SBIR-STTR Award

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. Although detailed predictions can be obtained using detailed state-to-state kinetics in conjunction with numerical schemes of high order accuracy in space and time, the computational cost associated with it is prohibitively high. The focus of this STTR project is to address some challenges in existing tools for prediction of nonequilibrium laminar hypersonic flows via development of a high-order accurate hypersonic flow code with capabilities for both detailed state-to-state kinetics and reduced order models of state-to-state kinetics based on coarse graining. Novel contributions in this project include: (a) high-fidelity tools based on high-order accurate formulations of hypersonic flow predictions with detailed state kinetics, along with relevant code development and implementation, (b) development and implementation of low/variable fidelity tools based on novel coarse grained models for state-to-state kinetics, (c) development of modules for assessment of performance of reduced order models of state-kinetics and (d) development of criteria for model selection based on local flow and/or thermochemical nonequilibrium conditions.

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.