Validation of Bayesian design for broadband microslit panel absorbers using causal inference

Abstract

This paper discusses experimental validations of multilayer microslit panels (MSPs) designed via Bayesian inference to obtain both high sound absorption and wide bandwidth simultaneously. Microslit perforation in thin panels is similar to microperforated panels [Xiang, Fackler, Hou, and Schmitt (2022). J. Acoust. Soc. Am. 151(5), 3094–3103]. MSP absorbers in single-layer configurations are functioning in a limited frequency range. By stacking the MSPs in multiple layered structures, absorbing performance may be widened in frequency ranges while retaining high absorption coefficients. Besides design challenges of multiple MSPs in layered structures to fulfill a practical requirement and minimize fabrication complexity, this paper further discusses challenges in experimental validations when experimental results undesirably deviate from the initial Bayesian design. Causation analysis is applied to the validation efforts where a causal model-based inference effectively provides causal reasoning of fabrication inaccuracies. Along with the causal inference, a causal reasoning conducted in this work can guide corrections due to fabrication inaccuracies during the iterative validation process.