Optimization of offset and cant angle winglet on remote control airplane using Taguchi – Particle swarm optimization

Bambang Junipitoyo; Setyo Hariyadi Suranto Putro; Fungky Dyan Pertiwi; Tri Vicca Kusumadewi; Apri Rahmadi; Syifa’ Zain Salsabila

doi:10.15282/jmes.17.4.2023.10.0774

Authors

Bambang Junipitoyo Aircraft Maintenance Engineering, Politeknik Penerbangan Surabaya, 60236 Surabaya, Indonesia. Phone: +62318410871; Fax: +62318490005
Setyo Hariyadi Suranto Putro Aircraft Maintenance Engineering, Politeknik Penerbangan Surabaya, 60236 Surabaya, Indonesia. Phone: +62318410871; Fax: +62318490005
Fungky Dyan Pertiwi Department of Mechanical Engineering, Universitas Muhammadiyah Magelang, 56172 Magelang, Indonesia
Tri Vicca Kusumadewi Mechanical Engineering Department, Faculty of Industrial Technology and Systems Engineering, Institut Teknologi Sepuluh Nopember Surabaya, 60111 Surabaya, Indonesia
Apri Rahmadi Mechanical Engineering Department, Universitas Muhammadiyah Pontianak, 78123 Pontianak, Indonesia
Syifa’ Zain Salsabila Mechanical Engineering Department, Faculty of Industrial Technology and Systems Engineering, Institut Teknologi Sepuluh Nopember Surabaya, 60111 Surabaya, Indonesia

DOI:

https://doi.org/10.15282/jmes.17.4.2023.10.0774

Keywords:

Cant angle, Offset winglet, Remote Control plane, Taguchi, PSO

Abstract

Incorporating winglets into aircraft has been empirically proven to notably improve aerodynamic efficiency by reducing vortex-induced effects at the wingtips. However, conducting comprehensive investigations necessitates the exploration of numerous winglet factors and value variations. This study pertains to remote control aircraft winglets, focusing on manipulating cant angle and offset factors across four distinct values. Two primary objectives guide this research: firstly, the maximization Cl/Cd_max, and secondly, the minimization Cd₀. The Taguchi experimental design is employed to randomize the variations in offset and cant angle values systematically. These variations are then used to generate pivotal regression values in the subsequent particle swarm optimization (PSO). The variance analysis evaluates the impact of winglet-related variables on each research goal. Additionally, the winglet design incorporates the open-source XFLR5 software, an accessible resource for aeromodelling clubs in Indonesia. XFLR5 enables the investigation of aerodynamic parameters across various angles of incidence and plays a crucial role in this research. The results of this study reveal that the Taguchi method yields two distinct combinations of factor values, aligning with the two primary research objectives. Conversely, particle swarm optimization generates a combination that effectively addresses both objectives. A comparative analysis of the winglet factor combinations from Taguchi and PSO underscores the greater efficiency of the PSO method in optimizing winglet variations for two distinct objectives.

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