Time-Accurate Modeling for Hypersonic Morphing Vehicles

To achieve enhanced tactical performance, speed, reach, and lethality, next-generation hypersonic vehicles must be designed for increased dynamics, control, and maneuverability. Morphing and adaptive structures, and active control surfaces will be critical in achieving these goals. However, the time-varying flow-field brought about by changes in vehicle orientation and configuration make such designs particularly difficult. The variations include non-linear changes in atmospheric conditions, chemical kinetics, vibrational excitation, turbulence, ablation products, and gas-surface interactions. The resultant changes in emissions intensity and spectral band means that mitigating strong electromagnetic signatures becomes a critical design requirement for stealth. Computational fluid dynamics (CFD) remains the most promising design tool for predicting these complex flow-fields, but requires robust techniques for tightly coupling the fluid, thermal, kinetic, and structural solutions for a single time-varying system. The goal of this R&D is to develop an innovative, high-fidelity toolkit capable of predicting time-accurate electromagnetic signatures by modeling the tightly-coupled, time-varying flowfield phenomenon occurring across a range of flight conditions, including rapid maneuvers and potential morphological changes. The Phase I methodology will focus on laying the fundamental theoretical groundwork by demonstrating time-accurate EO/IR signature prediction along a trajectory with small changes in vehicle geometry. We will utilize US3D to predict the chemical kinetics and turbulence along the full flight path, accounting for changes in vehicle geometry using in-the-loop CFD grid deformations. The resulting flow-field will be used to predict EO/IR signatures. Phase I will also include running Large Eddy Simulations for a subset of the flow-field. Finally, we will develop a comprehensive physics-based road-map for software expansion to TRL 5. Work in Phase II and beyond will involve expanding the Phase I prototype to include in-the-loop grid morphing, ablation, fluid-structure interactions, and radar signature prediction. We will also integrate the high-fidelity LES approaches demonstrated in Phase I into the toolkit framework.