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<p>Here, we propose a novel, fully automated framework for accelerated design of underwater acoustic coatings, targeting the reduction of acoustic signature of naval platforms under operational conditions, by coupling Bayesian Optimization (BO) with a 2-step Finite Element (FE) Model. The developed FE model evaluates the acoustic performance of polyurethane (PU) coatings with embedded metamaterial features under the influence of varying depth of operation, i.e., hydrostatic pressure-dependent acoustic attenuation. The frequency-dependent viscoelasticity, which has often been ignored in previous studies, is also considered in the FE model to obtain a realistic evaluation of the absorption behavior of these coatings over a wide range of operational frequencies. The main contribution of the proposed optimization framework is its efficient utilization of the expensive FE simulations through BO. The desired broad-band and low-frequency attenuation is achieved under the varying operating depth by an optimal design of the void layers. Moreover, this framework enables the targeted design of underwater acoustic coatings by effective exploration of the 10-dimensional, vast, and computationally expensive design space, leading to a significant reduction in the number of simulations required to run compared to conventional exhaustive search strategies.</p>

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Constrained Bayesian accelerated design of acoustic polyurethane coatings with metamaterial features under hydrostatic pressure

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月21日

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  • Pengyuan Ding,
  • Dominic Robe,
  • Michael Kirley,
  • Elnaz Hajizadeh

摘要

Here, we propose a novel, fully automated framework for accelerated design of underwater acoustic coatings, targeting the reduction of acoustic signature of naval platforms under operational conditions, by coupling Bayesian Optimization (BO) with a 2-step Finite Element (FE) Model. The developed FE model evaluates the acoustic performance of polyurethane (PU) coatings with embedded metamaterial features under the influence of varying depth of operation, i.e., hydrostatic pressure-dependent acoustic attenuation. The frequency-dependent viscoelasticity, which has often been ignored in previous studies, is also considered in the FE model to obtain a realistic evaluation of the absorption behavior of these coatings over a wide range of operational frequencies. The main contribution of the proposed optimization framework is its efficient utilization of the expensive FE simulations through BO. The desired broad-band and low-frequency attenuation is achieved under the varying operating depth by an optimal design of the void layers. Moreover, this framework enables the targeted design of underwater acoustic coatings by effective exploration of the 10-dimensional, vast, and computationally expensive design space, leading to a significant reduction in the number of simulations required to run compared to conventional exhaustive search strategies.