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Related Experiment Video

Updated: May 13, 2026

Trapping of Micro Particles in Nanoplasmonic Optical Lattice

Trapping of Micro Particles in Nanoplasmonic Optical Lattice

Published on: September 5, 2017

Noise source identification with the lattice Boltzmann method.

Etienne Vergnault¹, Orestis Malaspinas, Pierre Sagaut

¹Université Pierre et Marie Curie (UPMC), Paris 06 UMR 7190, Institut Jean Le Rond d'Alembert, F-75005 Paris, France. etienne.vergnault@univ-lyon1.fr

The Journal of the Acoustical Society of America

|March 8, 2013

Summary

This summary is machine-generated.

This study introduces a stable lattice Boltzmann method (LBM) for identifying sound sources. The approach uses a time-reversed LBM with a split equation to overcome instability, enabling effective noise source detection in fluid flows.

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Area of Science:

Computational fluid dynamics
Acoustics
Numerical methods

Background:

Sound source identification is crucial for noise control.
Traditional methods face challenges with stability and accuracy.
The lattice Boltzmann method (LBM) offers a promising alternative for fluid flow simulations.

Purpose of the Study:

To develop a stable and accurate method for sound source identification using LBM.
To address the inherent instability of time-reversed LBM schemes.
To apply the method to acoustic problems in fluid dynamics.

Main Methods:

Utilizing a time-reversed problem coupled with complex differentiation.
Implementing a split of the lattice Boltzmann equation into mean and perturbation components.
Formulating the LBM for arbitrary base flows with specific acoustic applications.

Main Results:

Successfully circumvented the instability of the time-reversed LBM.
Developed a noise source detection method applicable to 2D weakly compressible flows.
Demonstrated the practical applicability of the proposed method.

Conclusions:

The proposed LBM-based approach provides a stable and effective solution for sound source identification.
The method is particularly suitable for analyzing noise in low Mach number flows.
This work advances the application of LBM in computational aeroacoustics.