📚 “The whole purpose of education is to turn mirrors into windows” – Sydney J. Harris
Hey friends & nerds! 👋
Welcome to the Sunday Science Newsletter where we explore science, systems & tools that help us become smarter scientists.
💦 The Navier-Stokes Equations
In 1845, Sir George Stokes had derived the equation of motion of a viscous flow by adding Newtonian viscous terms, thereby the Navier-Stokes Equations had been brought to their final form which has been used to generate numerical solutions for fluid flow ever since.
🚀 Upcoming Masterclass - Becoming a Successful Freelancer
I will release a FREE Masterclass in collaboration with Skillshare in ~1-2 months.
I’ve been in a lucky position to scale my freelance business to over 10,000€/m in a matter of a few months. In this ~1-2 hour class, I will share:
How to land your first client
How to find your “genius zone”
How to define your brand strategy
How to get started with your website
How to start your first prototype business with less than 100€
And no, there will be no hidden costs or anything like that. It will be for free and you can even try Skillshare 1 month for free and see if my class is for you.
Reason why I give it away for free is because most people out there look for all kinds of excuses why they cannot do something. So I am releasing the free class to also take the last excuse away from you and want you to start earning your first $1 online!
🧠 AlphaGo - The Movie
With more board configurations than there are atoms in the universe, the ancient Chinese game of Go has long been considered a grand challenge for artificial intelligence.
On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history.
📚 Can Physics-Informed Neural Networks beat the Finite Element Method?
TL;DR: “Considering the solution time and accuracy, PINNs are not able to beat the finite element method in our study.”
The recent success of deep neural networks at various approximation tasks has motivated their use in the numerical solution of PDEs. These so-called physics-informed neural networks and their variants have shown to be able to successfully approximate a large range of partial differential equations. So far, physics-informed neural networks and the finite element method have mainly been studied in isolation of each other.
💻 Engineering Tool of the Week – OnScale Solve
OnScale Solve UI is cloud-native and built on the latest web browser technology, thus facilitating an efficient, intuitive simulation workflow and delightful user experience:
Meshing operations are fully automated allowing the user to concentrate on the simulation problem at hand.
From within the UI the user is able to interact with all of the simulation results data stored on the cloud, accessing only the data needed to generate charts, tables, images, and animations.
Team and project dashboards are available to efficiently navigate simulation studies and manage core-hour usage.
📚 Book of the Week
Introduction to the Finite Element Method by Ottosen & Petersson
This book provides a systematic approach and simple introduction to the finite element method. Helped me a LOT during my studies!
🙃 Meme of the Week
🎬 Animation of the Week
🫂 Solopreneurship, Science & Career
🫂 The Science Circle is a private community for all things around science, career, personal development, and earning your first Dollar online. Get instant access & personalised help in your journey - save $9 using code “JOIN9”.
So the first month is $1 only! 😉
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👉 Science Courses
🚀 (Early-Bird Access) The Python Bootcamp | From Zero to Hero
For any business related issues or collaborations, feel free to write me an email to email@example.com!
Keep engineering your mind! 🧠