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🤓 The first principle is that you must not fool yourself and you are the easiest person to fool. - Richard Feynman
Hey friends & nerds! 👋
Welcome to the Sunday Science Newsletter – in this newsletter we explore & discuss strategies, systems & tools that help us become better, smarter and more effective scientists.
💦 CFD Python: 12 steps to Navier-Stokes
CFD Python, a.k.a. the 12 steps to Navier-Stokes, is a practical module for learning the foundations of Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow. The module was part of a course taught by Prof. Lorena Barba between 2009 and 2013 in the Mechanical Engineering department at Boston University (Prof. Barba since moved to the George Washington University).
🎙️ We Want You 🫵 Be a Guest Speakers on "Jets In Space"
My friend Dennis Belen is looking for some guests on his great podcast with experience in Mechanical, Materials, Aerospace Engineering, Fluid Mechanics/Dynamics, engineering simulations, prototype development.
If you’re interested, feel free to contact him via email at belenaerospace@gmail.com
🌎 MIT Finite Element Procedures for Solids and Structures, Linear Analysis
Excellent MIT class on FEM by instructor and FEM legend Klaus-Jürgen Bathe.
🧠 Strategies for Turbulence Modelling and Simulations
This is a paper by P.R. Spalart that clarifies and size up the many levels possible for the numerical prediction of a turbulent flow, the target being a complete airplane, turbine, or car.
💻 Engineering Tool of the Week – deal.II
A C++ software library supporting the creation of finite element codes and an open community of users and developers.
📚 Book of the Week
Introducing Data Science
Big data, machine learning, and more, using Python tools
Introducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You'll explore data visualization, graph databases, the use of NoSQL, and the data science process. You'll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you'll have the solid foundation you need to start a career in data science.
🙃 Meme of the Week
🎬 Animation of the Week
👉 Science Courses
⚙️ MATLAB & Simulink - 50+ Lessons & 3-Page Cheat Sheet → 39€
🚀 (Early-Bird Access) The Python Bootcamp | From Zero to Hero → 30€
🎬 (Coming Soon!) SimScale - An Introduction → 15€
🫂 The Science Circle Community → Monthly Membership ($10/month)
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Keep engineering your mind! 🧠
Jousef