Validation of a Small UAV Dynamic Model Using CFD and Flight Test Data.

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Title: Validation of a Small UAV Dynamic Model Using CFD and Flight Test Data.
Authors: Jayanti, Eries Bagita1 erie002@brin.go.id, Atmasari, Novita1, Septiyana, Angga1,2, Rizaldi, Ardian1,3, Wardana, Try Kusuma1, Ramadian, Aries Asrianto1, Mardikasari, Hidayati1, Hartono, Hartono1
Source: Periodica Polytechnica: Transportation Engineering. 2026, Vol. 54 Issue 1, p88-104. 17p.
Subjects: Computational fluid dynamics, Flight testing, Single-degree-of-freedom systems, Dynamic models, Model validation, Aerodynamics
Abstract: Fixed-wing Unmanned Aerial Vehicles (UAV) are increasingly utilized in various missions requiring stable and responsive performance. Accurate dynamic models are essential to ensure effective UAV control. This study presents the development and validation of a 6-DOF UAV dynamic model, constructed using aerodynamic data derived from Computational Fluid Dynamics (CFD) simulations. The model integrates aerodynamics, weight, and thrust. To validate the model, three sets of flight test data were collected. The dataset showed the most consistent trends. The longitudinal, phugoid and short-period modes were successfully executed. However, residual oscillations in pitch angle and forward speed responses suggest the need to re-evaluate pitch-related aerodynamic coefficients and include CDu to the model. Despite these oscillations, pitch angle and pitch rate exhibited the lowest Mean Absolute Error (MAE) values when compared to flight data, indicating strong agreement in trend and amplitude. In contrast, forward speed showed the highest MAE due to discrepancies in initial conditions. For lateral/directional modes, characteristic responses such as roll subsidence, spiral, and Dutch roll were accurately reproduced. Yaw rate achieved the best fit, while yaw angle had the largest MAE due to range differences between simulation and flight test data. The differences between simulation results and flight test data are mainly due to the inaccuracy of aerodynamic coefficients in some parameters, simplifying assumptions in CFD simulations, as well as differences in initial conditions. Overall, the results demonstrate that the CFD-derived aerodynamic model, when validated against flight test data, can reliably represent the actual dynamic behaviour of a UAV. [ABSTRACT FROM AUTHOR]
Copyright of Periodica Polytechnica: Transportation Engineering is the property of Periodica Polytechnica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Validation of a Small UAV Dynamic Model Using CFD and Flight Test Data.
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  Data: <searchLink fieldCode="JN" term="%22Periodica+Polytechnica%3A+Transportation+Engineering%22">Periodica Polytechnica: Transportation Engineering</searchLink>. 2026, Vol. 54 Issue 1, p88-104. 17p.
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  Data: Fixed-wing Unmanned Aerial Vehicles (UAV) are increasingly utilized in various missions requiring stable and responsive performance. Accurate dynamic models are essential to ensure effective UAV control. This study presents the development and validation of a 6-DOF UAV dynamic model, constructed using aerodynamic data derived from Computational Fluid Dynamics (CFD) simulations. The model integrates aerodynamics, weight, and thrust. To validate the model, three sets of flight test data were collected. The dataset showed the most consistent trends. The longitudinal, phugoid and short-period modes were successfully executed. However, residual oscillations in pitch angle and forward speed responses suggest the need to re-evaluate pitch-related aerodynamic coefficients and include CDu to the model. Despite these oscillations, pitch angle and pitch rate exhibited the lowest Mean Absolute Error (MAE) values when compared to flight data, indicating strong agreement in trend and amplitude. In contrast, forward speed showed the highest MAE due to discrepancies in initial conditions. For lateral/directional modes, characteristic responses such as roll subsidence, spiral, and Dutch roll were accurately reproduced. Yaw rate achieved the best fit, while yaw angle had the largest MAE due to range differences between simulation and flight test data. The differences between simulation results and flight test data are mainly due to the inaccuracy of aerodynamic coefficients in some parameters, simplifying assumptions in CFD simulations, as well as differences in initial conditions. Overall, the results demonstrate that the CFD-derived aerodynamic model, when validated against flight test data, can reliably represent the actual dynamic behaviour of a UAV. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Periodica Polytechnica: Transportation Engineering is the property of Periodica Polytechnica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3311/PPtr.41190
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        Text: English
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        PageCount: 17
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      – SubjectFull: Computational fluid dynamics
        Type: general
      – SubjectFull: Flight testing
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      – SubjectFull: Single-degree-of-freedom systems
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      – SubjectFull: Dynamic models
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      – SubjectFull: Model validation
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      – SubjectFull: Aerodynamics
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      – TitleFull: Validation of a Small UAV Dynamic Model Using CFD and Flight Test Data.
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              Text: 2026
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