Constrained Optimization of a Commercial Aircraft Wing Using Non-dominated Sorting Genetic Algorithms (NSGA) (original) (raw)
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2015
In this paper, optimization of Boeing 747 wing has accomplished for cruise condition (Mach number=0.85 and flight altitude=35000 ft) and an optimal wing shape have been proposed. Optimization problem has two objectives and is constrained for this research. Objective functions are minimization of wing weight and drag force that as well as confining design parameters, two functional constrains are applied. The first functional constrain is fuel tank volume in the aircraft wing that supply the required fuel. The second functional constrain is lift coefficient that should be equal to initial lift coefficient. Design parameters are root chord, wing span and wing sweep angle. Non-dominating genetic algorithm has been used in optimization process until finding one optimal solution; set of solutions (pareto front) are obtained for two objective functions. Finally a criterion for selecting a best solution for the aircraft on the pareto frontier is addressed.
Genetic Optimization Applied in Conceptual and Preliminary Aircraft Design
This work describes the development of a Multidisciplinary Optimization Framework for the conceptual design and optimization of a business aircraft, through the use of genetic algorithms, in-house algorithms for Weight Estimation, Performance and Mission Analysis, and commercial and open-source softwares for evaluation of important characteristics of each aircraft, such as Aerodynamics, Propulsion and Static and Dynamic Stability Derivatives. The variables being optimizated are related to airfoil, wing planform, control surfaces planform, fuselage geometry and motorization. The framework is capable of optimizating many aircraft parameters, performing tasks such as drag reduction, lift improvement, weight reduction, mission optimization and cost reduction.
Multi-objective optimization procedure for the wing design at cruise and low-speed conditions
Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2013
The procedure for wing aerodynamic design based on the algorithm of simultaneous multiregime optimization of cruise and low-speed performance is considered. The method is based on the combination of fast direct methods for subsonic and transonic wing analysis, geometry variation module and the optimization procedure. The description of all the components and examples of practical application of the developed technique for design of the conventional medium-haul airplane wing and the ‘Flying Wing’ configuration are presented.
Non-linear modelling for Multi-Disciplinary and Multi-Objective Optimization of a complete aircraft
Aerotecnica Missili & Spazio, 2013
The aerospace engineering typically deals with multidisciplinary complex systems, and narrow margins of the design parameters make necessary the introduction of multi-objective approaches in order to pick the best design. Genetic algorithms, in addition to gradient-based ones, allow to evaluate Pareto frontiers, in the objective space, i.e. the set of best trade-offs, thanks to the current satisfactory level of computer performance. In the present paper, an integrated Multidisciplinary Design Optimization (MDO) has been used to solve a Multi-Objective Optimization (MOO) problem for a notional regional aircraft type comprised of fuselage, tail and wing, where the optimization criteria include minimal structural weight, maximum L/D and maximum mission range, taking into account also of aeroelastic constraints. The level of fidelity of the disciplines used for the analyses is a relevant issue in the optimization process although it may contrast computational cost. In the present paper a non-linear analyses have been proposed within the MDO/MOO process to evaluate the aerodynamic performance (i.e. the L/D is computed as the ratio of lift and drag coefficients) for a more fidelity estimate of the induced drag by using a free-wake approach.
2018
In the real world, aeronautics engineering design problems the designer often seeks to optimize multiple and conflicting merit functions or objectives relating to the performance of the given design. Several techniques are available today for design through numerical optimization. The first aim of this paper was to perform a complete, comprehensive comparison between different stochastic multi-objective optimization methods like: the Non-dominated Sorting Genetic Algorithm II (NSGA-II). A single and Multi Objective Simulated Annealing (MOSA). Multi-Objective Particle Swarm (MOPSO) and Multi Objective Genetic Algorithm (MOGA-II), by using the commercial Mode FRONTIER software to solve the aerodynamics wing design problem. The black-box objective function is a low-fidelity flow computation code solver, which was based on first order 3D panel method, for lift and induced drag coefficient calculation, and the boundary layer method for the friction drag coefficient calculation. The effic...
Influence of Search Algorithms on Aerodynamic Design Optimization of Aircraft Wings
International Journal of Soft Computing, 2012
The Method of search algorithms or optimisation algorithms is one of the most important parameters which will strongly influence the fidelity of the solution during an aerodynamic shape optimisation problem. Nowadays various optimisation methods such as Genetic Algorithm (GA), Simulated Annealing (SA), Particle Swarm Optimisation (PSO) etc., are more widely employed to solve the aerodynamic shape optimisation problems. In addition to the optimisation method, the geometry parameterisation becomes an important factor to be considered during the aerodynamic shape optimisation process. Since the reduction in the number of design parameters is one of the most important requirements for the aerodynamic shape optimisation problem, it becomes important to mathematically describe the airfoil geometry with minimum number of design parameters. The objective of this work is to introduce the knowledge of describing general airfoil geometry using twelve parameters by representing its shape as a polynomial function and coupling this approach with flow solution and optimisation algorithms. It is also demonstrated that the estimation of a suitable optimisation scheme for a given optimisation problem. An aerodynamic shape optimisation problem is formulated for NACA 0012 airfoil and solved using the methods of Particle Swarm Optimisation and Genetic Algorithm for 5.0 deg angle of attack. The results show that the particle swarm optimisation scheme is more effective in finding the optimum solution among the various possible solutions. It is also found that the PSO shows more exploitation characteristics as compared to the GA which is considered to be more effective explorer.
Wing Aerodynamic Optimization by Using Genetic Algoritm and Ansys
Acta Physica Polonica A, 2017
The design of aircraft wings can be examined in two ways, namely, by aerodynamic analysis and by structural analysis. In aerodynamic terms, the wing is expected to display such features as maximum lifting load, minimum drag force, and high stall performance; in structural terms, it is desired to be light, robust, and away from vibration effects. In this paper optimization of the wing aerodynamic analysis of a private jet plane has been performed. Wing simulation was conducted with Ansys-Fluent program, whereas optimization of design criteria was realised using genetic algorithm. Design criteria determined in parametric terms have been optimized with genetic algorithm, which was written in Python, inside the Ansys-Workbench. Python was not sufficient on its own for the realization of the genetic algorithm and for control of the Ansys modules, as a result, it was assisted with Javascript and Journaling. The developed method can be used in a variety of design applications.
Journal of Science and Technology in Civil Engineering (STCE) - NUCE, 2020
Multidisciplinary Design Optimization (MDO) has received a considerable attention in aerospace industry. The article develops a novel framework for Multidisciplinary Design Optimization of aircraft wing. Practically, the study implements a high-fidelity fluid/structure analyses and accurate optimization codes to obtain the wing with best performance. The Computational Fluid Dynamics (CFD) grid is automatically generated using Gridgen (Pointwise) and Catia. The fluid flow analysis is carried out with Ansys Fluent. The Computational Structural Mechanics (CSM) mesh is automatically created by Patran Command Language. The structural analysis is done by Nastran. Aerodynamic pressure is transferred to finite element analysis model using Volume Spline Interpolation. In terms of optimization algorithms, Response Surface Method, Genetic Algorithm, and Simulated Annealing are utilized to get global optimum. The optimization objective functions are minimizing weight and maximizing lift/drag. T...
12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2012
This paper examines the evolutionary approach for aircraft design optimization. Several niching and elitist models are first applied to Multiple-Objective Genetic Algorithms (MOGAs). Numerical results suggest that the combination of the fitness sharing and the best-N selection leads to the best performance. The resulting MOGA is then applied to multidisciplinary design optimization problems of transonic and supersonic wing planform shapes. The results confirm the feasibility of the present approach. Wing weight (lb) Drag (lb) Aspect ratio Minimum drag Minimum aspect ratio Minimum weight Center of Pareto surface