Self-Organizing Maps for Fast LES Combustion Modeling

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.

The US Air Force, GE Aircraft Engines, Aerojet, Pratt & Whitney-Rocketdyne, and Rolls-Royce are all major players in the field of airbreathing and rocket engine design and have expressed a high level of interest in development of high-fidelity engine design tools like reacting flow LES. Problems with combustion stability, for example, often appear late in an engine development program and can be quite difficult and costly to fix, but could be detected early enough to change inexpensively with high-fidelity computational tools. Other potential applications of our technology include better rocket plume simulations to more accurately predict radar and infrared signatures and base heating loads, industrial chemical processes, and automobile engine design to help reduce pollutant formation.

Incorporating fast reacting flow chemistry into LES calculations would represent an enabling technology and would be of great interest to NASA and the rest of the CFD community. Several groups at NASA would benefit from our project; NASA Glenn Research Center is developing the National Combustion Code (NCC) to aid in the design of rocket and gas turbine aircraft engines, while Wind-US, and VULCAN (developed at NASA-Langley), are two other NASA reacting flow CFD codes that could benefit from this research. The ability to accurately predict performance of hypersonic airbreathing systems burning higher hydrocarbons would be immediately useful.

This is early/mid-stage (TRL 3) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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