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This paper presents a novel physics-infused reduced-order modeling (PIROM)methodology for efficient and accurate modeling of non-linear dynamicalsystems. The PIROM consists of a physics-based analytical component thatrepresents the known physical processes, and a data-driven dynamical componentthat represents the unknown physical processes. The PIROM is applied to theaerothermal load modeling for hypersonic aerothermoelastic (ATE) analysis andis found to accelerate the ATE simulations by two-three orders of magnitudewhile maintaining an accuracy comparable to high-fidelity solutions based oncomputational fluid dynamics (CFD). Moreover, the PIROM-based solver isbenchmarked against the conventional POD-kriging surrogate model, and is foundto significantly outperform the accuracy, generalizability and samplingefficiency of the latter in a wide range of operating conditions and in thepresence of complex structural boundary conditions. Finally, the PIROM-basedATE solver is demonstrated by a parametric study on the effects of boundaryconditions and rib-supports on the ATE response of a compliant andheat-conducting panel structure. The results not only reveal the dramaticsnap-through behavior with respect to spring constraints of boundaryconditions, but also demonstrates the potential of PIROM to facilitate therapid and accurate design and optimization of multi-disciplinary systems suchas hypersonic structures.

Physics-Infused Reduced Order Modeling of Aerothermal Loads for Hypersonic Aerothermoelastic Analysis