An Adaptive Chemistry Approach to Modeling Emissions Performance of Gas Turbine Combustors

Award Information
Agency:
National Aeronautics and Space Administration
Branch
n/a
Amount:
$599,845.00
Award Year:
2010
Program:
SBIR
Phase:
Phase II
Contract:
NNX10RA06C
Award Id:
87982
Agency Tracking Number:
074346
Solicitation Year:
n/a
Solicitation Topic Code:
A2
Solicitation Number:
n/a
Small Business Information
45 Manning Road, Billerica, MA, 01821
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
030817290
Principal Investigator:
Hsi-Wu Wong
Principal Investigator
(978) 932-0218
hwwong@aerodyne.com
Business Contact:
Charles Kolb
President
(978) 663-9500
kolb@aerodyne.com
Research Institution:
n/a
Abstract
Computational Fluid Dynamics (CFD) simulations for combustion do not currently have the predictive capability typically found for non-reacting flows due to the prohibitively high computational cost incurred when one introduces detailed chemical kinetics. In this SBIR project, we propose a novel method, Adaptive Chemistry, to enable such detailed modeling. This method adapts the reaction mechanism used in CFD to local reaction conditions. Instead of a single comprehensive reaction mechanism throughout the computation, smaller, locally valid reduced models are used to accurately capture the chemical kinetics at a smaller cost. Our Adaptive Chemistry approach seeks to obtain a reduced model guaranteed to be valid within the variable range for each grid point, and controls errors rigorously without evaluating the very expensive full model. Adaptive Chemistry also dynamically constructs a reduced model library based on real-time reaction conditions to prevent large memory overhead for arbitrary solution trajectories. This also allows Adaptive Chemistry to be easily extendable to transient problems. Finally, Adaptive Chemistry allows users to set a constraint on the largest model size by using a skeletal model, but selects each reduced model based on the full, detailed chemistry, which obtains a guaranteed optimal solution more efficiently compared to the traditional skeletal model methods. In this project, we will develop an error-controlled reduced-species Adaptive Chemistry software package that can be easily interfaced with any CFD solver. The first objective of this work is to continue developing needed methods for error-controlled reduced-species Adaptive Chemistry for steady-state reacting flow simulations. The second objective is to implement the available methods into a modular package that can be easily interfaced with any CFD solver. We will also develop an Adaptive Chemistry module that can be coupled with the PREMIX program for commercialization.

* information listed above is at the time of submission.

Agency Micro-sites


SBA logo

Department of Agriculture logo

Department of Commerce logo

Department of Defense logo

Department of Education logo

Department of Energy logo

Department of Health and Human Services logo

Department of Homeland Security logo

Department of Transportation logo

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government