Department of Chemical Engineering
Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations
Abstract
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.
Degree
thesis:*- Grantor dc:publisher.institution
- Department of Chemical Engineering
- Year dc:date.issued
- 2025
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Mammen, Ashlen
- Advisor dc:contributor.advisor
-
- Moller, Klaus
Subjects
dc:subject × 1Rights
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/11427/41738
- OAI identifier oai:identifier
- oai:open.uct.ac.za:11427/41738