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Modeling of interior nozzle flows for transient effects, realistic high performance nozzle physics and coupling to Large Eddy Simulation modeling of t

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-14-C-0047
Agency Tracking Number: N132-102-0243
Amount: $149,995.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N132-102
Solicitation Number: 2013.2
Timeline
Solicitation Year: 2013
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-10-21
Award End Date (Contract End Date): 2015-09-15
Small Business Information
2445 Faber Place #100
Palo Alto, CA 94303
United States
DUNS: 000000000
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Hung Le
 General Manager
 (650) 521-0243
 hle@cascadetechnologies.com
Business Contact
 Donna Carrig
Title: CFO
Phone: (650) 521-0243
Email: carrig@cascadetechnologies.com
Research Institution
N/A
Abstract

The objective of the present proposal is to develop and apply accurate, robust and cost-effective methodologies for the prediction of the interior nozzle flow, seamlessly coupled with high-fidelity large eddy simulation (LES) for the prediction of the jet plume and radiated noise. The simulations will be performed in the massively-parallel unstructured LES framework developed at Cascade Technologies, using our flagship compressible solver Charles. In Phase I and I option, the proposed tasks focuses on near-wall adaptive mesh refinement, synthetic inflow turbulence and wall modeling inside the nozzle. In particular, the wall model will significantly reduce the computational cost by relaxing the grid resolution requirements in near-wall region inside the nozzle. In addition, physics-based mesh refinement and adaptation will be implemented. This automatic meshing approach has the potential to not only greatly simplify the meshing process and drastically reduce the burden on users, but also to improve accuracy while reducing the simulation run time. The impact of these additional modelings on the predictive capability of LES must be characterized and best practices must be developed. This proposal describes a scope of work that includes development, implementation and testing of these capabilities for complex jet configurations relevant to the Navy.

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

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