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Error-controlled kinetics reduction based on non-linear optimization and sensitivity analysis
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DOI：10.1016/j.combustflame.2018.11.007.png)
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Abstract
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Efficient reduction techniques are necessary for the construction of compact chemical kinetic mechanisms to enable the application to large-scale simulations. In this work, a new formulation is proposed to derive skeletal mechanisms by species elimination. The proposed method relies on a gradient-based non-linear optimization (NLO) method, allowing for direct error control on user-defined quantities of interest (Qols). The key idea consists in formulating the species elimination by relaxing an integer-optimization problem into a continuous optimization problem that is solved iteratively. A species-targeted sensitivity analysis (SA) formulation is presented that can be combined with the optimization method to reduce the overall computational complexity of the procedure. After illustrating its principle, the NLO procedure is applied to different fuels of increasing chemical complexity, including methane, n-dodecane, and a four-component kerosene surrogate. Direct comparisons are performed with the directed relation graph method with error propagation (DRGEP) and SA. For the reduction of a detailed methane mechanism, consistency with DRGEP and SA is demonstrated, and the NLO procedure is shown to generate smaller mechanisms compared to the other two methods. In application to larger hydrocarbon and multicomponent transportation fuels, it is shown that significantly smaller mechanisms are obtained with the NLO procedure compared to the other approaches. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
Keywords:
Reduced kinetics
Combustion
Optimization
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