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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…

Quantum Physics · Physics 2026-03-03 Yang Xiao , Liming Yang , Chang Shu , Yinjie Du

Central moment lattice Boltzmann method (LBM) is one of the more recent developments among the lattice kinetic schemes for computational fluid dynamics. A key element in this approach is the use of central moments to specify collision…

Computational Physics · Physics 2012-02-29 Yang Ning , Kannan N. Premnath

A Multi-scale Boltzmann Equation (MBE) is found from the gas-kinetic theory and the direct modeling philosophy as a master equation for complex physical systems of neutral gases across all flow regimes, which locates between the continuum…

Computational Physics · Physics 2025-06-19 Sha Liu , Junzhe Cao , Sirui Yang , Chengwen Zhong

We introduce a novel mesoscopic computational model based on a multiphase-multicomponent lattice Boltzmann method for the simulation of self-phoretic particles in the presence of liquid-liquid interfaces. Our model features fully resolved…

Soft Condensed Matter · Physics 2022-06-22 Lucas Palacios , Andrea Scagliarini , Ignacio Pagonabarraga

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…

Fluid Dynamics · Physics 2017-06-21 B. Dorschner , S. S. Chikatamarla , I. V. Karlin

A constraint penalization method is introduced within the Lattice Boltzmann (LBM) framework to model fluid-structure interactions involving rigid bodies. The proposed approach extends the fictitious domain concept by enforcing the…

Fluid Dynamics · Physics 2025-11-04 Tristan Millet , Erwan Liberge

We propose a quantum algorithm for solving physical problems represented by the lattice Boltzmann formulation. Specifically, we deal with the case of a single phase, incompressible fluid obeying the Bhatnagar-Gross-Krook model. We use the…

Quantum Physics · Physics 2023-04-13 Wael Itani , Katepalli R. Sreenivasan , Sauro Succi

This work presents a novel framework for physically consistent model error characterization and operator learning for reduced-order models of non-equilibrium chemical kinetics. By leveraging the Bayesian framework, we identify and infer…

Computational Physics · Physics 2024-10-18 Mridula Kuppa , Roger Ghanem , Marco Panesi

Complex colloidal fluids, such as emulsions stabilized by complex shaped particles, play an important role in many industrial applications. However, understanding their physics requires a study at sufficiently large length scales while…

Soft Condensed Matter · Physics 2012-04-27 Florian Günther , Florian Janoschek , Stefan Frijters , Jens Harting

For multiscale gas flows, kinetic-continuum hybrid method is usually used to balance the computational accuracy and efficiency. However, the kinetic-continuum coupling is not straightforward since the coupled methods are based on different…

Fluid Dynamics · Physics 2015-05-19 Jianping Meng , Yonghao Zhang , Xiaowen Shan

Lattice Boltzmann methods (LBM) are an important part of current computational fluid dynamics (CFD). They allow easy implementations and boundary handling. However, competitive time to solution not only depends on the choice of a reasonable…

Performance · Computer Science 2018-04-18 Markus Wittmann , Viktor Haag , Thomas Zeiser , Harald Köstler , Gerhard Wellein

This article introduces a novel framework for developing quantum algorithms for the Lattice Boltzmann Method (LBM) applied to the advection-diffusion equation. We formulate the collision-streaming evolution of the LBM as a compact…

Mathematical Physics · Physics 2026-02-11 Yuan He , Yuan Yu , Yue Yu

Modelling the vascular transport and adhesion of man-made particles is crucial for optimizing their efficacy in the detection and treatment of diseases. Here, a Lattice Boltzmann and Immersed Boundary methods are combined together for…

Fluid Dynamics · Physics 2016-06-07 Alessandro Coclite , Marco Donato de Tullio , Giuseppe Pascazio , Paolo Decuzzi

Over the last decade, the Lattice Boltzmann method has found major scope for the simulation of a large spectrum of problems in soft matter, from multiphase and multi-component microfluidic flows, to foams, emulsions, colloidal flows, to…

Soft Condensed Matter · Physics 2024-11-25 A. Tiribocchi , M. Durve , M. Lauricella , A. Montessori , J. M. Tucny , S. Succi

The immersed boundary lattice Boltzmann method (IB-LBM) has been widely used in the simulation of fluid-solid interaction and particulate flow problems, since proposed in 2004. However, it is usually a non-trivial task to retain the…

Computational Physics · Physics 2018-03-28 Shi Tao , Qing He , Baiman Chen , Simin Huang

The Lattice Boltzmann Method (LBM) has emerged as a powerful tool in computational fluid dynamics and material science. However, standard LBM formulation imposes some limitations on the applications of the method, particularly compressible…

Soft Condensed Matter · Physics 2025-03-14 Navid Afrasiabian , Colin Denniston

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…

Lattice Boltzmann method (LBM) is a promising approach to solving Computational Fluid Dynamics (CFD) problems, however, its nature of memory-boundness limits nearly all LBM algorithms' performance on modern computer architectures. This…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-08-11 Yuankun Fu , Fengguang Song

An algorithm is proposed to implement unsteady jump boundary conditions, presenting discontinuity in physical quantities, within the lattice Boltzmann method (LBM). This is useful to tackle problems involving mass or heat transfer through…

Computational Physics · Physics 2018-11-06 Badr Kaoui

Finding reduced models of spatially-distributed chemical reaction networks requires an estimation of which effective dynamics are relevant. We propose a machine learning approach to this coarse graining problem, where a maximum entropy…

Biological Physics · Physics 2018-08-15 Oliver K. Ernst , Thomas Bartol , Terrence Sejnowski , Eric Mjolsness
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