Application of dense neural networks for manifold-based modeling of flame-wall interactions

Bissantz, Julian; Karpowski, Jeremy; Steinhausen, Matthias; Luo, Yujuan; Ferraro, Federica; Scholtissek, Arne; Hasse, Christian

doi:10.1016/j.jaecs.2023.100113

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“…Also, using the combined ML and look-up table can become difficult to work with in terms of the numerical implementation and the usage. Bissantz et al [31] used a Dense Neural Network (DNN) to replace the tables in an FGM-CFD simulation of premixed methane-air flame quenching at the wall. They utilized a Sparse Principal Component Analysis (SPCA) to find the Control Variables (CVs).…”

Section: Introductionmentioning

confidence: 99%