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Modeling the localized intensive deformation in a damaged solid requires highly refined discretization for accurate prediction, which significantly increases the computational cost. Although adaptive model refinement can be employed for…

Computational Engineering, Finance, and Science · Computer Science 2022-05-18 Jonghyuk Baek , Jiun-Shyan Chen , Kristen Susuki

This paper presents a general high-order kernel regularization technique applicable to all four integral operators of Calder\'on calculus associated with linear elliptic PDEs in two and three spatial dimensions. Like previous density…

Numerical Analysis · Mathematics 2021-03-02 Luiz M. Faria , Carlos Pérez-Arancibia , Marc Bonnet

A discretization scheme for variable coefficient Helmholtz problems on two-dimensional domains is presented. The scheme is based on high-order spectral approximations and is designed for problems with smooth solutions. The resulting system…

Numerical Analysis · Mathematics 2012-06-20 P. G. Martinsson

A deterministic method is proposed for solving the Boltzmann equation. The method employs a Galerkin discretization of the velocity space and adopts, as trial and test functions, the collocation basis functions based on weights and roots of…

Computational Physics · Physics 2013-11-19 Gian Pietro Ghiroldi , Livio Gibelli

A collision-based hybrid method for the discrete ordinates approximation of the multigroup neutron transport equation is developed for two-dimensional time-dependent problems. At each time step, this algorithm splits the neutron transport…

Computational Physics · Physics 2025-02-17 Ben Whewell , Ryan G. McClarren

Quasi-2D Coulomb systems are of fundamental importance and have attracted much attention in many areas nowadays. Their reduced symmetry gives rise to interesting collective behaviors, but also brings great challenges for particle-based…

Numerical Analysis · Mathematics 2025-02-05 Zecheng Gan , Xuanzhao Gao , Jiuyang Liang , Zhenli Xu

We discuss a spectral method for the numerical solution of the Vlasov-Poisson system where the velocity space is decomposed by means of an Hermite basis. We describe a semi-implicit time discretization that extends the range of numerical…

Plasma Physics · Physics 2013-12-19 Enrico Camporeale , Gian Luca Delzanno , Benjamin K. Bergen , J. David Moulton

In this paper we study the numerical passage from the spatially homogeneous Boltzmann equation without cut-off to the Fokker-Planck-Landau equation in the so-called grazing collision limit. To this aim we derive a Fourier spectral method…

Numerical Analysis · Mathematics 2010-09-29 Lorenzo Pareschi , Giuseppe Toscani , Cédric Villani

Boltzmann solvers are an important tool for the computation of cosmological observables in the linear regime. In the presence of massive neutrinos, they involve solving the Boltzmann equation followed by an integration in momentum space to…

Cosmology and Nongalactic Astrophysics · Physics 2021-11-22 Caio Bastos de Senna Nascimento

Ideal gases can be modeled by the Boltzmann equation from statistical physics. Instead of trying to track the position and velocity of a large number of gas molecules, it is possible to describe the particles with a particle distribution…

Numerical Analysis · Mathematics 2025-11-27 Vienna B. Rossmanith

The Poisson-Boltzmann model is an effective and popular approach for modeling solvated biomolecules in continuum solvent with dissolved electrolytes. In this paper, we report our recent work in developing a Galerkin boundary integral method…

Computational Physics · Physics 2021-10-27 Jiahui Chen , Johannes Tausch , Weihua Geng

Grad's method is used on the linearized Boltzmann collision operator to derive the most general expressions for the collision coefficients for a multi-component, multi-temperature plasma up to rank-2. In doing so, the collision coefficients…

In this paper we present a numerical method for the Boltzmann equation. It is a spectral discretization in the velocity and a discontinuous Galerkin discretization in physical space. To obtain uniform approximation properties in the mach…

Numerical Analysis · Mathematics 2019-03-06 Gerhard Kitzler , Joachim Schöberl

Lattice-Boltzmann methods are known for their simplicity, efficiency and ease of parallelization, usually relying on uniform Cartesian meshes with a strong bond between spatial and temporal discretization. This fact complicates the crucial…

Numerical Analysis · Mathematics 2022-10-19 Thomas Bellotti , Loïc Gouarin , Benjamin Graille , Marc Massot

We apply the spectral-Lagrangian method of Gamba and Tharkabhushanam for solving the homogeneous Boltzmann equation to compute the low probability tails of the velocity distribution function, $f$, of a particle species. This method is based…

Numerical Analysis · Mathematics 2021-01-06 John Zweck , Yanping Chen , Matthew J. Goeckner , Yannan Shen

This paper describes an angular adaptivity algorithm for Boltzmann transport applications which for the first time shows evidence of $\mathcal{O}(n)$ scaling in both runtime and memory usage, where $n$ is the number of adapted angles. This…

Computational Physics · Physics 2020-01-29 S. Dargaville , A. G. Buchan , R. P. Smedley-Stevenson , P. N Smith , C. C. Pain

We present a new method for neutrino-matter coupling in multi-dimensional radiation-hydrodynamic simulations of core-collapse supernova (CCSN) with the full Boltzmann neutrino transport. The development is motivated by the fact that the…

High Energy Astrophysical Phenomena · Physics 2019-08-07 Hiroki Nagakura , Kohsuke Sumiyoshi , Shoichi Yamada

This paper describes an angular adaptivity algorithm for Boltzmann transport applications which uses Pn and filtered Pn expansions, allowing for different expansion orders across space/energy. Our spatial discretisation is specifically…

Computational Physics · Physics 2019-09-04 S. Dargaville , A. G. Buchan , R. P. Smedley-Stevenson , P. N Smith , C. C. Pain

The claim that Monte Carlo is the most accurate method is a case of misattributed credit. This claim is based on experience with advanced systems MCNPX, Geant4 and EGS. These systems achieve remarkable performance because they use most…

Medical Physics · Physics 2026-03-13 Oleg N Vassiliev , Radhe Mohan

Learning representations of molecular structures using deep learning is a fundamental problem in molecular property prediction tasks. Molecules inherently exist in the real world as three-dimensional structures; furthermore, they are not…

Machine Learning · Computer Science 2024-01-22 Daiki Koge , Naoaki Ono , Shigehiko Kanaya
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