In fluid dynamics, The projection method is an effective means of numerically solving time-dependent incompressible fluid-flow problems. It was originally introduced by Alexandre Chorin in 1967as an efficient means of solving the incompressible Navier-Stokes equations. The key advantage of the projection method is that the computations of the velocity and the pressure fields are decoupled. (Wikipedia).
A solar system, a simulation made with Excel
An Excel simulation of the solar system. You can see how things are recursively computed: the mutual gravity force from the locations, the accelerations, the velocities, and finally the updated locations. The solar eclipse is also shown. This is clip is intended to illustrate Chapter 24 Ap
From playlist Physics simulations
Most Insane Immersive Movie Experience EVER, Part 1
Check out this guy's room totally change into the movie he is watching! No SFX, no post production, no cuts, everything you see here is 100% for real. We were funded by the Video Store of PlayStation® Store (http://www.greatfilmsfillrooms.com) to make a series of movie related videos us
From playlist Projection Mapping inspirations
In this second part on Motion, we take a look at calculating the velocity and position vectors when given the acceleration vector and initial values for velocity and position. It involves as you might imagine some integration. Just remember that when calculating the indefinite integral o
From playlist Life Science Math: Vectors
What is the projection of one vector on another one and how is it useful? Free ebook https://bookboon.com/en/introduction-to-vectors-ebook (updated link) Test your understanding via a short quiz http://goo.gl/forms/CpZUX1mFLS
From playlist Introduction to Vectors
This video explains how to determine the projection of one vector onto another vector. http://mathispower4u.yolasite.com/
From playlist Vectors
This shows a 3d print of a mathematical sculpture I produced using shapeways.com. This model is available at http://shpws.me/q41V.
From playlist 3D printing
Machine Learning for Computational Fluid Dynamics
Machine learning is rapidly becoming a core technology for scientific computing, with numerous opportunities to advance the field of computational fluid dynamics. This paper highlights some of the areas of highest potential impact, including to accelerate direct numerical simulations, to i
From playlist Data Driven Fluid Dynamics
Visualization of Quantum Physics (Quantum Mechanics)
This video visually demonstrates some basic quantum physics concepts using the simple case of a free particle. All the simulations here are based on real equations and laws. See more information here: https://www.udiprod.com/quantum-physics/ The mathematics involved was taken from this
From playlist Animated Physics Simulations
Ex: Vector Projection in Two Dimensions
This video explains how to determine the projection of one vector onto another vector in two dimensions. Site: http://mathispower4u.com
From playlist Applications of Vectors
DDPS | Interpretable and Generalizable Machine Learning for Fluid Mechanics
Many tasks in fluid mechanics, such as design optimization and control, are challenging because fluids are nonlinear and exhibit a large range of scales in both space and time. This range of scales necessitates exceedingly high-dimensional measurements and computational discretization to r
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Hydrographic Printing | Two Minute Papers #7
3D printing is a technique to create digital objects in real life. This technology is mostly focused on reproducing the digital geometry itself - colored patterns (textures) still remains a challenge, and we only have very rudimentary technology to do that. Hydrographic printing on 3D sur
From playlist 3D Printing / 3D Fabrication
Panorama of Mathematics: Alfio Quarteroni
Panorama of Mathematics To celebrate the tenth year of successful progression of our cluster of excellence we organized the conference "Panorama of Mathematics" from October 21-23, 2015. It outlined new trends, results, and challenges in mathematical sciences. Alfio Quarteroni: "Reduced
From playlist Panorama of Mathematics
Wolfram Physics Project: Solving the Einstein Equations & Other PDEs Tuesday, Mar. 9, 2021
This is a Wolfram Physics Project working session on solving the Einstein equations and other PDE's in the Wolfram Model. Begins at 1:18 Originally livestreamed at: https://twitch.tv/stephen_wolfram Stay up-to-date on this project by visiting our website: http://wolfr.am/physics Check ou
From playlist Wolfram Physics Project Livestream Archive
Jose Antonio Font - Numerical analysis: binary neutron stars - IPAM at UCLA
Recorded 21 September 2021. Jose Antonio Font of the University of Valencia presents "Numerical analysis: binary neutron stars" at IPAM's Mathematical and Computational Challenges in the Era of Gravitational Wave Astronomy Tutorial. Abstract: Merging binary neutron stars are among the str
From playlist Tutorials: Math & Computational Challenges in the Era of Gravitational Wave Astronomy
Introductionadvanced hydraulics course structure
Advanced Hydraulics by Dr. Suresh A Kartha,Department of Civil Engineering,IIT Guwahati.For more details on NPTEL visit http://nptel.iitm.ac.in
From playlist IIT Guwahati: Advanced Hydraulics | CosmoLearning.org Civil Engineering
Nature Reviews Physics: Machine learning in fluid dynamics and climate physics
Researchers in field of fluid dynamics have been experimenting with machine learning since the 1990s, having driven many advances in the use of these methods in modelling and simulation. The combination of real and simulated data, together with physics-informed machine learning, is now use
From playlist Nature Reviews Physics - AI for science and government (ASG) series
Turbulence is Everywhere! Examples of Turbulence and Canonical Flows
Turbulence is one of the most interesting and ubiquitous phenomena in fluid dynamics. In this video, we explore several examples of canonical and real world turbulent fluids, with engineering applications. Check out the excellent notes by Lex Smits: http://profs.sci.univr.it/~zuccher/d
From playlist Fluid Dynamics
DDPS | Data-driven methods for fluid simulations in computer graphics
Fluid phenomena are ubiquitous to our world experience: winds swooshing through trembling leaves, turbulent water streams running down a river, and cellular patterns generated from wrinkled flames are some few examples. These complex phenomena capture our attention and awe due to the beaut
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
A mathematics bonus. In this lecture I remind you of a way to calculate the cross product of two vector using the determinant of a matrix along the first row of unit vectors.
From playlist Physics ONE
DDPS | libROM: Library for physics-constrained data-driven physical simulations | Youngsoo Choi
A data-driven model can be built to accurately accelerate computationally expensive physical simulations, which is essential in multi-query problems, such as inverse problem, uncertainty quantification, design optimization, and optimal control. In this talk, two types of data-driven mode
From playlist Data-driven Physical Simulations (DDPS) Seminar Series