Users Talk Common Mistakes in Simulation

SOLIDWORKS User Validates Product with Simulation


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

Arc Suspension Stress Analysis

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 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.

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