@inproceedings{9174e50b92e04e9dacddc1fe6b500b49,
title = "A Numerical Study for Prediction of Unmanned Aerial Vehicle Aerodynamic Performance Based on Chord Tip and Offset of the Wing",
abstract = "The development of unmanned aerial vehicle (UAV) is multiplying with its use in various fields, which is marked by the emergence of various models that can be adapted based on the functions and needs of the UAV. A UAV with the Cessna 182 type, which can be easily found, is the research object in this paper. Aerodynamic performance is an essential part of the design of a UAV. Therefore, in this study, the geometry of the chord tip (Ct) and the distance of the sweep-back angel (offset) on the wing, which is set as factor parameters, are varied to predict aerodynamic performance as response parameters in the form of a ratio of lift coefficient to maximum drag coefficient (CL/CD max.) and drag coefficient at 0° angle of attack (CD-0). Simulation using XFLR5 to find the value of aerodynamic performance. Artificial neural network (ANN) is used to predict the performance value and find the relationship between the factor parameters at the input layer and the response parameters at the output layer. By using a network arrangement of a maximum of two hidden layers and a maximum of ten neurons in each hidden layer, an MSE of 1.8591 × 10 - 7 is obtained for the maximum CL/CD response and 3.958 × 10 - 7 for the CD-0 response. Dimensional changes in Ct affect the aerodynamic performance of the UAV than dimensional changes of offset.",
keywords = "Aerodynamic performance, Neural network, UAV, Wing geometry",
author = "Firiana Firdaus and Arif Wahjudi and Widodo, {Wawan Aries}",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 5th International Conference on Mechanical Engineering, ICOME 2021 ; Conference date: 25-08-2021 Through 26-08-2021",
year = "2022",
doi = "10.1007/978-981-19-1581-9_5",
language = "English",
isbn = "9789811915802",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "45--51",
editor = "Mohan Kolhe and Aziz Muhammad and {El Kharbachi}, Abdel and Yuwono, {Tri Yogi}",
booktitle = "Recent Advances in Renewable Energy Systems - Select Proceedings of ICOME 2021",
address = "Germany",
}