Computational tools for reliable prediction of complex hypersonic flows

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-17-P-2429
Agency Tracking Number: F17A-014-0031
Amount: $144,537.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF17A-T014
Solicitation Number: 2017.0
Solicitation Year: 2017
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-07-13
Award End Date (Contract End Date): 2018-04-16
Small Business Information
3021 Cruden Dr, Norman, OK, 73072
DUNS: 080491037
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Prakash Vedula
 (405) 464-6980
Business Contact
 Prakash Vedula
Phone: (405) 464-6980
Research Institution
 University of Illinois, Urbana-Champaign
 Prakash Vedula
 (405) 464-6980
 Nonprofit college or university
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.

* Information listed above is at the time of submission. *

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