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Journals / International Journal of Automotive Engineering and Technologies / 2024 / Cilt: 13 Sayı: 4

Modeling the aerodynamic performance of unmanned aerial vehicle (UAV) propellers with multifidelity method

Hakan Ünsal(GAZİ ÜNİVERSİTESİ)0000-0002-9896-9877
Mesut Düzgün(GAZİ ÜNİVERSİTESİ)0000-0003-0582-4183
Pages
153–169
Publication Date
2024-12-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The obtained data constitutes a valuable resource for optimizing the design and performance of UAVs.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, an artificial neural network (ANN) based method is discussed to determine the aerodynamic performance of propellers used for Unmanned Aerial Vehicles (UAVs).
📊
Key Findings & Data:This study allows for more precise analysis of the aerodynamic performance of UAV propellers and optimization of their design.
💡
Conclusion & Impact:The obtained data constitutes a valuable resource for optimizing the design and performance of UAVs.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Unmanned Aerial Vehicles (UAV) · Propeller · Artificial Neural Network

Abstract

In this study, an artificial neural network (ANN) based method is discussed to determine the aerodynamic performance of propellers used for Unmanned Aerial Vehicles (UAVs). Here, wind tunnel test data was used to obtain data for propellers without test data. First, wind tunnel test data was converted to a specific format using Python and modeling was done using ANN. With this modeling process, it was seen how close the model obtained with artificial neural networks produced results to the data obtained from wind tunnel tests. This study allows for more precise analysis of the aerodynamic performance of UAV propellers and optimization of their design. This approach provided a very accurate modeling of the aerodynamic performance of UAV propellers and took an important step towards determining the performance of propellers without wind tunnel test data. The obtained data constitutes a valuable resource for optimizing the design and performance of UAVs.

Özet

In this study, an artificial neural network (ANN) based method is discussed to determine the aerodynamic performance of propellers used for Unmanned Aerial Vehicles (UAVs). Here, wind tunnel test data was used to obtain data for propellers without test data. First, wind tunnel test data was converted to a specific format using Python and modeling was done using ANN. With this modeling process, it was seen how close the model obtained with artificial neural networks produced results to the data obtained from wind tunnel tests. This study allows for more precise analysis of the aerodynamic performance of UAV propellers and optimization of their design. This approach provided a very accurate modeling of the aerodynamic performance of UAV propellers and took an important step towards determining the performance of propellers without wind tunnel test data. The obtained data constitutes a valuable resource for optimizing the design and performance of UAVs.

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Cite This Article

Ünsal, H., Düzgün, M. (2024). Modeling the aerodynamic performance of unmanned aerial vehicle (UAV) propellers with multifidelity method. International Journal of Automotive Engineering and Technologies, Cilt: 13 Sayı: 4, 153–169. https://doi.org/10.18245/ijaet.1485834

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References (11)

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