy of Dassault Systèmes.)

Second, engineers can save their topology optimization geometry into an STL file. Because there is a new ability to work with mesh bodies in SOLIDWORKS, this effectively brings the geometry into your CAD.

From here, the engineer can use the “calculate smooth mesh” function to get their geometry.

Finally, there are various partner products available to users that will surface wrap your geometry.

This will help engineers to keep the organic look of their optimizations while simultaneously cleaning up the geometry. One such surfacing add-in available to SOLIDWORKS users is NPower.

The Future of SOLIDWORKS’ Topology Optimization Tool

A drawback to the SOLIDWORKS topology optimization tool is that it currently lacks a strength-to-weight ratio topology optimization. Endersby notes that this is something we should expect to see in future releases. After all, it’s one thing to optimize your part stiffness so it doesn’t bend, but you also don’t want it to shatter.

“When we originally started designing the topology optimization engine,we were working on strength-to-weight ratio,” admitted Endersby. “We moved to stiffness-to-weight ratio because it was more accurate to what the solver was giving you in the first iteration. Plan on bringing in strength to weight.”

Another addition Endersby hopes to see added to the tool is the optimization of components within an assembly. Currently, loads from the assembly are imprinted on the part using motion analysis and assigning calculated loads onto regions of the part using contact forces.

Finally, Endersby is hoping to bring more multiphysics into the topology analysis. For instance, modal, thermal and buckling are all on his list.

As Endersby said, “We don’t want this to just be demo candy. We want people to use this in real life.”

To be used in real life, the topology optimization tool must model real life and therefore account for multiphysics. “There are more constraints in the real world than this first release,” agreed Endersby. “We will add more to match the real world.”

As a result, it looks like SOLIDWORKS will be putting a lot of future work into this new feature. It will not be surprising to see Dassault Systèmes announce more abilities from the topology optimization tool in future releases.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

The addition of free surface flows to SOLIDWORKS Simulation 2018 means you can simulate how water fills up this tank. (Image courtesy of Dassault Systèmes.)

Another SOLIDWORKS launch has come and gone, and this year has marked some big improvements for the SOLIDWORKS Simulation 2018 portfolio. One of the biggest additions of note is the new topology optimization tool for structural parts.

This tool gives users an optimal design for a part given its design space, loads, constraints and manufacturing methods. The discussion around this advancement could take up a whole article in and of itself, so we have written it here on Engineers Rule (click here).

But there is much more in the realm of simulation for SOLIDWORKS 2018 than topology optimization. Here you will learn about other tools Dassault Systèmes has added to the mix,including cyclic symmetry for computational fluid dynamics (CFD), free surface CFD flows, nonlinear safety factors and displacement controls for nonlinear analysis.

For more improvements to SOLIDWORKS Simulation 2018 not covered in this article, watch this video:

SOLIDWORKS Flow Simulation: Free Surface Flows and Sector Periodicity

According to Stephen Endersby, director of product portfolio management at SOLIDWORKS, one of the biggest simulation additions to this release is the ability to simulate free surface flows.

Any flow where fluids and gas interact is considered a free surface flow. Examples include anything from a half-filled gas tank to a canoe on a river.

The simulation assesses the interface between gases and liquids. The software also considers any solids that might be affecting the flow of either the gas or liquid. To properly assess the interface of the gases, liquids and solids, these locations will need a finer mesh than any bulk areas.

“When you look at energy, power and utilities, there are a lot of flows that are free flows,” said Endersby. “They are challenging to solve computationally so it took us a while to get there.”

The first step to start a free surface flow simulation is to set the water level. Then the workflow changes depending on internal or external flows.

The setup of a free surface flow changes depending on if it is internal or external. (Image courtesy of Dassault Systèmes.)

For internal flows, like the gas tank, the simulation will model how the fuel slushes around. The sneaky way SOLIDWORKS modeled this is by moving the gravity vector around while keeping the tank stationary.

“Changing the gravity is a little smoke and mirrors, but it is physically correct if you are only working with a single physics,” said Endersby. “For now, it is just a single physics so we can get away with moving the gravity. But in the future, we want to incorporate multiphysics so we will need to have a more rigorous setup.”

For external flows, like the canoe on the river, the engineer must first decide if modeling the bottom of the riverbed will be important to the simulation. In a deep river, the riverbed will likely have little effect; however, near the shore, where the canoe is tied up, this is a different story. In this simulation, you can’t really play with gravity to perform the simulation.Instead, the programmers set it up to change the velocity of the liquid. The liquid velocity can also be pulsed to create a wave effect.

Unfortunately, there is no automated way to set up the water level for floating objects. However, Endersby hopes to add a bouncy function in future releases. It would certainly improve the customer experience to not have to break out an equation every time something is floating. For now, users must rely on hand calculations and any macros they can get their hands on.

Additionally, the free flow function is currently incompatible with simulations containing transitions, rotations, porous media or fans. Endersby is pushing for these to be added in future releases.

To reduce the size of the model, the user has simulated only a quarter of the cylinder. The results can then be mirrored across the axis of symmetry. (Image courtesy of SOLIDWORKS.)

Another big addition to SOLIDWORKS Flow Simulation is sector periodicity, or as a structural engineer might call it, cyclical symmetry. This tool is used to cut down on the number of elements in a model.

Instead, the simulation focuses on a portion of the model that is cyclically symmetric. For this to work, the fluid must flow along the path of the axis of symmetry.

Sector periodicity should also be useful to those in the oil and gas or production industries.

Unfortunately,sector periodicity is currently not compatible for phase transitions, cavitation, high Mach and mixing simulations. Endersby hopes to see these functionalities in future releases.

SOLIDWORKS Simulation: Nonlinear Safety Factors and Displacement Control

Nonlinear safetyfactor definitions new to SOLIDWORKS Simulation 2018. (Image courtesy of Javelin.)

The prime SOLIDWORKS Simulation offering has also seen some new additions in the form of displacement control and safety factors for nonlinear simulations.

An important note about the safety factor functions for nonlinear systems is that the user requiresa considerable amount of understanding about their part and its material makeup.

Endersby explains that for traditional materials, the default safety factor is typically all you need. The material is well known and contains homogeneous properties. In this case, you take the yield stress of the material and divide it by the measured stress to get your safety factor. You then optimize the part until said safety factor is at a desired level.

This isn’t true for brittle or nonlinear materials like composites and plastics. For these materials, the user must define a maximum stress value, as the material might yield before it fully breaks or snap before showing signs of failure.

“You want to make sure the part stays in a linear range of behavior,” said Endersby. “If it ratchets and becomes deformed, it will not go back to the original shape. To avoid this, set a maximum stress at a range where the material still acts linear.”

Another addition to SOLIDWORKS Simulation is the use of displacement controls for nonlinear parts. This tool helps to control the iteration when solving a part that experiences large deformations under small forces. The displacement control function ensures that the system won’t jump to a large displacement under a small increase in the force.

“Take a straw,” said Endersby. “You push it on one end and then it collapses. You get a small displacement at first. But as you increase the force, you eventually get one huge displacement. With displacement control, you can set how the system reacts to get a stable result. It controls the force so you don’t move too quickly.”

The system does this by defining a series of displacements and then calculating the force needed to achieve that displacement. This is alternative to increasing the force and hoping it will have a smooth linear displacement.

Other useful additions to SOLIDWORKS Simulation include:

• Improved stress singularity detection in stress hotspot diagnosis
• Single pin connector for multiple coaxial cylinders and hinge definitions
• Ability to copy simulation features of a part or subassembly into a new study of the assembly
  • Importable features include material, element types, contact, connectors, fixtures, loads and mesh controls (which you can import individually or all at once)
• Ability to export deformed geometry for CAE analysis in various CAE tools
  • Formats include Abaqus, STL, NASTRAN andnative SOLIDWORKS
• Ability to exclude area from clamp force (used to simulate plastic part production with slides and undercuts)
• Improved detection of short stops in plastic mold simulations
• Assessment of density results to ensure uniform density in plastic molded parts
• Emailing when analysis is complete

For more on SOLIDWORKS Simulation 2018, check out Dassault Systèmes’ launch page.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

Aerovelo’s Eta zipped past the human-powered land speed record, clocking in at a whopping 144.17 kph (89.58 mph)! Let it into the left lane, folks. (Image courtesy of Aerovelo.)

We’ve all been there, driving down a one-lane street, backed up behind a cyclist that blocks our ambition of hitting the speed limit. Seriously, bikes limp along at 10 mph and hit what—30 mph—max? Well, no. How does 90 mph sound?

That’s right. Thanks to the engineering minds of Aerovelo and its bike, Eta, cyclists could theoretically complain about passing that big bead on your high performance vehicle.

Aerovelo Cofounders Cameron Robertson and Todd Reichert lead their team of University of Toronto (U of T) engineering students and alumni to design, simulate, optimize, build and pilot this escape pod-encased bike into the history books.

After breaking its own human-powered land speed record a few times over, this little tear drop settled on an impressive 144.17 kph (89.59 mph).

“It was a culmination of years of effort,” said Robertson. “There was a lot of excitement and relief that we have taken a good path and all the choices we made showed it could be done. With Eta’s design, we showed the range of improvement. In 2000 to 2015, there wasn’t much change to the [human-powered land] speed record. It incremented 10 mph in 15 years, from 73 to 83 mph. The rate of technological change was small; it was incremental improvements. In the span of two years with Eta, however, we incremented [the record] by 6.5 mph.”

There is no wonder why the team named their bike after the Greek letter us engineers know represents efficiency. And the racing pun asking Eta’s estimated time of arrival at the finish line wasn’t lost either.

How Do You Design a Bike That Can Break a World? Use CFD Simulations!

Consistency is one of the hardest challenges when designing a vehicle to break any speed record. This is because the racing team typically only gets a few kicks at the can on official race days.

“Every day you need to execute as you will only get some days where the environment is what you want,” said Robertson. “We didn’t expect this to be a big point, but we took it based on advice from other teams that have broken records and were always on the ball. We wanted to emulate this.”

So how does one get from the snail on the road to Formula One? And better yet, how do you make the performance of this bullet consistent? The answer is computational fluid dynamics (CFD) simulations, a lot of experience, and trial and error.

“With the bike, it was important to change the design of the outer shell and then slightly modify the simulation results to get a sense of how it performed with respect to that change. Then, we would iterate again,” said Robertson. “Todd [Reichert] did 30 different iterations on the bike’s fairings, and without SOLIDWORKS we would never have been able to do that in an informed way.”

The majority of the Eta simulations were in SOLIDWORKS Flow Simulation. This simulation in-CAD package was a platform that the U of T alumni and students at Aerovelo were well versed in using. They wanted to investigate the airflow around the outer shell. To do this, the team would perform numerous pressure profile simulations.

“We use pressure profiles, which are accurately evaluated in software like SOILDWORKS Flow Simulation. As the air goes over the surface, you can assess the pressure at every point. You can then shape the pressure profile as you go down the bike and have the shape of the profile be maximally conducive to extend laminar flow,” explained Robertson. “From there, we expect, based on the pressure profile, the change to be positive or negative.”

The goal is to maintain laminar flow around the bike as long as possible due to its lower resistance compared to turbulence and transitional flows. One would think that ideally, the goal is to maintain laminar flow around the shell completely. However, if the flow doesn’t transition before the trailing edge then it can fully separate from the surface which will cause tremendous drag.

A red herring of sorts in the optimization and simulation of their bike, according to Robertson, was trying to determine the actual spot on the bike where the air transitions from laminar to turbulent. He said, “When that prediction happens, there is a large margin of error. It’s subject to small variations and it will be [hard] to implement in the real world versus simulation. We see some team point to a spot on their bike and say, ‘we have laminar flow until here and we predict it will run 150kph,’ and then it runs worse than their previous bike.”

This shows the importance of validating your simulation. No engineer should trust their model blindly. This has become a regular practice for Aerovelo. It performs simulations and then tests the bike to compare the turbulence and pressure profile. The team also relies heavily on its experiences and the experiences of the community of engineers working on breaking the human-powered land speed record.

How Does Eta Differ from Traditional Bikes?

So, after all the design changes, optimizations and simulations, what sets Eta apart from that bike in the garage?

“Well, it’s different from a normal bike in almost every way,” said Robertson. “First, Eta is very recumbent. The pilot is almost completely lying down. The bike is fully enclosed for aerodynamics except for controlled intakes for ventilations. Next, it’s steered using cameras on top of the bike connected to screens in front of the pilot’s face, and steering is limited to three degrees to each side. Finally, the tires are not good for turning. So, it’s clearly designed to go straight.”

Robertson also explains that the gearing for the bike is also very different. Eta uses a two-stage drive train to accommodate the bike’s top speed. Due to the reduction created by the two-stage drive train, the wheels of Eta are able to spin many times faster than anyone can spin on a traditional bike.

With the vast differences between Eta and traditional racing bikes, don’t expect to see it on the Tour de France anytime soon (unless there’s a total relaxation of racing rules). However, Robertson is interested in a biking version of Formula1 (F1), similar to Australia’s Pedal Prix, where the engineering behind the equipment is perhaps more important than the driving of said equipment. He said, “F1 is more about the engineering and could be interesting in a bike format.”

But what really interests Robertson is how this technology could affect transportation. He imagines going to work at highway speeds on a vehicle that is human powered and 300 times more fuel efficient than your average car.

“One thing we thought about is how you could use these in the future. Imagine if you were not contending with several thousand-pound cars on the road,” wondered Robertson. “It’s interesting when comparing a small power of the human engine at about two-thirds horsepower. To ride an hour and achieve 60 mph, the bike needs to be very efficient—about 9500 mpg to an average car that is about 30 mpg.”

The Future of Aerovelo’s Record-Breaking Bike Designs

The Aerovelo team is all smiles while huddled around Eta after breaking the record. But how long will they hold the title? How much room for improvement is there? From left to right Tomek Bartczak, Alex Selwa, Victor Ragusila, Todd Reichert, Cameron Robertson and Trefor Evans. (Image courtesy of Aerovelo.)

So, what is next for Aerovelo and the human-powered land speed record?

Well, Robertson believes that there are still many potential areas of improvement for Eta and similar record-chasing bikes.

Unfortunately for Eta, many of these improvements will require a completely new design and even more thinking outside the box from engineers. Two examples involve heat capture and active boundary layers.

The rule books says that the bike must be powered by humans, but does that mean it has to be powered by the legs alone? Remember, that pilot in an enclosed spot will produce a lot of heat. Capturing this human body heat could theoretically help power a bike. This might seem a little like cheating, but remember that it is still human power, and it worked well enough for The Matrix.

“You can’t use energy storage devices on the bike, but you could still drive a bike on an electric motor,” said Robertson. “So, imagine if the driver provides power to the drive train. Humans are 20 to 30 percent efficient on converting energy and the rest goes to heat. Capturing that with some efficiency using heat recapturing tiles or heat pumps could theoretically increase the energy output.”

To test out this theory, engineers at Aerovelo could create a heat transfer simulation of Eta’s replacement and use that data to crunch the electromechanical numbers.

“Simulations would also play a role in active boundary control, which is used to extend the laminar flow around a vehicle,” explained Robertson. “Active boundary control senses and manipulates the boundary layer in order to allow longer runs of laminar flow than would be possible otherwise.”

Active boundary control can be done in two ways: using either wave theory or clever ventilation.

“When air transitions from laminar to turbulent, energy and unstable waves oscillations grow to a point where the stable smooth conditions turn into the chaotic movements,” noted Robertson.“The technology senses the oscillations in the air and then introduces more waves to cancel out those waves that are promoting the turbulence transition.”

Another active boundary layer method would add a system that sucks in the nearly turbulent boundary layer of air. The air is sucked in can then be used for ventilation. However, more importantly, the surrounding flow would fill the gap made by the pre-existing boundary layer. This would effectively give the bike a new laminar boundary layer.

Unfortunately, this method would need precise knowledge of the transitional point. As previously mentioned, this would require simulations with questionable accuracy in this particular application.

Similar to the heat capture option, active boundary layer does use up energy to work the sensors, oscillators and/or pumps and any other equipment. The question is will you get more energy out of the rider than you waste on this added equipment?

“Everything we do is about system design,” noted Robertson. “We look at how we can do more with less or get more from what we have. Reduce the weight and increase strength—that is an important mind-set.”

Engineers need to remember to perform thermal analysis on industrial equipment like the shredder pictured above. Otherwise, the equipment can overheat during use, damaging the equipment. (Image courtesy of Dassault Systèmes.)

Take an industrial shredder. At first glance, a thermal analysis might not seem necessary when designing the equipment, but any mechanical engineer worth their salt will know that when metal shreds, heat will be generated, resulting in thermal stresses on the equipment. If this heat isn’t accounted for in the design phases, then production processes can suffer from a lot of downtime while waiting for material cool-downs.

As for consumer products, they are becoming more complex, smarter and smaller. “This is a very common challenge in electronic devices,” said Lotfi Derbal, senior product portfolio manager at SOLIDWORKS. “Electronic devices have less and less space to provide airflow as they get smaller and smaller, so it is an ongoing issue that needs to be examined to keep the equipment in good health. Finding effective solutions to heat transfer problems has become an increasingly important part of new product development.”

By simulating the heat transfer of a product, engineers will be better informed through the development of the product. Prototypes are costly to work with and it is quite difficult to map out heat flux when dealing with prototypes. As a result, simulation is a much faster and affordable option when looking to optimize a product’s thermal flow.

“While designing your product, you can compare temperature distribution, heat flux and air circulation,” noted Derbal. “With this type of insight and knowledge, you will be able to analyze innovative new concepts more cost-effectively. It doesn’t matter if you’re designing high-tech electronic gadgets, consumer products, medical devices, HVAC systems or industrial heaters/coolers.”

Simulation in CAD Brings Thermal Analysis Early into the Development Cycle

A great way to bring thermal assessments into the early design cycle is to use simulation-in-CAD tools. This particular breed of computer-aided engineering (CAE) software integrates the simulation tools into the CAD environment.

Simulation in CAD democratizes the workflow by packaging it into a familiar user interface (UI). This will reduce the amount of training engineers will need as they will be using a tool that is already familiar to them. SOLIDWORKS offers a series of simulation-in-CAD tools that incorporate thermal analysis.

“With SOLIDWORKS Simulation and/or Flow Simulation, you can simulate structural thermal and fluid flow as well as coupling it with heat transfer, such as convection, conduction or radiation,” said Derbal. “Designers can apply heat sources, thermal properties on components, and define fan position. [Users also] get the resultant temperature distribution for both the fluid and the product itself.”

SOLIDWORKS Simulation and Flow Simulation have the capability to assess numerous heat transfer problems. And as it is incorporated into the CAD environment, an engineering team can save time—and often money—using the simulation-in-CAD option.

How Thermal Simulations Differ from Structural Simulations

Engineers familiar with simulation in CAD have likely spent much of their time with the structural finite element analysis (FEA) capabilities. Though much of the workflow will transfer over, thermal assessments are not as easy as modeling a structural simulation.

Natural and forced convection problems, like the ones pictured above, have heat transfer coefficients that are hard to pinpoint without computational fluid dynamic studies. (Image courtesy of Dassault Systèmes.)

Derbal explained that, “thermal analysis is not as intuitive as structural analysis because of the complexity of combining heat transfer laws like conduction, radiation and convection.”

Much of this difficulty comes from determining the convective heat transfer coefficients needed to create an accurate assessment. Engineers can make an educated guess or model the fluid flow within Flow Simulation to determine a more accurate coefficient value.

“Conduction is easy; it’s based on material properties,” explained Derbal. “But for forced or natural convection, you have to deal with known or estimated heat transfer coefficients for wall conditions as well as for emissivity and thermal resistance.”

“Using SOLIDWORKS Flow Simulation,” he added, “you may take into account the real environment. Engineers can couple the fluid flow, both internal and/or external, and heat transfer analysis. Then most of the coefficients will be calculated by the software.”

Engineers who are having difficulty setting up their thermal simulations can gain access to online learning material, such as tutorials and manuals, on MySolidWorks.

Versatility of SOLIDWORKS’ Thermal Simulation Offerings

The thermal simulation tools available in the SOLIDWORKS Simulation portfolio offer design engineers a lot of the versatility that they will need for their early development cycle assessments. However, like many other simulation-in-CAD options, an analyst might find the UI too restrictive for their advanced CAE needs.

Simulation is targeting engineering designers who are trying to give themselves direction when producing their designs early in the development cycle. It isn’t meant to be used for the advanced product verification stages.

In this respect, the simulation-in-CAD tool should be considered for its numerous thermal assessments and multiphysics simulation options such as:

• Coupling thermal and static loadings to assess thermal stresses
• Thermal contractions and expansions
• Fully coupled computational fluid dynamics (CFD) and thermal conjugate heat transfer when using Flow Simulation

“Most of thermal analysis can be simulated as steady state at least for predesign,” recommended Derbal. “However, transient thermal analysis can be necessary for strongly nonlinear and time-dependent problems, which need computer resources and large solver times.”

Performing a transient simulation will, of course, require more computational power than the steady-state analysis. This might be a lot of work for a computer optimized to work with CAD but not CAE.

To combat this, Simulation allows for a few tricks to keep the computation analysis down when working with transient simulations. Derbal suggested the following processes:

• Increase the time step if there is little risk of missing transient detail
• Use a function to govern the time step based on manual and automatic intervals
• Assess the flow field using time-averaged results

As for engineers working with heating, ventilation and air conditioning (HVAC) or electronics cooling, Derbal suggested that there are SOLIDWORKS modules with thermal analysis tools specifically tailored to these disciplines. For instance, HVAC engineers can access tools like human comfort factors, while electronics design engineers can perform Joule heating calculations that assess the heat released from a direct electrical current.

To find out more about the capabilities of SOLIDWORKS Simulation, read: SOLIDWORKS 2016 Adds Tools to Help Simulations and Validation.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

A 3D SOLIDWORKS CAD model of a Haiku fan. A Haiku fan embeds the fan light and uses airfoils instead of planks to move air around the room. The result is a sleeker, more optimized design. A sleek design optimized to perform its task efficiently should be enough reason to buy the product. IoT is just a cherry on top. Engineers need to understand that this is often the case. Start with a good product and add IoT. IoT doesn’t make a product good; it just adds to it. (Image courtesy of Haiku Home.)

Often, the best-designed products just blend into reality and are taken for granted. But that doesn’t mean there isn’t room for improvement. When it comes to fans made by Haiku Home from Big Ass Solutions (yes, that is its real name), the company uses its expertise of blowing air around to not only optimize the design of fans, but also to add them to the Internet of Things (IoT).

Starting with a Good Disconnected Product Is the Key to a Great IoT Product

“If you don’t get the product right then, you might as well not bother with the smart piece,” said Landon Borders, director of Connected Devices at Big Ass Solutions. “If done correctly, adding connectivity to the product is just an incremental improvement.”

He explains that the start of any good IoT product is the product itself. You can’t just slap connectivity to any old design and call it a day. You need to think how you have improved the product for your customers. Not all products lend themselves to the IoT. Similarly, no amount of connectivity features will improve a bad design.

“A lot of the challenges with designing an IoT device comes down to not having a playbook,” said Borders. “A lot of this is very new and we’re all learning as we go. But it starts with the product. I see so many smart devices out there, and they are really not solving any problems for anyone. I shake my head sometimes. So one of the challenges is learning what customers want and translating those needs into specifications and requirements.”

When it came to classic fan designs, there were many things Haiku Home discovered it could improve upon from a user perspective. First, take those noisy motors. Borders explained that Haiku works on brushless motors that reduce the noise and improve the life of the product.

Next, the dangling lights and chains often associated with ceiling fans had to go. The chains were always confusing to use, they fail or break frequently, and they are difficult for those who aren’t especially tall to use. And the dangling lights could become a literal headache inducer for those who are tall. These interesting design changes were all crafted in a SOLIDWORKS CAD model.

Control for the fan went to an IoT app, while the lights were replaced with LEDs that are built into the fan’s sleek frame.

To really see how much energy Haiku Home puts into the design of its IoT products, before even adding IoT, look no further than the blades.

Traditionally, the blades on fans are a little more than a plank. However, Haiku Home designs its blades into airfoils. The company even performs computational fluid dynamics (CFD) simulations to optimize the fans’ design. These simulations are also used by Haiku Home’s sales team to ensure that a fan is properly sized for a room and the contents within it.

“We also simulate the air movement and how light is distributed into a facility,” said Borders. “Our design engineers can simulate the air movement and then calculate how a specific pitch or angle on a foil might produce a particular cubic foot per minute (CFM) [flow], and this is normally spot on when we get to the physical prototype.”

In other words, Haiku Home wanted to make a product that people would want because it was already an optimized stand-alone product. Adding IoT just became the cherry on top.

I Have a Good Product Design. How Do I Make It a Great IoT Design?

“A lot of people get caught up in the connectivity and interoperability piece,” mentioned Borders. “But If I were the one designing the product, I would think first about use cases and what the customer would want accomplished that they don’t have today. Ask what sucks about a product, and figure out how to make it suck less. But in our case, we blow air.”

In fact, Borders noted that adding the connectivity to a product itself isn’t the big challenge when designing IoT products. After all, many products already incorporate electronics.

“Electrical engineers, mechanical engineers and industrial designers have been fighting over space in products for years, and that hasn’t changed,” explained Borders. “The only exception to that might be antenna placement, which often leads to material decisions."

Therefore, answering why your product needs IoT is a lot harder and more important than answering how you will add the connectivity in the first place. As an example, ask yourself, will your product need to be a part of a larger IoT ecosystem? Will the user experience of your fan improve if it can talk to the stove and know to speed up to help cool the kitchen while you are cooking?

“It’s one thing to be connected, but it’s another thing to have something to say,” said Borders. “I think about these things in terms of ecosystems of products. Your blender and your fan and thermostat really don’t have much to say. They can be connected, but they don’t need to be connected to one another. When I think of our ecosystem of comfort and energy conservation, I’m thinking about products that have something to say to one another, and when they do, they can sense environmental conditions and react accordingly.”

Communication between products on the IoT can become complicated. Take ecobee’s smart thermostat. It has coin cell battery sensors located around the home and a wall-mounted thermostat with a battery backup. Due to these power limitations, the thermostats will need to be strategic when communicating data. In contrast, Haiku’s fans are plugged in and do not have a limited power supply. As a result, they are continuously connected.

“For us, that means we can only pull the smart thermostat for information at certain intervals and because of that there is some latency. This latency isn’t that perceptible to our customers, but you do have to think [during the design] how this latency affects the user experience.”

I Have a Great IoT Design. What Do I Do with All This Big Data?

“People see value in data, but they don’t know what it is,” remarked Borders. “Oftentimes, they will jump to ‘How do I monetize this?’ But that’s not how we look at it. For us, the data gives us insights into how our products are being used at a macro level.”

Borders joked that they don’t have an employee looking at the data come in like some operator in the Matrix movies. Instead, Haiku Home aggregates the data, sterilizes it from personal information, and looks for patterns in customer usage.

“Looking at the data at an aggregate view gives you an idea of how products are used and how you can make them better and create new features for customers,” explained Borders.

For instance, Borders explained that by looking at the data, the company discovered that over 90 percent of the time users were using their fans at 60 percent of maximum speed. In other words, the vast majority of the fans were over-engineered for their purpose.

As a result, the company was able to design a fan with a smaller motor and lower profile without affecting the performance expectations of users. The added benefit is that this design translated into cost benefits for both Haiku Home and its customers.

I’m Collecting This Useful Big Data. Now How Do I Secure My IoT Connection?

Security is dependent on the product and the service it provides. As a result, engineers need to take into consideration the product and what might be on the network it is connected to. They then must theorize what might go wrong in the event of a hack.

In other words, security means something different for those who are designing IoT deadbolt locks than an IoT fan. But once that fan connects to the deadbolt, then things can get fishy.

“People look at the scenario at Target, which was a very high-profile security breach,” said Borders. “There was a lot to lose there, and I can’t believe how there was a loophole where the hackers hijacked the air conditioning and somehow ended up with a bunch of credit cards.”

“That was a massive failure on many fronts, not just smart devices,” he added. “Security means a lot of different things, and you need to think of the consequences if someone hijacks the control of a smart [device]. They might turn on and off a light and it might be annoying, but if someone hacks a security system, the repercussions are a lot greater. So we look at security at a bunch of different layers at the security stack.”

Another thing Borders notes is that security and privacy are not the same thing, although they are certainly connected. When collecting customer data from the IoT, it is important that the data that goes to sales is different from the data that gets to the design engineers. Engineers don’t care about your name and zip code. They care about how you use the product. As a result, it is best to use firewalls to separate this data to ensure the privacy of the users and to ensure that their personal information is secure.

To help ensure that no alarming errors exist in an IoT product’s security, Borders suggests that a company use third-party security audits on a regular basis. The last thing you want is to release a product that accidentally saves the Wi-Fi log-in information in plain text somewhere in the system. Mistakes like this can happen if you are not careful and you don’t look into your system. Performing regular audits of the product and company will help reduce the likelihood that these vulnerabilities will occur. So get in contact with a good white hat.

Finally, Borders suggests that security doesn’t rest solely on the engineers creating the products; users need to think about their own security as well. He suggests that users should use Wi-Fi Protected Access (WPA) 2 encryption for their networks and ensure that their passwords are complicated enough to limit hacking. He explained that it’s difficult for hackers to crack such an encryption. And if they can’t get into the network, they can’t control anything. He said, “WPA 2 is very important. That’s a layer of security that you just can’t overlook. So there is some fear mongering in the media.”

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

How to Add Topology Optimization to SOLIDWORKS?

ParetoWorks is a SOLIDWORKS add-in that allows engineers to perform topology optimizations on their parts based on stiffness or strength. This software uses simulation and optimization algorithms to lightweight parts without sacrificing the structural integrity of the parts.

ParetoWorks can automate the lightweighting optimization of a part based on stiffness and strength. (All images courtesy of SOLIDWORKS and SciArt.)

The software imports the SOLIDWORKS geometry as an STL file. The program then runs a finite element analysis (FEA) solver and a design optimization engine to give engineers an idea of how to reduce the weight of a part. Though ParetoWorks operates within the SOLIDWORKS framework, it is also a cloud technology available through a browser.

“Design optimization lies at the heart of modern engineering,” said Krishnan Suresh, mechanical engineering professor and CTO of SciArt, makers of ParetoWorks. “It is critical in reducing cost, reducing material, reducing weight and increasing quality, and is a driving force behind innovation. [However], design optimization can be very tricky and difficult for humans to carry out manually.”

To set up the problem, the user needs to input the units of the system, any boundary conditions, the limiting variable for optimization (stiffness or strength) and the forces the part will experience. All of these inputs are made in a simplified field of entry.

“[ParetoWorks’] focus is to make sure these structural loads are done right,” said Praveen Yadav, director of engineering at SciArt, makers of ParetoWorks. “We have the capability of handling thermomechanical loading, transient loading, modal analysis and buckling analysis. We include all of these analyses in the optimization for multi-constrained, multi-material and multi-load optimizations.”

The optimizations can also take constraints into consideration when assessing the part. Some of these constraints include:

• Maximum volume fraction
• Stiffness and displacement constraints
• Manufacturing constraints like casting draw direction
• Assembly constraints like which surfaces to maintain

The Benefits of Subtractive Topology Optimization to Additive Topology Optimization

ParetoWorks isn’t the only topology optimization software out there. However, many of them are based on additive optimization of the part as opposed to subtractive optimizations.

Though additive can give engineers a good starting point for a part based on a design space and loads, it does take a lot of data to perform this optimization. Subtractive optimization, however, requires less data but it will need to start with a part before the optimization can be performed.

Instead of mapping the whole design space, ParetoWorks uses subtractive optimization to modify the geometry, saving data costs.

“[Additive optimizations] try to map out the entire design space, this requires the storage of a lot of data, which gets expensive as you get new designs and you compare to the existing stored variable,” said Yadav. “ParetoWorks, on the other hand, attempts to stay as close as possible to the optimality front. This reduces the requirement of storing data.”

“All we care about is where we are right now and where we are headed,” Yadav clarified. “Based on that, we can choose a suitable search direction and make small increments to update the geometry. Once the geometry is updated we also perform fixed-point filtration to make sure it is robust and stable in that region.”

Since the entire design space isn’t mapped out, engineers might wonder how ParetoWorks handles the constraints. When performing this optimization, if the part hits a constraint made by the engineer, the software will reassess the step size for subsequent iterations in the optimization. This will slow down the changes made to the part and allow for a more detailed localized search for the best design in that region.

For more on ParetoWorks, read this ENGINEERING.com article. To learn more about structural optimizations using simulation, follow this link.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

Let’s face it. The Internet of Things (IoT) can be a distracting place. Phones, tablets, computers are sucking our attention enough as it is. Do we really need smart devices on the IoT grabbing even more of our attention?

Yves Béhar, founder of the Fuseproject and world-famous industrial designer, doesn’t think so. At SOLIDWORKS World 2016, the award-winning product visionary said, “There’s a huge conflict between our tech tools and living in the moment. Our screens have become giant attention-sucking monsters. We’ve become prisoners of our displays and phones.”

Béhar has a big problem with the so-called “distraction hell” being created with current IoT designs. He suggests that engineers and product developers should aim for a more invisible interface. Something so natural and instinctive that you don’t even realize it’s there until you need it.

“People confuse using the phone with being distracted and not in the moment,” said Béhar. “We all experience the social tension caused by the screens and displays that control the information we can’t live without. The alternative is to think about how that information can be transmitted in subtle and invisible ways. As humans, we have five senses—so why are we just focused on sight and screens to comprehend the signals that technology sends us?”

This idea might sound crazy, but think about it. Béhar argues that humans experience invisible interfaces constantly when interacting with nature. Who needs a weatherman when you can step outside, look at the sky, feel the temperature and moisture on your skin? The goal is to mimic these subtle cues to drive the future of IoT devices.

“IoT need to be discreet, to disappear and be a part of the way we wear or live with something—which is a really big challenge,” explained Béhar. “Technology was never a field that was easy for everyone to get into, it wasn’t discreet or the background with invisible signals and pretty designs integrated into fashion. This has been a big shift in the past few years.”

The Importance of Industrial Design to Advance IoT Technology

To bring these subtle notifications into our IoT devices, Béhar noted that we need to pay attention to industrial design early in the development cycle.

“I think back to when designers were called in last-minute to make something look pretty. It’s completely impossible to think of a good user experience that late in the design cycle,” expressed Béhar. “If you don’t have the user experience and design at the forefront you won’t be able to catch up at the end. You can’t just redesign at the end of the process.”

At SOLIDWORKS World 2016, Béhar jokes about how ignoring design in favor of technology led to Microsoft’s initial failed attempts at creating a tablet computer. Apple, however, took the idea and made it marketable.

To demonstrate why design is so important to technology, Béhar compared the failure of the early Microsoft tablets to the success of Apple’s iPad years later.

“In the mid-90s, Silicon Valley did not think design was important. Technology was mostly in enterprises and hidden from view. It wasn’t something people were using in their everyday lives,” joked Béhar. “Of course, Microsoft has done a lot of work on design lately so this is a slightly older slide but it still works.”

This is a great lesson for IoT designers to pay attention to. After all, a classic complaint made against Apple is that the company repackages inventions and innovations of others into more marketable products. But who is really to blame here? The company that made the innovation and couldn’t design it to sell? Or the company that picked up the bright idea and made millions off of a sleek design?

“Technology today is commoditized. It’s not about specs anymore. Instead it’s really about the experience,” argued Béhar. “Technology is the raw feature before design gets to it. When design gets hold of that raw feature, what we do with it to shape and mold it to our needs and lives is the job.”

Data Collection Lessons from a Smart Device that Predates the IoT

Designing subtlety into an IoT products is a challenge but it isn’t impossible once you get your head out of the box.

Béhar’s Learning Shoe was one of the first smart connected devices before the IoT was a concept.

Forget about onboard displays or phone apps. Think about how we need to interact with the product. Think about how you can make it look and feel like the traditional product.

Béhar noted the subtlety in one of his earliest smart devices, the Learning Shoe. The shoe collected data about how a user walked. Their pronation, weight and heart rate were all recorded.

The data was collected in an attempt to change the relationship between the user and the shoe maker. Béhar said, “I wanted that relationship to be continuous. I didn’t want it to be about a single product that I purchased for one season. It should be a product made smarter. It should give people a reason to go back to the manufacturer. I was interested in a customized fit and how the product is designed and made just for me.”

The challenge at the time was how to transfer the data to the manufacturer so they could make the custom shoe. When Béhar worked on this shoe, it was before the widespread use of Wi-Fi, Bluetooth and the IoT. But was this an advantage in disguise?

“Back then the data was collected on a chip and the chip was removed and then the shoe recycled and a better shoe made from this data,” explained Béhar.

The point is that the users and the designers were not inundated with data as the tests were being conducted. The user just continued on their routine, walking around. The data wasn’t transferred or even considered important until the moment it was needed.

Béhar’s Learning Shoe collects data discretely.

Though this custom-made shoe didn’t take off, it sparked Béhar’s interest in the idea of making technology more discreet, wearable, fashionable and personal. And given the wearable trends of the IoT industry, he wasn’t the only one interested.

Using Camouflage to Hide an IoT Interface Until It is Needed

Some IoT devices are not just about collecting data. At times, users will also need to give some IoT devices feedback and instructions.

However, having this interface constantly available will naturally steal the user’s attention—even when that attention isn’t needed. The best strategy is to hide the interface until the user chooses to interact with it.

hive thermostat blends into its surrounding by hiding its interface in a mirror when not in use.

Béhar noted that an IoT device he worked on that used this strategy was the hive thermostat. The device uses camouflage to blend into the home environment by hiding the user interface behind a one-way mirror coating. The interface will then come to life as soon as the user needs it.

This device is unique in that it doesn’t attempt to distract people from the world around them. In fact, it reflects that world as a means of hiding from the user.

“As IoT products enter our homes they have to be designed with the home in mind; an environment where you don’t want distraction and you don’t want complexity,” said Béhar. “[Design] isn’t just about making things pretty or work. It’s about shifting our perception of the world and making new experiences by pushing the limits of what’s possible.”

What if You Don’t Realize an IoT Design Interface is Even There?

Contrary to popular belief, not every IoT device needs a visual interface after the initial installations or even for the odd tweaks and troubleshooting. Some devices work best when you forget they are even there. They just do their job.

August smart lock gives users subtle clues as to the status of the locking mechanism.

Béhar notes that one such example he worked on is the August smart lock. This tiny little robot fits into your door and unlocks itself when it recognizes the phone in your pocket. The user just walks up to the door and feels a vibration from the phone signaling that the door is now unlocked.

Though the user can add chimes and lights to help add cues to express the status of the lock, these are not necessary. The user just needs to toss out their clunky keys, walk to the door and open the door as if the lock isn’t even there.

“Imagine if this level of attention to user experience, design and brands went into everything: your car, appliances, the things we interact with every day,” said Béhar. “It would transform technology from being something that needs to be learned to something that integrates seamlessly into our lives.”

“Technology in the home is typically installed by a ‘tech person’ and then everyone else hates it,” Béhar added. “When you install something in the home everyone has to love it or it will fail. If only one person knows how to use it or get it into the home, you’re in trouble so it’s a different bar to reach compared to a computer or a single-use tech product.”

To read about the industrial IoT (IIoT), click here. To learn about designing an IoT device that makes beer, click here.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

The process of brewing beer has been known for thousands of years. So when you add the Internet of Things (IoT) to the process, one needs to wonder how connectivity can really improve the process?

Meet the Brewbot, an IoT-enabled beer production device. (All images courtesy of Brewbot.)

One area in which IoT can help brewing is in the automation of smaller-scale productions.

Though large-scale brewing operations might have this automation down pat, any microbrewer and homebrewer will tell you that automating systems on their scale, while trying to make a consistent product, isn’t as easy as you might think.

“Brewing beer is a manual and messy process. We take this out of the equation,” said Samuel Khamis, chief science officer at Brewbot.

Khamis explained that brewing beer can take about 4.5 hours. Traditionally, this time is spent measuring water, grain and hops, and continuously checking the water temperature. The Brewbot, however, does a lot of this work for you. It will:

• Fill the tank with water
• Heat up the mash and brew while maintaining temperature
• Prompt users to add pre-measured ingredients
• Prompt users to test the specific gravity in the fermenter
• Transfer all of the fluids to where they need to go

The system communicates to the user through the Brewbot app. The app also offers a shop where users can buy brew master–approved beer recipes and ingredients. Order them on the app and they will be sent to you in premeasured amounts. All you have to do is follow the app’s instructions when making the brew.

“With our robot, you can make any beer you can make in any other brewing system,” said Khamis. “We have partnership with 40 different breweries and we are adding more all the time. Or you can make your own recipes or tweak them on your own.”

As a result, this system should save quite a lot of money and energy in shipping. After all, shipping the dry solids to make the beer is a lot easier and lighter than shipping the beer itself.

“That whole distribution network represents $24 billion a year,” said Khamis. “Just to ship glass and water around!”

“Let’s say you travel the world and you taste a beer you would like to get at home, but you can’t get it at the bars around you as they are not on the distribution for that beer. Or it doesn’t taste the same after it’s been shipped. There is no reason for that,” Khamis said. “With Brewbot, you download the recipe for the beer you want and you brew it on site where you want to serve it.”

You might then wonder, what’s in it for the company that makes the beer? Well, as Khamis explained, “they’d rather people have the beer, whether it’s coming from their bottle or through the Brewbot. A lot of the recipes on our network come from our partnership of 40 breweries.”

One key drawback to the Brewbot is that the water used in the process will have a significant impact on the results from many beer recipes. However, by assessing the data collected by the system over the IoT, the team can better assess the local water quality. This will allow for recipes to ship better water conditioning tables in the future to ensure the beer’s quality.

Designing an IoT Beer Brewing System Takes a Lot of Work

Brewbot and its phone app.

A lot of intellectual property went into the Brewbot, according to Khamis.

A team of about 20 engineers was split between designing the hardware and software of the brewery.

“Every time you set out to design something that seems simple, a lot of issues come up,” said Khamis. “From how to automate it, how you will measure out the right amount of water, how you get the feedback for the temperature. A lot of things just to make it work, then make the user experience nice and then to make it smart.”

For instance, a lot of the design went into the safety of the product. “None of the outside surfaces get hotter than about 30°C [86°F],” Khamis explained. “Nothing is exposed to the user where they can actually get hurt. The high temperature is in one process: the boiling of the water. Once that is done, there is no high temperature or high pressure process.”

To ensure these safe operational temperatures, the engineers needed to verify their designs using mechanical, thermal and flow testing. When the team got into trouble with these tests, Khamis said that they got a lot of help from the team at SOLIDWORKS.

“We used SOLIDWORKS for everything,” he said. “We get great support from them. There is no other design tool in-house, and all of our suppliers link up to that network.”

Another key part of the design came when deciding where to automate the system. Currently, all the mixing, adding of ingredients (except water) and post-brewing processes still have a human in the loop.

“Where we made the initial decisions is [in] places where people can make the biggest error,” explained Khamis. “When you are measuring out the water, the speed at which you add it and the temperature at which you add it can all affect the final quality of the beer immensely, so we try to reduce human error on anything that is mission-critical to the user process.”

However, commercial users of the Brewbot, such as microbreweries and restaurants, will want a turnkey system. To assess this, the team is looking into creating more IoT devices to connect to the brewery.

“We are working on a new product, which will be a smart fermentation vessel,” noted Khamis. “Currently, we use a standard fermentation, where you monitor the number of bubbles in the airlock. This new device will work with our brewing system and app to tell you when it’s done and what the specific gravity is.”

Khamis hinted that one day they will be able to automate the whole microbrewery system over the IoT. After all, large breweries have been able to automate much of their production cycle.

He added, “We’re working to make a system akin to Lego blocks that is fully expandable. You can buy modules and plug them in. Maybe you will want a brewing system and three fermenters or ten fermenters and no brewing system so you can hook it up to your own. All our future devices will be completely compatible with all the technology out there.”

To see more on the design of the Brewbot, watch this video:

Brewbot’s Benefit to Microbrewer Is Clear, but Fizzy for Homebrewers and Large-Scale Producers

One big question about Brewbot that seems to be confusing is, who are they are trying to market this device too?

Brewbot presentation shows off their custom beer for SOLIDWORKS World 2016.

During their presentation at SOLIDWORKS World 2016, homebrewers, microbrewers and even large-scale brewers were all mentioned, at least in passing.

Khamis said, “With Brewbot, we have democratized the beer making process, making it accessible to homebrewers, restaurants, bars and large-scale breweries.”

For the large-scale breweries, the Brewbot would really only work for pilot plant purposes, to test out new recipes. The system maxes out at producing 45 liters (11.9 gallons), and most recipes only make 25 liters (6.6 gallons). This is simply not enough for large-scale operations. And, besides that, many large-scale operations have already automated much of the process, so Brewbot doesn’t offer them much benefit with the IoT feature.

As for homebrewers, the trial and error of the process is 90 percent of the fun. Learning on the fly. Do it yourself. Making bad beers. And laughing about it. The idea is to get better by yourself until you get it right. Brewbot takes away this experience.

Additionally, the $10,000 price tag of the brewing system is rather prohibitive for the homebrewer. This is especially true when a homebrewer needs little more than a large pot, thermometer, carboy/bucket (fermenting vessel with an airlock) and some tubing to perform the same overall function of Brewbot, sans the IoT element.

As a result, the Brewbot is really only economical when working on a microbrewery or restaurant scale. Using a simple back of the napkin calculation, a brewer can break even from buying the Brewbot in about 28 batches. This calculation ignores water, electrical and kegging costs and tax. The equation also assumes recipe costs of $60 per batch, making 25 liters a batch (6.6 gallons/batch) and selling beer at $8/U.S. pint.

Since each batch will need about a week or two of fermentation time, you might want to stagger out this process with multiple fermentation tanks. To break even in about a year at this rate, you need to sell about four pints a day.

Again, this volume doesn’t seem feasible for a homebrewer operation.

However, Khamis did hint at a product called the Brewbot Core. This will be an app that can apply much of the software IP collected by Brewbot into any brewery system. If so, this will be a good way to tap into the homebrewer market and perhaps even some of the larger-scale operations that have yet to set up much of their automation.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

After all, electronics need to fit into these small devices and these small devices need to protect our electronics.With new Internet of Things (IoT) products emerging all the time, more and more mechanical designs will be driven by electronic constraints and vice versa.

Anatomy of an IoT product doesn’t leave a lot of space for the electronics. (All images courtesy of Dassault Systèmes SOLIDWORKS.)

As a result, “the software we use to design these products, mechanical CAD [MCAD] and electronic CAD [ECAD], need to drive what is happening in the real world,” said Louis Feinstein, product manager at Dassault Systèmes SOLIDWORKS. “Geometry, spacing and tolerancing all have tight constraints in IoT. Blending the MCAD and ECAD makes it easier to design for these constraints.”

The transfer of data between ECAD and MCAD users is nothing new. Various tools use industry standards to translate data from one format to another. However, this data transfer becomes complicated when users have to deal with multiple software products, versioning and metadata issues.

To address these issues, Dassault Systèmes and Altium have teamed up to create the SOLIDWORKS PCB (SW PCB) and SOLIDWORKS PCB Connector powered by Altium. Unlike other MCAD/ECAD communications tools, this new product aims to have one data file. To achieve this, the program employs Altium’s ECAD technology but is branded and operates as if it is part of the SOLIDWORKS system of software.

“We see this product as an ECAD for the design of smart connected devices,” said Aram Mirkazemi, CEO of Altium. “The way these products come together forms a platform for work that would accommodate things that were not possible in the past because of the fences between the MCAD and ECAD worlds.”

What a Unified MCAD/ECAD System Looks Like

Side-by-side comparison of SW PCB and a converter.

With these tools, users will be able to design their circuit boards with traditional techniques, such as ECAD schematic, routing and layout tools.Feinstein and his team hope SW PCB and the SW PCB Connector will revolutionize MCAD/ECAD integration. He explained that the former is a standalone product aimed at the ECAD market while the latter gives core Altium users the same functionality.

However, whereas these tools are traditionally in separate platforms, SW PCB will make them available in one single environment and user interface (UI). In addition, the software also offers electrical engineers the ability to see their SW PCB designs in a 3D environment. Finally, MCAD and ECAD users will be able to access a shared library of supplier components during their design.

“It will have all the power for the power users,” assured Feinstein. “But the UI changes will make the learning faster as you won’t need to jump between tools. It will all be in one space. The tool also uses minimalistic icons so it’s easy to pick up.”

Summary of SW PCB functionality.

How Users Can Better Merge Their MCAD and ECAD ExperienceSW PCB uses a UI similar to SOLIDWORKS 2016, a release that saw significant UI changes designed to simplify workflows. But given the reaction of the SOLIDWORKS community to the 2016 user interface, SW PCB may want to allow the user to select a “classic” SOLIDWORKS interface in a future release.

How Users Can Better Merge Their MCAD and ECAD Experience

Layout view of ECAD data.

To access the ECAD drawings in SOLIDWORKS, SW PCB users need to push their changes to the mechanical engineer through an imbedded instant messaging service. SOLIDWORKS users can access this service through an included plug-in.“We are not relying on a translator, which allows us to get tighter coupling of the information into one unified data file,” said Feinstein. “We are moving native data between the SOLIDWORKS collaborative server, but it is working in a database. It’s not translated data; it’s the data. And the MCAD and ECAD engineer can access that file at the same time.”

The mechanical engineer has the option to accept or decline the changes. If accepted, the changes are automatically updated into MCAD drawings. If declined, the ECAD drawings are sent back to the electrical engineer.

Once the mechanical engineer is finished with their work, they can send their changes to the electrical engineer through the same messaging process to ensure proper collaboration.

“Traditionally, you would have to do this all with translation type files [IDF, IDx etc.] and generate the final files through a translator,” explained Feinstein. “You don’t need a translator here. So you don’t have to do any extra work.”

Traditionally, users have relied on Windows File Explorer and subdirectories, third-party software or a more primitive “throw-it-over-the-wall” data exchange between electrical and mechanical design teams.  While admitting that the SW PCB product data manager may be a little clunky, Feinstein sees a future with SW PCB data management that approaches the highly-integrated and automated data management systems like the ones MCAD users enjoy.

What Are the Benefits of Merging ECAD and MCAD?

3D view of ECAD data.

“Once you bring ECAD into the ecosystem, we can bring in all the inner layers, materials and geometry downstream,” said Feinstein. “This allows you to do any type of simulation with higher fidelity and accuracy—from thermal to electronic cooling flow and structural simulations.”Since the ECAD and MCAD data is all available in one SOLIDWORKS-compatible file (not Parasolid, but a file format specially created for SW PCB), engineers will be able to bring that data into the SOLIDWORKS system of products.

Feinstein explained that this merger between MCAD and ECAD can open the door to various simulation options that are traditionally hard to produce with ECAD alone. “Electronics simulations typically are done with a 2.5D field solver: methods and moments sliced into integrals,” he said. However, since the ECAD models are now in a SOLIDWORKS-compatible format, the door to native 3D electronics simulations is now open for a higher fidelity model.

The benefits don’t end at simulation. Engineers will be able to use the model-based definition (MBD), tolerancing and inspection tools available from within their MCAD/ECAD model. “Often these tools are associated with MCAD, but now we are blurring the lines between MCAD and ECAD,” said Feinstein.

The Future of SOLIDWORKS’ ECAD Portfolio

Upon its release, “SOLIDWORKS Powered by Altium” will replace Altium’s PCBWorks. CircuitWorks, on the other hand, will still be maintained due to its popularity in the industry. In fact, Feinstein hinted that SW PCB capabilities may be passed on to CircuitWorks whenever possible.

The cost of SW PCB is still to be published. We expect its price to be set at around $5,900, matching the price of SOLIDWORKS Electrical Schematic Professional.

Are you excited for this new program? How often will you be using the 3D ECAD functions? Comment below.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

New Default Solver Improves Speed and Accuracy of Plastics Simulations

A significant change in SOLIDWORKS Plastics 2016 is the selection of a default solver.

Previously, users had to choose between two different solvers based on their application and the direct and indirect solvers.

CPU runtime versus test models for the CICSAM 2016, Indirect 2016 and Indirect 2015 solvers. Image courtesy of Dassault Systèmes SOLIDWORKS

“The indirect solver is faster but less accurate, and the direct solver is accurate but takes more CPU time,” said Lotfi Derbal, product portfolio manager for SOLIDWORKS Plastics at Dassault Systèmes.

Derbal noted that the new solver, named compressive interface capturing scheme for arbitrary meshes, or CICSAM, is almost as fast as the indirect solver and almost as accurate as the direct solver.

“It isn’t a good user experience to have the user decide on a solver, and we didn’t have a method to tell them what is the best solver for the situation at hand,” said Derbal. “We have decided to make the new CICSAM the default solver, as it can cover any phenomena.”

The direct and indirect solver can still be used if the user prefers to do so; this will typically be for validations and other sanity checks. Because the direct solver is known for its high accuracy, it will likely remain a popular solver in the user community, particularly when CICSAM isn’t accurate enough for their specific simulations. However, over time, Derbal suspects that the indirect solver will be phased out, so take note for any legacy code.

Other solver solutions include:

• The ability to control the number of CPUs used by the solver
• Quadratic mesh options for the warp solver
• Automatic detection of effects in the simulation

Runner Domains for Improved User Interface

User defines the runner domains for fast selections. Image courtesy of Dassault Systèmes SOLIDWORKS.

Users might find it easier to set up their models, now that they can define the runners within their injection mold as a separate domain to the mold’s cavity.

“In previous versions of the software, we couldn’t make a differentiation between cells from the runner to cells in the cavity,” explained Derbal.

“This wasn’t a problem for the simulation but it made it harder to select the hot runner and runner mesh within the user interface,” he added. “Users often needed to rotate their designs a few times to catch the whole runner if something needed to be defined to the whole runner system.”

Now when a user defines a part’s category, they can choose "runner" as one of the options. If the user wishes to set a parameter for all of the runner, they can then more quickly select all of the cells in the model that have this runner label.

Derbal notes that a situation when this would be useful is performing a warp analysis. “This assessment is calculated when the cavity and the runner is ejected,” he explained. “If we remove the runner before the cavity reaches ambient temperature, then the simulation should only focus on the cavity. So users can now set these two regions to be assigned a different category.”

SOLIDWORKS Plastics 2016 Works on Making Reporting More Legible

Another improvement to the SOLIDWORKS Plastic user experience in the 2016 release can be seen in the report template.

Derbal noted that avid SOLIDWORKS Simulation users will recognize how the Plastic 2016 reports will now look rather similar. This isn’t too surprising, as the Simulation template for the report was provided to the Plastics team from the SOLIDWORKS Simulation team to converge the formats.

Sample report made in SOLIDWORKS Plastic 2016. Image courtesy of Dassault Systèmes SOLIDWORKS.

Sample report made in SOLIDWORKS Plastic 2016. Image courtesy of Dassault Systèmes SOLIDWORKS.

All of the information in the report is the same, assured Derbal; it is now organized in a fashion that looks more professional and legible.

For instance, prior versions of the reports used to be coded in HTML; however, the new release opted for Microsoft Word formats. This will allow for easier amendments of the report by the author.

SOLIDWORKS Plastic 2016 User Interface Aligns with Product Family

Previous releases of SOLIDWORKS Plastics had a user interface that differed from the rest of the SOLIDWORKS product family.

“There were differences like how to deal with features in the dialog box,” Derbal pointed out. “Now, SOLIDWORKS Plastics uses the same general dialog box, fonts, buttons, cursor and sliders. SOLIDWORKS Plastics is now compatible with higher resolution screens just like SOLIDWORKS 2016. Today, SOLIDWORKS Plastics looks like a standard SOLIDWORKS product. It took two to three versions to have this transition. It was requested by the users.”

New SOLIDWORKS Plastics interface aligns with other SOLIDWORKS Products. Image courtesy of Dassault Systèmes SOLIDWORKS.

New SOLIDWORKS Plastics interface aligns with other SOLIDWORKS Products. Image courtesy of Dassault Systèmes SOLIDWORKS.

Due to this convergence between SOLIDWORKS and the SOLIDWORKS Plastics user interface, expect to see future updates to the general SOLIDWORKS user interface come to Plastics sooner, if not immediately.

To learn what else is new in SOLIDWORKS 2016, follow this link.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

Meshing Is Key to SOLIDWORKS Flow Simulation 2016

Lotfi Derbal, product portfolio manager for SOLIDWORKS Flow Simulation at Dassault Systèmes, notes that perhaps the most important improvement to the software is its meshing enhancements.

“For any simulation, the time spent on meshing is important to the user,” said Derbal. “When you have a large model, it means more CPU time. The compromise is: do you want a quick automatic mesh, or should you spend time to optimize the size of the global mesh?”

Typically, an automatic mesh will yield a less desirable computational model than one that is manually optimized by the user. However, Derbal notes that “with current enhancement of the mesh, even with manual operation, you can optimize the mesh very fast … faster than the last version.”

Flow Simulation also has the ability to create more uniform meshes for improved convergence and accuracy. This meshing ability can be used for both internal and external flows. Users are able to set local mesh domains within which the mesh is optimized. To define these domains more easily, Flow Simulation 2016 allows users to directly create domains around a specific design detail without adding a geometric feature, which was previously needed. Each domain can be set to have either a particular cell size or cell number for local optimization of the mesh to capture all the detail of the model while still maintaining a uniform mesh around that model.

Another added tool to SOLIDWORKS Flow Simulation is the mesh plot. This tool creates a quick reference the engineer can use to see where the mesh still needs to be refined.

The plot shows how many levels of refinement a mesh cell has undergone from the initial global mesh size. The higher the number, the more times a cell’s size has been reduced and thus finer the mesh. This information is useful in understanding if the mesh is well suited for its purpose of capturing both the geometry and the resulting flow field.

Nested Iterations Reduce CFD Computations for Transient Analysis

A significant time saver for engineers will be the ability to use nested iterations when computing a transient analysis. Derbal explained that simulations that traditionally need small time steps can take days or weeks to solve.

“If the simulation requires a time step of say 0.1 milliseconds and you want to investigate a range of 5 seconds total, then you are looking at 50,000 time steps," said Derbal. "A compressible gas flow in a vessel, for example, can take days to calculate.”

With the nested iterations, however, much larger time steps are permissible, reducing your computational time considerably. Derbal noted that the new computation will not be able to capture tiny transient details in the results, so the accuracy may be reduced by a small percentage. However, if that accuracy level is good enough for your simulation, then the time savings is well worth it.

Using nested iterations, SOLIDWORKS Flow Simulation can solve the same problem with larger time steps, thereby reducing overall computational time. Image courtesy of SOLIDWORKS.

“The problem with transient flow is that you have to follow the changing flow field,” said Derbal. “The goal of nested iterations is to get a value at a specific time stamp, where there is no interest in intermediate values. Overall, fewer time steps are needed and you get the desired time results faster.”

However, users should be aware that this new transient solver isn’t compatible with all CFD models in the 2016 version. Although full integration is expected for the 2017 release, nested iterations will currently not work on simulations with:

• Cavitation
• High mach numbers
• Rotation
• Condensation, humidity, steam and real gases

Other improvements to the transient solver include the ability to reduce the size of result data files by saving only specific parameters and the ability to produce time-averaged results.

Mirroring Symmetrical Simulations without Cutting Geometry

Solving a model in Flow Simulation with symmetry isn’t a new feature. Users were able to cut the computational domain in half, declare that domain face as a plane of symmetry and then perform their analysis.

What is new in SOLIDWORKS Flow Simulation 2016 is that now results from a simulation using symmetry can be mirrored to display the results of a full model.

Even though only half of the wing was analyzed with symmetry, results can be mirrored to show the full model. Image courtesy of SOLIDWORKS.

Considering that you can cut the computational domain not only in half but again to solve only a quarter of the geometry of a cylindrical pipe, for example, there is significant time savings to gain by employing symmetry in an analysis.  But you don’t have to sacrifice displaying the results on only a portion of the model for unknowing observers who might ask where the rest of the model has gone.

Importing Sunlight Properties for Analysis and Photo Realism

Another interesting feature in SOLIDWORKS Flow Simulation is the ability to import a Solar Access study from SOLIDWORKS into solar radiation simulations.

Solar data is not just for rendering shadows on your presentation images anymore, because there is direct applicability in simulations as well.

“Users can directly import the sunlight properties for CFD calculations so that the flow simulation doesn’t need to recalculate the view factor and then use that to deal with the radiation effect,” said Derbal.

The solar heat gain on the face of a body is a critical piece of information when looking into, for example, the air conditioning system in a car or assessing the HVAC loads of a skyscraper.

“When one part of a body is in the sunlight and the other parts are partially or fully shaded, there are different thermal values on each face,” explained Derbal. “So to calculate the flow simulation properly, knowing about the solar rays is important in getting the right thermal flux on each face.”

For more information on what is new in SOLIDWORKS 2016, follow this link.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

Engineers need tools like SOLIDWORKS Sustainability in order to begin this optimization process. Otherwise, even with the best environmental intentions, they may be flying blind.

Environmental Life-cycle Assessment 101 for Engineering Design

SOLIDWORKS Sustainability assesses the environmental impacts of a product’s lifecycle to help optimize designs. Image courtesy of Dassault Systèmes-SolidWorks.

SOLIDWORKS Sustainability works off of the environmental life-cycle assessment (LCA) framework. To engineers experienced with systems engineering, the concept is similar. However, LCA aims to add environmental optimization to a systems analysis mindset.

“LCA is a method to quantitatively assess the environmental impact of a product throughout its entire lifecycle, from the procurement of the raw materials, through the production, distribution, use and disposition of that product,” explained Eric Leafquist, senior product manager at Dassault Systèmes SOLIDWORKS.

In other words, LCA calculates the resource consumption, transportation, energy and waste production during five stages of a product’s life. These stages are defined as:

• Raw material extraction
• Material processing
• Manufacturing/assembly
• Product use
• End-of-life (EOL)

For SOLIDWORKS Sustainability, this equates to the assessment of air pollutants, water usage, carbon footprint and energy footprint, from the product’s cradle to its grave.

How Do My Design Decisions Affect the Environment?

Visual and graphical representation of the carbon footprint based on part (red = higher carbon footprint, green = lower carbon footprint). Image courtesy of Dassault Systèmes-SolidWorks.

“Typically, decisions by an engineer early in the design process lock in the environmental impact of the product for the entire life of the product,” explained Leafquist.

In the early days of simulation, environmental assessments were typically an afterthought of design, if done at all.

These assessments were made as serial processes after the design was completed for confirmation. However, if these assessments were to highlight any issues, changes to the product would be expensive or even unfeasible.

“SOLIDWORKS Sustainability allows engineers to create simple mock-ups of their products, attach materials and lifecycle processes to them, and start an analysis into the environmental impact,” said Leafquist. “As the product becomes more defined, you can continue to assess the environmental impacts in a more parallel process.”

Just as costing and simulation assessments are trending toward working in parallel with product design, environmental assessments can now also be added to this mix. This is useful as counterintuitive results for costing, simulation and the environmental impact can arise in your assessments.

SOLIDWORKS Sustainability can suggest materials for your product that have similar material properties but are better for the environment. Image courtesy of Dassault Systèmes-SolidWorks.

For instance, you can choose a more expensive material, pound for pound, that will make your product stronger, more sustainable and cost less overall. This can typically happen when the strength of the material allows the engineer to produce a smaller part that is easier to manufacture and recycle from the benchmark.

However, it is also possible that the opposite can happen. A cheaper material can produce a more expensive, less environmentally-friendly product.

The point of SOLIDWORKS Sustainability is that if you never check, you never know. Additionally, to make this material selection easier, SOLIDWORKS Sustainability has a feature that allows engineers to select a similar material for their product that might ease the environmental impact.

“Whether you like it or not, you might design a perfectly sustainable product from various perspectives, but it may end up costing too much,” said Leafquist. “Being able to gauge your design aesthetics, sustainability, strength and cost from the earliest times is a great recipe for success.”

How SOLIDWORKS Calculates Your Environmental Assessment

SOLIDWORKS Sustainability lifecycle input dashboard. Image courtesy of Dassault Systèmes-SolidWorks.

Using SOLIDWORKS Sustainability, engineers are able to input the lifecycle processes their products will likely experience within the recognizable SOLIDWORKS platform.

Based on the information the user provides for each part, SOLIDWORKS Sustainability will produce an LCA based on the GaBi sustainability database from thinkstep.

“The SOLIDWORKS CAD and Sustainability products provided the geometry, part relationships, material assignment, integrated user interface and display of the results,” said Leafquist. “The GaBi database provides the sustainability data for materialsand the algorithms for performing the LCA assessment.”

He added, “The database factors in the impacts of raw material production, use of recycled content, production methods to make the final part, painting or other finishings, transportation of parts to the point of use (or assembly), and how to process the part after its useful life. Each part can be controlled individually.”

Engineers make all the necessary selections to run the LCA from the dashboard inside the SOLIDWORKS platform.

“We can assign the manufacturing processes, use and end-of-life,” Leafquist said. “A common example is an injection-molded part out of ABS. We ask questions like, where will it be made? Where will it be used? Where will it be consumed? For instance, you can set the design to be manufactured in China, and then used and incinerated or recycled in America.”

He added, “It is an approximation to some extent, but we have a lot of factors we can add in here. For each of these we can assign the material, place of manufacture, typical use, how it will be transported and the distance from point to point.”

How to Assess Your SOLIDWORKS Sustainability Results?

There are various ways that the LCA results can be displayed using SOLIDWORKS Sustainability. For instance, there is a series of pie charts in the dashboard that will outline how much each stage in the product’s lifecycle affects each of the environmental factors.

Pie charts inform the engineer which processes contribute the most to various environmental impacts. Image courtesy of Dassault Systèmes-SolidWorks.

This will help the engineers to narrow down what processes within the product’s life contribute most to the environment.

The Assembly Visualization mode helps engineers to further narrow down which factors in the design have the greatest impact on the environment. This function color codes your assembly model to show you which parts are contributing the most to a particular environmental factor.

Leafquist noted that there is a considerable amount of freedom when the designer uses SOLIDWORKS to assess their product based on cost, simulations and environmental impact.

He said, “The tools are very closely integrated so you can run many different parametric optimizations studies with respect to the environment and the part’s performance.”

Using parameter-based optimization, and connecting these tools together, the engineer can simultaneously learn more and more about how their product will perform in the field, in production and in the environment.

Engineers should note, however, that, similar to early-stage simulations, an LCA typically used to generate relative results. In other words, it’s best used to judge one variation compared to another, rather than to find absolute results.

“It’s not a question of being inaccurate and it’s not about targeting a certain value,” clarified Leafquist. “It’s a relative measure of things. There are different ways to improve the outcome depending on how you design and plan to produce the product. It’s about getting as low as you can and [balancing] real-world requirements. If you can improve the carbon footprint and water usage, you can make better decisions. And if you do it correctly, you can also reduce costs.”

To learn more about SOLIDWORKS Sustainability, now part of the SOLIDWORKS Premium CAD product, follow this link.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

Without validation, the colorful plots of your simulation will be little more than art. Even if your model manages to converge, without validation there is no way to determine it has merged to a correct value. Setting up simulation models is getting easier, but make a bad assumption and you will find it is also easy to get bad results.
This is why validation is so important. It gives you a sanity check and could expose an inaccurate simulation result. Here are a few methods engineers can use to ensure their simulations obey the laws of physics.

Build a Lab and Track a Field Variable

Lab testing results and simulation
results compared for a hyperelastic material.
Image courtesy of Noumenon Multiphysics.

“We are always looking for new ways to calibrate our results,” notes Stuart Brown, managing partner of consulting firm Veryst Engineering.
For example, he said, “Veryst can validate the final simulation by testing the physics with a field variable or scalar quantity (like strain) we can track through experimentation. These methods can convince us and our clients that the answers are correct.”
As a result, Brown explained, Veryst and many other simulation consultants have started to build in-house laboratory capabilities. These labs have the added benefit that they can also be used to collect data, like material properties, just as easily as they can be used to validate simulations.
However, lab testing can get a little messy and complicated depending on what is being tested. This is particularly true for biological simulations. After all, you can’t just start testing on humans.
Kerim Genc, technical sales manager at Simpleware, suggested that to validate interactions between mechanical designs and biological models, such as with medical devices and safety equipment, you might need to call the butcher before you call Fisher Scientific. He said, “We were working with a large medical device company, and to validate their simulations they studied a pig. The pig they scanned for their model in the software was the same pig they performed their experiments on in real life.”
In this case, using pigs was actually kosher—with respect to validation. Since pigs are anatomically similar to people, validating the simulation with swine was a good way to ensure the mechanical design can save a human’s life.
However, validating the whole system isn’t always an easy, cheap or fast approach. Take Fatima Alleyne, research general engineer at the U.S. Department of Agriculture. She works on simulating agricultural dryers in rural and third world settings.
She said, “We take our design, embed it into a simulation, gather the data and test it in the field. Once we conduct a full testing, which can take days, we compare the results to the simulation. Based on that, we then determine if the simulations are feasible.”
Additionally, waiting to test your simulation on the final design isn’t a great idea. At this point in the design cycle it will be hard and expensive to make changes. As a result, verifying the material properties for a part of your design near the end of the development cycle is asking for trouble.

Simplify Your Model and Experiments

Image courtesy of SOLIDWORKS.

To avoid waiting too long to start validating your simulation, you might want to start with smaller experiments and simpler simulation models. It is also useful to use simpler models to represent subcomponents when modeling large systems and assemblies. These simpler subassemblies can then be independently validated. For example, engineers might model a design with beam or plate elements first before moving to 3D elements.
“Ultimately, validation of simulation is done with empirical testing; however, in cases where empirical testing is cost prohibitive or impossible, our approach is to conduct relevant material testing and verify the constitutive model(s) against the material testing data,” said Oren Lever, principal engineer for Gas Technology Institute.
Lever explained that a certain amount of trust can be put into the finite method software because it is tested every day by engineers who obtain accurate results when they input the correct models, input values and input geometry mesh resolutions. He suggests it is often enough to simulate simpler models and verify the results to available data like material testing. Once the building blocks of the simulation are all validated, the idea of the whole will be valid, as well.
Kyle Koppenhoefer, principal at consulting firm AltaSim Technologies, LLC, agreed. He said, “Validation can be a very challenging thing. For one thing, we know the software companies do a great deal of validation, so we are confident with what they are providing us. So we need to validate and verify the techniques we use the software for. So we will often look for an analytic solution or experimental data to compare against when dealing with a specific class of problems.”

Look for Data and Other Computational Methods

Image courtesy of SOLIDWORKS.

Though physical testing of your simulation is typically the most concrete method to validate your simulation, there are other tricks up an engineer’s sleeve. For instance, you can try to use another method to solve the problem and compare your results.
Udayan Kanade, CEO of Oneirix Labs, says that though his consulting firm has its own lab, there are still other ways to tackle the validation problem.
Kanade said, “Finite element analysis is one way to do it, but spectral methods and other computations, like series summation, can be used to do the same thing. Often, many of these methods are applicable and separate enough so that if the values match you can better believe what you did was right.”
Kanade has even more alternative solutions to using an in-house lab, such as:

• Comparing analytical solutions or simplified analytical models with FEA models
• Use another solver or use an in-house solver (if you have one) and compare results
• Compare the simulation with reference data from customers, literature or third parties

Sometimes, You Have to Go with Your Gut.

Image courtesy of SOLIDWORKS.

It’s not a good idea to blindly go with your gut. However, Jeffrey Crompton, principal at AltaSim Technologies, explains that there is a point where if you have enough experience, information and understanding of the system, then your gut knows best.
“It cascades down,” said Crompton. “In some cases you have an exact solution for the problem ... [or] you might find an analytical solution for specific problems. But after that you are looking at experimental data. Finally, it just comes down to gut feel. The results of the model can be accurate in so far as how the model is set up and you just have to say, ‘That feels right. I understand what is going on.’”
As previously discussed, if you have been using some sort of validation in your model throughout its creation, then at a point this validation will become natural to the engineer who will start to inherently understand the system. At that point, you just know.
But what about situations where it is impossible to do any sort of validation? This can become tricky. At this point, Crompton says, “Statistics and back of the napkin calculations can be helpful in cases where it’s more of a gut feel to validate your simulation. In these cases, you use whatever you can. You might be more reliant on extrapolations and statistical approaches, but you still need to have some level of confidence moving forward or there is no point going forward with the simulation at all.”
What methods do you use to validate your simulations? Is there anything we missed? Comment below.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

The education system can be slow to adopt technology used in the real world. Blame it on funding, tenure, legacy, bureaucracy or whatever you wish. Just don’t be surprised to see outdated hardware running outdated software in the halls of academia.
“One of the challenges with having access to engineering software is identifying what software is even available to the university or how invaluable it is to your career,” said Fatima Alleyne, research and general engineer at the United States Department of Agriculture. “As a student, I didn’t understand the scope of using CAD, C++ or simulation as a tool for my engineering career.”
Like Alleyne, many students may not get exposed to the most useful technology. Or the importance of the technology may be downplayed if covered in one week within a four-year degree. However, there is a lot of computer technology out there that engineers will need knowledge of when they walk into their new jobs. To help fill in the gaps, here are some engineering software suggestions for students from practicing engineers.

Data Analysis: Excel, MATLAB, Mathematica

“Features of Excel have been quite useful for me with creating charts and figures for my research,” said Alleyne. “I think it’s important for children in middle school and high school to learn the great features that Excel has. Or they can even learn how to use MATLAB for features that Excel is unable to facilitate. It would have been useful to me while I was in grad school.”
Alleyne has a great point; however, from personal experience, I will add that universities need to focus on this software as well. When I was a grad student, many of the engineering undergrads I taught as a TA had never touched Excel, let alone MATLAB or Mathematica. I found myself ensuring that my lesson plans reinforced what was taught in lecture through hands-on Excel computations. This ensured that the students learned to use the spreadsheet, which has inadvertently become universally used by engineers (it was invented for business).
During an assignment, a student asked his father, an engineer, for help. The student’s father showed him a new way to tackle the problem—one with which I was unfamiliar—and the student shared it wit me. The new method used a pivot table. I never knew pivot tables existed myself, and I had been diving into Excel for almost a decade. That method was instrumental to my future projects. Just goes to show the importance of continual education and why universities need to ensure that the “basics” like Excel aren’t taken for granted.

If no Program Fits the Task, Make one with C, C++ or Something Similar

Excel, MATLAB and Mathematica may not solve certain engineering problems, such as data collection and analysis or machine control. In this case, a custom application would have to be created. Enter high level programming languages.
The question often posed by students is: “which programming language to focus on?” The answer can be a bit complicated.
Learning fundamental programming concepts and structure is far more important than the syntactical idiosyncrasies of a particular language. Learning how to code in one language will make it much easier to pick up a second language, then a third. So a language like BASIC or Turing might be a good option for a novice just starting to program, as they are designed to help the programmer learn. However, these languages are not that practical in the engineering world. If you have, or hope to gain, experience programming, then a more powerful language like C, C++ or Fortran (yes, it is still in use) might be a better option down the line.

Statistics and Design of Experiments

Tools like Excel, MATLAB and Mathematica are useless if you don’t understand basic statistics, linear algebra and calculus. Of those three mathematic disciplines, statistics education is often lacking in an engineering curriculum. This is a particular shame because statistics also open the door to more advanced engineering concepts such as optimizations and design of experiments (DOE).
The ability to explore a product’s design space with a tool like modeFRONTIER can accelerate the design iteration process, bring the product’s development cycle to a minimum and help find solutions that humans couldn’t find on their own.
“DOE is important because it is a very useful method for understanding the influence of input parameters of a multidimensional system on its output(s), as well as the interaction between the input parameters,” said Oren Lever, principal engineer at Gas Technology Institute. “Moreover, DOE rolls in statistics, which is essential in getting prediction and confidence limits.”
Oren also noted that failing to teach DOE will lead to other gaps in knowledge of tools used by engineers, such as:

• Response surface models
• Interpolation
• Statistical robustness
• Selecting parameter combinations

Computer Aided Design (CAD)

“One area the schools do a fair amount of teaching in is CAD,” said Kyle Koppenhoefer, principal at AltaSim Technologies, LLC. “Those classes have morphed into teaching AutoCAD, SOLIDWORKS or similar software. The students do learn these fairly well and then have to transfer that knowledge to other packages in the industry.”
Unfortunately, drafting in engineering curricula is often limited to 2D sketches and drawings—certainly a dated practice. Universities would do well by their students if they focused more on 3D modeling. Stuart Brown, managing partner of Veryst Engineering, noted that there are many benefits to 3D CAD; benefits realized when engineers transfer CAD knowledge to other applications.
He explains that engineers can use CAD information while they use various other tools ranging from simulation (computer aided engineering (CAE)), to computer aided manufacturing (CAM). He said, “What I think will happen now is greater linkage and greater connection between the engineer and manufacturing codes. The ability to not only prototype the part but also understand its properties so you remove the iterative step of making and testing. You can make something that works the right way the first time.”

Think Outside the Engineering Wheelhouse: CAM and Product Lifecycle Management (PLM)

Not many engineers get to step in a machine shop these days. This can lead to quite a lot of confusion when workplace collaboration with the machine shop is necessary. But the same can likely be said about the sales office, the management office and even the marketing office. It can be tricky for engineers to step outside their comfort zones to work well with their corporate teams.
To help alleviate this problem, engineers would do well to learn from some product data/lifecycle management (PDM or PLM) and CAM software. The former will ensure that the team will all be on the same page, the latter will ensure that your designs are manufacturable.
Edward Lopategui, engineer, author, CEO and founder of RevVision, said that CAM and PLM are relatively non-existent in engineering curricula. He then added that, “CAM is important just to understand producibility — how things are tooled and reliably built at scale. That every edge and hole has a consequence and cost associated with it that may not be ideal.”
Lopategui further explained that “PLM is important in understanding team think — engineering increasingly is not a one man show, but many working in concert to create very complex products where ideas are not bound by imagination, but cost, schedule, supply chain, regulation and other factors, most of which are wholly outside an engineer's purview. Finding ways to efficiently map those external limitations to a design process and to coordinate those efforts among many is critical for modern design.”

Simulation: Finite Element Analysis (FEA) and Computation Fluid Dynamics

Students will spend a lot of time focusing on the theoretical physics, but these can often be impractical in the real world. After all, your designs will look quite different than a free body diagram. In fact, FEA can be instrumental when a free body diagram is statistically indeterminate.
Udayan Kanade, CEO of Oneirix Labs and Noumenon Multiphysics, said, “Simulation is very instrumental to us for what we do. I wish it was taught better or even taught in school. Simulation software is really a mathematics software. If that was taught in a more precise fashion … after all the entire world is a partial differential equation. If all of that was taught better it would be great.”
Understanding simulation software that can actually compute these physical outcomes on complex designs is necessary for many engineers in the workforce.
“Students need less theory and more practical finite element methods,” said Kerim Genc, technical sales manager at Simpleware. “There is almost no practical level knowledge taught in undergrad, and only a little taught in grad school. Even in grad school it’s mostly theory and very little hands on education. Students need a focus on FEM in industry. That is how we get people interested: real world applications.”
Though it is important for engineers to understand the theory behind the physics they are simulating to ensure their inputs and outputs are reasonable, Genc gave a perfect example of why practicing with finite elements is so vital. He said, “Students don’t get an understanding of how the use of a model influences the final model. This is called functional creep—when you have a very complex model when all you need is a simple one. I had a friend at NASA that solved what others would see as complex problems in Excel. He said, ‘This is all I need to answer my question.’ We need to encourage students to keep their models simple.”
Genc has a point: with overly complex models there is more opportunity to break them or introduce a bug. Additionally, why have a large model with large compute times when a simple model will do the trick in a few seconds?
As for which simulation software to focus on, Jeffrey Crompton, principal at AltaSim Technologies, has some suggestions. He said, “The main pieces of [simulation] software we find that are systemic across the industry are COMSOL, Abaqus, ANSYS Icepak, Fluent. Most of the time students will get some exposure to those. We are not bothered by expertise of a specific software. We much rather them be able to demonstrate they have the capability of understanding. Using the tools is relatively straightforward due to easy GUI. The problem with that is you can easily set up the problem wrong if you don’t have the fundamentals, so you need that to ensure you set up the problem correctly.”

Too Much Math and Science?

Lopategui feels that the limitation starts with the curriculum itself. There just isn’t enough time. He said, “CAE gets some coverage, but most CAM software is also largely missing. Even most CAD software is given rather cursory coverage in most engineering curricula; limited to rudimentary modeling and drawing skills rather than meaningful techniques for efficiently approaching design intent, similar to resilient modeling philosophies. There just isn't enough bandwidth in most 4-year degree programs already saturated with math and science.”
With this time limitation in mind, Koppenhoefer believes that the focus should remain on math and science. He said, “That is largely where the universities should be. When it comes to specific pieces of software, we typically see students picking them up themselves in their masters and PhD theses. They are often learning on their own. So we would want to see more students taking classes like the ones we offer so they get up to speed. We want engineers that can look at results from the computer and say, ‘We don’t think that’s correct,’ and then move on to validation of the model.”

How to Learn Engineering Software on Your Own?

Having entered her grad studies without experiencing much engineering software, Fatima Alleyne felt lost in her post graduate studies. She knew better than the undergrads the importance of the optional courses or short, week-long sessions. But as these courses weren’t targeted to graduate students, she felt there was a barrier to taking those at that point in her student career. Perhaps it’s time to make these optional courses core courses?
Alleyne said, “I learned a lot about the different software tools available on campus through conversations with undergrads and looking through the schedule of introductory classes. I missed them as a grad student as it was aimed at undergrads. In the future, if I could relive my grad experience, I would enroll in those classes.”
However, not all is lost for Alleyne or for practicing engineers that missed the boat of engineering software on campus. She said, “While working as an engineer with the USDA I’m considering to enroll in a course online so I can learn a skillset that will be invaluable to my career.” Some online material Alleyne will be looking at is from online resources such as Coursera, i Get IT, MITx, HarvardX, as well as other courses from schools and private firms.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

StrongArm Technology’s V22 is designed to transfer the loads a worker will lift from their spine to their core muscles. This tool will improve posture and reduce workplace injury.

The StrongArm team, led by vice president of engineering Mike Kim, has been using SOLIDWORKS Simulation to ensure the device is ready for manufacturing.

“From day one, until now and going forward we have been designing everything from the 18 different injection molding plastic parts, to the soft goods and aluminum clutch housing in SOLIDWORKS,” said Kim.

Over this time, Kim and his team have learned of some common simulation mistakes when validating their product.

Common Mistakes in Simulation Typically from Setup

Many simulation mistakes start from the ground up. Kim notes that assuming the wrong conditions and not understanding software limitations or how your product behaves are all common mistakes.

Before checking a mesh or simplifying geometry, it is key to know and understand the physics, loads and boundary conditions a part will actually experience.

“Boundary conditions are really important,” Kim noted. “It affects the data you get out and how the part behaves in your simulation. It ties back to understanding each part’s specifications and use case; that is the only way to understand boundary conditions.”

With regards to understanding the physics, engineers might be tempted to play with a simulation tool they don’t quite fully understand. Nicholas Veikos, simulation consultant and president of CAE Associates, wrote of once talking to an engineering team that believed they had revolutionized how to capture energy from wind when playing with a simulation tool.

However, when Veikos pointed out their error, all “Betz” were off. He wrote, “Unfortunately, they were using an incompressible fluid assumption in their CFD code to model supersonic flow. Let's just say that breaking the news to them was … uncomfortable.”

Another common simulation mistake can be inferred with the name of Kim’s product, the V22 or version 22: waiting too long to simulate.

It took Kim’s team 22 iterations of the product to come up with their final design. Though much of these iterations involved sending prototypes out in the field, others were based around simulations to ensure the product would be structurally sound and manufacturable. Waiting too long to start simulating would have delayed the development cycle.

The later someone waits to simulate, the less informed his or her design decisions will be. Engineers will essentially be working off gut instinct. By the time they simulate their final design to verify the properties it will be too late in the development cycle to do any good.

Setting up a simulation might eat up time at the start of the development cycle. However, it’s much faster to test failed designs digitally than with physical prototypes. Therefore, be sure to make time for simulations throughout a product’s development.

Kim also noted what he called the “silly small mistakes.” This is when someone puts an extra zero somewhere, have a decimal error or use the wrong material without double-checking the properties. Kim said, “These silly mistakes can really throw off your calculations.”

Users should keep track of what their inputs should be to ensure that when these errors occur they can be found easily.

The World Is Uncertain: Don’t Base Simulations on Your Expectations

A major mistake that Kim is passionate about preventing is when users have a preconceived notion of test results.

This can often cause someone to see errors where there are none. Users may doubt and change the conditions of a simulation until the results are what they expect.

“It is a mistake to not understand the data, what you put in and what you get out,” said Kim.

“I think that is one of the worst things we can do as engineers. When we are fixated on an idea or result and our data tells us otherwise, we’ve seen people do misleading things based on their findings,” he said.

A method to prevent this error is to perform some basic benchmarking and material testing. Veikos suggests that a simulation shouldn’t be the only predictive tool used by an engineering team.

Without experimentations to back up a simulation’s findings engineers are essentially flying blind. These experiments can ensure that a simulation is going in the right direction. Even if that direction is unexpected.

It should go without saying that not trusting a simulation when it is properly constructed can be disastrous. These incorrect assumptions can lead to misguided design choices that can cause a prototype or final product to fail in the field.

Additionally, Veikos notes that assuming the outcome can lead to another common simulation error: ignoring uncertainties. There will always be uncertainties that can affect results. Engineers should perform simulations based on these uncertainties even after they have completed the initial model.

“The real world is uncertain,” Veikos wrote. “Nothing is manufactured with all dimensions being ‘nominal.’ The analysis of one geometric configuration, using one set of loads, material properties and boundary conditions, barely scratch the surface.”

Error Checking Your Simulation

Kim noted that sometimes errors in the simulations will cause a mismatch between the simulation and expectations.

He said, “When this happens you have to embrace the fact that you have to double check everything. Make sure everything you have done from the beginning was correct.”

Kim explained that a good way to do this is to record assumptions and test parameters, throughout the simulation process.

“This way when something goes wrong you can trace back your process,” Kim said. “You will know what you were supposed to put in, what you expected to get out, what you were looking for and why you did certain things.”

Engineers can use their record to perform an incremental back check of the parameters. As they change these parameters, they can then compare their results to real life models.

After all, even with correct simulations, engineers still need to use a prototype to ensure the simulation is true to reality. This will allow them to really see when things don’t look right.

In other words, if the steel beam is bending a few inches instead of a fraction of an inch then maybe look into the Young’s modulus, the load, or boundary conditions.

At the end of the day, a simulation is only as smart as its users. Without a proper understanding of the physics, system and results it will be impossible to tell when a simulation is producing acceptable results. It’s all about garbage in, garbage out. If an engineer doesn’t know what they are doing, they should take the time to learn or leave it to an expert.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

StrongArm Technologies allows industrial workers, aka industrial athletes, the ability to lift heavy objects safer with more efficient posture. Using the V22 Ergoskeleton, the load of the lifted mass is moved from the arms to the lower back where stronger muscles take the majority of the load.

Additionally, the shape and stiffness of the device encourage the user to lift using proper posture, bending with the knees and keeping the back straight. The result is a 41 percent reduction in pain and fatigue.

Mike Kim, vice president of engineering at StrongArm Technologies explains how the device was designed, optimized and simulated using SOLIDWORKS and how the device can improve the workforce.

SOLIDWORKS CAD and Simulation Abilities Ensured a Manufacturable Product

Kim explained that they have been using SOLIDWORKS since the initial concepts of StrongArm’s device. All 18 injection-molded plastic parts, soft goods and even the aluminum clutch housing was first designed with the SOLIDWORKS platform.

A CAD drawing of their product allowed the StrongArm team to generate a mesh. This mesh was then used to perform simulations that verified the product was manufacturable and able to handle the stresses it would see in the field.

“In terms of optimizing our product, SOLIDWORKS has helped us incredibly,” said Kim. “Once we figured out the CAD design we wanted we took it to manufacturing. However, there is a big chasm between a CAD from a prototype to an industrial manufactured good with injection molding.”

The StrongArm team used SOLIDWORKS Plastics to ensure the product’s draft angles and ability to be injection molded. However, these changes to the product could affect how it would perform structurally in the field.

Fortunately, Kim’s team was able to use SOLIDWORKS’s structural simulation FEA capabilities to assess the product’s performance. He said, “We have been able to optimize our design one for manufacturability and be able to go back and make sure that each iteration will work structurally.”

Let the Customer Guide the Product Design

“We built the device that the [industry] told us they wanted,” said Kim. “With the V22, you have a full range of motion when you are not lifting something. But as soon as you place your hands under an object you will engage the clutches and the load will be transferred away from your hands, into the cords, over the shoulders down the spine and to your waist. This will give you the compression where you need it and shift that load away from your hands.”

It doesn’t take long for the device to help with back issues. After a few seconds you can feel the device correct your posture and ease back pain that you might feel. Kim said, “We realized working with industrial workers in the warehouse they seem very comfortable without any limitation in actual use.”

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.

SOLIDWORKS 2016's release has been announced and it includes a significant number of improvements to the platform’s simulation and validation tools.

Stephen Endersby, director of product portfolio management for SOLIDWORKS, joked that a lot of the advancements are “fundamental but not necessarily sexy. But we’ve done a lot of things with functionality that will enhance the experience of our power users.” As a result, expect evolution as opposed to revolution in the SOLIDWORKS 2016 release.

Perhaps the biggest difference that SOLIDWORKS Simulation users will notice is an overall change to the SOLIDWORKS UI. The improvements are targeted to work better with Windows 10 and higher resolution 4K and 5K monitors. Though users will need to spend some time getting reacquainted with icon locations, changes like the “breadcrumb” menus near the cursor promise a significant improvement to productivity between SOLIDWORKS 2015 and 2016.

One UI change specific to SOLIDWORKS Simulation, Flow Simulation and Plastics is the Analysis Preparation tab in the Command Manager. The tab appears when your active document is a part and you have one of the aforementioned SOLIDWORKS simulation tools added into your platform. The tab is preprogramed with frequently used tools and can be customized with user specified add-in icons.

Click here to find out more about the SOLIDWORKS UI improvements.

SOLIDWORKS Simulation has also made the jump to a browser-based system with SOLIDWORKS Online. “The online experience will be a great enhancement for SOLIDWORKS Simulation,” said Endersby. “We are still carving out the level of what you can do with simulation [on the cloud] but you can imagine that you can maximize your performance by configuring your machine online.”

Unfortunately, the function to configure your machine within SOLIDWORKS online isn’t available just yet; it’s something Endersby envisions in the future. “If I have all of the Amazon data centers to crunch my numbers then I can go pretty fast. So cloud is a huge enabler across the board,” he said.

Currently, SOLIDWORKS online is only available to a few test users and for trial-based sales purposes. There has yet to be an announcement for a wide release or licensing options.

Get Internal Insight of the Simulation with Mesh Sectioning

Expert simulation users will be excited to see that SOLIDWORKS Simulation now boasts a mesh-sectioning tool.

With this tool you can better understand and interpret results by looking into the internal mesh density. This should help users feel more confident about their results, and help make the needed mesh adjustments before running a simulation.

“The mesh sectioning is something a more advanced user will look into as they look to understand the stress gradient through a part,” said Endersby. “Mesh sectioning will ensure that the mesh is good enough through the thickness, not just along the surface.”

The tool allows users to create mesh plots to see result variations across elements. Plots can also be made based on elements clipped by a section plane.

“If I’m looking at fatigue or strain hardening,” said Endersby, “then all of these things are intrinsically coupled with material modeling and you need to know that gradient and where it is affected to mitigate the stresses created during manufacturing.”

Minimize Tension When Flattening Sheets for 3D Surfaces

SOLIDWORKS’ flatten tool was first released in 2015. Though not a simulation tool, strictly speaking, the updated version allows users to validate and reduce the tension of a flattened sheet for 3D surfaces.

For example, if you need to design a metal sheet to be bent into a boat hull, or a label to be placed on your curved surface, then this tool would be of some benefit.

“The tool creates a thin surface over an existing part and then it looks at the surface morphology,” said Endersby. “The relationships of every thin mesh there are flattened down into a nominal flat surface you define.”

Traditional FEA tools look at a material stress strain curve relationship between nodes and elements. On the other hand, the flatten tool looks at a thin sheet that is meshed but based on surface morphologies, not the material properties. In other words, the tool will create a mesh and attempt to minimize the tension between the nodes while flattening the surface.

As a result you can use the tool to see a deformation plot to detect the problem places, but you will not be able to determine the thinning of the material. You can see where holes are stretched from a circle to an oval and areas where tears and bubbles might form when molding the surface into a 3D shape. This helps users find optimal locations to cut the sheet to allow for more stretching.

Movement Simulations Define Loads without Artificial Stresses

SOLIDWORKS has also put some focus in sequencing and part movements. The new intermittent fixture capability allows users to activate and deactivate displacements over a selected time sequence in a nonlinear study.

With this tool you can sequence the movements of your parts to accurately calculate the loads needed to perform the movements without artificial stresses.

“The movements define the loads that the components are subjected too,” said Endersby. “Once you apply those loads you can use them in the part simulation.”

Endersby notes that these loads can be applied to the adaptive mesh function in SOLIDWORKS. “The adaptive mesh function will do another simulation with a refined mesh. It will look at two solutions and decide if there is a big change. This will iterate with the loads affecting the refinement of the mesh. This year we made sure that the base mesh is as good as possible so you don’t need as many refinements.”

SOLIDWORKS Plastics and Flow Simulation

SOLIDWORKS didn’t just stop with their Simulation suite. They also made some significant improvements to SOLIDWORKS Plastics and Flow Simulation.

In fact, Endersby’s favorite advancement this release was FLOW Simulation’s new transient solver.

“It will allow people to solve problems much faster than they used to before. Things will go from days to hours, hours to minutes. It’s a strong piece of technology.”

Improvements to the transient analysis allow users to:

• Speed up the calculations using nest iterations and large time steps
• Observe the flow field under time averaged results
• Save storage by saving transient data for specific parameters, instead of all parameters

As for SOLIDWORKS Plastics, the program has a new mesher. Per user requests, you can now create a high quality quadratic element mesh to improve the accuracy of warp analysis results.

According to SOLIDWORKS, the Plastics solver provides upwards of 20-30 percent improvement in speed and performance. The new flow solver can track flow fronts based on a compressive interface-capturing scheme for arbitrary meshes. Additionally, users can now control the number of CPU’s to run their SOLIDWORKS Plastics simulation.

SOLIDWORKS Plastics users will note that the software got its own UI update. This was done to ensure the software better conforms to the rest of the SOLIDWORKS family. As a result, users of SOLIDWORKS will not have to learn a new UI when they open SOLIDWORKS Plastics.

Other improvements to SOLIDWORKS Simulation 2016 include:

• Simulation

o An alternate curvature-based mesher with new algorithms
o Algorithm automatically bonds for non-touching shells within a certain distance
o Using bolts and pins on the same part
o Custom define colors, maxima and minima results in contour plots
o Detect under constrained bodies with animations based on active degrees of freedom
o Plot response graphs at the center of gravity to be treated as a remote mass for dynamic linear studies
o Equation driven results
o Improved solver error messages with links to solution articles
o More report publishing options

• Flow Simulation

o Mesh settings for uniform mesh, control planes and quality plots
o Mirror results around a 3D symmetrical model
o Import solar radiation study properties

• Plastics

o More readable report template
o Assigning a part as a runner domain

For more on what’s new in SOLIDWORKS 2016, follow their release notes. What is your favorite news from the SOLIDWORKS Simulation release? Comment below.

About the Author

Shawn Wasserman (@ShawnWasserman) is the Internet of Things (IoT) and Simulation Editor at ENGINEERING.com. He is passionate about ensuring engineers make the right decisions when using computer-aided engineering (CAE) software and IoT development tools. Shawn has a Masters in Bio-Engineering from the University of Guelph and a BASc in Chemical Engineering from the University of Waterloo.