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

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,928.00
Award Year:
2010
Program:
STTR
Phase:
Phase I
Contract:
N68335-10-C-0422
Award Id:
95057
Agency Tracking Number:
N10A-002-0225
Solicitation Year:
n/a
Solicitation Topic Code:
NAVY 10T002
Solicitation Number:
n/a
Small Business Information
6210 Kellers Church Road, Pipersville, PA, 18947
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
929950012
Principal Investigator:
Neeraj Sinha
Vice President & Chief Sc
(215) 766-1520
sinha@craft-tech.com
Business Contact:
Brian York
Principal Scientist & Tr
(215) 766-1520
york@craft-tech.com
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
Abstract
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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