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Multi-objective optimization of batch distillation methods

TÉMAKIÍRÁS

Intézmény: Budapesti Műszaki és Gazdaságtudományi Egyetem
gépészeti tudományok
Pattantyús-Ábrahám Géza Gépészeti Tudományok Doktori Iskola

témavezető: Hégely László
helyszín (magyar oldal): Department of Building Service and Process Engineering
helyszín rövidítés: EPGET


A kutatási téma leírása:

a.) Antecedents:
Publications in international journals and conferences, project works, BSc and MSc theses and the research projects No. K-106268 (2013-2016) and K-120083 (2016-2019) funded by the Hungarian Scientific Research Funds (OTKA).
b.) Aim of the research:
The aim of the research is to study and optimize conventional batch distillation and batch extractive processes both from an economic and from an environmental point of view. This can be realized by applying multi-objective optimization where one of the objective func-tions is the profit of the production, while the other(s) represent environmental indicators (CO2 emission, waste production, ecoindicators, etc). However, multi-objective optimization problems cannot be solved by the built-in optimizers of professional flow-sheet simulators. Thus, there is a need for using external optimization modules that can be coupled to the flow-sheet simulator. The work is limited even in the field of mono-objective optimization of batch distillation using rigorous models (i.e. not simplified ones). It is especially so for batch extractive distillation. Multi-objective optimization of batch distillation was only considered by a handful works. However, they considered a single environmental objective function and the number of optimization variables was also limited.
The aim is to develop a method for the multi-objective optimization of batch distillation. Such a method would make it possible to take environmental factors into account in the design and operation of batch distillation technology. The results of optimization can be validated by laboratory experiments.
c.) Tasks, main items, necessary time:
• Study of the previously collected literature (4 months)
• Review of new literature including looking for potential objective function (5 months)
• Getting acquainted with the available programs and codes (3 months)
• Algorithm development and calculations for conventional batch distillation (14 months)
• Calculations for batch extractive distillation (6 months)
• Extension of the method for batch heteroazeotropic distillation (5 months)
• Laboratory experiments (5 months)
• Writing of the thesis (6 months)
d.) Necessary equipment:
Professional and in-house software (partially available, partially to be developed or im-proved).
Laboratory distillation column (available).
e.) Expected scientific results:
• Development of optimization methods for the multi-objective optimization of con-ventional batch distillation with emphasis on environmental effects.
• Extension of the method to batch extractive and heteroazeotropic distillation.
f.) Literature:
L. Hegely, P. Lang: Optimization of a batch extractive distillation process with recycling off-cuts, Journal of Cleaner Production, 2016, 136, 99-110.
L. Hegely, P. Lang: Optimization of Entrainer Feeding in Batch Extractive Distillation, Computer-Aided Chemical Engineering, 2014, 33, 1177-1182.
L Hegely, V Gerbaud, P Lang: General model for studying the feasibility of heterogeneous extractive batch distillation, Industrial & Engineering Chemistry Research, 2014, 53 (45), 17782-17793.
L Hegely, P Lang, G Kovacs: A New Batch Extractive Distillation Operational Policy for Methanol Recovery, Chemical Engineering Transactions, 2013, 35, 949-954.
L Hegely, P Lang, V Gerbaud: Off-cut Recycle for Batch and Batch Extractive Distillation Separation of a Multicomponent Azeotropic Mixture, Chemical Engineering Transactions, 2013, 35, 967-972.

előírt nyelvtudás: angol
felvehető hallgatók száma: 1

Jelentkezési határidő: 2021-03-23

 
Minden jog fenntartva © 2007, Országos Doktori Tanács - a doktori adatbázis nyilvántartási száma az adatvédelmi biztosnál: 02003/0001. Program verzió: 2.2358 ( 2017. X. 31. )