This paper presents a novel physics-infused reduced-order modeling (PIROM) methodology for efficient and accurate modeling of non-linear dynamical systems. The PIROM consists of a physics-based analytical component that represents the known physical processes, and a data-driven dynamical component that represents the unknown physical processes. The PIROM is applied to the aerothermal load modeling for hypersonic aerothermoelastic (ATE) analysis and is found to accelerate the ATE simulations by two-three orders of magnitude while maintaining an accuracy comparable to high-fidelity solutions based on computational fluid dynamics (CFD). Moreover, the PIROM-based solver is benchmarked against the conventional POD-kriging surrogate model, and is found to significantly outperform the accuracy, generalizability and sampling efficiency of the latter in a wide range of operating conditions and in the presence of complex structural boundary conditions. Finally, the PIROM-based ATE solver is demonstrated by a parametric study on the effects of boundary conditions and rib-supports on the ATE response of a compliant and heat-conducting panel structure. The results not only reveal the dramatic snap-through behavior with respect to spring constraints of boundary conditions, but also demonstrates the potential of PIROM to facilitate the rapid and accurate design and optimization of multi-disciplinary systems such as hypersonic structures.
翻译:本文为非线性动态系统的高效和准确建模提供了一种新型物理学和降序模型(PIROM)方法,用于高效和精确的非线性动态系统建模;PIROM是一个基于物理的分析部分,代表已知物理过程,一个数据驱动的动态部分,代表未知物理过程;PIROM用于超声脉动(ATE)分析的热热热负载模型,并被认为加速以二至三个数量级进行ATE模拟,同时保持与基于计算流体动态的高不端解决方案(CFD)的精确度相当的精确度;此外,基于PIROM的解答器是参照常规的POD-Krig 代金模型,并参照常规的POD-rigging 代金模型进行基准分析,发现后者在广泛的操作条件下和复杂的结构边界结构条件下的准确性、可比较性和采样效率大大超出其准确性;最后,基于PIROM的ATE解析度解算法解算法解算法的解析系统的影响,但只能通过对符合性和正性原则的系统的反应进行分辨分析研究,同时展示透透透透透透视系统,并显示透视系统的潜在边界结构结构。