Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations

dc.contributor.advisorMoller, Klaus
dc.contributor.authorMammen, Ashlen
dc.date.accessioned2025-09-10T07:38:31Z
dc.date.available2025-09-10T07:38:31Z
dc.date.issued2025
dc.date.updated2025-09-10T07:23:47Z
dc.description.abstractThe paper presents an in-depth exploration of a debutaniser distillation column, a critical component in a typical separation train. The primary function of this unit is to separate the upstream distillation column product flow into LPG and a heavier stream of catalytic naphtha. The operation of the Debutaniser is crucial for maintaining the total C5 vol% and RVP within specified limits, ensuring optimal operation of downstream units. Given the high costs associated with real-time analysers, the study explores the development of various modelling techniques, including principal component analyses, decision trees, random forests, gradient boosting, neural networks and partial least squares, to optimize the prediction accuracy and process control. By leveraging these models, the study aims to enhance the automation and optimization of process units within chemical process plants, ultimately contributing to the overall efficiency of the chemical process plant.
dc.identifier.apacitationMammen, A. (2025). <i>Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations</i>. (). University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Chemical Engineering. Retrieved from http://hdl.handle.net/11427/41738en_ZA
dc.identifier.chicagocitationMammen, Ashlen. <i>"Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations."</i> ., University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Chemical Engineering, 2025. http://hdl.handle.net/11427/41738en_ZA
dc.identifier.citationMammen, A. 2025. Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations. . University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Chemical Engineering. http://hdl.handle.net/11427/41738en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Mammen, Ashlen AB - The paper presents an in-depth exploration of a debutaniser distillation column, a critical component in a typical separation train. The primary function of this unit is to separate the upstream distillation column product flow into LPG and a heavier stream of catalytic naphtha. The operation of the Debutaniser is crucial for maintaining the total C5 vol% and RVP within specified limits, ensuring optimal operation of downstream units. Given the high costs associated with real-time analysers, the study explores the development of various modelling techniques, including principal component analyses, decision trees, random forests, gradient boosting, neural networks and partial least squares, to optimize the prediction accuracy and process control. By leveraging these models, the study aims to enhance the automation and optimization of process units within chemical process plants, ultimately contributing to the overall efficiency of the chemical process plant. DA - 2025 DB - OpenUCT DP - University of Cape Town KW - Degradation analyses LK - https://open.uct.ac.za PB - University of Cape Town PY - 2025 T1 - Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations TI - Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations UR - http://hdl.handle.net/11427/41738 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/41738
dc.identifier.vancouvercitationMammen A. Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations. []. University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Chemical Engineering, 2025 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/41738en_ZA
dc.language.isoen
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Chemical Engineering
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subjectDegradation analyses
dc.titleDegradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMSc
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