Wind Tunnel Experiments and CFD Analysis of Blended Wing Body (BWB) Unmanned Aerial Vehicle (UAV) at Mach 0.1 and Mach 0.3

Wisnoe, Wirachman; Nasir, Rizal Effendy Mohd; Kuntjoro, Wahyu; Mamat, Aman Mohd Ihsan

doi:10.21608/asat.2009.23441

Cited by 23 publications

(13 citation statements)

References 3 publications

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“…The turbulence modeling in transitional flows was obtained using the − SST transitional model. This turbulence model is the most suitable one used in many studies, as observed here [15,16]. Table 3 shows the results of the aerodynamic variables of all the 4 UAV models.…”

Section: Boundary Conditionsmentioning

confidence: 99%

Unmanned Aerial Vehicle Production With Additive Manufacturing

Koç

Çalışkan

Coşkun

et al. 2020

Journal of Aviation

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In this study, unmanned aerial vehicle (UAV) design, analysis and production was made using selective laser sintering (SLS) system. Four different aircraft bodies were designed in the interdisciplinary project, one of the models was selected by comparing the computational fluid dynamics (CFD) analysis results. According to the numerical study, the model 4 design was found to be the most suitable among the tested models, then the design was produced with the SLS system. Finally, the actual flight test was carried out in three different weather conditions, and the results are presented here.

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Section: Boundary Conditionsmentioning

confidence: 99%

Unmanned Aerial Vehicle Production With Additive Manufacturing

Koç

Çalışkan

Coşkun

et al. 2020

Journal of Aviation

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“…One of the most important characteristics that affect flight performance and stability is the aerodynamic shape of the UAV. In the literature, various methods such as computational fluid dynamics (CFD) and wind tunnel (WT) are used to determine the aerodynamic shape (Acree and Johnson, 2006;Wisnoe et al, 2009;Yeo and Johnson, 2009;Mariens, 2012). In their studies which these methods are used, the maximum value of lift/drag ratio (E max ) that significantly influences flight performance is often preferred (Beechook and Wang, 2013;Smith et al, 2001;Azlin et al, 2011;Bourdin et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Redesign of morphing UAV's winglet using DS algorithm based ANFIS model

Konar

2019

AEAT

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Purpose The purpose of this paper is to present a novel approach based on the differential search (DS) algorithm integrated with the adaptive network-based fuzzy inference system (ANFIS) for unmanned aerial vehicle (UAV) winglet design. Design/methodology/approach The winglet design of UAV, which was produced at Faculty of Aeronautics and Astronautics in Erciyes University, was redesigned using artificial intelligence techniques. This approach proposed for winglet redesign is based on the integration of ANFIS into the DS algorithm. For this purpose, the cant angle (c), the twist angle (t) and taper ratio (λ) of winglet are selected as input parameters; the maximum value of lift/drag ratio (Emax) is selected as the output parameter for ANFIS. For the selected input and output parameters, the optimum ANFIS parameters are determined by the DS algorithm. Then the objective function based on optimum ANFIS structure is integrated with the DS algorithm. With this integration, the input parameters for the Emax value are obtained by the DS algorithm. That is, the DS algorithm is used to obtain both the optimization of the ANFIS structure and the necessary parameters for the winglet design. Thus, the UAV was reshaped and the maximum value of lift/drag ratio was calculated based on new design. Findings Considerable improvements on the max E are obtained through winglet redesign on morphing UAVs with artificial intelligence techniques. Research limitations/implications It takes a long time to obtain the optimum Emax value by the computational fluid dynamics method. Practical implications Using artificial intelligence techniques saves time and reduces cost in maximizing Emax value. The simulation results showed that satisfactory Emax values were obtained, and an optimum winglet design was achieved. Thus, the presented method based on ANFIS and DS algorithm is faster and simpler. Social implications The application of artificial intelligence methods could be used in designing more efficient aircrafts. Originality/value The study provides a new and efficient method that saves time and reduces cost in redesigning UAV winglets.

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“…Wind tunnel test is high-cost and time-consuming, most of all, the results are not accurate in the flight condition of low Reynolds number. And CFD software analysis usually has heavy work on the 3D model meshing, and the gap effect as well as the frictional drag is often neglected [ 4 , 5 ]. DATCOM, introduced by the US Air Force, is another choice for the parameter calculation.…”

Section: Introductionmentioning

confidence: 99%

Calculation and Identification of the Aerodynamic Parameters for Small-Scaled Fixed-Wing UAVs

Jieliang

Liang

2018

Sensors

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The establishment of the Aircraft Dynamic Model (ADM) constitutes the prerequisite for the design of the navigation and control system, but the aerodynamic parameters in the model could not be readily obtained especially for small-scaled fixed-wing UAVs. In this paper, the procedure of computing the aerodynamic parameters is developed. All the longitudinal and lateral aerodynamic derivatives are firstly calculated through semi-empirical method based on the aerodynamics, rather than the wind tunnel tests or fluid dynamics software analysis. Secondly, the residuals of each derivative are proposed to be identified or estimated further via Extended Kalman Filter (EKF), with the observations of the attitude and velocity from the airborne integrated navigation system. Meanwhile, the observability of the targeted parameters is analyzed and strengthened through multiple maneuvers. Based on a small-scaled fixed-wing aircraft driven by propeller, the airborne sensors are chosen and the model of the actuators are constructed. Then, real flight tests are implemented to verify the calculation and identification process. Test results tell the rationality of the semi-empirical method and show the improvement of accuracy of ADM after the compensation of the parameters.

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Wind Tunnel Experiments and CFD Analysis of Blended Wing Body (BWB) Unmanned Aerial Vehicle (UAV) at Mach 0.1 and Mach 0.3

Cited by 23 publications

References 3 publications

Unmanned Aerial Vehicle Production With Additive Manufacturing

Unmanned Aerial Vehicle Production With Additive Manufacturing

Redesign of morphing UAV's winglet using DS algorithm based ANFIS model

Calculation and Identification of the Aerodynamic Parameters for Small-Scaled Fixed-Wing UAVs

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