Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests

The work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine’s power coefficient (C<sub>P...

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Main Authors: Juan Camilo Pineda, Ainhoa Rubio-Clemente, Edwin Chica
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Energies
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Online Access:https://www.mdpi.com/1996-1073/17/22/5747
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author Juan Camilo Pineda
Ainhoa Rubio-Clemente
Edwin Chica
author_facet Juan Camilo Pineda
Ainhoa Rubio-Clemente
Edwin Chica
author_sort Juan Camilo Pineda
collection DOAJ
description The work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine’s power coefficient (C<sub>P</sub>): the number of blades (N), helix angle (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>γ</mi></semantics></math></inline-formula>), and aspect ratio (AR). Central composite design (CCD) was used for the design of experiments (DOE). For the CFD simulations, a three-dimensional computational domain was established in the Ansys Fluent software, version 2021R1 utilizing the k-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ω</mi></semantics></math></inline-formula> SST turbulence model and the sliding mesh method to perform unsteady flow simulations. The objective function was to achieve the maximum C<sub>P</sub>, which was obtained using a high-correlation quadratic mathematical model. Under the optimum conditions, where N, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>γ</mi></semantics></math></inline-formula>, and AR were 5, 78°, and 0.6, respectively, a C<sub>P</sub> value of 0.3072 was achieved. The optimal turbine geometry was validated through experimental testing, and the C<sub>P</sub> curve versus tip speed ratio (TSR) was determined and compared with the numerical results, which showed a strong correlation between the two sets of data.
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series Energies
spelling doaj-art-bf1f5035151b4a2d9ebc2c9a7e9a65c12024-11-26T18:02:36ZengMDPI AGEnergies1996-10732024-11-011722574710.3390/en17225747Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental TestsJuan Camilo Pineda0Ainhoa Rubio-Clemente1Edwin Chica2Grupo de Energía Alternativa, Facultad de Ingeniería, Universidad de Antioquia, Calle 70 No. 52-21, Medellín 050010, ColombiaGrupo de Energía Alternativa, Facultad de Ingeniería, Universidad de Antioquia, Calle 70 No. 52-21, Medellín 050010, ColombiaGrupo de Energía Alternativa, Facultad de Ingeniería, Universidad de Antioquia, Calle 70 No. 52-21, Medellín 050010, ColombiaThe work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine’s power coefficient (C<sub>P</sub>): the number of blades (N), helix angle (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>γ</mi></semantics></math></inline-formula>), and aspect ratio (AR). Central composite design (CCD) was used for the design of experiments (DOE). For the CFD simulations, a three-dimensional computational domain was established in the Ansys Fluent software, version 2021R1 utilizing the k-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ω</mi></semantics></math></inline-formula> SST turbulence model and the sliding mesh method to perform unsteady flow simulations. The objective function was to achieve the maximum C<sub>P</sub>, which was obtained using a high-correlation quadratic mathematical model. Under the optimum conditions, where N, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>γ</mi></semantics></math></inline-formula>, and AR were 5, 78°, and 0.6, respectively, a C<sub>P</sub> value of 0.3072 was achieved. The optimal turbine geometry was validated through experimental testing, and the C<sub>P</sub> curve versus tip speed ratio (TSR) was determined and compared with the numerical results, which showed a strong correlation between the two sets of data.https://www.mdpi.com/1996-1073/17/22/5747computational fluid dynamicsresponse surface methodologyoptimizationGorlov helical turbinepower coefficient
spellingShingle Juan Camilo Pineda
Ainhoa Rubio-Clemente
Edwin Chica
Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests
Energies
computational fluid dynamics
response surface methodology
optimization
Gorlov helical turbine
power coefficient
title Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests
title_full Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests
title_fullStr Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests
title_full_unstemmed Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests
title_short Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests
title_sort optimization of a gorlov helical turbine for hydrokinetic application using the response surface methodology and experimental tests
topic computational fluid dynamics
response surface methodology
optimization
Gorlov helical turbine
power coefficient
url https://www.mdpi.com/1996-1073/17/22/5747
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AT ainhoarubioclemente optimizationofagorlovhelicalturbineforhydrokineticapplicationusingtheresponsesurfacemethodologyandexperimentaltests
AT edwinchica optimizationofagorlovhelicalturbineforhydrokineticapplicationusingtheresponsesurfacemethodologyandexperimentaltests