A feedforward neural network for modelling of average pressure frequency response
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Publication:6355273
arXiv2012.02276MaRDI QIDQ6355273
Author name not available (Why is that?)
Publication date: 3 December 2020
Abstract: The Helmholtz equation has been used for modelling the sound pressure field under a harmonic load. Computing harmonic sound pressure fields by means of solving Helmholtz equation can quickly become unfeasible if one wants to study many different geometries for ranges of frequencies. We propose a machine learning approach, namely a feedforward dense neural network, for computing the average sound pressure over a frequency range. The data is generated with finite elements, by numerically computing the response of the average sound pressure, by an eigenmode decomposition of the pressure. We analyze the accuracy of the approximation and determine how much training data is needed in order to reach a certain accuracy in the predictions of the average pressure response.
Has companion code repository: https://github.com/klaspettersson/FrRe1
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