Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube
dc.contributor.author | Daniels, SJ | |
dc.contributor.author | Rahat, AAM | |
dc.contributor.author | Tabor, GR | |
dc.contributor.author | Fieldsend, JE | |
dc.contributor.author | Everson, RM | |
dc.date.accessioned | 2021-03-10T08:20:18Z | |
dc.date.issued | 2021-03-06 | |
dc.description.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. | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | Published online 6 March 2021 | en_GB |
dc.identifier.doi | 10.1007/s11081-021-09602-6 | |
dc.identifier.grantnumber | EP/M017915/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/125079 | |
dc.language.iso | en | en_GB |
dc.publisher | Springer | en_GB |
dc.rights | © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ | en_GB |
dc.subject | Hölleforsen–Kaplan draft tube | en_GB |
dc.subject | Bayesian optimisation | en_GB |
dc.subject | Multi-objective optimisation | en_GB |
dc.subject | Shape optimisation | en_GB |
dc.subject | Sub-division curves | en_GB |
dc.title | Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2021-03-10T08:20:18Z | |
dc.identifier.issn | 1389-4420 | |
dc.description | This is the final version. Available on open access from Springer via the DOI in this record | en_GB |
dc.description | Data availability: The research data supporting this publication are provided within this paper | en_GB |
dc.identifier.journal | Optimization and Engineering | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2021-02-08 | |
exeter.funder | ::Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2021-02-08 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2021-03-09T20:52:45Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2021-03-10T08:20:33Z | |
refterms.panel | B | en_GB |
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Except where otherwise noted, this item's licence is described as © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/