Designing and Modelling of Delta Wing Genetic-Based Prediction Model

Designing and Modelling of Delta Wing Genetic-Based Prediction Model

Arun M. P., Satheesh M., J. Edwin Raja Dhas
Copyright: © 2021 |Pages: 25
DOI: 10.4018/IJACI.2021010107
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Abstract

The designing and modeling of delta wing is one of the interesting topics. A number of researchers has contributed different works on modeling the same. This paper comes out with a new delta wing modeling with the inclusion of optimization concept. The obtained data from the investigation is integrated and given as the input to the classifier for predicting the drag and lift coefficients. This paper uses neural network (NN) classifier for predicting the drag and lift coefficients. Moreover, the weight of the NN is optimized using a proposed genetic algorithm. After the implementation, the performance of proposed model is compared to other conventional methods like individual adaptive genetic algorithm (IAGA-NN), deterministic adaptive genetic algorithm (DAGA-NN), self-adaptive genetic algorithm (SAGA-NN), genetic algorithm (GA-NN), gradient descendent (GD-NN), and Levenberg masquerade (LM-NN), respectively, in terms of drag and lift coefficient.
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1. Introduction

In general, the Micro aerial vehicles (MAVs) are the tiny aircraft that holds small wing span. The MAV’s magnitude order is very low when compared to Unmanned Aerial Vehicles (UAV) (Jang & Liccardo, 2007; Olavo, et al., 2018; Poksawat, et al., 2018; Wang, et al., 2018; Zhang & Deng, 2017). MAV is very much adaptive to greatly discrete service with small frames and quiet operating conditions. Still, the enhancement of flying robot to navigate various areas is in its infant stage that needs lightning rapid reflexes for greater control, than the human capability. Thus, certain autonomous sensory control is necessary to attain this goal. The approaches can be utilized for avoiding the objects while flight and also to grant a steady configuration to aircraft. Some of the major applications are defence applications, surveillance, broadcasting and so on. Further, it is used to observe the biochemical as well as hazardous material along with the sensor implantation in the civilian applications domain. The commercial applications specify the traffic monitoring, check up of power line, wildlife survey and etc.

The shortage of typical control surfaces makes the tiny vehicle hard to fly as the control effectors are tremendously used to attain various benefits. Thus, the controllability of the vehicles is improved through the wing implementation that enhances the performance of vehicle. In spite, the wing flexibility could minimize the MAV (Swaim, 1964; Gao, et al., 2018; Wang, 2011; Rucco, et al., 2018; Zhu, et al., 2017; Salichon & Tumer, 2012) power consumption. These small airplanes are highly receptive to wind gusts such that it can sustain the stability of flights. Hence, while windy conditions, the wings get twisted because of high load through the washout impact that reduces the induced drag and forms the greatest lift to drag ratio. Furthermore, the original wing shape is improved after struggling with the gust of wind that makes the flight stable.

Delta wings are the wings that are basically utilized in high-speed aircrafts, particularly for the transonic flights as they has the perfect flight behavior through weakening the compressibility impacts and also by granting greatest maneuver ability for the aircraft. The accurate prediction of the difficult flow enhancement on the suction surface of wing is of vast significant because of the two formed vortices. This UAV wings (Hsiao, et al., 2012; Michael, et al., 2010; Hinzmann, et al., 2018; Li, et al., 2018; Loianno, et al., 2018; Mitikiri & Mohseni, 2018) are designed in a manner that its chord is closer to 0.0755m with 5% double camber configuration, low Reynolds number and unit aspect ratio. Hence, the distinctive aerodynamic properties like high stall-angles of attack as well as nonlinear lift versus angle of attack curves are achieved with the above configurations. Advancement in designing the UAV wings is still under the research analysis that makes the researches to move in a novel way. Certain designing has been made previously, however encounters many flaws that often fails to provide accurate results. Hence, some new idea must be proclaimed for effective design of delta wings.

This paper comes with three major contributions, as depicted below:

  • 1.

    This paper proposes a new delta wing designing along with the concept of optimization algorithm.

  • 2.

    The NN algorithm is used to predict the drag and lift coefficient.

  • 3.

    Moreover, the weight of the NN is optimally chosen using the proposed genetic algorithm.

The rest of the paper is organized as follows: Section II reviews the literature work. Section III explains the catia based delta wing designing. Section IV explains the optimization concept. Section V explains the NN model. Section VI concludes the paper.

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