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Conjugate heat transfer for LES of gas turbine engines

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0795
Agency Tracking Number: N19B-027-0050
Amount: $139,989.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N19B-T027
Solicitation Number: 19.B
Timeline
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-09-11
Award End Date (Contract End Date): 2020-03-11
Small Business Information
2445 Faber Place #100
Palo Alto, CA 94303
United States
DUNS: 179576715
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Sanjeeb Bose
 Chief Technology Officer
 (650) 521-0243
 stbose@cascadetechnologies.com
Business Contact
 Donna Carrig
Phone: (650) 521-0243
Email: carrig@cascadetechnologies.com
Research Institution
 Pennsylvania State University
 Loretta Weaver Loretta Weaver
 
Office of Sponsored Programs 110 Technology Center Bldg
University Park, PA 16802
United States

 (814) 865-9178
 Nonprofit college or university
Abstract

Current design tools for gas turbine engines invoke a variety of simplifying assumptions to estimate heat transfer to solid/metal engine components (e.g., isothermal boundary conditions). These approximations are often not valid, result in inaccurate predictions of heat transfer, and ultimately compromise the thermal integrity of propulsion and power systems. Wall-modeled large eddy simulation (WMLES) has been recently used to predict heat transfer rates in a variety of relevant flow environments, including separated flows and reactive effusion cooling. Despite these advances, WMLES often does not include conjugate heat conduction in the solid materials due to added computational cost and temporal stiffness from the vast timescale separation between the flow, combustion, and solid-side conduction. In this proposal, Cascade Technologies and The Pennsylvania State University present a plan to build efficient computational tools to predict conjugate heat transfer using WMLES on massively parallel computers. The proposed algorithms will be validated against a battery of cases relevant to turbine blades and effusion cooling, with comparison to detailed experimental data and state-of-the-art RANS simulations. The team will additionally supplement existing experimental databases to advance understanding of conjugate heat transfer in the broader gas turbine community.

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

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