... of jig shape (Sherif et al., 2002), cruise shape and the scaling of models for testing (Filippou et al., 2024). Aeroelasticity Wing optimization Particle swarm optimization Preliminary design Flexible wings Lift-to-drag ratio The process of aircraft wing...

... problem with multiple constraints and proposing an advanced algorithm to enhance the operational efficiency. Design/methodology/approach A novel leader–follower-based hybrid particle swarm-grey wolf optimizer algorithm (LFHPS-GWO) is proposed. In this approach, the particle swarm optimization (PSO...

...Volkan Yasin Pehlivanoglu; Perihan Pehlivanoğlu Purpose The purpose of this paper is to present an efficient path planning method for the multi-UAV system in target coverage problems. Design/methodology/approach An enhanced particle swarm optimizer (PSO) is used to solve the path planning...

... © Emerald Publishing Limited 2022 Emerald Publishing Limited Licensed re-use rights only Aircraft Ant colony optimization Particle swarm optimization Turbojet Component matching Off-design calculation a = acceleration (m/s^{2); A = Area; P = Presure [kPa}...

... code is integrated with various benchmark and test functions that are selected suitable to the difficulty level of the aero propulsion performance problems. Findings Ant colony and particle swarm optimization (ACOPSO) has performed satisfactorily with benchmark problems. Research limitations...

... at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output...

... Optimization Particle swarm optimization Design Surrogate Aerostat LTA vehicles Symbols A_f = fin axial aerodynamic force, N; A_h = hull axial aerodynamic force, N; a₁ = forward ellipse semi-major axis, m...

..., aerodynamics, propulsion and trajectory. Nineteen design variables were selected to optimize expendable MSLV to launch a 100 kg satellite at an altitude of 600 km in the low earth orbit. Modern heuristic optimization methods such as genetic algorithm (GA), particle swarm optimization (PSO) and SA are applied...

...Ridvan Oruc; Tolga Baklacioglu Purpose The purpose of this paper is to create a new fuel flow rate model for the descent phase of the flight using particle swarm optimization (PSO). Design/methodology/approach A new fuel flow rate model was developed for the descent phase of the B737-800...

...-order particle swarm optimization (FAPSO) method is proposed for velocity updates to design the guidance method for gliding reentry flight vehicles with fixed final energy. Findings By using the common aero vehicle as a test case for the simulation purpose, it is found that during the initial phase...

...Ridvan Oruc; Tolga Baklacioglu Purpose The purpose of this paper is to create high-accuracy thrust modelling for cruise flight using particle swarm optimization (PSO) algorithm. Design/methodology/approach In this study, using PSO, new thrust models with high accuracy for the cruise flight...

...Chengchao Bai; Jifeng Guo; Wenyuan Zhang; Tianhang Liu; Linli Guo Purpose The purpose of this paper is to verify the feasibility of lunar capture braking through three methods based on particle swarm optimization (PSO) and compare the advantages and disadvantages of the three strategies...

...Wei He; Yuanming Xu; Yaoming Zhou; Qiuyue Li Purpose This paper aims to introduce a method based on the optimizer of the particle swarm optimization (PSO) algorithm to improve the efficiency of a Kriging surrogate model. Design/methodology/approach PSO was first used to identify the best group...

... design prediction based on local surrogate models in particle swarm optimization (PSO) algorithm. Local response surface approximations are constructed by using radial basis neural networks. The principal role of surrogate models is to answer the question of which individuals should be placed...