Simulation and testing, at the heart of Engineering a Better World


Engineers today create products and processes that have the potential to make the world a better place for us by improving the way people live, travel, connect and treat disease. As they develop new products or improve existing ones to meet demand for more personalized, lighter, and safer products, they must adhere to updated specifications and requirements to reduce emissions, improve energy efficiency, and increase operational performance.

One of the greatest challenges engineers face is to design reliable and sustainable products while managing complexity, reducing costs and speeding time to market. How does an engineer turn these seemingly contradictory requirements into opportunities?

The introduction of a comprehensive digital twin is the key factor for sustainable industrial innovation success. By applying a digital twin, engineering teams can manage the complexity with trade-offs in design decisions that lead to product innovation. The combination of simulation and testing is crucial to bring the digital twin to life. I see this as the “beating heart” of such comprehensive digital twins. Digital simulation and testing applications help leverage design complexity and accelerate innovation across the lifecycle by providing insights into real-world performance of products and processes.

There are four key investment requirements that can accelerate innovation through simulation and testing solutions:

Model the complexity

Solving complex industrial problems requires an approach that encompasses multiple disciplines and physical methods to capture all the complexities that affect product performance. Although engineers can now evaluate performance for a wide range of physical phenomena, historically each area required a specific set of software tools. Interfaces, processes, files and vocabulary can be completely different and hinder collaboration. In this situation, full integration between multiple analysis tools is required to better predict the performance of the products. A model-based approach that enables multi-domain simulation and verification is essential for the development of modern advanced products.

Let’s take a look at an incredible example of complexity: the human body. Vyaire Medical is a leading manufacturer of solutions for the treatment and monitoring of respiratory diseases in all life stages. Their engagement poses a significant engineering challenge. After all, patients come in different shapes and sizes (morphologies), and each patient has a unique respiratory profile.

In the past they used simplified models and while they were able to extract some meaningful insights from them, their lack of realism limited their use. Gradually, the team began to introduce patient-specific data into their CFD (Computational Fluid Dynamics) simulations provided by Siemens Simcenter software. Today, they use scans of real human heads that depict feature morphologies for all patient populations: adults, children, and infants.

Discover the possibilities

Exploring designs requires the use of different technologies. Using artificial intelligence (AI) and machine learning, hundreds of system architectures can be generated, which can be quickly evaluated to identify the most promising through a process called generative engineering.

That’s how it goes NEVS, a Swedish electric car manufacturer, designs premium electric vehicles and mobility experiences that are simple, engaging and distinctive, while also shaping a better, cleaner future for all. They leveraged the flow-based topology optimization in Simcenter and then coupled it with Siemens NX Additive Manufacturing solution. The result was a 400% increase in demisting ability, 80% more flow around passengers’ feet, and 16% less volume for potential cost savings. They are a great example of sustainable industrial innovation in action.

walk faster

Speed ​​and agility can be achieved by using models in development and extending them to other phases of the product lifecycle. For example, reduced-order models allow digital twins to be used in many applications by conveying only their core attributes, including design, control, and condition monitoring.

Artificial intelligence is a ubiquitous technology today, and the tech only scratches the surface of what’s possible with AI. For example, it can help engineers by enabling faster setup processes and predicting the next command they are likely to use, allowing both new and experienced engineers to work with the same tool. Neural network models can accelerate performance predictions for early designs by orders of magnitude while capturing the trends of the changes. AI can transform digital twin models created during the design engineering phase into executable digital twins that run as real-time intelligent virtual sensors on the edge device. Digital twin models can be used to continuously predict performance while monitoring the product in real-time.

Simulation and testing tools in the cloud enable engineering teams to analyze larger problems with higher fidelity, run more complex simulations, run multiple design exploration studies simultaneously, and even adapt to changes in the simulation as needed. The goal of these solutions is to help engineering teams make better design decisions, faster, with performance data provided by simulation and testing solutions.

Stay integrated

Linking relevant activities throughout the product development process ensures that the right person has access to the right information at the right time. Traditional CAD-to-CAE processes can be error-prone because they are disconnected and involve multiple users from different teams with different technical backgrounds. For today’s complex products, an integrated toolset that combines design with multidisciplinary simulation allows engineering teams to stay aligned, work much faster, and avoid rework.

Today, the role of physical testing is evolving. In this new digital age, it is crucial to test, validate and optimize real designs. Test departments are feeling the impact of this development in their work, both in terms of volume and technical content. In order to achieve maximum productivity, innovative test solutions are crucial.

Princess Yachts is a great example of combining simulation and testing. They are one of the world’s leading builders of luxury motor yachts, offering a range of sport yachts, flybridge motor yachts and super yachts. Each yacht is unique, so noise and vibration are different for each build. Rigorous testing is required to perfect overall acoustic performance inside and out. They use advanced digital NVH (Noise, Vibration, Harshness) test methods. Physical tests on new materials ensure their initial simulation models are accurate, and they use automated test templates and batch reports to efficiently certify dozens of configurations.

Combining testing and simulation, the physical and virtual worlds interact closely to complement each other in multiple scenarios. Test data is used to create, validate, improve, and advance simulation models. Simulation models expand testing capabilities and improve and validate test data. As product complexity increases, simulation and testing teams cannot afford to work in isolation from the rest of the organization. Traceability and standardization of processes are becoming crucial. Investing in a managed environment can pay off tremendously.

Looking beyond the typical applications, electrification and autonomous driving applications, which increasingly require more complex wiring design, are a prime example of an additional layer of complexity. Staying integrated in this case means that teams designing wire harness and routing systems need to be coordinated with teams performing system simulation, mechanical simulation, and electromagnetic analysis to avoid interference.

For years, Siemens has invested in the accuracy, precision and completeness of what is commonly referred to as a digital twin, essentially a digitized model of a product or system. The concept is used across many industries to design and build products ranging from the largest chemical process plants to the smallest mobile devices and everything in between, whether it’s airplanes, ships, cars, engines, medical devices, home appliances, and batteries is .

The Siemens Xcelerator portfolio of software, services and low-code tools for application development contributes to digital transformation. By blurring the lines between industries, today’s leading engineering teams can leverage the latest solutions to design tomorrow’s innovative products, today.


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