./episode_178.sh
📚 "The ideal engineer is a composite, using knowledge and techniques from various disciplines to solve engineering problems.” – N.W. Dougherty
💻 FEBio - Multiphysics Finite Element Simulations in Biomechanics & Biophysics
FEBio is a software tool for nonlinear finite element analysis in biomechanics and biophysics and is specifically focused on solving nonlinear large deformation problems in biomechanics and biophysics. Aside from structural mechanics, it can also solve problems in mixture mechanics (i.e. biphasic or multiphasic materials), fluid mechanics, reaction-diffusion, and heat transfer.
🤓Machine Learning for Fluid Mechanics
This paper outlines fundamental ML methodologies and discuss their uses for understanding, modeling, optimizing, and controlling fluid flows. The strengths and limitations of these methods are addressed from the perspective of scientific inquiry that considers data as an inherent part of modeling, experiments, and simulations.
📚 The Anatomy of a Dynamical System
Dynamical systems are how we model the changing world around us. This video explores the components that make up a dynamical system.
👨💻 1989 Computational Fluid Dynamics Highlights
🚀 How Machine Learning Transformed the Porsche 919 Hybrid Evo
The Porsche engineers have utilized machine learning algorithms to revolutionize airfoil design. By analyzing a database of approximately 1600 airfoils, they distilled an "airfoil DNA" comprising only 5 to 10 critical design parameters. To find the best airfoil, optimization algorithms inspired by natural evolution were employed, significantly reducing the number of designs to evaluate and leading to remarkable efficiency in identifying optimal solutions.
💻 Engineering Tool of the Week – FeenoX
FeenoX can be seen either as
a syntactically-sweetened way of asking the computer to solve engineering-related mathematical problems, and/or
a finite-element(ish) tool with a particular design basis.
📚Book of the Week
Approaching ML Problems in CFD & CAE Applications: A Monograph for Beginners
This is a monograph; a practical guide and crash- course to enable mechanical and aerospace engineers to complete machine learning projects on simulation data, from start to finish.
Who this book is for: If you are interested in ML for CFD/FEA/CAE, it's probably a fit for you. This is an abstraction of experiences into a practical guide to get CFD/CAE practitioners more comfortable in machine learning projects. After hundreds of requests for support, I felt the conviction to set aside my nights for 6 months and produce this book as a more scalable means to help.
❤️ Support the Blog & Newsletter
Let’s connect on Twitter or Instagram or LinkedIn!
For any business-related issues or collaborations, feel free to write me an email to support@jousefmurad.com!
Keep engineering your mind! 🧠
Jousef