Challenges of model-based multiphysics systems simulation

Multiphysics system simulation captures your system’s behavior before it exists in the real world. It gives you the ability to address the complexity of smart, automated and electrified products that bring together mechanics, electrics, electronics, fluids, thermal effects and controls.



With multiphysics simulation, you have a factory that optimizes a system’s performance early in the design process to improve quality and reduce development time and costs. When configuring a plant model, many times it’s based on past experiences. With a modern factory, you can reduce safety margins on some components due to physical testing of worst-case scenarios; therefore, the system will be sized efficiently based on those results. Also, use this same model to optimize the system’s architecture and control scheme.

This type of future plant model is the foundation for virtual commissioning, the designing and testing of the PLC virtually, and saving time and cost towards real-life commissioning.

The simulation model is the foundation for sizing and optimizing, with the use of that model throughout your product’s lifecycle.

Model, solutions, time and gain


When looking for simulation solutions in your manufacturing process, there’s no single simulation model to cover everything you need for engineering. A multiphysics system simulation model should serve a specific purpose for a need and you can build it accordingly.



It all comes down to your system’s boundaries. If you want to optimize your energy consumption, you will need a model which covers your whole process on a high level, meaning it should capture the general behavior of pumps, heat exchangers, mixers and piping networks. This model and its components are on a system level and therefore not meant to be the most detailed version.

However, if you need to optimize a specific component like a pump, you need a model at a deeper, more complex level. A true multiphysics or system simulation platform should provide you with the several levels of complexity in the form of suitable modeling components.

In general, the boundaries between modeling levels are somewhat floating, so you want a platform with the flexibility to go into the depth you need while staying on a generic level where it suffices. The more modeling and development cycles you go through, the more you can reuse them to jump between the different levels and save time in model creation.

When considering simulation technology, remember that any starting point is good. However, if you’re trying to convince skeptics of the technology’s benefits, start at the inception to get a quick win to solve an existing problem. This approach not only reduces the chance for errors and miscalculations but will prove the value of your system.

Experts are necessary


For this kind of simulation to work, you need to incorporate the right people, with the necessary system simulation technical expertise to do the modeling and simulation, who are willing to take that next step.



Experts must also be able to create models for non-experts who consume the models. When this kind of simulation is available for a broader audience, it can also be used for consulting or sales activities. For example, a salesperson could take a predefined model of a manufacturing process to a prospective customer. While engaging in discussions about functional requirements, the salesperson can adapt the model on a high level to give insights about the required subsystems, such as the size of pumps, size of heat exchangers and influence of pipe length.

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Challenges, advantages and the future


Even though multiphysics system simulation can be used on a smaller scale at one specific point in your process, don’t be limited by using it for only one use case. You can adopt it as part of your full engineering process to reap its total rewards.



The advantages of multiphysics system simulation are many, including:

• Reducing safety margins. By virtually testing all extreme use cases, you can be sure you chose the right product for the job.

• Sizing components to the system. Being able to simulate your system in the context of varying load and behavior scenarios means being confident that your design fits under all circumstances, even if your system runs in the coldest winter or hottest summer.

• Optimizing your system architecture to run more efficiently. What systems or multiphysics simulations can do in terms of optimization goes beyond incrementally enhancing your existing design: it gives you the ability to explore new models and architectures. Unfortunately, the potential of rearranging the system’s architecture isn’t often realized until you’re looking at the full picture. System simulation can shift this realization to the beginning by frontloading your design process.

• Ensuring your simulation becomes the by-product you can use repeatedly. By going through several development cycles, you increase the number of reusable models. After a few cycles have been completed, you’ll have a set of templates guiding you much faster and more efficiently through the succeeding cycles.

The aerospace and automotive industries are paving the way with a standardized process. They incorporate system simulation in their design processes from early conception until the completion of virtual testing of components and systems; it helps them track and ensure the requirements along the development cycle.



Most companies developing products, processes or machines use some form of multiphysics system simulation. Even smaller companies are simulating where it fits their needs, especially companies with manufacturing plants in high labor-cost countries where they justify their market pricing with additional insights, quality assurances and consultancy services built on the concepts of simulation.

For smaller companies, the investment into system simulation might look like a significant risk. However, once it solves some engineering issues, the ROI is secured quickly.

One company, which is developing large injection moulding plants, had a recurring issue with vibration in their injection valves. This issue resulted in costly maintenance services and lowered customer trust. With multiphysics system simulation, they found the cause of the vibration and eliminated it; they also found that many customer claims weren’t even related to the injector, but due to some structural changes that the customer made themselves. With this simulation, they were able to enhance their product, gain confidence in their design and inform their customers of the real reason for malfunctions.



There is so much potential to leverage in this space — and many companies are getting on board with this technology.

Counteracting errors before they happen is an excellent advantage to reducing safety margins on components and improving the overall quality of your system. Though there is no single model to cover everything you need, multiphysics simulation can serve a specific purpose towards building a successful model accordingly. Moreover, experts with the necessary technical skills and expertise to implement the modeling and simulation ensures that you take all the steps towards multiphysics simulation properly.

This concludes our series on multiphysics simulation. Visit our simulation hub on the blog to learn more about what other experts are saying about the future holds for this area. 

About the author
Eric Link works in the Siemens Digital Factory division as a Presales Solutions Consultant. As part of the Simulation & Test business segment, he is responsible for the mechatronic system simulation tool Simcenter Amesim and works with customers from different industries all over Germany. Eric earned his bachelor’s degree in engineering from the University of Applied Sciences Karlsruhe in 2012 and finished his Master of Science in sustainable energy systems at the Hamburg University of Applied Sciences in 2014. His area of expertise lies within energy generation systems and thermodynamic processes such as Rankine Cycles of different kinds. Beginning as a working student and later in combination with his master’s thesis, he worked on a waste heat recovery system project.

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