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Lattice Boltzmann method (LBM) simulations of incompressible flows are nowadays common and well-established. However, for compressible turbulent flows with strong variable density and intrinsic compressibility effects, results are…

流体动力学 · 物理学 2024-12-13 Philipp Spelten , Dominik Wilde , Mario Christopher Bedrunka , Dirk Reith , Holger Foysi

A D2Q9 Hybrid Lattice Boltzmann Method (HLBM) is proposed for the simulation of both compressible subsonic and supersonic flows. This HLBM is an extension of the model of Feng et al: [12], which has been found, via different test cases, to…

流体动力学 · 物理学 2020-11-05 Florian Renard , Yongliang Feng , Jean-François Boussuge , Pierre Sagaut

A double-distribution-function based lattice Boltzmann method (DDF-LBM) is proposed for the simulation of polyatomic gases in the supersonic regime. The model relies on an extended equilibrium state that is constructed to reproduce the…

计算物理 · 物理学 2020-02-13 Jonas Latt , Christophe Coreixas , Joel Beny , Andrea Parmigiani

We present a quantitative analysis of the inertial range statistics produced by Entropic Lattice Boltzmann Method (ELBM) in the context of 3d homogeneous and isotropic turbulence. ELBM is a promising mesoscopic model particularly…

流体动力学 · 物理学 2021-07-14 Michele Buzzicotti , Guillaume Tauzin

A novel Lattice Boltzmann Method applicable to compressible fluid flows is developed. This method is based on replacing the governing equations by a relaxation system and the interpretation of the diagonal form of the relaxation system as a…

元胞自动机与格子气 · 物理学 2015-04-28 S. V. Raghurama Rao , Rohan Deshmukh , Sourabh Kotnala

This work thoroughly investigates a semi-Lagrangian lattice Boltzmann (SLLBM) solver for compressible flows. In contrast to other LBM for compressible flows, the vertices are organized in cells, and interpolation polynomials up to fourth…

计算物理 · 物理学 2020-05-13 Dominik Wilde , Andreas Krämer , Dirk Reith , Holger Foysi

We conduct an investigation into the dispersive post-shock oscillations in the entropic lattice-Boltzmann method (ELBM). To this end we use a root finding algorithm to implement the ELBM which displays fast cubic convergence and guaranties…

统计力学 · 物理学 2015-05-13 D. Packwood

An original spectral study of the compressible hybrid lattice Boltzmann method (HLBM) on standard lattice is proposed. In this framework, the mass and momentum equations are addressed using the lattice Boltzmann method (LBM), while finite…

计算物理 · 物理学 2020-06-16 Florian Renard , Gauthier Wissocq , Jean-François Boussuge , Pierre Sagaut

Turbulent compressible flows are traditionally simulated using explicit time integrators applied to discretized versions of the Navier-Stokes equations. However, the associated Courant-Friedrichs-Lewy condition severely restricts the…

计算物理 · 物理学 2021-08-11 Dominik Wilde , Andreas Krämer , Dirk Reith , Holger Foysi

A recently introduced family of lattice Boltzmann (LB) models (Karlin, B\"osch, Chikatamarla, Phys. Rev. E, 2014) is studied in detail for incompressible two-dimensional flows. A framework for developing LB models based on entropy…

流体动力学 · 物理学 2015-07-10 Fabian Bösch , Shyam S. Chikatamarla , Ilya Karlin

Simulating inhomogeneous flows with different characteristic scales in different coordinate directions using the collide-and-stream based lattice Boltzmann methods (LBM) can be accomplished efficiently using rectangular lattice grids. We…

流体动力学 · 物理学 2021-06-02 Eman Yahia , Kannan Premnath

The Lattice Boltzmann method (LBM) is a well-established mesoscopic approach for simulating fluid dynamics by evolving particle distribution functions on discrete lattices. While the LBM is highly parallelizable on classical hardware, its…

量子物理 · 物理学 2026-04-14 Trong Duong , Matthias Möller , Norbert Hosters

Entropic lattice Boltzmann methods have been developed to alleviate intrinsic stability issues of lattice Boltzmann models for under-resolved simulations. Its reliability in combination with moving objects was established for various…

流体动力学 · 物理学 2017-06-21 B. Dorschner , S. S. Chikatamarla , I. V. Karlin

Quantum computing shows substantial potential in accelerating simulations and alleviating memory bottlenecks in computational fluid dynamics (CFD), owing to its inherent properties of superposition and entanglement. The lattice Boltzmann…

量子物理 · 物理学 2026-03-03 Yang Xiao , Liming Yang , Chang Shu , Yinjie Du

Despite decades of research, creating accurate, robust, and efficient lattice Boltzmann methods (LBM) on non-uniform grids with seamless GPU acceleration remains challenging. This work introduces a novel strategy to address this challenge…

计算物理 · 物理学 2026-01-06 Christophe Coreixas , Jonas Latt

Minimal Boltzmann kinetic models, such as lattice Boltzmann, are often used as an alternative to the discretization of the Navier-Stokes equations for hydrodynamic simulations. Recently, it was argued that modeling sub-grid scale phenomena…

Convergence acceleration of flow simulations to their steady states at lower Mach numbers can be achieved via preconditioning the lattice Boltzmann (LB) schemes that alleviate the associated numerical stiffness, which have so far been…

计算物理 · 物理学 2022-08-17 Eman Yahia , Kannan Premnath

The birth of the lattice Boltzmann method (LBM) fulfils a dream that simple arithmetic calculations can simulate complex fluid flows without solving complicated partial differential flow equations. Its power and potential of resolving more…

计算工程、金融与科学 · 计算机科学 2019-01-10 Jian Guo Zhou

We present a systematic account of recent developments of the relativistic Lattice Boltzmann method (RLBM) for dissipative hydrodynamics. We describe in full detail a unified, compact and dimension-independent procedure to design…

高能物理 - 格点 · 物理学 2020-05-29 A. Gabbana , D. Simeoni , S. Succi , R. Tripiccione

Lattice Boltzmann method (LBM) is particularly well-suited for implementation on quantum circuits owing to its simple algebraic operations and natural parallelism. However, most quantum LBMs fix $\tau$ = 1 to avoid nonlinear collision,…

量子物理 · 物理学 2025-05-19 Yang Xiao , Liming Yang , Chang Shu , Yinjie Du , Hao Dong , Jie Wu
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