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Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations
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...
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| Format: | Thesis |
| Language: | English English |
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Department of Chemical Engineering
2025
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| _version_ | 1867613244704686080 |
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| access_status_str | Open Access |
| author | Mammen, Ashlen |
| author2 | Moller, Klaus |
| author_browse | Mammen, Ashlen Moller, Klaus |
| author_facet | Moller, Klaus Mammen, Ashlen |
| author_sort | Mammen, Ashlen |
| collection | Thesis |
| description | 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. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/41738 |
| institution | University of Cape Town (South Africa) |
| language | English eng |
| last_indexed | 2026-06-10T12:33:04.194Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Department of Chemical Engineering |
| publisherStr | Department of Chemical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/41738 Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations Mammen, Ashlen Moller, Klaus Degradation analyses 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. 2025-09-10T07:38:31Z 2025-09-10T07:38:31Z 2025 2025-09-10T07:23:47Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/41738 en eng application/pdf Department of Chemical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Degradation analyses Mammen, Ashlen Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations |
| thesis_degree_str | Master's |
| title | Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations |
| title_full | Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations |
| title_fullStr | Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations |
| title_full_unstemmed | Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations |
| title_short | Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations |
| title_sort | degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic empirical equations |
| topic | Degradation analyses |
| url | http://hdl.handle.net/11427/41738 |
| work_keys_str_mv | AT mammenashlen degradationanalysesofempiricalinferentialpredictorsforthedevelopmentofimproveddynamicmechanisticempiricalequations |