Inverse design of a Helmholtz resonator based low-frequency acoustic absorber using deep neural network

Abstract

The design of low-frequency sound absorbers with broadband absorption characteristics and optimized dimensions is a pressing research problem in engineering acoustics. In this work, a deep neural network based inverse prediction mechanism is proposed to geometrically design a Helmholtz resonator (HR) based acoustic absorber for low-frequency absorption. Analytically obtained frequency response from electro-acoustic theory is deployed to create the large dataset required for training and testing the deep neural network. The trained convolutional neural network inversely speculates optimum design parameters corresponding to the desired absorption characteristics with high fidelity. To validate, the inverse design procedure is initially implemented on a standard HR based sound absorber model with high accuracy. Thereafter, the inverse design strategy is extended to forecast the optimum geometric parameters of an absorber with complex features, which is realized using HRs and a micro-perforated panel. Subsequently, a quasi-perfect low-frequency acoustic absorber having minimum thickness and broadband characteristics is deduced. Importantly, it is demonstrated that the proposed absorber, comprising four parallel HRs and a microperforated panel, absorbed more than 90% sound in the frequency band of 347–630 Hz. The introduced design process reveals a wide variety of applications in engineering acoustics as it is suitable for tailoring any sound absorber model with desirable features.

Case studies on aeroacoustics damping performances of Coupled Helmholtz Resonators over low frequency ranges

“…The corresponding resonant frequency is found to be shifted from 88 Hz to ∼100 Hz, as Mu is increased from 0 to 0.1. This investigation reveals that the developed numerical tool is applicable to evaluate the acoustic attenuation performances of a Helmholtz resonator, 34,35 as there is a grazing mean flow.…”

“…In this way, it enables acoustic damper corresponding to the operating condition changes of the engines. [31][32][33][34] Helmholtz resonators 4,5,8 have a wide application in air-breathing engine industries, such as gas turbine engines 11 and internal combustion engines. 12 Extensive research [16][17][18] has been conducted to optimize the design and the acoustic noise damping performance of such resonators at a low frequency range, typically below 800 Hz.…”

Numerical optimizing noise damping performances of Helmholtz resonators with a rigid baffle implemented at neck in presence of a grazing flow

“…The 2D numerical model is governed by linearized NS equations, since we consider low Mach number incompressible viscous flow (Ma<0.2). Thus, the mass conservation relationship [30][31][32][33][34] holds as…”

“…The 2D numerical model is governed by linearized NS equations, since we consider low Mach number incompressible viscous flow (Ma<0.2). Thus, the mass conservation relationship 30-34 holds asThe instantaneous parameters include velocity u , density ρ, pressure p, and temperature T, respectively. Each parameter consists of a mean/average (denoted by subscript 0) and a fluctuating part.…”

Piezoelectric Micromachined Ultrasonic Transducer-Integrated Helmholtz Resonator with Microliter-Sized Volume-Tunable Cavity

“…Conventional Helmholtz resonators are typically used for sound absorption [ 4 , 5 , 6 , 7 ]. For example, Zhao and Morgans [ 8 ] used Helmholtz resonators as passive dampers.…”