A HyChem Model of Polyoxymethylene Dimethyl Ether 5 Optimized with a Differential Evolution Algorithm

This study develops a machine learning-optimized combustion model for the ether-based fuel PODE<sub>5</sub> based on the HyChem approach, which decouples fuel combustion steps into lumped pyrolysis and detailed oxidation. Due to its main-chain oxygen and high oxygen-to-carbon ratio, PODE...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Guohua Li (550125) (author)
مؤلفون آخرون:	Yujie Tao (17355486) (author)
منشور في:	2025
الموضوعات:	Medicine Evolutionary Biology Ecology Science Policy Computational Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified requiring special consideration reaction rate parameters ignition delay times ignition delay time differential evolution algorithm defining optimization objectives pode fuels differ methyl ester fuels 5 </ sub 3 </ sub 2 </ sub optimized combustion model based fuel pode hychem model based based fuels reference model model development hychem model study develops satisfactory performance machine learning lumped pyrolysis hychem method hychem approach high oxygen flame speeds existing models detailed oxidation conventional hydrocarbon chain oxygen carbon ratio adjustment process
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A HyChem Model of Polyoxymethylene Dimethyl Ether 5 Optimized with a Differential Evolution Algorithm

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