Bayesian estimation of dissipation and sound speed in tube measurements using a transfer-function model

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Bayesian analysis improves tube measurement accuracy for acoustic dissipation and sound speed, suggesting enhanced material characterization.

Improved accuracy of tube measurements arises from accurate sound speed estimates and dissipation models.
A reduction to 1% in residual absorption coefficients highlights the significance of this approach for enhancing precision.
Observational analysis using a transfer function model showcases the benefits of integrating various dissipation predictions and Bayesian estimation techniques for acoustic measurements of materials. with experimental measurements supporting claims of accuracy enhancement in tube measurement methodologies.

Chen et al. (2024) studied this question.

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View Full Paper

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Authors

Bayesian analysis improves tube measurement accuracy for acoustic dissipation and sound speed, suggesting enhanced material characterization.

Improved accuracy of tube measurements arises from accurate sound speed estimates and dissipation models.
A reduction to 1% in residual absorption coefficients highlights the significance of this approach for enhancing precision.
Observational analysis using a transfer function model showcases the benefits of integrating various dissipation predictions and Bayesian estimation techniques for acoustic measurements of materials. with experimental measurements supporting claims of accuracy enhancement in tube measurement methodologies.

Chen et al. (2024) studied this question.

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