航天器环境工程2026，Vol.43Issue(4)：257-266,10.DOI:10.12126/see.2026042
航天器柔性伸展臂热致振动的高精度PINN预测方法
High-precision PINN prediction method for thermally induced vibration of flexible spacecraft booms
摘要
Abstract
To address the problem of predicting thermally induced vibrations in flexible spacecraft booms,a physics-informed neural network(PINN)prediction framework based on mixed variables and hard constraints was proposed.Based on the Euler-Bernoulli beam theory and the assumption of one-way uncoupled heat conduction,a thermo-mechanical semi-decoupling strategy was employed to precompute thermal bending moments as boundary inputs,effectively avoiding training oscillations caused by direct thermo-structural coupling.To mitigate gradient instability and the spectral bias problem,mixed variables were introduced to reduce the equation order,and geometric hard constraints were designed to satisfy the boundary conditions at the root.Fourier feature mapping was also integrated to enhance the network's ability to capture multi-frequency transient response features.Validations against high-fidelity finite element simulation data demonstrate that the predicted tip displacements agree well with the benchmark solutions,with the root mean square error reaching the order of 10-5 and the relative error remaining not exceeding 1.27%.The proposed method exhibits high accuracy and robustness in rapid prediction of multiphysics-coupled dynamic responses.关键词
热致振动预测/物理信息神经网络/航天器柔性伸展臂/混合变量/硬约束Key words
thermally induced vibration prediction/physics-informed neural network/flexible spacecraft boom/mixed variables/hard constraints分类
航空航天引用本文复制引用
王钰超,张强,蔡守宇,刘磊,卫洪涛..航天器柔性伸展臂热致振动的高精度PINN预测方法[J].航天器环境工程,2026,43(4):257-266,10.基金项目
国家自然科学基金项目(编号:51675430) （编号:51675430）
