Optimization of a Gorlov helical turbine for hydrokinetic application using the response surface methodology and experimental test

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 (CP): the numb...

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Autores:
Pineda Ortiz, Juan Camilo
Rubio Clemente, Ainhoa
Chica Arrieta, Edwin Lenin
Tipo de recurso:
Article of investigation
Fecha de publicación:
2024
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/46094
Acceso en línea:
https://hdl.handle.net/10495/46094
Palabra clave:
Computational fluid dynamics
Dinámica de fluidos computacional
Process Optimization
Optimización de Procesos
Turbinas hidráulicas
Hydraulic turbines
Gorlov helical turbine
http://id.loc.gov/authorities/subjects/sh2007008173
ODS 7: Energía asequible y no contaminante. Garantizar el acceso a una energía asequible, fiable, sostenible y moderna para todos
ODS 9: Industria, innovación e infraestructura. Construir infraestructuras resilientes, promover la industrialización inclusiva y sostenible y fomentar la innovación
ODS 13: Acción por el Clima. Adoptar medidas urgentes para combatir el cambio climático y sus efectos
Rights
openAccess
License
http://creativecommons.org/licenses/by/4.0/
Description
Summary: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 (CP): the number of blades (N), helix angle (γ), and aspect ratio (AR). Central composite design (CCD) was used for the design of experiments (DOE). For the CFD simulations, a threedimensional computational domain was established in the Ansys Fluent software, version 2021R1 utilizing the k-ω SST turbulence model and the sliding mesh method to perform unsteady flow simulations. The objective function was to achieve the maximum CP, which was obtained using a high-correlation quadratic mathematical model. Under the optimum conditions, where N, γ, and AR were 5, 78°, and 0.6, respectively, a CP value of 0.3072 was achieved. The optimal turbine geometry was validated through experimental testing, and the CP 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.