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Facilitating Bayesian analysis of combustion kinetic models with artificial neural network · Study

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ArticleFacilitating Bayesian analysis of combustion kinetic models with artificial neural network

Jiaxing Wang2019

Article2019

Facilitating Bayesian analysis of combustion kinetic models with artificial neural network

Jiaxing Wang · Zijun Zhou · Keli Lin · Chung King Law · Bin Yang

60 citations·0/0 files stored·Combustion and Flame

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Probabilistic and Robust Engineering Design Advanced Combustion Engine Technologies Model Reduction and Neural Networks

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References

2007Global sensitivity analysis using polynomial chaos expansions 2006Bayesian analysis of computer code outputs: A tutorial 2001High Dimensional Model Representations 2004Uncertainty propagation using Wiener–Haar expansions 2007Efficient Sampling for Non-Intrusive Polynomial Chaos Applications with Multiple Uncertain Input Variables 2014Combustion kinetic model uncertainty quantification, propagation and minimization 2015Chaospy: An open source tool for designing methods of uncertainty quantification 2003Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection

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2023Neural network approach to response surface development for reaction model optimization and uncertainty minimization 2022OptEx: An integrated framework for experimental design and combustion kinetic model optimization 2023Uncertainty quantification of a deep learning fuel property prediction model

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Details

Year2019

Typearticle

Published2019-12-04

VenueCombustion and Flame

ISSN-L0010-2180

Languageen

Citations60

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.combustflame.2019.11.035

openalex_workW2993566524

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