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Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations

A. P. Roberts Orcid Logo, Alma Rahat Orcid Logo, D. S. Jarman Orcid Logo, J. E. Fieldsend Orcid Logo, G. R. Tabor Orcid Logo

Optimization and Engineering

Swansea University Author: Alma Rahat Orcid Logo

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DOI (Published version): 10.1007/s11081-024-09907-2

Abstract

The shape of a hydrodynamic particle separator has been optimized using a parallelized and robust formulation of Bayesian optimization, with data from an unsteady Eulerian flow field coupled with Lagrangian particle tracking. The uncertainty due to the mesh, initial conditions, and stochastic disper...

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Published in: Optimization and Engineering
ISSN: 1389-4420 1573-2924
Published: Springer Science and Business Media LLC 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa67078
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spelling v2 67078 2024-07-12 Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations 6206f027aca1e3a5ff6b8cd224248bc2 0000-0002-5023-1371 Alma Rahat Alma Rahat true false 2024-07-12 MACS The shape of a hydrodynamic particle separator has been optimized using a parallelized and robust formulation of Bayesian optimization, with data from an unsteady Eulerian flow field coupled with Lagrangian particle tracking. The uncertainty due to the mesh, initial conditions, and stochastic dispersion in the Eulerian-Lagrangian simulations was minimized and quantified. This was then translated across to the error term in the Gaussian process model and the minimum probability of improvement in infill criterion. An existing parallelization strategy was modified for the infill criterion and customized to prefer exploitation in the decision space. In addition, a new strategy was developed for hidden constraints using Voronoi penalization. In the approximate Pareto Front, an absolute improvement over the base design of 14% in the underflow collection efficiency and 10% in the total collection efficiency was achieved. The corresponding designs were attributed to the effective distribution of residence time between the trays via the removal of a vertical plume. The plume also reduced both efficiencies by creating a flow path in a direction that acted against effective settling. This demonstrates the value of Bayesian optimization in producing non-intuitive designs, which resulted in the filing of a patent. Journal Article Optimization and Engineering 0 Springer Science and Business Media LLC 1389-4420 1573-2924 Industrial hydrodynamic separator; Multi-objective Bayesian shape optimization; Multi-surrogate parallelization; Voronoi failure penalization; Eulerian-Lagrangian one-way coupling; uRANS; k-ω SST 17 8 2024 2024-08-17 10.1007/s11081-024-09907-2 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Another institution paid the OA fee This work was supported by Innovate UK and the EPSRC (partnership number 11477). 2024-08-30T14:08:28.3257052 2024-07-12T06:24:22.2714530 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science A. P. Roberts 0000-0001-7226-5102 1 Alma Rahat 0000-0002-5023-1371 2 D. S. Jarman 0000-0001-6582-5239 3 J. E. Fieldsend 0000-0002-0683-2583 4 G. R. Tabor 0000-0003-3549-228x 5 67078__31191__ffab8abaa2bf4e47b8ea3ed1eaae9aed.pdf 67078.VoR.pdf 2024-08-30T14:07:06.4821535 Output 3792897 application/pdf Version of Record true © TheAuthor(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License. true eng http://creativecommons.org/licenses/by/4.0/
title Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations
spellingShingle Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations
Alma Rahat
title_short Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations
title_full Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations
title_fullStr Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations
title_full_unstemmed Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations
title_sort Multi-objective Bayesian shape optimization of an industrial hydrodynamic separator using unsteady Eulerian-Lagrangian simulations
author_id_str_mv 6206f027aca1e3a5ff6b8cd224248bc2
author_id_fullname_str_mv 6206f027aca1e3a5ff6b8cd224248bc2_***_Alma Rahat
author Alma Rahat
author2 A. P. Roberts
Alma Rahat
D. S. Jarman
J. E. Fieldsend
G. R. Tabor
format Journal article
container_title Optimization and Engineering
container_volume 0
publishDate 2024
institution Swansea University
issn 1389-4420
1573-2924
doi_str_mv 10.1007/s11081-024-09907-2
publisher Springer Science and Business Media LLC
college_str Faculty of Science and Engineering
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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 shape of a hydrodynamic particle separator has been optimized using a parallelized and robust formulation of Bayesian optimization, with data from an unsteady Eulerian flow field coupled with Lagrangian particle tracking. The uncertainty due to the mesh, initial conditions, and stochastic dispersion in the Eulerian-Lagrangian simulations was minimized and quantified. This was then translated across to the error term in the Gaussian process model and the minimum probability of improvement in infill criterion. An existing parallelization strategy was modified for the infill criterion and customized to prefer exploitation in the decision space. In addition, a new strategy was developed for hidden constraints using Voronoi penalization. In the approximate Pareto Front, an absolute improvement over the base design of 14% in the underflow collection efficiency and 10% in the total collection efficiency was achieved. The corresponding designs were attributed to the effective distribution of residence time between the trays via the removal of a vertical plume. The plume also reduced both efficiencies by creating a flow path in a direction that acted against effective settling. This demonstrates the value of Bayesian optimization in producing non-intuitive designs, which resulted in the filing of a patent.
published_date 2024-08-17T14:08:26Z
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score 11.035655

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