No Cover Image

Journal article 579 views 66 downloads

Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube

S. J. Daniels, Alma Rahat Orcid Logo, G. R. Tabor, J. E. Fieldsend, R. M. Everson

Optimization and Engineering, Volume: 23, Pages: 689 - 716

Swansea University Author: Alma Rahat Orcid Logo

  • 56256.pdf

    PDF | Version of Record

    © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License

    Download (2.87MB)

Check full text

DOI (Published version): 10.1007/s11081-021-09602-6

Abstract

The draft tube of a hydraulic turbine plays an important role for the efficiency and power characteristics of the overall system. The shape of the draft tube affects its performance, resulting in an increasing need for data-driven optimisation for its design. In this paper, shape optimisation of an...

Full description

Published in: Optimization and Engineering
ISSN: 1389-4420 1573-2924
Published: Springer Science and Business Media LLC 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa56256
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2021-02-15T10:05:34Z
last_indexed 2022-05-13T03:26:36Z
id cronfa56256
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-05-12T17:44:48.7059536</datestamp><bib-version>v2</bib-version><id>56256</id><entry>2021-02-15</entry><title>Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube</title><swanseaauthors><author><sid>6206f027aca1e3a5ff6b8cd224248bc2</sid><ORCID>0000-0002-5023-1371</ORCID><firstname>Alma</firstname><surname>Rahat</surname><name>Alma Rahat</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-02-15</date><deptcode>SCS</deptcode><abstract>The draft tube of a hydraulic turbine plays an important role for the efficiency and power characteristics of the overall system. The shape of the draft tube affects its performance, resulting in an increasing need for data-driven optimisation for its design. In this paper, shape optimisation of an elbow-type draft tube is undertaken, combining Computational Fluid Dynamics and a multi-objective Bayesian methodology. The chosen design objectives were to maximise pressure recovery, and minimise wall-frictional losses along the geometry. The design variables were chosen to explore potential new designs, using a series of subdivision-curves and splines on the inflow cone, outer-heel, and diffuser. The optimisation run was performed under part-load for the Kaplan turbine. The design with the lowest energy-loss identified on the Pareto-front was found to have a straight tapered diffuser, chamfered heel, and a convex inflow cone. Analysis of the performance quantities showed the typically used energy-loss factor and pressure recovery were highly correlated in cases of constant outflow cross-sections, and therefore unsuitable for use of multi-objective optimisation. Finally, a number of designs were tested over a range of discharges. From this it was found that reducing the heel size increased the efficiency over a wider operating range.</abstract><type>Journal Article</type><journal>Optimization and Engineering</journal><volume>23</volume><journalNumber/><paginationStart>689</paginationStart><paginationEnd>716</paginationEnd><publisher>Springer Science and Business Media LLC</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1389-4420</issnPrint><issnElectronic>1573-2924</issnElectronic><keywords>H&#xF6;lleforsen&#x2013;Kaplan draft tube; Bayesian optimisation; Multi-objective optimisation; Shape optimisation; Sub-division curves</keywords><publishedDay>6</publishedDay><publishedMonth>3</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-03-06</publishedDate><doi>10.1007/s11081-021-09602-6</doi><url/><notes/><college>COLLEGE NANME</college><department>Computer Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SCS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This work was supported by the UK Engineering and Physical Sciences Research Council [grant number EP/M017915/1].</funders><lastEdited>2022-05-12T17:44:48.7059536</lastEdited><Created>2021-02-15T10:01:33.2726742</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>S. J.</firstname><surname>Daniels</surname><order>1</order></author><author><firstname>Alma</firstname><surname>Rahat</surname><orcid>0000-0002-5023-1371</orcid><order>2</order></author><author><firstname>G. R.</firstname><surname>Tabor</surname><order>3</order></author><author><firstname>J. E.</firstname><surname>Fieldsend</surname><order>4</order></author><author><firstname>R. M.</firstname><surname>Everson</surname><order>5</order></author></authors><documents><document><filename>56256__20014__8bfc55d2b51849afa49e5ac88e297042.pdf</filename><originalFilename>56256.pdf</originalFilename><uploaded>2021-05-26T16:52:25.1707025</uploaded><type>Output</type><contentLength>3004347</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2022-05-12T17:44:48.7059536 v2 56256 2021-02-15 Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube 6206f027aca1e3a5ff6b8cd224248bc2 0000-0002-5023-1371 Alma Rahat Alma Rahat true false 2021-02-15 SCS The draft tube of a hydraulic turbine plays an important role for the efficiency and power characteristics of the overall system. The shape of the draft tube affects its performance, resulting in an increasing need for data-driven optimisation for its design. In this paper, shape optimisation of an elbow-type draft tube is undertaken, combining Computational Fluid Dynamics and a multi-objective Bayesian methodology. The chosen design objectives were to maximise pressure recovery, and minimise wall-frictional losses along the geometry. The design variables were chosen to explore potential new designs, using a series of subdivision-curves and splines on the inflow cone, outer-heel, and diffuser. The optimisation run was performed under part-load for the Kaplan turbine. The design with the lowest energy-loss identified on the Pareto-front was found to have a straight tapered diffuser, chamfered heel, and a convex inflow cone. Analysis of the performance quantities showed the typically used energy-loss factor and pressure recovery were highly correlated in cases of constant outflow cross-sections, and therefore unsuitable for use of multi-objective optimisation. Finally, a number of designs were tested over a range of discharges. From this it was found that reducing the heel size increased the efficiency over a wider operating range. Journal Article Optimization and Engineering 23 689 716 Springer Science and Business Media LLC 1389-4420 1573-2924 Hölleforsen–Kaplan draft tube; Bayesian optimisation; Multi-objective optimisation; Shape optimisation; Sub-division curves 6 3 2021 2021-03-06 10.1007/s11081-021-09602-6 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University This work was supported by the UK Engineering and Physical Sciences Research Council [grant number EP/M017915/1]. 2022-05-12T17:44:48.7059536 2021-02-15T10:01:33.2726742 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science S. J. Daniels 1 Alma Rahat 0000-0002-5023-1371 2 G. R. Tabor 3 J. E. Fieldsend 4 R. M. Everson 5 56256__20014__8bfc55d2b51849afa49e5ac88e297042.pdf 56256.pdf 2021-05-26T16:52:25.1707025 Output 3004347 application/pdf Version of Record true © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
spellingShingle Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
Alma Rahat
title_short Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
title_full Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
title_fullStr Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
title_full_unstemmed Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
title_sort Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
author_id_str_mv 6206f027aca1e3a5ff6b8cd224248bc2
author_id_fullname_str_mv 6206f027aca1e3a5ff6b8cd224248bc2_***_Alma Rahat
author Alma Rahat
author2 S. J. Daniels
Alma Rahat
G. R. Tabor
J. E. Fieldsend
R. M. Everson
format Journal article
container_title Optimization and Engineering
container_volume 23
container_start_page 689
publishDate 2021
institution Swansea University
issn 1389-4420
1573-2924
doi_str_mv 10.1007/s11081-021-09602-6
publisher Springer Science and Business Media LLC
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description The draft tube of a hydraulic turbine plays an important role for the efficiency and power characteristics of the overall system. The shape of the draft tube affects its performance, resulting in an increasing need for data-driven optimisation for its design. In this paper, shape optimisation of an elbow-type draft tube is undertaken, combining Computational Fluid Dynamics and a multi-objective Bayesian methodology. The chosen design objectives were to maximise pressure recovery, and minimise wall-frictional losses along the geometry. The design variables were chosen to explore potential new designs, using a series of subdivision-curves and splines on the inflow cone, outer-heel, and diffuser. The optimisation run was performed under part-load for the Kaplan turbine. The design with the lowest energy-loss identified on the Pareto-front was found to have a straight tapered diffuser, chamfered heel, and a convex inflow cone. Analysis of the performance quantities showed the typically used energy-loss factor and pressure recovery were highly correlated in cases of constant outflow cross-sections, and therefore unsuitable for use of multi-objective optimisation. Finally, a number of designs were tested over a range of discharges. From this it was found that reducing the heel size increased the efficiency over a wider operating range.
published_date 2021-03-06T04:11:04Z
_version_ 1763753763663773696
score 11.012678

Similar Items