Balancing accurate and efficient estimation of aerothermodynamic loads is a significant challenge for multidisciplinary modeling and analysis of high-speed vehicles. This study focuses on this issue by studying the impact of analytical and data-driven model reductions over a broad operational space. Reduced models are compared with Reynolds-averaged Navier–Stokes predictions for steady-state aerodynamic pressure and heat flux on the surface of a complete hypersonic vehicle geometry over a broad operational space. Both accuracy and computational requirements are considered so as to provide guidance on tradeoffs when carrying out multidisciplinary simulation of high-speed vehicles.

平衡空气动力学动力载荷的准确和有效估算是高速车辆多学科建模和分析的重大挑战。本研究通过研究在广泛的运营空间中分析和数据驱动的模型缩减的影响来解决此问题。将简化后的模型与雷诺平均的Navier-Stokes预测进行比较，以预测在广阔的操作空间中完整超音速飞行器几何形状表面的稳态空气动力压力和热通量。考虑准确性和计算要求，以便在进行高速车辆的多学科仿真时在权衡方面提供指导。