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Symbolic regression (SR) methods have been extensively investigated to explore explicit algebraic Reynolds stress models (EARSM) for turbulence closure of Reynolds-averaged Navier-Stokes (RANS) equations. The deduced EARSM can be readily…

Fluid Dynamics · Physics 2024-10-15 Yu Zhang , Kefeng Zheng , Fei Liu , Qingfu Zhang , Zhenkun Wang

This paper proposes a topology optimization method for non-thermal and thermal fluid problems using the Lattice Kinetic Scheme (LKS).LKS, which is derived from the Lattice Boltzmann Method (LBM), requires only macroscopic values, such as…

Numerical Analysis · Mathematics 2024-11-06 Yuta Tanabe , Kentaro Yaji , Kuniharu Ushijima

The rigorous simulation of stratified turbulence remains challenging due to pronounced flow anisotropy, suppressed vertical transport, and high sensitivity to numerical dissipation. This study systematically evaluates the predictive…

Fluid Dynamics · Physics 2026-05-15 Hongxuan Zhang

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…

Computational Engineering, Finance, and Science · Computer Science 2019-01-10 Jian Guo Zhou

Machine-learning (ML) techniques provide a new and encouraging perspective for constructing turbulence models for Reynolds-averaged Navier--Stokes (RANS) simulations. In this study, an iterative ML-RANS computational framework is proposed…

Fluid Dynamics · Physics 2021-07-27 Weishuo Liu , Jian Fang , Stefano Rolfo , Charles Moulinec , David R Emerson

Flows through medical devices as well as in anatomical vessels despite being at moderate Reynolds number may exhibit transitional or even turbulent character. In order to validate numerical methods and codes used for biomedical flow…

Fluid Dynamics · Physics 2020-05-25 Kartik Jain

Tissue growth underpins a wide array of biological and developmental processes, and numerical modeling of growing systems has been shown to be a useful tool for understanding these processes. However, the phenomena that can be captured are…

Soft Condensed Matter · Physics 2023-11-08 Andrew Killeen , Benjamin Partridge , Thibault Bertrand , Chiu Fan Lee

We present a two-level (fluid-kinetic) coupling procedure for the simulation of wall-bounded flows at Reynolds numbers up to thousands. The method combines a kinetic Direct Simulation Monte Carlo (DSMC) treatment of the near-wall layer,…

In this paper, a diffuse-interface lattice Boltzmann method (DI-LBM) is developed for fluid-particle interaction problems. In this method, the sharp interface between the fluid and solid is replaced by a thin but nonzero thickness…

Computational Physics · Physics 2021-06-17 Jiao Liu , Changsheng Huang , Zhenhua Chai , Baochang Shi

This paper presents an improved immersed moving boundary model (IBM) for solving complex fluid-particle interactions in a coupled lattice Boltzmann method (LBM) and an adhesive discrete element method (DEM), using the "partially saturated…

Soft Condensed Matter · Physics 2020-10-21 Wenwei Liu , Chuan-Yu Wu

We propose a novel multi-domain grid refinement technique with extensions to entropic incompressible, thermal and compressible lattice Boltzmann models. Its validity and accuracy are accessed by comparison to available direct numerical…

Fluid Dynamics · Physics 2016-12-21 B. Dorschner , N. Frapolli , S. S. Chikatamarla , I. V. Karlin

A lattice Boltzmann method (LBM) approach to the Charney-Hasegawa-Mima (CHM) model for adiabatic drift wave turbulence in magnetised plasmas, is implemented. The CHM-LBM model contains a barotropic equation of state for the potential, a…

Plasma Physics · Physics 2021-09-28 M. Held , A. Kendl

Boiling is a complex phenomenon where different non-linear physical interactions take place and for which the quantitative modeling of the mechanism involved is not fully developed yet. In the last years, many works have been published…

Fluid Dynamics · Physics 2022-05-23 Alfredo Jaramillo , Vinícius Pessoa Mapelli , Luben Cabezas-Gómez

Non-Newtonian fluid flows, especially in three dimensions (3D), arise in numerous settings of interest to physics. Prior studies using the lattice Boltzmann method (LBM) of such flows have so far been limited to mainly to two dimensions and…

Computational Physics · Physics 2021-01-28 Saad Adam , Farzaneh Hajabdollahi , Kannan Premnath

The simulation of geometrically resolved rigid particles in a fluid relies on coupling algorithms to transfer momentum both ways between the particles and the fluid. In this article, the fluid flow is modeled with a parallel Lattice…

Fluid Dynamics · Physics 2021-03-22 Lukas Werner , Christoph Rettinger , Ulrich Rüde

In this paper, a boundary scheme is proposed for the two-dimensional five-velocity (D2Q5) lattice Boltzmann method with heterogeneous surface reaction, in which the unknown distribution function is determined locally based on the kinetic…

Computational Physics · Physics 2019-04-04 Long Jv , Chunhua Zhang , Zhaoli Guo

We study the diffusivity of a small particle immersed in a square box filled with a non-ideal multicomponent fluid in the presence of thermal fluctuations. Our approach is based on the numerical integration of fluctuating lattice Boltzmann…

Fluid Dynamics · Physics 2021-12-14 Xiao Xue , Luca Biferale , Mauro Sbragaglia , Federico Toschi

Wall-modeled large-eddy simulation (WMLES) is performed for flow over a wing with a focus on documenting grid resolution requirements to predict both the laminar and turbulent regions accurately. Flow over a spanwise extruded NACA0012…

Fluid Dynamics · Physics 2026-02-13 P. Balakumar , Prahladh S. Iyer

Quantum algorithms have been identified as a potential means to accelerate computational fluid dynamics (CFD) simulations, with the lattice Boltzmann method (LBM) being a promising candidate for realizing quantum speedups. Here, we extend…

We propose a framework for developing wall models for large-eddy simulation that is able to capture pressure-gradient effects using multi-agent reinforcement learning. Within this framework, the distributed reinforcement learning agents…

Fluid Dynamics · Physics 2024-07-29 Di Zhou , H. Jane Bae