Computational tools for reliable prediction of complex hypersonic flows

In order to enable reliable predictions based on full scale vehicle simulations relevant to high-speed ISR missions, detailed interactions among various nonequilibrium physical phenomena and their coupling to turbulent flow structures, characterized by a broad range of length/time scales, need to be accurately modeled. Through this Phase II STTR project new computational tools for reliable and efficient predictions of complex nonequilibrium, turbulent hypersonic flows (relevant to high-speed ISR missions) are proposed. Key contributions of this project include: (a) development of high-order accurate CFD code that accounts for full and reduced order representation of state-kinetics, (b) development of subgrid scale models for large eddy simulation (LES) of nonequilibrium, hypersonic flows, (c) detailed, state-dependent representation of transport coefficients, (d) consideration of machine learning frameworks for speedup, (e) development of tools to enable uncertainty quantification (UQ) and (f) development of tools for model assessment, validation and adaptation. Information needed for state-kinetics modeling is obtained from quasi-classical trajectory (QCT) method. Preliminary results obtained from coarse-grained binning approaches were found to be encouraging.