Structure Estimation of Vertical Axis Wind Turbine Using Artificial Neural Network
dc.authorid | Azginoglu, Nuh/0000-0002-4074-7366 | |
dc.authorscopusid | 56728619900 | |
dc.authorscopusid | 55364407100 | |
dc.authorscopusid | 6603264417 | |
dc.authorwosid | Teksin, Suleyman/Afk-3449-2022 | |
dc.authorwosid | Azgınoğlu, Nuh/G-7335-2019 | |
dc.authorwosid | Akansu, Selahaddin/Aal-4052-2020 | |
dc.contributor.author | Teksin, S. | |
dc.contributor.author | Azginoglu, N. | |
dc.contributor.author | Akansu, S. O. | |
dc.date.accessioned | 2025-05-10T17:13:02Z | |
dc.date.available | 2025-05-10T17:13:02Z | |
dc.date.issued | 2022 | |
dc.department | T.C. Van Yüzüncü Yıl Üniversitesi | en_US |
dc.department-temp | [Teksin, S.; Akansu, S. O.] Erciyes Univ, Dept Mech Engn, Fac Engn, TR-38039 Kayseri, Turkey; [Azginoglu, N.] Kayseri Univ, Engn Architecture & Design Fac, Dept Comp Engn, TR-38280 Kayseri, Turkey; [Teksin, S.] Yuzuncu Yil Univ, Dept Mech Engn, Fac Engn, TR-65080 Van, Turkey | en_US |
dc.description | Azginoglu, Nuh/0000-0002-4074-7366 | en_US |
dc.description.abstract | Vertical axis wind turbines (VAWTS) can be a suitable choice for usage in urban areas. Wind conditions and structural parameters are critical to power production. In this study, some variations of a darrieus vawt was attempted via wind tunnel testing. A modified naca4412 blade profile was selected for this investigation. The influence of aspect ratios, angle of attack, chord length, etc. were investigated experimentally. After taken more than 800 data artificial neural network (ANN) was applied to estimate the other range of scales using different algorithms that are utilized the aforementioned experimental parameters. This study focuses on the design criteria and application of VAWTS inbuilt real environments without testing. The results have been promising and will provide ease of design for similar designs. Moreover, this work will contribute to environmental cleanup and a more livable world by increasing renewable energy resources. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. | en_US |
dc.description.sponsorship | Scientific And Technological Research Council Of Turkey, Tubtak [315M478]; doctorate foundation of Erciyes University, Scientific Research Center [9685] | en_US |
dc.description.sponsorship | This work was supported in part by the Scientific And Technological Research Council Of Turkey, Tubtak under grant no. 315M478 and the doctorate foundation of Erciyes University, Scientific Research Center, Project No: 9685. | en_US |
dc.description.woscitationindex | Science Citation Index Expanded | |
dc.identifier.doi | 10.1016/j.aej.2021.05.002 | |
dc.identifier.endpage | 314 | en_US |
dc.identifier.issn | 1110-0168 | |
dc.identifier.issn | 2090-2670 | |
dc.identifier.issue | 1 | en_US |
dc.identifier.scopus | 2-s2.0-85110088074 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.startpage | 305 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.aej.2021.05.002 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14720/8072 | |
dc.identifier.volume | 61 | en_US |
dc.identifier.wos | WOS:000709484000003 | |
dc.identifier.wosquality | Q1 | |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Ann | en_US |
dc.subject | Estimation | en_US |
dc.subject | Sustainable Energy | en_US |
dc.subject | Vawt | en_US |
dc.subject | Wind | en_US |
dc.subject | Environment | en_US |
dc.title | Structure Estimation of Vertical Axis Wind Turbine Using Artificial Neural Network | en_US |
dc.type | Article | en_US |