Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Xiao, Tianbai"'
Autor:
Hu, Shiwei, Xiao, Tianbai, Han, Mingshuo, Li, Zuoxu, Oterkus, Erkan, Oterkus, Selda, Zhang, Yonghao
Understanding the quasi-static fracture formation and evolution is essential for assessing the mechanical properties and structural load-bearing capacity of materials. Peridynamics (PD) provides an effective computational method to depict fracture me
Externí odkaz:
http://arxiv.org/abs/2410.12552
This work explores the application of deep operator learning principles to a problem in statistical physics. Specifically, we consider the linear kinetic equation, consisting of a differential advection operator and an integral collision operator, wh
Externí odkaz:
http://arxiv.org/abs/2402.16613
Autor:
Xiao, Tianbai, Frank, Martin
This paper addresses a neural network-based surrogate model that provides a structure-preserving approximation for the fivefold collision integral. The notion originates from the similarity in structure between the BGK-type relaxation model and resid
Externí odkaz:
http://arxiv.org/abs/2211.08149
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. The aim of this code framework is to provide a collection of classic
Externí odkaz:
http://arxiv.org/abs/2205.08417
Publikováno v:
In Journal of Computational Physics 15 November 2024 517
The multi-scale nature of gaseous flows poses tremendous difficulties for theoretical and numerical analysis. The Boltzmann equation, while possessing a wider applicability than hydrodynamic equations, requires significantly more computational resour
Externí odkaz:
http://arxiv.org/abs/2203.02933
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 differential equations, such as entropy dissipation and hyperbolicity. The
Externí odkaz:
http://arxiv.org/abs/2201.10364
The study of uncertainty propagation poses a great challenge to design numerical solvers with high fidelity. Based on the stochastic Galerkin formulation, this paper addresses the idea and implementation of the first flux reconstruction scheme for hy
Externí odkaz:
http://arxiv.org/abs/2112.05946
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 paper, we consider the moment system of the Boltzmann equation, which
Externí odkaz:
http://arxiv.org/abs/2106.09445
Autor:
Xiao, Tianbai
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 first flux reconstruction method for high-order Boltzmann solutions. Based
Externí odkaz:
http://arxiv.org/abs/2103.10371