activity
20182022
most citedNeural network-based, structure-preserving entropy closures for the Boltzmann moment system

1 citations · 1 across the 4 of their papers we have counts for

collaborators

8 papers

physics.med-ph2022

KiT-RT: An extendable framework for radiative transfer and therapy

Jonas Kusch, Steffen Schotthöfer, Pia Stammer +2

In this paper we present KiT-RT (Kinetic Transport Solver for Radiation Therapy), an open-source C++ based framework for solving kinetic equations in radiation therapy applications…

math.NA20221 cited

Neural network-based, structure-preserving entropy closures for the Boltzmann moment system

Steffen Schotthöfer, Tianbai Xiao, Martin Frank +1

This work presents neural network based minimal entropy closures for the moment system of the Boltzmann equation, that preserve the inherent structure of the system of partial diff…

math.NA2021

A structure-preserving surrogate model for the closure of the moment system of the Boltzmann equation using convex deep neural networks

Steffen Schotthöfer, Tianbai Xiao, Martin Frank +1

Direct simulation of physical processes on a kinetic level is prohibitively expensive in aerospace applications due to the extremely high dimension of the solution spaces. In this…

physics.comp-ph2021

A flux reconstruction kinetic scheme for the Boltzmann equation

Tianbai Xiao

It is challenging to solve the Boltzmann equation accurately due to the extremely high dimensionality and nonlinearity. This paper addresses the idea and implementation of the firs…

physics.comp-ph2020

Using neural networks to accelerate the solution of the Boltzmann equation

Tianbai Xiao, Martin Frank

One of the biggest challenges for simulating the Boltzmann equation is the evaluation of fivefold collision integral. Given the recent successes of deep learning and the availabili…

physics.comp-ph2020

Modeling and Simulation of Non-equilibrium Flows with Uncertainty Quantification

Tianbai Xiao

In the study of gas dynamics, theoretical modeling and numerical simulation are mostly set up with deterministic settings. Given the coarse-grained modeling in theories of fluids,…