Development of a Computational Method for Prediction of After-Burning Effect

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-10-C-0422
Agency Tracking Number: N10A-002-0225
Amount: $69,928.00
Phase: Phase I
Program: STTR
Awards Year: 2010
Solitcitation Year: 2010
Solitcitation Topic Code: N10A-T002
Solitcitation Number: 2010.A
Small Business Information
Combustion Research and Flow Technology,
6210 Kellers Church Road, Pipersville, PA, 18947
Duns: 929950012
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Neeraj Sinha
 Vice President & Chief Sc
 (215) 766-1520
Business Contact
 Brian York
Title: Principal Scientist & Tr
Phone: (215) 766-1520
Research Institution
 The Pennsylvania State University
 Richard Yetter
 College of Engineering
111 Research Blg. East
University Park, PA, 16802
 (814) 863-6375
 Nonprofit college or university
The problem of interest is the development of a physics based model for conducting high-fidelity simulation of afterburning munitions, which are unique in that that they contain solid and/or liquid fuels that continue burning after the initial detonation to raise the temperature, enhance the overpressure, and strengthen secondary shock waves. From the standpoint of first-principles modeling, accurate depiction of dynamic mechanisms such as shock compression, multi-phase effects, stiff chemical kinetics, reactive heat release, etc., is a complex undertaking that challenges modeling efforts. This is due in large part to the very stiff spatio-temporal conditions inherent in these highly non-linear and very transient processes. Energy deposition can be spatially localized with a wide range of time scales (fluid dynamic, activation and reaction scales) whose numerical resolution requires extremely fine spatial and temporal discretization. A multi-phase CFD approach is proposed to model energy deposition scenarios of interest to the US Navy, with the model also finding utility in identifying the dominant physics, supporting the development of scaling laws and providing interpretation of test data. The modeling will be closely supported by fundamental experiments in a laboratory environment that will supply crucial data for characterization of key sub-models within the overall CFD model.

* information listed above is at the time of submission.

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