SimScale

This edition of our newsletter breaks down how AI is cutting engineering workflows from months to hours. We spotlight real case studies, the roles of Physics AI and Engineering AI, and why cloud integration is key to scaling it all. 🔄 Plus, you can try an interactive demo to experience the workflow yourself. Give it a read and see what the future of engineering feels like. #EngineeringAI #DigitalEngineering #Simulation #CloudNative #PhysicsAI #AIinEngineering

How DLR Group Engineers the Irreplaceable with SimScale? 💪 DLR Group is known for pushing design beyond code and beyond convention, and SimScale became a key part of that mission. By moving to cloud-native simulation, their team: ⚡ Accelerated design iterations 2–3x 🌬️ Validated HVAC performance and comfort early 🏗️ De-risked innovative ideas before they became costly 🌎 Collaborated in real time across teams and locations 💡 Made data-driven decisions during design, not after From optimizing cooling strategies to ensuring outdoor wind safety to preventing condensation risks in humid climates, SimScale helped DLR Group explore every “what if” and bring performance intelligence into the earliest design moments. They are a great example of how SimScale empowers engineers to Engineer the Irreplaceable! See what other customers say about designing smarter, faster, and safer: https://hubs.la/Q03WPmhz0 #EngineerTheIrreplaceable #SimScale #EngineeringExcellence #DesignInnovation #CloudSimulation #DigitalEngineering #CFD #SustainableDesign

In the second session of our AI Engineering Bootcamp, Jon Wilde and Brian Sather showed how to scale AI-powered simulation across teams, tackling common challenges like data silos, tool sprawl, and trust. Check out this snippet: an AI agent in SimScale sets up a new simulation type, moves materials and boundary conditions automatically, and even checks for mistakes, all in seconds. What usually takes 10 minutes of manual work is done instantly. Want the full insights? Watch all the sessions here 👉 https://hubs.la/Q03WQtWK0

💡 Experience Engineering AI Firsthand Check out our interactive demo and see directly how you can leverage SimScale to: - Scale Output: Embed expert knowledge for shared, high-efficiency team workflows. - Accelerate R&D: Automate complex simulations to speed up your entire pipeline. - Win More Bids: Generate intelligent, automated RFQ responses instantly. See it for yourself! https://hubs.la/Q03W71_-0 #EngineeringAI #AIinEngineering #SimScale #Innovation #DigitalTransformation

For many engineering organizations, a simulation lead time of one month is not unusual. Of course, there is always the "high-priority" fast lane where results happen overnight. But the average lead time - the true speed of innovation for the broader team - is often measured in weeks, not hours. In a recent conversation with an engineering leader, we broke down what that standard "one month" actually looks like: - Compute: Hours - Setup: Days - Queue: Weeks sitting in a backlog waiting for someone to pick it up. This of course depends on the industry+workflow and Solve speed matters, especially for deep design space exploration. But for many NPD or RFQ projects, the bottleneck is time spent waiting and manual clicking. This is why both Physics AI and Engineering AI are needed to materially accelerate engineering innovation beyond the lab: Physics AI creates value by collapsing hours of compute into seconds. Engineering AI creates leverage by addressing the wait. By automating setup and reporting, agents allow design teams to self-serve while sim experts maintain governance and visibility. If you want to see how Engineering AI helps remove the "queue tax" from your workflow, check out the link below.

If the world was linear, simulation would be much easier. (We might be bored though...) But most relevant engineering problems are nonlinear. During the last months, we continued to expand SimScale's natively integrated solver coverage across all physics, including deeper nonlinear capabilities, more material models and complex contact handling. More sophisticated analysis types usually come with more tedious setup and longer solve times. That’s where the AI systems help: - Engineering AI: To automate the click-heavy setup - Physics AI: To swap computational bottlenecks for fast predictions once you have a trained model Ultimately, with the goal to enable orders of magnitude more design decisions within the same time frame. Jon Wilde and Alex Graham are walking through the latest updates - and how they help engineering teams innovate faster - in the seasonal product update webinar on Dec 4 (link below)

We’ve brought another round of powerful updates to the SimScale platform, and you can catch the full tour in our latest product update webinar! 💪 From major boosts in structural and CFD performance to new electromagnetics features and smoother workflows across the platform, this session is packed with improvements built for real engineering impact. If you want a quick, clear rundown of what’s new, and how it can speed up your design cycle, join us 👇 🔗 https://hubs.la/Q03W1Fmq0 #Engineering #Simulation #CFD #FEA #DigitalTwin #CloudEngineering #Innovation #SimScale

🤝 Big thanks to Ram Seetharaman (Synera) and Matthias Bauer (Autodesk/NAVASTO), and everyone who joined our latest bootcamp session. We had a great chat about moving past simple AI pilots and building truly integrated, AI-native engineering processes. The key questions we tackled revolved around practical implementation and achieving real speed gains. A few practical takeaways for engineering teams: ✔️ Differentiating AI: We clarified the roles: Agentic AI (LLMs) handles complex planning and process orchestration, while Physics AI (GNNs) provides ultra-fast design predictions. ✔️ Integration is Key: Just swapping a solver for an AI model won't work. True ROI comes from deeply integrating AI into tools like CAD and redesigning the workflow—like upgrading a whole factory for an electric motor. ✔️ Building Trust: The best way to use AI today is like a "junior engineer." It handles the tedious 80% and always shows its "chain of thought" or confidence score so the expert engineer can review and sign off. If you're focused on leveraging AI to accelerate design, this session is worth a watch. Catch the full discussion here: https://hubs.la/Q03VW3-f0 #AIEngineering #EngineeringWorkflows #GenerativeAI

Engineering teams everywhere are asking the same questions: How do we adopt AI into our engineering workflows? What impact could it have? 🚀 Simulation is an area of great opportunity for AI. Early adopters are: • Capturing expert knowledge in AI tools for rapid decision-making • Autonomously managing complex simulation & RFQ workflows • Accelerating R&D cycles by exploring design spaces in seconds We created an interactive Engineering AI demo to show what this looks like in action. 👉 Experience engineering AI: https://hubs.la/Q03VMT1_0 #EngineeringAI #AIDrivenEngineering #Simulations #PhysicsAI #AgenticAI #RAndD #EngineeringInnovation #DigitalEngineering #FutureOfEngineering

Every simulation team we work with already uses automation. Scripts, macros, templates - they’re great, right up until the geometry or requirements change in a non-trivial way. That brittleness is why automation typically remains productivity tooling for the sim team, rather than an enabler for the rest of the engineering organization. We built the Engineering AI system on SimScale to change that dynamic, providing AI reasoning capabilities woven into the simulation workflow. It allows to define agents that understand intent rather than just recording clicks. Instead of hard-coding exactly which boundary condition goes where, the agent reasons through deviations, adapts autonomously if the deviation is within the realm of the expected and flags the issue and involves a human if it’s outside the guardrails. It is a mechanism to capture engineering knowledge effectively, such that simulation engineers don't have to set up the same simulation for the 50th time. The main impact isn't just time savings within the CAE group - it is the ability for the organization at large to explore way more design decisions in less time If that sounds relevant, check out the small demonstration via the link below or get in touch and we’ll show you around.