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Self-Organizing Maps for Fast LES Combustion Modeling

Award Information

National Aeronautics and Space Administration
Award ID:
Program Year/Program:
2011 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
17301 W COLFAX AVE STE 160 GOLDEN, CO 80401-4886
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2011
Title: Self-Organizing Maps for Fast LES Combustion Modeling
Agency: NASA
Contract: NNX11CD81P
Award Amount: $99,997.00


Tremendous advances have been made in the development of large and accurate detailed reaction chemistry models for hydrocarbon fuels. Comparable progress has also been achieved in CFD as an engineering design tool. Highly accurate hydrocarbon chemistry is now desired for simulating gas turbine combustors and automobile engines to better predict both performance and pollutant emissions. Newer and more accurate CFD techniques like Large Eddy Simulation (LES) are being used more as computational power increases along with the demand for better flow predictions. Unfortunately, using large, detailed chemical mechanisms to simulate real turbulent combustion devices is problematic due to the sheer computational burden of the added chemistry. As a result, chemistry mechanisms employing a large number of chemical species are currently only feasible to run in the simplest of flow geometries, and only the simplest and least accurate chemistry models are currently tractable to run in LES CFD codes. We propose using a unique neural network approach to create a fast and accurate species source term function that could alleviate both of these problems.

Principal Investigator:

Bradley D. Hitch
Principal Investigator

Business Contact:

Todd Leeson
Business Official
Small Business Information at Submission:

Reaction Systems, LLC
19039 E. Plaza Dr., Suite 290 Parker, CO 80134-

EIN/Tax ID: 202875490
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No