{"title":"A Machine Learning Approach to Model Oxidation of Toluene in a Bubble Column Reactor","authors":"Raihan Tayeb, Yuwen Zhang","doi":"10.1115/1.4057022","DOIUrl":null,"url":null,"abstract":"\n A machine-learned (ML) subgrid-scale (SGS) modeling technique is introduced for efficient and accurate prediction of reactants and products undergoing parallel competitive reactions in a bubble column. The model relies on data generated from a simple substitute problem with a small number of features. The machine-learned model replaces the iterative approach associated with the use of analytical profiles for previous subgrid-scale models for correcting concentration profiles in boundary layers. The present model, thus, offers a significant performance bonus as well as the flexibility to extend to more complex scenarios due to its data-driven nature.","PeriodicalId":15937,"journal":{"name":"Journal of Heat Transfer-transactions of The Asme","volume":"35 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Heat Transfer-transactions of The Asme","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4057022","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
A machine-learned (ML) subgrid-scale (SGS) modeling technique is introduced for efficient and accurate prediction of reactants and products undergoing parallel competitive reactions in a bubble column. The model relies on data generated from a simple substitute problem with a small number of features. The machine-learned model replaces the iterative approach associated with the use of analytical profiles for previous subgrid-scale models for correcting concentration profiles in boundary layers. The present model, thus, offers a significant performance bonus as well as the flexibility to extend to more complex scenarios due to its data-driven nature.
期刊介绍：
Topical areas including, but not limited to: Biological heat and mass transfer; Combustion and reactive flows; Conduction; Electronic and photonic cooling; Evaporation, boiling, and condensation; Experimental techniques; Forced convection; Heat exchanger fundamentals; Heat transfer enhancement; Combined heat and mass transfer; Heat transfer in manufacturing; Jets, wakes, and impingement cooling; Melting and solidification; Microscale and nanoscale heat and mass transfer; Natural and mixed convection; Porous media; Radiative heat transfer; Thermal systems; Two-phase flow and heat transfer. Such topical areas may be seen in: Aerospace; The environment; Gas turbines; Biotechnology; Electronic and photonic processes and equipment; Energy systems, Fire and combustion, heat pipes, manufacturing and materials processing, low temperature and arctic region heat transfer; Refrigeration and air conditioning; Homeland security systems; Multi-phase processes; Microscale and nanoscale devices and processes.
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