Bottom-up approaches for rapid on-demand design of modular metaporous structures with tailored absorption

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As a new trend in the studies on sound-absorbing structures design, customizable metaporous structures (MPSs) have drawn a great deal of interest due to their distinct advantages, which include designable broadband absorption, light weight, and low thickness. Conventional finite element-based design methods, such as trial-and-error and iterative optimization, are inefficient and expensive in terms of computational resources. Inspired by the widely used bottom-up method, in this study, we develop a data-driven metaheuristic optimization framework to accomplish the rapid on-demand design for a novel modular metaporous structure (MMPS) of only 30mm thickness from the local to the global level. Two cascade variants of the genetic algorithm (GA) are employed for local optimization and global customized design, accordingly. The local design level involves the development of a surrogate-assisted genetic algorithm (SAGA) for design space optimization. On the basis of the structural dataset, a well-tuned convolutional neural network (CNN) model is developed for expediting the forward prediction of the acoustic properties of the two-dimensional (2D) MPS. In the subsequent phase, the validated CNN model is combined with SAGA to expedite the fitness evaluation for optimizing the structural units. At the global design stage, the developed SAGA is coupled with the population initialization process of an elitist genetic algorithm (EGA) to achieve inverse design for the MMPS with customizable broadband absorption based on the optimized design space. Furthermore, an acoustic measurement is performed on the fabricated MMPS samples to validate the finite element method (FEM) simulation and impedance design method. The utilization of this optimization method opens up fresh possibilities not solely for the customized design of sound-absorbing structures, but also for optimization processes in various other domains. Meanwhile, the proposed MMPS with customizable broadband absorption in a thickness of 30mm could well be utilized for noise reduction in a variety of practical applications.