./episode_124.sh
./episode_124.sh
📚 “Who questions much, shall learn much, and retain much.” – Francis Bacon
Hey friends & nerds! 👋
Welcome to the Sunday Science Newsletter where we explore science, systems & tools that help us become smarter people.
♨️ Thermal Engineering, Heat Sink Optimisation & Coldstream – Lieven Vervecken | Podcast #83
🌀 Mathematicians Tame Turbulence in Flattened Fluids
By squeezing fluids into flat sheets, researchers can get a handle on the strange ways that turbulence feeds energy into a system instead of eating it away.
💻 A Basic Derivation of the Finite Element Method (FEM)
A beginner’s approach to derive the infamous FEM formula KU=F from a one dimensional (1D) Bar element problem.
🧠Introduction to Deep Learning for Fluid Mechanics
💦 CFD Python: 12 steps to Navier-Stokes
This post describes the first practical module of Prof. Barba's Computational Fluid Dynamics class, as taught between 2010 and 2013 at Boston University. The module is called "12 steps to Navier-Stokes equations".
✍️ My Twitter Productivity Tool – PixieBrix
If you hate coming up with ideas of things to tweet, GPT and PixieBrix can help save you valuable time. This mod analyzes your Twitter profile to suggest topics, tone, and audience, and then suggests a tweet for you. 🤓
💻 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
Turbulence: The Legacy of A. N. Kolmogorov
This textbook presents a modern account of turbulence, one of the greatest challenges in physics. The state-of-the-art is put into historical perspective five centuries after the first studies of Leonardo and half a century after the first attempt by A. N. Kolmogorov to predict the properties of flow at very high Reynolds numbers. Elementary presentations of dynamical systems ideas, of probabilistic methods (including the theory of large deviations) and of fractal geometry make this a self-contained textbook.
🙃 Meme of the Week
Professors be like.
Invest in Yourself👇
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🎬 Animation of the Week
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Keep engineering your mind! 🧠
Jousef