Kinetic subspace investigation using neural network for uncertainty quantification in nonpremixed flamelets
Author:
Publisher
Elsevier BV
Subject
Physical and Theoretical Chemistry,Mechanical Engineering,General Chemical Engineering
Reference23 articles.
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2. Chemical kinetic uncertainty quantification for large eddy simulation of turbulent nonpremixed combustion;Mueller;Proc. Combust. Inst.,2013
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4. Bayesian calibration of a methane-air global scheme and uncertainty propagation to flame-vortex interactions;Armengol;Combust. Flame,2021
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1. Designing green chemicals by predicting vaporization properties using explainable graph attention networks;Green Chemistry;2024
2. Multi-target active subspaces generated using a neural network for computationally efficient turbulent combustion kinetic uncertainty quantification in the flamelet regime;Combustion and Flame;2023-12
3. Multi-fidelity neural network for uncertainty quantification of chemical reaction models;Combustion and Flame;2023-12
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