Low-Code in MATLAB, Free ML for Fluid Mechanics Course & 80 Years of FEM
💨 Turbulence breaks a tree’s branches, but only tickles an eagle’s wings.
🤖 Low-Code AI in MATLAB
MATLAB strengthens its low-code AI capabilities: the Classification Learner and Regression Learner apps now support explainability with LIME and Shapley values, so you can understand how trained models make predictions at a local level.
This is part of a bigger trend: low-code AI is becoming mainstream. Whether it’s MATLAB apps for data scientists or automation platforms like n8n, low-code is lowering the barrier to building, deploying, and explaining AI systems. Instead of writing complex code from scratch, more professionals can now experiment, automate, and operationalize AI directly, making innovation faster and more accessible.
💧Machine Learning for Fluid Mechanics: Analysis, Modeling, Control and Closures
This is the second lecture series dedicated to machine learning for fluid mechanics. The course is hosted by the Université libre de Bruxelles (ULB) from 29 January to 02 February 2024.
The lecture series is co-organized by Miguel A. Mendez from the von Karman Institute (Belgium), Alessandro Parente from the Université libre de Bruxelles (Belgium), Andrea Ianiro from Universidad Carlos III de Madrid (Spain), Bernd R. Noack from Harbin Institute of Technology, Shenzhen (China) and TU Berlin (Germany) and Steven L. Brunton from University of Washington (US).
🤓 Eighty Years of the Finite Element Method: Birth, Evolution, and Future
This document presents comprehensive historical accounts on the developments of fnite element methods (FEM) since 1941, with a specifc emphasis on developments related to solid mechanics. We present a historical overview beginning with the theoretical formulations and origins of the FEM, while discussing important developments that have enabled the FEM to become the numerical method of choice for so many problems rooted in solid mechanics.
🚀 Noise cancelation gone too far!
Getting rid of the side-view mirrors is an aggressive but effective solution to the problem of decreasing its induced aeroacoustics sound, especially more prominent in our vehicle fleet becoming quieter through electrification…
Learn about side mirrors aeroacoustics CFD predictions in this great Siemens article.
Free European Conference on Meshless CFD - Register for Free
My friends at Particleworks are hosting an event in Munich on October 8–9, 2025, bringing together engineers, simulation experts, and R&D professionals for two days of knowledge sharing and discussions.
Highlights:
E-Mobility & Thermal Management – 90% faster EV simulation cycles, with demos from Dumarey Group, R&DCFD & ZF Group
Drivetrain & Gearbox Design – WITTENSTEIN, SDF & SKF on lubrication, drag optimization & gearbox loss estimation
Industrial Process Optimization – JKU Linz, SADEN & TotalEnergies on drying, startup modeling & oil aeration
🎬 Video of the Week
💻 Engineering Tool of the Week - Open Source Multiphase Flow Modeling for Real-world Applications
This open-source software has over three decades of development history and more than 7,000 registered users worldwide. MFiX has become the standard for comparing, implementing, and evaluating multiphase flow constitutive models and has been applied to an extremely diverse range of multiphase flows applications. The successes achieved in modeling complex multiphase flow systems have led to new and improved key attributes such as drag, polydispersity, attrition, and agglomeration models, among other significant advances.
📚 Book of the Week
Modern Fortran by Milan Curcic 📚
Modern Fortran teaches you to develop fast, efficient parallel applications using twenty-first-century Fortran. In this guide, you'll dive into Fortran by creating fun apps, including a tsunami simulator and a stock price analyzer. Filled with real-world use cases, insightful illustrations, and hands-on exercises, Modern Fortran helps you see this classic language in a whole new light.
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Keep engineering your mind! ðŸ§
Jousef