2017
DOI: 10.1177/0954410017705903
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Modeling the motion of small unmanned aerial system (sUAS) due to ground collision

Abstract: The aim of this paper is to develop a modeling method in order to predict the rebounce distance of a small size unmanned aerial system (sUAS) after collision with the ground. This distance would be useful to determine the safe range on the ground when operating the UAS. A two-step strategy is developed to model this procedure. In step one, numerical simulations are performed to model the first impact and predict the rebounce angle and impact velocity. Based on the information obtained, in step two, an analytic… Show more

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Cited by 6 publications
(4 citation statements)
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“…While the previous research focused on population and crowd modeling while including basic dynamics of the vehicle upon impact, other research has been done to model the dynamics of the vehicle including bounce effects to better understand the potentially affected area [56].…”
Section: Failure Impact Analysis and Crowd Modelingmentioning
confidence: 99%
“…While the previous research focused on population and crowd modeling while including basic dynamics of the vehicle upon impact, other research has been done to model the dynamics of the vehicle including bounce effects to better understand the potentially affected area [56].…”
Section: Failure Impact Analysis and Crowd Modelingmentioning
confidence: 99%
“…The aerodynamic analysis of the UAV is obtained using a computational fluid dynamic (CFD) through the CFX module of ANSYS software. Other authors have used the ANSYS software to predict aerodynamics coefficients of UAVs with satisfactory results [27], [28]. For this aerodynamic analysis, we built a control volume to simulate the air around UAV (Figure 4).…”
Section: Cfd Modelingmentioning
confidence: 99%
“…In the development of complex structures, such as a vehicle or aircraft, a large number of full-scale numerical simulations are often needed. As the supplement and partial substitute of these expensive simulations, surrogate models have been widely used in engineering design and optimization to reduce the computational cost [1][2][3]. A surrogate model is established from the design or simulation datasets through regression, to approximate the real model.…”
Section: Introductionmentioning
confidence: 99%