A sample-efficient deep learning method for multivariate uncertainty qualification of acoustic-vibration interaction problems (Q2138808)

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English	A sample-efficient deep learning method for multivariate uncertainty qualification of acoustic-vibration interaction problems	scientific article

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instance of

scholarly article

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title

A sample-efficient deep learning method for multivariate uncertainty qualification of acoustic-vibration interaction problems (English)

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Stéphane Pierre Alain Bordas

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published in

Computer Methods in Applied Mechanics and Engineering

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publication date

12 May 2022

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zbMATH Keywords

FEM/BEM coupling

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isogeometric analysis

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vibro-acoustic analysis

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Monte Carlo simulation

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deep neural network

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SVD-RBF

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describes a project that uses

MLMSRBF

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1016/j.cma.2022.114784

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cites work

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Deep learned finite elements

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Acoustic topology optimization of sound absorbing materials directly from subdivision surfaces with isogeometric boundary element methods

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Identifiers

Mathematics Subject Classification ID

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10.1016/J.CMA.2022.114784

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Mathematics(1 entry)

mardi Publication:2138808