Estimation of the Acoustic Field in a Uniform Duct with Mean Flow using Neural Networks

Fuente: arXiv
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Main Authors: Veerababu, D., Ghosh, Prasanta K.
Format: Preprint
Published: 2025
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author Veerababu, D.
Ghosh, Prasanta K.
author_facet Veerababu, D.
Ghosh, Prasanta K.
contents The study of sound propagation in a uniform duct having a mean flow has many applications, such as in the design of gas turbines, heating, ventilation and air conditioning ducts, automotive intake and exhaust systems, and in the modeling of speech. In this paper, the convective effects of the mean flow on the plane wave acoustic field inside a uniform duct were studied using artificial neural networks. The governing differential equation and the associated boundary conditions form a constrained optimization problem. It is converted to an unconstrained optimization problem and solved by approximating the acoustic field variable to a neural network. The complex-valued acoustic pressure and particle velocity were predicted at different frequencies, and validated against the analytical solution and the finite element models. The effect of the mean flow is studied in terms of the acoustic impedance. A closed-form expression that describes the influence of various factors on the acoustic field is derived.
format Preprint
id arxiv_https___arxiv_org_abs_2503_19412
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Estimation of the Acoustic Field in a Uniform Duct with Mean Flow using Neural Networks
Veerababu, D.
Ghosh, Prasanta K.
Computational Engineering, Finance, and Science
Neural and Evolutionary Computing
34A06
G.1.6; I.6.4; J.2
The study of sound propagation in a uniform duct having a mean flow has many applications, such as in the design of gas turbines, heating, ventilation and air conditioning ducts, automotive intake and exhaust systems, and in the modeling of speech. In this paper, the convective effects of the mean flow on the plane wave acoustic field inside a uniform duct were studied using artificial neural networks. The governing differential equation and the associated boundary conditions form a constrained optimization problem. It is converted to an unconstrained optimization problem and solved by approximating the acoustic field variable to a neural network. The complex-valued acoustic pressure and particle velocity were predicted at different frequencies, and validated against the analytical solution and the finite element models. The effect of the mean flow is studied in terms of the acoustic impedance. A closed-form expression that describes the influence of various factors on the acoustic field is derived.
title Estimation of the Acoustic Field in a Uniform Duct with Mean Flow using Neural Networks
topic Computational Engineering, Finance, and Science
Neural and Evolutionary Computing
34A06
G.1.6; I.6.4; J.2
url https://arxiv.org/abs/2503.19412