声辐射和散射的边界集成神经网络和代码

IF 3.4 Q1 ENGINEERING, MECHANICAL 国际机械系统动力学学报(英文) Pub Date : 2024-06-04 DOI:10.1002/msd2.12109
Wenzhen Qu, Yan Gu, Shengdong Zhao, Fajie Wang, Ji Lin
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引用次数: 0

摘要

本文提出了一种用于分析声辐射和散射的新方法,即边界集成神经网络(BINNs)。该方法引入时谐波方程的基本解,在神经网络中编码边界积分方程(BIEs),取代了物理信息神经网络(PINNs)中传统的调控方程。这种方法有几个优点。首先,BINNs 神经网络的输入数据只需要 "边界 "定位点的坐标,因此非常适合分析无边界域中的声场。其次,BINNs 的损失函数不是复合形式,收敛速度快。第三,BINNs 使用较少的配准点和隐层/神经元就能达到与 PINNs 相当的精度。最后,BIEs 的半解析特性有助于提高 BINNs 的精度。本文列举了一些数值示例来证明所提方法的性能,并提供了 MATLAB 代码实现作为补充材料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Boundary integrated neural networks and code for acoustic radiation and scattering

This paper presents a novel approach called the boundary integrated neural networks (BINNs) for analyzing acoustic radiation and scattering. The method introduces fundamental solutions of the time-harmonic wave equation to encode the boundary integral equations (BIEs) within the neural networks, replacing the conventional use of the governing equation in physics-informed neural networks (PINNs). This approach offers several advantages. First, the input data for the neural networks in the BINNs only require the coordinates of “boundary” collocation points, making it highly suitable for analyzing acoustic fields in unbounded domains. Second, the loss function of the BINNs is not a composite form and has a fast convergence. Third, the BINNs achieve comparable precision to the PINNs using fewer collocation points and hidden layers/neurons. Finally, the semianalytic characteristic of the BIEs contributes to the higher precision of the BINNs. Numerical examples are presented to demonstrate the performance of the proposed method, and a MATLAB code implementation is provided as supplementary material.

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Issue Information Cover Image, Volume 4, Number 3, September 2024 Design of bionic water jet thruster with double-chamber driven by electromagnetic force A data-assisted physics-informed neural network (DA-PINN) for fretting fatigue lifetime prediction Comparison of the performance and dynamics of the asymmetric single-sided and symmetric double-sided vibro-impact nonlinear energy sinks with optimized designs
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