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Multiphysics Modeling of Dynamic Combustion Processes Using Pareto-Efficient Combustion Framework

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9300-19-P-1502
Agency Tracking Number: F18B-010-0076
Amount: $149,955.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF18B-T010
Solicitation Number: 2018.2
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-03-04
Award End Date (Contract End Date): 2020-03-04
Small Business Information
3221 NW 13th Street, Suite A, Gainesville, FL, 32609
DUNS: 090574786
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Siddharth Thakur
 (352) 271-8841
 st@snumerics.com
Business Contact
 Siddharth Thakur
Phone: (352) 271-8841
Email: st@snumerics.com
Research Institution
 Stanford University
 Ms. Virginia   Gregg
 417 West Hall
110 8th Street
Troy, NY, 12180
 (518) 276-6426
 Nonprofit college or university
Abstract
The objective is to develop zonal multi-physics capability for turbulent combustion simulations. The foundation of the proposed work is a novel Pareto-Efficient Combustion (PEC) framework for fidelity-adaptive combustion modeling. The PEC model utilizes a combustion submodel assignment, combining the low-cost flamelet-based models with the more expensive finite rate chemistry models where necessary. The complex flows encountered in rocket engines include fluids and flows which transition between multiple modeling regimes. The nature of the PEC model condones the inclusion of additional models which can capture those different regimes of fluid physics. That model transition is important for local thermodynamic and transport properties, the treatment of turbulence, the treatment of chemical reactions and combustion, and turbulence-chemistry interaction. The developments in this work would improve internal consistency of fluid properties, which can greatly vary when switching from a critical fluid to essentially an ideal fluid, as well as help reduce computational costs by applying the more computationally expensive models only where necessary. Furthermore, tying the selection of turbulence treatment (such LES, DES and URANS) to a figure of merit rather than strictly the local mesh density has the potential to both improve fidelity of the simulation as well as limit computational cost.

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

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