Computational fluid dynamics

Flux-corrected transport

Flux-corrected transport (FCT) is a conservative shock-capturing scheme for solving Euler equations and other hyperbolic equations which occur in gas dynamics, aerodynamics, and magnetohydrodynamics. It is especially useful for solving problems involving shock or contact discontinuities. An FCT algorithm consists of two stages, a transport stage and a flux-corrected anti-diffusion stage. The numerical errors introduced in the first stage (i.e., the transport stage) are corrected in the anti-diffusion stage. (Wikipedia).

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Bertrand Maury - Transport optimal et mouvements de foules sous contrainte de congestion (Part 2)

Transport optimal et mouvements de foules sous contrainte de congestion (Part 2)

From playlist Inter’actions en mathématiques 2015

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When is the particle at rest from a velocity graph

Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function

From playlist Particle Motion Problems

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When is the particle increasing decreasing from a velocity graph

Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function

From playlist Particle Motion Problems

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How to determine the displacement of a particle from a table

Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function

From playlist Particle Motion Problems

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How to find the acceleration at a given time from the velocity graph

Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function

From playlist Particle Motion Problems

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Determine when a particle's speed is increasing from a graph

Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function

From playlist Determine Increasing or Decreasing Function From a Table

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Geometric properties of adiabatic thermal machines by Liliana Arrachea

PROGRAM CLASSICAL AND QUANTUM TRANSPORT PROCESSES : CURRENT STATE AND FUTURE DIRECTIONS (ONLINE) ORGANIZERS: Alberto Imparato (University of Aarhus, Denmark), Anupam Kundu (ICTS-TIFR, India), Carlos Mejia-Monasterio (Technical University of Madrid, Spain) and Lamberto Rondoni (Polytechn

From playlist Classical and Quantum Transport Processes : Current State and Future Directions (ONLINE)2022

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ITCZ Dynamics and Indian Monsoon: Energy Constraints (Lecture 7) by B N Goswami

ICTS Summer Course 2022 (www.icts.res.in/lectures/sc2022bng) Title : Introduction to Indian monsoon Variability, Predictability, and Teleconnections Speaker : Professor B N Goswami (Cotton University) Date : 23rd April onwards every week o

From playlist Summer Course 2022: Introduction to Indian monsoon Variability, Predictability, and Teleconnections

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Learn how to determine the position when the particle is at rest calculator

Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function

From playlist Particle Motion Problems

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Duality in Optimal Transport

We define the Kantorovich dual of Kantorovich problem of Optimal Transport and give a (well known) interpretation in terms of "outsourcing" the task of transporting goods.

From playlist Optimal Transport

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MFEM Workshop 2021 | Laser Plasma Modeling with High-Order Finite Elements

The LLNL-led MFEM (Modular Finite Element Methods) project provides high-order mathematical calculations for large-scale scientific simulations. The project’s first community workshop was held virtually on October 20, 2021, with participants around the world. Learn more about MFEM at https

From playlist MFEM Community Workshop 2021

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Learn how to find the displacement of a particle

Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function

From playlist Particle Motion Problems

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A variational approach to the regularity theory for the Monge-Ampère equation -Felix Otto

Analysis Seminar Topic: A variational approach to the regularity theory for the Monge-Ampère equation Speaker: Felix Otto Affiliation: Max Planck Institute Leipzig Date: April 20, 2020 For more video please visit http://video.ias.edu

From playlist Mathematics

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19. Classical Size Effects, Parallel Direction

MIT 2.57 Nano-to-Micro Transport Processes, Spring 2012 View the complete course: http://ocw.mit.edu/2-57S12 Instructor: Gang Chen License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 2.57 Nano-to-Micro Transport Processes, Spring 2012

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Vlad VICOL - On global regularity for the 2D Muskat equations with finite slope

We consider the 2D Muskat equation for the interface between two constant density fluids in an incompressible porous medium, with velocity given by Darcy's law. We establish that as long as the slope of the interface between the two fluids remains bound

From playlist Trimestre "Ondes Non linéaires" - June Conference

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22. Simplifying Neutron Transport to Neutron Diffusion

MIT 22.01 Introduction to Nuclear Engineering and Ionizing Radiation, Fall 2016 Instructor: Michael Short View the complete course: https://ocw.mit.edu/22-01F16 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP61FVzAxBP09w2FMQgknTOqu As many simplifications as possible a

From playlist MIT 22.01 Introduction to Nuclear Engineering and Ionizing Radiation, Fall 2016

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What determines the Hall and Thermal Hall signs of metals by Assa Auerbach

DISCUSSION MEETING NOVEL PHASES OF QUANTUM MATTER ORGANIZERS: Adhip Agarwala, Sumilan Banerjee, Subhro Bhattacharjee, Abhishodh Prakash and Smitha Vishveshwara DATE: 23 December 2019 to 02 January 2020 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Recent theoretical and experimental

From playlist Novel Phases of Quantum Matter 2019

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Geometric phases and the separation of the world by Michael Berry

DISCUSSION MEETING : GEOMETRIC PHASES IN OPTICS AND TOPOLOGICAL MATTER ORGANIZERS : Subhro Bhattacharjee, Joseph Samuel and Supurna Sinha DATE : 21 January 2020 to 24 January 2020 VENUE : Madhava Lecture Hall, ICTS, Bangalore This is a joint ICTS-RRI Discussion Meeting on the geometric

From playlist Geometric Phases in Optics and Topological Matter 2020

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Sliced Partial Optimal Transport - Bonneel - Workshop 1 - CEB T1 2019

Bonneel (CNRS) / 07.02.2019 Sliced Partial Optimal Transport Sliced optimal transport is a blazing fast way to compute a notion of optimal transport between uniform measures supported on point clouds via 1-d projections. However, it requires these point clouds to have the same cardinali

From playlist 2019 - T1 - The Mathematics of Imaging

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Marcel Langer - Message passing neural networks for atomistic systems: Materials - IPAM at UCLA

Recorded 01 April 2022. Marcel Langer of Technische Universität Berlin presents "Message passing neural networks for atomistic systems: Materials" at IPAM's Multiscale Approaches in Quantum Mechanics Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/workshop-i-mul

From playlist 2022 Multiscale Approaches in Quantum Mechanics Workshop

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Computational magnetohydrodynamics | Computational fluid dynamics | Volume of fluid method