Performance Assessment of the Immersed Boundary Method in the Framework of the Moment Representation Lattice Boltzmann Method

ABSTRACT This study implements the immersed boundary method (IBM) coupled with the moment representation lattice Boltzmann method (MR‐LBM) for simulating fluid–structure interactions. Due to the nature of the MR‐LBM framework, which only stores moments, it is possible to eliminate some steps of the coupling with IBM compared to traditional LBM methods that store populations. As a result, the performance improves, and memory bandwidth requirements are reduced, a crucial factor in GPU implementations. We present results demonstrating the impact of parameters such as node spacing, kernel size, and node distribution on the computational speed of the method. Analyzing these metrics enables the assessment of which parts of the method impact performance and, therefore, should be targeted for future development.

Authors

Institutions

Publication Details

Journal
International Journal for Numerical Methods in Fluids
Published
2026-02-26
DOI
https://doi.org/10.1002/fld.70071
Primary Topic
Lattice Boltzmann Simulation Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance Assessment of the Immersed Boundary Method in the Framework of the Moment Representation Lattice Boltzmann Method

Ricardo Luiz de Souza, Marco A. Ferrari, A. T. Franco
International Journal for Numerical Methods in Fluids
Lattice Boltzmann Simulation Studies
article

Performance Assessment of the Immersed Boundary Method in the Framework of the Moment Representation Lattice Boltzmann Method

Ricardo Luiz de Souza, Marco A. Ferrari, A. T. Franco
article en

Abstract

ABSTRACT This study implements the immersed boundary method (IBM) coupled with the moment representation lattice Boltzmann method (MR‐LBM) for simulating fluid–structure interactions. Due to the nature of the MR‐LBM framework, which only stores moments, it is possible to eliminate some steps of the coupling with IBM compared to traditional LBM methods that store populations. As a result, the performance improves, and memory bandwidth requirements are reduced, a crucial factor in GPU implementations. We present results demonstrating the impact of parameters such as node spacing, kernel size, and node distribution on the computational speed of the method. Analyzing these metrics enables the assessment of which parts of the method impact performance and, therefore, should be targeted for future development.

International Journal for Numerical Methods in Fluids
Universidade Tecnológica Federal do Paraná (BR)
Openalex Percentile: Top 27%
Lattice Boltzmann Simulation Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.