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Measurement and Modeling of Surface Coking in Fuel-Film Cooled Liquid Rocket Engines

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9300-17-C-2501
Agency Tracking Number: F15A-T21-0120
Amount: $749,998.80
Phase: Phase II
Program: STTR
Solicitation Topic Code: AF15-AT21
Solicitation Number: 2015.0
Timeline
Solicitation Year: 2016
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-03-02
Award End Date (Contract End Date): 2019-05-30
Small Business Information
701 McMillian Way NW, Huntsville, AL, 35806
DUNS: 185169620
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: Y
Principal Investigator
 Dr. Ranjan Metha
 (256) 726-4800
 proposals-contracts@cfdrc.com
Business Contact
 Mrs. Deborah Phipps
Phone: (256) 726-4884
Email: deb.phipps@cfdrc.com
Research Institution
 Purdue University
 Susan Corwin
 155 South Grant Street
West Lafayette, IN, 47907
 (765) 494-6204
 Nonprofit college or university
Abstract
Designing an efficient and effective film cooling system to protect critical components of modern rocket engines requires a significant number of problems and challenges to be addressed. Complicating the already difficult hydrodynamic challenges, thermal and/or catalytic cracking of hydrocarbon fuels is always accompanied with coke formation. Coke deposits on combustor and nozzle walls reduce heat fluxes and can have unwanted effects on regenerative heating of the fuel flowing through the outer channels. The overall goal of this project is to develop and validate models for surface coking under conditions relevant to fuel film cooled liquid rocket engines. In Phase I, the team of CFDRC Purdue University and Dr. Hai Wang demonstrated feasibility of developing such models. Phase II plans include a) complete the development and implementation of predictive coke deposition models, b) conduct target experiments to isolate effects of different aspects of coke deposition and to provide improved understanding of coke formation, c) validate and calibrate coke deposition models against test data, d) quantify measurement and prediction uncertainties and identify error bounds associated with heat transfer prediction, and e) develop APIs to integrate developed models with 3-D CFD codes used by the Air Force for liquid rocket engine analysis.

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

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