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Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping

Axial air flow fans are widely used for air movement. In an increasingly international and competitive market, smaller fan companies find themselves in need of rapid preliminary design. This need is addressed in this study through the development of a first-revision, Computational Fluid Dynamics (CF...

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Main Author: Van Rooyen, Jacobus A
Other Authors: Malan, Arnaud G
Format: Thesis
Language:English
Published: Department of Mechanical Engineering 2017
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access_status_str Open Access
author Van Rooyen, Jacobus A
author2 Malan, Arnaud G
author_browse Malan, Arnaud G
Van Rooyen, Jacobus A
author_facet Malan, Arnaud G
Van Rooyen, Jacobus A
author_sort Van Rooyen, Jacobus A
collection Thesis
description Axial air flow fans are widely used for air movement. In an increasingly international and competitive market, smaller fan companies find themselves in need of rapid preliminary design. This need is addressed in this study through the development of a first-revision, Computational Fluid Dynamics (CFD) based, optimisation tool which allows for rapid prototyping of a ducted axial fan. The result is an ElementalTM-based multi-disciplinary software tool, comprising 2D CFD, mesh movement, and constrained geometric optimisation. The analytical equation employed to represent the aerofoil significantly reduces the cost of the optimisation. A pseudo-3D fan model is generated by superimposing 2D CFD results. This is done without the general assumption of the free-vortex method, which is not a necessity for fan design and other velocity distributions may be used. For this purpose, an enhanced finite volume discretisation method was developed. A penalty function minimisation, by means of an unconstrained optimisation algorithm, is implemented thereafter. The primary objective is to deliver a specific fan static pressure rise, while optimising for fan static efficiency by means of altering the rotor blade geometry. The spherical quadratic steepest descent method is employed, which does not rely on any explicit line searches, as required by traditional steepest descent techniques. The rapid prototyping tool is finally applied to an under-performing base fan (Fan-D) which cannot meet a specified duty point. The resulting optimised fan (Fan-Optim) is manufactured and experimentally tested, in accordance with the ISO 5801 standard. The pseudo-3D model is proven to predict fan performance accurately at the target duty point, while capturing fan behaviour over a range of volumetric flow rates. The former is to within 13% of the fan static pressure rise and within 2.3% of fan static efficiency. While Fan-Optim meets the desired duty point within 2%, it offers a considerable improvement in fan static efficiency over Fan-D. Furthermore, an approximate 38% reduction in blade material is achieved as a secondary effect.
format Thesis
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institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:33:15.376Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2017
publishDateRange 2017
publishDateSort 2017
publisher Department of Mechanical Engineering
publisherStr Department of Mechanical Engineering
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source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/24931 Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping Van Rooyen, Jacobus A Malan, Arnaud G Mechanical Engineering Axial air flow fans are widely used for air movement. In an increasingly international and competitive market, smaller fan companies find themselves in need of rapid preliminary design. This need is addressed in this study through the development of a first-revision, Computational Fluid Dynamics (CFD) based, optimisation tool which allows for rapid prototyping of a ducted axial fan. The result is an ElementalTM-based multi-disciplinary software tool, comprising 2D CFD, mesh movement, and constrained geometric optimisation. The analytical equation employed to represent the aerofoil significantly reduces the cost of the optimisation. A pseudo-3D fan model is generated by superimposing 2D CFD results. This is done without the general assumption of the free-vortex method, which is not a necessity for fan design and other velocity distributions may be used. For this purpose, an enhanced finite volume discretisation method was developed. A penalty function minimisation, by means of an unconstrained optimisation algorithm, is implemented thereafter. The primary objective is to deliver a specific fan static pressure rise, while optimising for fan static efficiency by means of altering the rotor blade geometry. The spherical quadratic steepest descent method is employed, which does not rely on any explicit line searches, as required by traditional steepest descent techniques. The rapid prototyping tool is finally applied to an under-performing base fan (Fan-D) which cannot meet a specified duty point. The resulting optimised fan (Fan-Optim) is manufactured and experimentally tested, in accordance with the ISO 5801 standard. The pseudo-3D model is proven to predict fan performance accurately at the target duty point, while capturing fan behaviour over a range of volumetric flow rates. The former is to within 13% of the fan static pressure rise and within 2.3% of fan static efficiency. While Fan-Optim meets the desired duty point within 2%, it offers a considerable improvement in fan static efficiency over Fan-D. Furthermore, an approximate 38% reduction in blade material is achieved as a secondary effect. 2017-08-23T12:52:02Z 2017-08-23T12:52:02Z 2017 Doctoral Thesis Doctoral PhD http://hdl.handle.net/11427/24931 eng application/pdf Department of Mechanical Engineering Faculty of Engineering and the Built Environment University of Cape Town
spellingShingle Mechanical Engineering
Van Rooyen, Jacobus A
Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping
thesis_degree_str Doctoral
title Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping
title_full Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping
title_fullStr Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping
title_full_unstemmed Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping
title_short Computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping
title_sort computational fluid dynamic based optimisation of an industrial axial fan for rapid prototyping
topic Mechanical Engineering
url http://hdl.handle.net/11427/24931
work_keys_str_mv AT vanrooyenjacobusa computationalfluiddynamicbasedoptimisationofanindustrialaxialfanforrapidprototyping