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Title: Optimal configuration, design and operation of batch distillation processes
Author: Low, Kian Huat
Awarding Body: University of London
Current Institution: University College London (University of London)
Date of Award: 2003
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The overall objective of this thesis is to study the optimal configuration. design and operating policy of batch distillation processes in different separation scenarios. In so doing, this work also aims to provide conceptual insights and compare the performance of the traditional regular column against unconventional columns. In the first part of the thesis, the optimal operation of extractive batch distillation is investigated. A rigorous dynamic optimisation approach based on a detailed model is employed. In addition to the regular column, the optimal operation of the process in the unconventional middle vessel column is examined. The liquid and vapour stream configurations at the middle section of the column is explored for the first time, resulting in improved process performance. The performance of both columns are compared and the results show how their relative performances are affected by different feed compositions. The second part of the thesis is concerned with the simultaneous design and operation of batch distillation processes. The thesis proposes a stochastic optimisation methodology based on genetic algorithm and penalty function. Using the proposed methodology, the simultaneous optimal designs and operations of the regular column for different design scenarios are investigated using rigorous models. Furthermore, the optimal design of the unconventional multivessel column for multicomponent separation is studied for the first time. The effect of different factors such as objective function, feed composition, relative volatility, product specification and number of components on the optimal design of the multivessel system is investigated. A comparison of the performance of the multivessel system with the regular column is also presented. In the final part of the thesis, the feasibility of the genetic algorithm-penalty function approach in tackling simultaneous configuration selection, column sizing and operation is explored. In the case of binary mixture separation, the regular column was found to be more profitable for feeds with a high fraction of the light component whilst the inverted column is optimal for heavier feeds. There exists a flip point, the location of which is case study specific. For the multicomponent separation case study, the multivessel system is found to be superior to both the regular and inverted configurations
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available