Model-based multi-objective optimisation of reheating furnace operations using genetic algorithm

Simple item page
dc.contributor.authorHu, Yukun
dc.contributor.authorTan, C. K.
dc.contributor.authorBroughton, Jonathan
dc.contributor.authorRoach, Paul Alun
dc.contributor.authorVarga, Liz
dc.date.accessioned2018-02-14T09:26:54Z
dc.date.available2018-02-14T09:26:54Z
dc.date.issued2018-01-30
dc.description.abstractAn effective optimisation strategy for metal reheating processes is crucial for the economic operation of the furnace while supplying products of a consistent quality. An optimum reheating process may be defined as one which produces heated stock to a desired discharge temperature and temperature uniformity while consuming minimum amount of fuel energy. A strategic framework to solve this multi-objective optimisation problem for a large-scale reheating furnace is presented in this paper. For a given production condition, a model-based multi-objective optimisation strategy using genetic algorithm was adopted to determine an optimal temperature trajectory of the bloom so as to minimise an appropriate cost function. Definition of the cost function has been facilitated by a set of fuzzy rules which is easily adaptable to different trade-offs between the bloom desired discharge temperature, temperature uniformity and specific fuel consumption. A number of scenarios with respect to these trade-offs were evaluated and the results suggested that the developed furnace model was able to provide insight into the dynamic heating behaviour with respect to the multi-objective criteria. Suggest findings that current furnace practice places more emphasis on heated product quality than energy efficiency.en_UK
dc.identifier.citationYukun Hu, C.K. Tan, Jonathan Broughton, Paul Alun Roach, Liz Varga, Model-based multi-objective optimisation of reheating furnace operations using genetic algorithm, Energy Procedia, Volume 142, December 2017, Pages 2143-2151en_UK
dc.identifier.issn1876-6102
dc.identifier.urihttps://doi.org/10.1016/j.egypro.2017.12.619
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/12995
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectzone modelen_UK
dc.subjectreheating furnaceen_UK
dc.subjectmulti-objective optimisationen_UK
dc.subjectgenetic algorithmen_UK
dc.titleModel-based multi-objective optimisation of reheating furnace operations using genetic algorithmen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Model-based_multi-objective_optimisation_of_reheating_furnace_operations-2017.pdf
Size:
551 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SWEE)