Design Challenges

The team aimed to implement numerous geometry optimizations to reduce drag but initially faced challenges in identifying the most aerodynamically effective solutions. To address this, they utilized SimScale’s CFD tools to simulate changes in drag force resulting from modifications to various parts of their car. Their CAD models were created in Onshape, and thanks to SimScale’s direct integration with Onshape, the team was able to import their car bodies seamlessly—greatly improving workflow efficiency compared to other CAE software.

In addition to CFD, the team also leveraged SimScale’s FEA suite to optimize components such as the wheels and the wing support structure, ensuring these parts were both lightweight and structurally sound.

The integration of several CAE tools within a single streamlined user interface makes SimScale, compared to other options, very easy and convenient to use.

– Team Zephyros

How SimScale Simulations Led to Success

To set up their CFD simulations, the team imported their car geometry from Onshape into SimScale. They created an external flow volume, applied boundary conditions including a pressure outlet and moving wall to simulate ground and wheel motion, and selected an incompressible steady-state analysis using the k-omega SST turbulence model. A region refinement was added around the car to improve mesh resolution, and force/moment controls were used to track aerodynamic performance.

For FEA simulations, the team imported their wheel geometry, applied appropriate boundary conditions (a 60N vertical load and fixed support), and increased mesh quality to improve accuracy. These simulations were key to optimizing weight and structural integrity.

One major challenge was fine-tuning the car’s body design for aerodynamic efficiency. After researching natural streamlined shapes, the team experimented with a concave front-end profile inspired by penguins, which research showed had a lower drag coefficient than traditional teardrop shapes. Simulations confirmed their hypothesis: the concave body produced less drag (0.354N vs. 0.362N), leading the team to adopt this optimized design. The pressure visualization tools in SimScale were especially helpful in guiding this decision

Using just a few core hours, the team achieved an excellent CFD convergence with acceptable range of residual values showing an improvement over the method used in the previous season despite lower computational cost. Over the course of the project, they ran 165 simulations across both CFD and FEA. The standard meshing algorithm with a fineness level of 5 proved most effective, with region refinements providing sufficient accuracy.

SimScale proved to be an invaluable tool throughout our development process, offering both efficiency and ease of use. We’re excited to continue this partnership as we head into the World Finals.

– Team Zephyros

The post Student Success Story: Team Zephyros appeared first on SimScale.

An agentic Engineering AI is in active development at SimScale, integrated directly into our simulation platform, and we have customers using it today in alpha testing. This agent is set to make simulation even more accessible, intelligent, and productive, regardless of your experience level.

In this article, we dive into five agentic workflows that we see Engineering AI unlocking, either today or in the near future. The technology is maturing fast and we are excited about what’s coming next!

1. Helping Novice Users Get to a Working Simulation Sooner

Making simulation approachable for new users has always been at the core of SimScale’s mission. Engineering AI agents turbocharge this democratization. Rather than relying on static documentation or guides, an agent understands your CAD model and context in real time. It can proactively guide you step-by-step toward a viable setup—automatically diagnosing missing inputs, suggesting best practices, and flagging potential challenges long before you hit “run.” This transforms onboarding from a knowledge hurdle into a guided, confidence-building experience.

2. Accelerating Model Setup With Intelligent Automation

Setting up a simulation is often time-consuming, particularly when it comes to assigning boundary conditions, materials, or physics models. SimScale’s Engineering AI leverages both geometric information and vast simulation knowledge to streamline this process. The agent recognizes context from your geometry and model setup, recommends or auto-applies suitable settings, and raises issues only when human judgment is needed. The result: faster, more consistent model preparation with less context switching or uncertainty—bringing value to novices and seasoned analysts alike.

3. Guiding the Application of Company Best Practices

Scaling simulation quality and consistency across a distributed team remains an industry pain point. Engineering AI can actively reinforce organizational best practices. It serves as a digital mentor, surfacing internal guidelines and guarding against common pitfalls as users progress through a workflow. Over time, such agents learn from recurring mistakes or successes, driving incremental improvement and consolidating hard-won expertise—no matter the user’s prior experience.

4. Collaborating With Other Agents

Some of the most exciting potential of Engineering AI agents emerges through collaboration—between agents, not just humans. Multiple specialized agents, each with domain-specific reasoning, can work together across complex engineering challenges. Recently, during a joint webinar with Generative Engineering, we demonstrated a proof-of-concept agent-to-agent workflow. Here, SimScale and Generative Engineering agents jointly orchestrated a design space exploration, translating broad goals into practical analyses and autonomously iterating on concepts in the background. This kind of digital teamwork could transform the status quo of tool interoperability and ultimately deliver seamless, agent-powered multi-tool engineering workflows in the near future.

5. Automating RFQ Responses

One high-impact future application of the workflow demonstrated above is automating RFQ (Request for Quotation) responses. Mature engineering agents will soon be able to ingest customer requirements, map them to relevant design specs, set up and run appropriate simulations, and validate that the proposal meets performance criteria—all automatically. For organizations handling large volumes of RFQs or routine design studies, this unlocks significant value: reducing manual workload, speeding up response times, and freeing engineers to focus on high-impact, creative tasks.

Webinar: Is Your Organization Ready for AI?

Looking Ahead

Engineering AI agents represent a step change for simulation-driven design. They reduce ramp-up times, accelerate core workflows, promote best practices, enable multi-agent collaboration, and automate entire processes. At SimScale, we’re building these capabilities directly into our platform so that more organizations and engineering teams can benefit from agentic workflows.

If you’re interested in what AI-accelerated engineering could do for your team, get in touch with us below and be part of this new era of digital engineering.

The post What can Engineering AI do for you? Here are 5 agentic workflows set to transform productivity appeared first on SimScale.

Led by Product Manager Nur Öztürk, the session provided valuable insights into leveraging advanced simulation techniques for solenoid workings.

If you missed the live session, here are the top five highlights from the webinar:

• Optimizing Magnetic Field Distribution for Enhanced Efficiency
• Refining Electromagnetic Actuator Design
• Improving Thermal Management and Heat Dissipation
• Reducing Material Waste and Development Time
• Validating Performance Without Physical Prototypes

On-Demand Webinar

If the above highlights caught your interest, there are many more to see. Watch the on-demand Simulation Expert Series webinar from SimScale on how real-time simulation with AI is driving faster design cycles and superior products by clicking the link below.

Watch On Demand

1. Optimizing Magnetic Field Distribution for Enhanced Efficiency

The webinar emphasized the importance of precise magnetic field distribution in solenoid design. Using SimScale’s electromagnetic simulation capabilities, engineers can visualize and adjust magnetic fields to ensure optimal performance. This approach allows for the identification of areas with magnetic saturation or leakage, enabling targeted design modifications that enhance solenoid efficiency.

2. Refining Electromagnetic Actuator Design

A key focus was on the iterative refinement of electromagnetic actuators. By simulating various design configurations, engineers can assess the impact on actuator force and response time. This process facilitates the development of actuators that meet specific performance criteria, reducing the reliance on physical prototypes and accelerating the design cycle.

3. Improving Thermal Management and Heat Dissipation

Thermal performance is critical in solenoid operation. The session demonstrated how SimScale’s thermal simulation tools enable the analysis of heat generation and dissipation within solenoid components. By identifying hotspots and evaluating cooling strategies, engineers can design solenoids with improved thermal stability and longevity.

4. Reducing Material Waste and Development Time

The integration of simulation into the design process contributes to material and time savings. By virtually testing and validating designs, engineers can minimize the need for multiple physical prototypes. This approach not only conserves resources but also shortens the development timeline, allowing for quicker iterations and faster time-to-market.

5. Validating Performance Without Physical Prototypes

The webinar highlighted the capability of SimScale to validate solenoid performance through simulation alone. By accurately predicting operational behavior under various conditions, engineers can ensure that designs meet performance requirements before any physical manufacturing. This virtual validation is particularly beneficial in industries where prototyping is costly or time-consuming.

Final Thoughts

This webinar underscored the transformative impact of cloud-native simulation in engineering. By reducing simulation lead time, breaking down silos, and integrating AI-driven insights, organizations can drive faster design cycles and superior products.

For those who missed the live session, the full webinar is available on-demand on SimScale’s website. Watch it here: Enhance & Optimize Solenoid Design with SimScale.

For further reading on solenoid design and modeling, check out our blog post: Solenoid Design and Modeling: Cloud-Native Simulation.

Stay tuned for more insights in our Simulation Experts Webinar Series!

The post Top 5 Webinar Highlights: Enhance & Optimize Solenoid Design appeared first on SimScale.

This growth has also been fueled by an equally rapid expansion of model capabilities. The first steps toward multi-modality came quickly and introduced the same text-to-output inference to other content types. We already almost take for granted the ability to generate high-quality images, video, and source code through such tools.

Can AI Generate Engineering Output?

Mechanical engineering teams have adopted these tools as well to accelerate all sorts of work processes. For example, to analyze and summarize RFQs faster or to search faster for technical information. But these use cases are mostly adjacent to the core engineering work and mechanical design. So why is it that we can ask AI to generate very useful text, images, video, and code but not a useful engineering design?

Let’s consider how these types of AI models are trained. Generative AI models have been trained on trillions of tokens, primarily from the internet. Transformer models on huge datasets of public text/code and diffusion models on equally large datasets of text-image pairs. Not only is this training data available in vast quantities, but the data formats are also very straightforward to read and use for model training.

Things look rather different in the engineering realm, the most obvious challenge being that, unlike text or source code, there is little to no public product design engineering data available. Then there is also the question of data quality, in the sense of whether or not a given design is fit-for-purpose, meeting the requirements that it was designed for. Added to that is the fact that the most widely used data formats storing mechanical design information are proprietary, requiring commercial licenses even to read it, let alone manipulate it. In summary, the idea of obtaining and processing millions of engineering designs to train a generative model still looks like a very challenging ask today, but technical progress in this field is happening fast.

Does That Mean That Core Engineering Work Will Remain AI-Free for Now?

Absolutely not. In due course, novel AI approaches might rise to the challenge of handling big chunks of typically manual engineering workflows, possibly including the transformation of a text prompt into a meaningful design, but it is going to take time to get there.

Meanwhile, there are AI engineering workflows that are easier to attain while still very helpful. We can get a long way by using AI to speed up the cycle time for a single design iteration to such an extent that it appears to be instantaneous. We will do this by accelerating all of the steps in the workflow, including CAD generation, model preprocessing and setup, simulation workflows, and the analysis of results.

Once we have all that proven out, an AI agent can then drive the (accelerated) machine, taking design decisions along the way and looping around to discover optimal solutions.

Replacing a human-in-the-loop with a machine-in-the-loop in this way has the advantage of leaving the workflow and toolchain fundamentally unchanged, with the AI system ‘driving’ the tools in the same way that a human does. This means the human can easily understand what is being done and intervene at any point. Most importantly, the human can provide input to direct the AI, for example, where a design needs to balance competing objectives – decisions that require careful consideration and mutual understanding.

Not Just a Case of “Prompt Engineering”

Let’s dig into how we deploy AI to accelerate and augment engineering workflows. Let’s start by looking at how these processes work today. They tend to be centered around the manual engineering work where humans make decisions to advance the iterative design by designing and evaluating the design’s performance, depicted in green below. The CAD system involved can be conceptualized as a computational process going from parameterization to geometry (yellow) and the CAE system going from the simulation setup to the results (blue). 

This is a very simplified conceptual view of the engineering process, but helpful as it differentiates between the unstructured, human workflows in the middle and the purely computational ones left and right. All three can be automated already, to search through a prescribed design space for example. But this automation is very much rate-limited when using so-called traditional physics solvers to evaluate each design. What’s more is that AI can transform this process into something not only automatic, but autonomous.

Introducing Physics AI & Engineering AI

Let’s tackle that first bottleneck of simulation run time (the right-hand block in the diagram above). Depending on the physics and fidelity needed, a computing time of hours to days is not unusual. A growing set of AI methodologies to speed up this solve process is available, from deep learning surrogate models that replace full physics solvers to tools that speed up those ‘traditional’ solvers. Given the availability of a suitable, pre-trained, method, you can reduce the solve time almost to zero. We call these ‘Physics AI’ methods to indicate that, at the core, it’s about predicting physics with AI, and with the big benefit of being able to do that very fast. 

The second, more dispersed bottleneck visible in the process is the human interaction needed to go from a given design to a well defined simulation setup, then to consider the results of that simulation, and lastly to determine which point in the design space to look at next (the middle block in the diagram). These are all steps where an AI agent can assist, facilitate, accelerate, as well as act autonomously – performing complete workflows by operating on the existing tool stack just as a human would. As such, it is performing a series of discrete and logical steps that can be justified or even debated, as you might with a colleague. Since this agent is performing the core engineering work for you, we refer to it as ‘Engineering AI’.

Lastly, let’s turn our attention to the left-hand block – the CAD definition of a design. Once a model has been created and parameterized, generating a new variant based on a new set of parameters is already near-instantaneous. What is very much slower, though, is the process of creating that CAD model in the first place.

There are several exciting technologies emerging in the CAD space that could make the process of CAD generation far faster and more robust. Latent space parameterization, implicit representations, and cloud-native BREP are just three such technologies that could enable vastly faster design iterations, and we are actively working on integrating them into SimScale.

We Are Placing AI Tools in the Hands of Every Engineer

Thanks to its cloud-native architecture with built-in AI infrastructure, SimScale is uniquely able to provide AI features to help you navigate engineering workflows and accelerate performance predictions by leveraging your simulation data in the cloud. As we have explored so far in this blog, unlocking value from AI means touching almost every aspect of the simulation workflow. It requires a deep and immediate connection to models and data which is only practical to do in a cloud-native stack.

Engineering AI and Physics AI are built into SimScale in such a way that it can become second nature to use these tools to supercharge your productivity. SimScale users do not need to deal with any of the typical headaches experienced when attempting to deploy AI tools such as data cleaning/organizing/relocation, model versioning and management, or provisioning of suitable GPU resources for model training and execution. All of these are taken care of by the vertically integrated tool stack and intuitive user experience.

At NVIDIA GTC 25, we announced that we are making it even easier and faster to adopt Physics AI for certain applications by building a set of pre-trained foundation models. The unique aspect of these models is that they are pre-trained on a broad set of designs, providing users with a Physics AI model that they can use out-of-the-box or that they can augment with a small amount of their own proprietary training data. To learn more about foundation models in SimScale, check out this blog.

Unlock AI Value by Selecting an Impactful Application to Start With

Once you have test-driven the capability, the next step is to test-drive the value unlock. Each engineering team we work with has unique legacy data stored, sometimes from decades of engineering work. We frequently see teams expecting to start there, trying to find value in it. The reality is that finding and processing legacy data can be an immensely difficult task, and one that may take a very long time to yield results, even if useful data exists.

We recommend a different approach: Select an engineering process in your organization that – if collapsed to seconds – would create hard value for your organization (revenue or costs) and try tackling that with an AI-powered workflow. 

Remember: The best time to start leveraging AI systems in your engineering team was yesterday. The second best is today – give us a ring!

The post AI Is Sweeping Into Knowledge Work. What About Engineering? appeared first on SimScale.

The team began competing in 2023, securing 3rd place in Scotland and earning the Best Pit Display Award, which qualified them for the 2023-24 UK National Finals. Building on this success, they achieved an impressive 2nd place overall at the Nationals, once again winning the Best Pit Display Award, outperforming 30 teams at the event and over 5,000 competitors across the UK. The team’s school has a strong history in the STEM Racing competition, with three teams over the years qualifying for the World Finals, further cementing its legacy in the competition.

Design Challenges

Throughout the project, the team was tasked with designing and creating a model F1 car, incorporating aerodynamic development within the competition’s regulations. This process was meticulously documented in a comprehensive ten-page portfolio, which included a requirement to demonstrate the use of CFD (Computational Fluid Dynamics) software in the car’s development. A significant portion of the design was informed by CFD analysis, while additional engineering challenges, such as the development of custom wheel support systems, required the use of FEA (Finite Element Analysis) to ensure structural integrity under stress.

We chose SimScale as the ideal software due to its intuitive interface, which made it easy to learn and implement within our tight time constraints. It also provided invaluable data, including force coefficient graphs and detailed cross-sectional pressure images, enabling us to refine our design with precision.

– Team Statement

How SimScale Simulations Led to Success

The team began setting up the simulation by importing half of the full model to optimize meshing speed and calculation efficiency. A flow body was then created with dimensions closely matching those of the track. By utilizing a combination of cutting planes, particle traces, and force coefficient graphs, the team effectively refined key components of the car, including the end pods and front wing.

Throughout the project, challenges were minimal; however, a significant setback occurred due to a meshing issue. Upon investigation, the team identified the problem as a modeling error, which was quickly resolved using a few additional modeling commands, allowing the development process to continue smoothly.

The simulations performed exceptionally well, with each run completing meshing and computations within just a few minutes. The initial simulations took approximately 25 minutes to run, utilizing around 20 core hours. Overall, the software operated smoothly, enabling quick adjustments to both the model and the simulation settings and streamlining the development process.

SimScale has significantly reduced our development time. Its cloud-based platform allowed us to run simulations on school computers despite software and internet restrictions. Having simulations open alongside our design work improved efficiency, and moving forward, we plan to integrate SimScale into all prototypes to accelerate design iterations before finalizing race-ready models.

– Team Statement

The post Student Success Story: Team Sterna Racing appeared first on SimScale.

If you missed the live session, here are the top five highlights from the webinar.

On-Demand Webinar

If the above highlights caught your interest, there are many more to see. Watch the on-demand Engineering Leaders Series webinar from SimScale on how real-time simulation with AI is driving faster design cycles and superior products by clicking the link below.

Watch On Demand

1. The Bottleneck: Simulation Lead Time Slows Innovation

John Wilde opened the discussion by identifying one of the biggest challenges in engineering today: the long lead time of simulation in the design process. Traditionally, engineers create designs and wait for simulation experts to analyze them, causing delays and slowing iteration cycles. To accelerate innovation, organizations need to reduce simulation lead time and allow engineers to get immediate feedback on their designs.

Key takeaway: Companies that empower engineers with real-time simulation tools can drastically shorten development cycles and improve product quality.

2. How Cloud-Native Simulation is Breaking Down Silos

A prime example of reducing simulation lead time comes from Uelzener Maschinen GmbH (Uelzener), a manufacturer of industrial food processing equipment. By giving hundreds of engineers direct access to SimScale, they eliminated bottlenecks, allowing design teams to validate their work instantly rather than waiting for simulation experts.

Additionally, cloud-native simulation ensures that data is always accessible across global teams, breaking down traditional engineering silos and fostering collaboration.

Key takeaway: Cloud-based tools enable distributed teams to share insights and iterate faster without IT and hardware limitations.

3. AI-Powered Simulation: What’s Available Now and What’s Next?

John Wilde showcased SimScale’s AI-driven capabilities, which are already making real-time simulation a reality:

• Physics AI: Enables instantaneous predictions of simulation results, drastically reducing computational time
• Engineering AI (proof-of-concept): Automates aspects of simulation setup, error checking, and analysis to assist engineers in making better decisions faster

While these AI-driven enhancements are still evolving, the goal is to create foundation models for various applications (e.g., pumps, valves, heat exchangers) that allow engineers to get real-time feedback on designs without needing to run full simulations.

Key takeaway: AI is already reducing simulation times, but future advancements will further integrate AI into design workflows, making real-time physics predictions and automated engineering intelligence more powerful.

4. Trusting AI in Engineering: A Matter of Accountability

Dr. Alesandro Scafato tackled an important question: Why is AI underutilized in engineering compared to other industries like software development? The answer: Accountability. Unlike AI-generated text or images, engineering decisions have real-world consequences, impacting safety, regulations, and product integrity.

To ensure AI adoption in engineering, it must be transparent and interpretable, allowing engineers to verify assumptions and remain accountable for final decisions.

Key takeaway: AI can augment engineering workflows, but human oversight remains critical in high-stakes industries.

5. The Future of AI in Simulation: Automation, Optimization & Innovation

The webinar concluded with a look at how AI and cloud-native simulation will continue to shape engineering. The vision includes:

• Automating tedious setup tasks to allow engineers to focus on design improvements
• Optimizing complex systems by leveraging AI to instantly explore vast design spaces
• Empowering engineers to shift from “doers” to decision-makers, using AI as a tool to enhance, rather than replace, their expertise

Key takeaway: AI-driven simulation will redefine engineering by accelerating design cycles and enabling engineers to focus on higher-level problem-solving and innovation.

Final Thoughts

This webinar underscored the transformative impact of AI and real-time, cloud-native simulation in engineering. By reducing simulation lead time, breaking down silos, and integrating AI-driven insights, organizations can drive faster design cycles and superior products.

For those who missed the live session, the full webinar is available on-demand on engineering.com. Watch it here: Webinar Recording.

Stay tuned for more insights in our Engineering Leaders Webinar Series!

The post Top 5 Webinar Highlights: Real-Time Simulation with AI appeared first on SimScale.

The focus was the groundbreaking integration of Hexagon’s Marc nonlinear solver into SimScale’s cloud-native simulation platform, making advanced nonlinear FEA more accessible than ever. Here are the top five takeaways from this insightful discussion.

On-Demand Webinar

If the above highlights caught your interest, there are many more to see. Watch the on-demand Engineering Leaders Series webinar from SimScale on Revolutionizing Advanced Non-linear Simulation using Marc and SimScale integration by clicking the link below.

Watch On Demand

1. The Power of Nonlinear Simulation in Modern Engineering

Real-world engineering challenges often involve nonlinear behavior, from material plasticity to large deformations and complex contact interactions. Traditional linear solvers fall short in these scenarios, which is where Marc’s advanced nonlinear capabilities shine. Industries like automotive, industrial machinery, consumer products, and electronics require highly accurate predictions of structural performance, and the Marc solver is designed to tackle these challenges head-on.

2. Why Bringing Marc to the Cloud is a Game-Changer

SimScale’s cloud-native platform already democratizes simulation by removing the need for expensive hardware and complex software setups. By integrating Marc’s industry-leading nonlinear solver, engineers can now run highly sophisticated simulations directly in their browsers with unlimited scalability and instant collaboration. This means faster results, lower costs, and improved design decision-making at any stage of development.

3. Faster, More Robust Simulation Workflows

Nonlinear simulations can be computationally demanding, often requiring extensive fine-tuning. One of the standout benefits of using Marc on SimScale is its robust contact handling and efficiency. During the webinar, Richard Szöke-Schuller highlighted a benchmark study comparing a plastic push pin simulation:

• With traditional solvers, the simulation took almost 2 hours on 8 cores.
• With Marc on SimScale, the same simulation ran in just 13 minutes: an 80%+ reduction in runtime!

This performance boost means engineers can iterate designs faster than ever, enabling more frequent testing and optimization without sacrificing accuracy.

4. Key Applications: From Automotive to Electronics

With Marc’s nonlinear capabilities now available in the cloud, engineering teams can tackle a broad range of real-world applications scalably and more accessibly, including:

• Automotive fasteners & seals: Optimize plastic rivets and push pins with hyperelastic material models.
• Consumer product drop tests: Simulate impact scenarios to improve durability and safety.
• Electronics & PCB design: Evaluate the structural integrity of connectors, casings, and assembled components under varying loads.
• Industrial machinery: Analyze gasket sealing, elastomer components, and high-load assemblies for long-term reliability.

5. How to Get Early Access to Marc on SimScale

This powerful integration is launching soon, and engineers looking to leverage advanced nonlinear simulation in the cloud can apply for our Early Access Program.
By joining, you’ll gain hands-on experience with Marc on SimScale and help shape the future of cloud-based nonlinear analysis.

Learn more about how you can apply for early access here.

Looking Ahead: The Future of Nonlinear Simulation

As the industry moves toward more complex, high-fidelity simulations, integrating powerful solvers like Marc with cloud-native accessibility will redefine how engineers approach structural analysis. SimScale remains committed to providing cutting-edge simulation tools that are fast, flexible, and accessible without the traditional barriers of desktop-based software.

Stay tuned for more updates, and if you missed the live session, be sure to check out the full webinar recording here!

The post Top 5 Webinar Highlights: Hexagon’s Marc Solver Now on the Cloud appeared first on SimScale.

What is Engineering Analysis Software?

Imagine designing an electric vehicle and needing to know exactly how its structure will perform under varying loads. Or consider managing the heat dissipation of a densely packed telecom tower. Engineering analysis software transforms these challenges into solvable tasks by simulating real-world conditions before a single part is built. From validating designs to optimizing performance, this software is indispensable in industries like automotive, electronics, and industrial equipment, where every detail counts.

Here are some key applications and capabilities to address real-world challenges:

• Structural Analysis: Engineers can predict how materials and structures will respond to stresses, strains, and external forces. This is essential in ensuring product durability and safety across applications, from bridges to vehicle components.
• Fluid Dynamics: Simulation of fluid flow, whether for optimizing aerodynamics in vehicles or ensuring efficient cooling systems, helps engineers fine-tune designs for peak performance.
• Thermal Analysis: Managing heat is critical in industries like electronics, where overheating can compromise functionality. Thermal analysis tools allow engineers to design effective heat dissipation systems, ensuring reliability and longevity.
• Multiphysics Simulation: Real-world problems often involve overlapping physical phenomena, such as thermal and structural interactions. Multiphysics tools empower engineers to analyze these complexities in a unified framework, reducing the risk of unexpected failures.

These physics modeling applications enable engineers to make informed decisions, iterate rapidly, and deliver solutions with greater confidence and precision.

Key Features to Look for in Engineering Software

1. Comprehensive Design Visualization and Prototyping

Design space exploration tools enable engineers to predict how changes in design will affect real-world performance. These tools provide a framework for testing edge cases, analyzing trade-offs, and optimizing configurations, allowing engineers to predict real-world outcomes accurately. This ensures that every detail of a design is refined and validated before moving to production, reducing risks and improving overall performance.

Design visualization and virtual prototyping capabilities in SimScale enable engineers to iterate on multiple scenarios rapidly, benefiting from an infinite number of parallel simulations that can be used for parameterization. This capability ensures that the final prototype is robust, cost-effective, and ready for manufacturability, helping engineers meet tight deadlines while maintaining high standards of precision and reliability.

2. Cost Estimation and Manufacturability

Modern engineering tools must incorporate cost estimation and manufacturability analysis to streamline production processes. SimScale’s advanced simulation capabilities allow engineers to assess material usage, assembly challenges, and production feasibility early in the design phase. This proactive approach reduces waste, lowers costs, and ensures that designs can be manufactured without extensive modifications, making workflows more efficient and reliable.

3. Integration with Motion and Stress Analysis Tools

Motion and stress analysis tools are essential for predicting how components will perform under operational conditions. These features help engineers understand load distributions, identify weak points, and verify structural stability. SimScale’s structural analysis tools provide detailed insights into stresses, deformations, and material behavior, ensuring that products meet safety and durability standards. By incorporating these analyses, engineers can eliminate rework and reduce time-to-market.

4. Cloud-Connected Collaboration

Cloud-based solutions enhance collaboration by enabling teams to work together in real time, regardless of geographic location. SimScale’s cloud-native platform offers secure data storage and seamless sharing, allowing stakeholders to review and modify designs collaboratively. Engineers can provide real-time feedback, integrate client inputs, and maintain version control effortlessly. This fosters a cohesive development process, reducing delays caused by miscommunication or siloed workflows.

5. AI Integration for Enhanced Analysis

Artificial intelligence is transforming engineering workflows by automating repetitive tasks, optimizing designs, and improving simulation accuracy. SimScale leverages AI to accelerate simulations, allowing engineers to analyze multiple design scenarios simultaneously and predict simulation results as soon as a CAD is input to the workbench. This capability supports predictive modeling, identifies the most efficient configurations, and contributes to sustainability by optimizing energy and resource use. By integrating AI, SimScale empowers engineers to achieve precise results faster, boosting productivity and innovation.

Categories of Engineering Software for Advanced Analysis

3D Design and CAD Software

Tools like SolidWorks, Fusion 360, and Onshape by PTC are widely used for creating 3D models, CAD/CAM designs, and manufacturability checks. These platforms and software enable engineers to create detailed 3D models, conduct manufacturability checks, and streamline CAD modeling workflows. They simplify the transition from concept to production, enabling precise and efficient product development.

Simulation Software

Simulation software plays a crucial role in validating designs under real-world conditions, allowing engineers to test and refine concepts before committing to physical prototypes. Among well-known tools like ANSYS and COMSOL, SimScale distinguishes itself with its cloud-native approach. This platform enables faster design iterations by allowing engineers to run multiple simulations in parallel, reducing lead times significantly. Its ease of use makes it accessible to both seasoned engineers and those new to simulation, while its scalability supports projects and enterprises of all sizes.

Cloud-Native Engineering Platforms

Cloud-native platforms enhance accessibility and reduce hardware dependencies, enabling engineers to work with greater flexibility and efficiency. SimScale’s platform is optimized for real-time simulation, offering engineers the ability to run detailed analyses and share results without delays. Its real-time collaboration features allow teams to synchronize efforts seamlessly, focusing on tasks like optimizing aerodynamics, enhancing thermal performance, or ensuring structural integrity, all within a single, cohesive workflow.

Industry-Specific Applications of Engineering Software

Engineering software adapts to meet the unique demands of different sectors. Whether tackling the complexities of electric vehicle designs, optimizing telecom infrastructure, or improving industrial water systems, engineering software offers tailored solutions that drive efficiency and innovation.

Engineering Software for the Automotive Industry

SimScale’s cloud-native platform empowers automotive engineers to address critical design challenges across multiple domains. By enabling detailed airflow simulations, for example, engineers can optimize vehicle aerodynamics to reduce drag and improve energy efficiency. Thermal management simulations help refine cooling systems, ensuring optimal performance of EV batteries and power electronics. Additionally, SimScale supports structural analysis to help safeguard structural integrity and durability, which can be critical for safety compliance and long-term reliability. Its ability to handle multiphysics scenarios allows automotive teams to integrate thermal, structural, and fluid dynamics into a single simulation environment, streamlining the design process and accelerating time-to-market.

An automotive supplier of sustainable fastening solutions utilized SimScale to enhance the design of EV battery module connectivity. By running multiple thermal and structural simulations, they were able to validate their design faster, ensuring it met performance and reliability standards. This approach not only accelerated their development process but also minimized the risk of thermal runaway, a common challenge in EV battery systems.

Engineering Software for Electronics

Thermal and structural analyses are critical for ensuring the reliability and performance of electronic devices, especially as systems become more compact and powerful. SimScale provides tools that enable engineers to simulate heat transfer, evaluate cooling strategies, and predict structural behavior under varying loads. With the ability to handle high-fidelity thermal simulations, SimScale helps engineers optimize designs to prevent overheating, improve efficiency, and ensure durability.

Beamlink, for example, used SimScale to redesign its telecom towers. By conducting detailed thermal simulations, they identified and resolved potential heat management issues early in the design process. Additionally, structural analysis performed with SimScale validated the mechanical integrity of their towers, ensuring they could withstand environmental stresses while maintaining optimal functionality. This approach led to a faster design cycle, reduced development costs, and improved product reliability.

Engineering Software for Industrial Equipment Manufacturing

SimScale provides vital tools for improving flow efficiency, thermal performance, and structural durability in industrial equipment. It enables engineers to simulate fluid flow, optimize cooling systems, and ensure the robustness of structural components under various operational conditions. By leveraging SimScale, industrial equipment manufacturers can address challenges related to energy efficiency, sustainability, and reliability.

Nalco Water, a leader in water treatment solutions, faced urgent challenges in improving the efficiency and reliability of industrial water nozzles for high-throughput paper mills. SimScale’s CFD simulations enabled them to analyze and optimize flow distribution, reducing pressure losses and enhancing operational efficiency. This led to a 70% reduction in unplanned downtime, saving approximately $10 million annually. The redesigned nozzle also improved machine stability, product quality, and throughput while reducing material and steam consumption. By leveraging SimScale, Nalco Water achieved a streamlined design process that not only addressed immediate operational challenges but also supported long-term sustainability and cost savings.

SimScale: The Best Tool for Engineering Analysis

Cloud-Native Simulation Leadership

SimScale is a versatile platform designed to revolutionize engineering analysis. With its cloud-native architecture, it enables engineers to simulate complex scenarios without the need for costly hardware, democratizing access to advanced simulation tools. This scalability and ease of use make it suitable for experts and new users alike, transforming how teams approach engineering challenges.

AI Integration

SimScale’s AI capabilities significantly enhance simulation workflows by automating repetitive tasks and improving accuracy. By leveraging predictive modeling, engineers can analyze multiple design iterations more efficiently, leading to faster decision-making and reduced time-to-market.

For example, RLE International, a leading development, technology, and consultation service provider, sought to enhance product design, accelerate development, and reduce costs to remain competitive in the automotive industry. Using SimScale’s AI-powered tools and deploying machine learning models trained within SimScale, RLE obtained accurate aerodynamic parameters like lift, drag, and speed within seconds. As a result, RLE reduced computation costs by 45% and significantly shortened prototyping cycles. These rapid simulations enabled RLE to explore innovative aerodynamic designs while maintaining high efficiency.

Integrating AI and cloud-native simulation tools streamlines engineering workflows, enabling rapid and cost-effective design iterations. These technologies empower engineers to obtain precise results faster, optimize resources, and drive innovation in complex projects.

Accessibility for Education

SimScale also offers free access to students and educators, providing a competitive edge for those entering the engineering field by delivering hands-on experience with professional-grade simulation tools. The platform includes a comprehensive suite of learning resources such as tutorials, and learning videos which provides structured courses in CFD, FEA, and thermal analysis. These resources empower learners to tackle engineering challenges confidently while gaining practical skills applicable to real-world solutions.

SimScale also fosters collaborative opportunities through shared projects, enabling students and educators to work together and build a sense of community. By equipping the next generation with accessible, high-quality educational tools, SimScale ensures that future engineers are well-prepared to innovate and excel.

Driving Engineering Innovation with SimScale

Choosing the right engineering software is vital for staying ahead in today’s competitive environment. Digital engineering is transforming traditional practices, enabling engineers to integrate advanced tools like AI and cloud-native platforms into their workflows. SimScale exemplifies this transformation by combining cloud-native technology, AI-driven simulation, and accessibility into a single platform. Engineers can streamline workflows, iterate faster, and optimize designs with unprecedented precision and efficiency. This digital shift empowers teams to tackle complex projects confidently while staying aligned with modern engineering demands. To explore how SimScale can transform your projects, start a free trial or dive into its case studies to see the platform in action.

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Physics simulation allows engineers to model physical forces, interactions, and behavior digitally. Instead of relying solely on physical prototypes, simulations provide insights faster and at a lower cost. Effective physics modeling software empowers engineers to analyze and optimize designs across multiple domains.

This guide explores physics simulation, its diverse applications, and how SimScale, a cloud-native platform, stands out as a versatile and collaborative physics modeling tool.

What is Physics Simulation and Physics Modeling Software?

Physics simulation is the process of modeling and analyzing how physical systems behave under various conditions. It uses numerical methods to predict responses like fluid flow, thermal distribution, structural deformation, and electromagnetic fields.

Physics modeling software enables engineers to create, run, and analyze these simulations. It provides a digital environment where users define geometries, apply physical parameters, and visualize results.

Key Features of Effective Physics Modeling Software

1. Multiphysics Capabilities: The ability to combine different types of physics (e.g., thermal, structural, and fluid) within a single simulation to capture complex interactions.
2. Flexibility: Support for user-defined physics parameters, allowing engineers to tailor simulations to specific challenges.
3. Ease of Use: Intuitive interfaces and streamlined workflows make advanced simulations accessible, even for those without deep simulation expertise. This focus on user experience helps teams adopt simulation more effectively, leading to better project outcomes.
4. Real-time Collaboration: SimScale’s cloud-native platform enables teams to share simulation results effortlessly. Design engineers, manufacturing teams, and testing departments can access the latest simulation data in real time, ensuring everyone stays aligned.
5. Workflow Efficiency: Integrating simulations into the design process reduces development time. Instead of waiting for physical prototypes, engineers can make real-time adjustments based on simulation insights, accelerating decision-making.

SimScale integrates these features, providing a unified platform where engineers can model complex physical systems, simulate multiple physics domains, and collaborate effectively to achieve precise and actionable insights. By leveraging SimScale, teams can seamlessly bridge the gap between design and simulation, ensuring higher productivity and innovation.

Diverse Engineering Applications of Physics Simulation

SimScale supports a wide range of engineering applications, making it an indispensable tool across various industries, including automotive, industrial equipment, electronics manufacturing, and Architecture, Engineering, and Construction (AEC). By enabling simulations for complex physical systems, SimScale helps engineers address challenges in design, optimization, and testing more efficiently. Below is an overview of the physics available in SimScale and how to leverage them in key domains:

1. Structural Mechanics

Structural analysis simulations assess how components handle stresses, loads, and deformations. Engineers use these simulations to ensure designs meet safety and performance standards.

One example of structural analysis using cloud-native simulation is validating the load-bearing capacity of industrial machinery frames. This ensures designs meet safety standards and comply with regulatory requirements, reducing the risk of costly failures in real-world applications.

2. Fluid Flow (CFD)

Computational Fluid Dynamics (CFD) models how gases and liquids flow through and around objects. CFD simulations help engineers improve efficiency and performance in fluid-related systems.

For instance, HVAC simulations are essential for engineers looking to optimize airflow and temperature distribution in buildings. By using CFD, engineers can design systems that enhance energy efficiency while maintaining occupant comfort.

3. Heat Transfer

Heat transfer simulations model the distribution of heat within systems, helping engineers design effective cooling or heating solutions.

Thermal simulations are particularly valuable for improving battery thermal management. By modeling thermal distribution, engineers can prevent overheating and enhance the lifespan of electric vehicle batteries, ensuring both performance and safety.

4. Electromagnetics

Electromagnetic simulations predict how electric and magnetic fields interact with components. These simulations are crucial for optimizing electrical devices and minimizing interference.

For example, electromagnetic simulations can help optimize the design of electric motors by modeling the interactions of electric and magnetic fields. This enables engineers to identify inefficiencies, reduce energy losses, and enhance motor performance, ensuring reliable operation and cost savings in the long term.

5. NVH (Noise, Vibration, and Harshness) Simulation

NVH simulations evaluate and minimize noise and vibration in mechanical systems. This is especially valuable for automotive engineers seeking to enhance vehicle comfort (user experience) and product quality. For example, by modeling and reducing cabin noise and vibrations, engineers can create smoother and quieter rides, enhancing the overall driving experience for passengers.

SimScale supports all these applications in a single cloud-native platform, making it easier for engineers to switch between different types of simulations seamlessly.

The Role of Physics Simulation in Optimizing Designs

By leveraging the power of the cloud with SimScale, engineers can efficiently identify design flaws early in the development process, significantly reducing the need for physical prototypes. The platform’s ability to explore multiple design variations quickly not only accelerates development cycles but also lowers associated costs and enhances precision and accuracy.

Additionally, the flexibility of SimScale’s user-defined physics capabilities provides engineers with customization capabilities, enabling them to adapt simulations to address unique and specialized challenges and ensure results remain accurate and highly relevant to the problem at hand.

Case Study: Bühler Group

Bühler, a global leader in industrial equipment, leveraged SimScale’s cloud-native simulation to revolutionize their design process. By deploying early-stage simulations across 25 departments, over 100 engineers were able to run simulations online and on demand without capacity limitations. This approach enabled faster design convergence and reduced reliance on physical prototypes, saving both time and costs.

SimScale allowed Bühler to evaluate 60 design variants in just two weeks, a feat that previously required far more time and resources. This rapid iteration capability not only accelerated innovation but also supported bottom-line savings by eliminating the need for expensive hardware and traditional simulation tools. By streamlining workflows and enhancing collaboration across globally distributed teams, Bühler could achieve greater operational efficiency and bring products to market faster. Read more about Bühler’s success here.

“Integrating simulation early in the product development process allows one to better understand the physics and gain confidence in design choices. With SimScale, every design engineer has access to simulation.”

Clément Zémerli Senior Simulation Engineer in Corporate Technology at Bühler

Advanced Model Management Capabilities

SimScale’s advanced model management tools provide engineers with the capabilities to organize, track, and collaborate on their simulation projects seamlessly. These features are designed to enhance productivity, streamline workflows, and ensure precision throughout the simulation process.

SimScale’s model management capabilities stand out by providing:

• Version Control: Engineers can manage and track multiple iterations of their simulations, ensuring no critical updates are lost, and previous iterations remain accessible.
• Collaboration Tools: Customizable user permissions allow teams to collaborate securely, ensuring data integrity even with multiple contributors.
• Search and Organization: Engineers benefit from features such as tags, filters, and efficient search functions, enabling them to organize and locate simulation files with ease.
• Cloud-Native Integration: All model data is stored securely in the cloud, making it accessible from any location and removing the need for specialized hardware setups.
• AI-Powered Simulation Insights: SimScale leverages artificial intelligence to analyze simulation data, offering engineers predictive insights and optimization suggestions. This feature accelerates decision-making by identifying potential performance improvements or design flaws early in the process.

These tools empower engineers to streamline project workflows and make informed decisions efficiently.

Guided Simulation Workflows for Efficient Modeling

SimScale’s guided simulation workflows allow simulation experts to create templates and standardized processes. These workflows ensure consistency and help non-experts perform reliable simulations.

Step-by-Step Process

1. Import your CAD file into a SimScale template.
2. Adjust simulation parameters based on your company design guide.
3. Run the simulation in the cloud and get instant, standardized results.
4. Access, track, and share your results in SimScale from anywhere and with any team member.
5. Sync your results with your PLM system for seamless integration into your workflow.

Benefits of Guided Templates

• Efficiency: Standardized workflows reduce setup time.
• Accuracy: Templates ensure simulations are performed correctly.
• Collaboration: Teams can follow established processes, enhancing teamwork.

More about SimScale’s guided simulation workflows here.

The Power of Multiphysics Simulation in SimScale

SimScale’s Multiphysics simulation in the cloud allows engineers to model multiple physical phenomena in a single comprehensive analysis. This provides a more accurate representation of real-world behavior.

It also enables flexibility and a seamless combination of analyses, all in a single workbench. SimScale’s “One Platform, Broad Physics” approach enables engineers to combine different physics types, such as thermal, structural, electromagnetic, and fluid simulations, to analyze complex interactions within a design.

Here are some real-world examples:

• EV Motor Development: Analyze heat, stress, magnetic flux, and fluid interactions to optimize motor performance.
• Battery Thermal Management: Ensure efficient cooling in battery packs to prevent overheating.
• Fluid Flow Optimization: Improve industrial processes by modeling fluid dynamics accurately.

Give SimScale a Try?

Physics simulation enables engineers to overcome design challenges with precision and speed, making it an indispensable tool in modern engineering. By providing access to multiphysics analysis, guided workflows, and real-time collaboration, SimScale ensures engineers can streamline their processes and achieve optimized designs faster and more effectively.

Explore SimScale’s comprehensive resources for more information, or start simulating today by clicking the button below.

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SimScale offers cloud-native structural analysis tools based on Finite Element Analysis (FEA) for all types of structures under different conditions. In this article, we address some of the frequently asked questions (FAQs) about structural analysis in SimScale, offering practical insights for engineers seeking faster and more accurate simulation.

FAQs About Structural Analysis

Conclusion

Structural analysis is a critical process for ensuring the safety, efficiency, and durability of various structures by thoroughly examining their responses under different loading conditions. The use of advanced tools like SimScale, which leverages Finite Element Analysis (FEA) and integrates the robust Code_Aster solver, enables engineers to perform precise and comprehensive simulations. Do you have any other questions that we did not cover above? Contact us and let us know. Our support team is available to support you and answer your questions.

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