Optimization Of Aircraft Wing Research Articles

Convex approximation of the design space in the aircraft wing optimization problem

A convex approximation of the design space of the submodel of the aircraft wing, which describes the set the wing airfoils in chosen cross-sections, is constructed. In the available model, constraints specifying a nonconvex space are imposed on the cross-section parameters. In the course of the wing modeling procedure, dimensionality reduction methods, which enable wing description with some error by a lesser number of parameters, are used. In this paper, we propose an approach allowing one to replace with the same error constraints specifying a nonconvex set by a system of inequalities describing a convex polyhedron. In the obtained model, the system of constraints for each cross-section can be replaced by one constraint in the form of an extremal ellipsoid constructed based on a set of available reference airfoils.

Global/Local Optimization of Aircraft Wing Using Parallel Processing

The structural optimization of a cantilever aircraft wing with stiffeners and curvilinear spars and ribs is described. The decomposition technique for the wing structure is widely used for the optimization of a complex wing. The optimization procedure is divided into two subsystems: the global wing optimization, which determines the geometry and location of spars and ribs, and local panel optimization to further reduce wing weight. Because the design variables that are changed in the global step have an impact on those changed in the local step and vice versa, an iterative process that iterates between the global and local optimizations is employed. Particle swarm optimization and gradient-based optimization are used to perform integrated global/local optimization. Parallel computing is used, implemented using Python, to reduce the central processing unit time. The license cycle-check method and memory self-adjustment method are developed and applied in the parallel processing framework to optimize the use of the resources. The integrated global/local optimization approach has been applied to the NASA Common Research Model wing, which proves the methodology’s application with finite element method analysis of appropriate fidelity. A 40% weight reduction of the Common Research Model wing has been achieved by the global/local optimization at an acceptable computational time.

Influence of Optimization Algorithm on Airfoil Shape Optimization of Aircraft Wings

Computational fluid dynamics (CFD) is one of the computer-based solution methods which are more widely employed in aerospace engineering. The computational power and time required to carry out the analysis increases as the fidelity of the analysis increases. Aerodynamic shape optimization has become a vital part of aircraft design in the recent years. The Method of search algorithms or optimization algorithms is one of the most important parameters which will strongly influence the fidelity of the solution during an aerodynamic shape optimization problem. Nowadays various optimization methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) etc., are more widely employed to solve the aerodynamic shape optimization problems. In addition to the optimization method, the geometry parameterisation becomes an important factor to be considered during the aerodynamic shape optimization process. Generally if we want to optimize an airfoil we have to describe the airfoil and for that, we need to have at least hundred points of x and y co-ordinates. It is really difficult to optimize airfoils with this large number of co-ordinates. Nowadays many different schemes of parameter sets are used to describe general airfoil such as B-spline, Hicks- Henne Bump function, PARSEC etc. The main goal of these parameterization schemes is to reduce the number of needed parameters as few as possible while controlling the important aerodynamic features effectively. Here the work has been done on the PARSEC geometry representation method. The objective of this work is to introduce the knowledge of describing general airfoil using twelve parameters by representing its shape as a polynomial function. And also we have introduced the concept of Particle Swarm optimization Algorithm which is one kind of Non-Traditional Optimization technique to optimize the aerodynamic characteristics of a general airfoil for specific conditions. An aerodynamic shape optimization problem is formulated for NACA 2411 airfoil and solved using the method of Particle Swarm Optimization for 5.0 deg angle of attack. A MATLAB program has been developed to implement PARSEC, Panel Technique, and PSO Algorithm. This program has been tested for a standard NACA 2411 airfoil and optimized to improve its coefficient of lift. Pressure distribution and co-efficient of lift for airfoil geometries has been calculated using panel method. NACA 2411 airfoil has been generated using PARSEC and optimized for 5.0 deg angle of attack using PSO Algorithm. The results show that the particle swarm optimization scheme is more effective in finding the optimum solution among the various possible solutions.

A methodology for the shape optimization of flexible wings

PurposeTo propose an integrated algorithm for aerodynamic shape optimization of aircraft wings under the effect of aeroelastic deformations at supersonic regime.Design/methodology/approachA methodology is proposed in which a high‐fidelity aeroelastic analyser and an aerodynamic optimizer are loosely coupled. The shape optimizer is based on a “CAD‐free” approach and an exact gradient method with a single adjoint state. The global iterative process yields optimal shapes in the at‐rest condition (i.e. with the aeroelastic deformations substracted).FindingsThe methodology was tested under different conditions, taking into account a combined optimization goal: to reduce the sonic boom production, while preserving the aerodynamic performances of flexible wings. The objective function model contains both aerodynamic parameters and an acoustic term based on the sonic boom downwards emission.Practical implicationsThis paper proposes a shape optimization methodology developed by researchers but aiming at the final strategic goal of creating tools that can be really integrated in design processes.Originality/valueThe paper presents an original loosely coupled method for the shape optimization of flexible wings in which recent and modern techniques are used at different levels of the global algorithm: the aerodynamic optimizer, the aeroelastic analyser, the shape parametrization and the objective function model.