A nonlinear principal component analysis approach for turbulent combustion composition space

作者：Mirgolbabaei Hessam; Echekki Tarek^*; Smaoui Nejib

来源：International Journal of Hydrogen Energy, 2014, 39(9): 4622-4633.

DOI：10.1016/j.ijhydene.2013.12.195

• Turbulent combustion
• Nonlinear principal component analysis
• Autoignition

An approach for the determination of principal components using nonlinear principal component analysis (NLPCA) is proposed in the context of turbulent combustion. NLPCA addresses complex data sets where the contours of the inherent principal directions are curved in the original manifold. Thermo-chemical scalars' statistics are reconstructed from the optimally derived moments. The tabulation of the scalars is then implemented, using artificial neural networks (ANN). The approach is implemented on numerical data generated for the stand-alone one-dimensional turbulence (ODT) simulation of hydrogen auto-ignition in a turbulent jet with preheated air. It is found that 2 nonlinear principal components are sufficient to capture thermo-chemical scalars' profiles. For some of the scalars, a single principal component reasonably captures the scalars' profiles as well.

• 出版日期2014-3-18