Optimal Design of Composite Wing-Box by Genetic Algorithm

2014 ◽  
Vol 697 ◽  
pp. 365-368
Author(s):  
Guang Rong Pu ◽  
Peng Gang Mu

With the increasing use of composite materials in aviation structures, stability and weights of wing-box are important projects that engineers care about. In this paper, the genetic algorithm is chosen to deal with the conceptual design problems of composite wing-box. For the more excellent capabilities in optimization computation of multi-dimensional functions, particularly when overcoming local-best solutions, genetic algorithm is presented to determine the design variables of complicated wing-box. Optimization algorithm is realized with MATLAB software, which calls the finite element program MSC.Nastran to get buckling load factors, and structural layout, thickness of plies and minimum weight of wing-box are obtained simultaneously. The results show that the approach proposed is available, effective to preliminary design of the mainly aeronautical structures.

2009 ◽  
Vol 1 (2) ◽  
pp. 80-88 ◽  
Author(s):  
Dmitrij Šešok ◽  
Rimantas Belevičius

Aim of the article is to suggest technology for optimization of pile positions in a grillage-type foundations seeking for the minimum possible pile quantity. The objective function to be minimized is the largest reactive force that arises in any pile under the action of statical loading. When piles of the grillage have different characteristics, the alternative form of objective function may be employed: the largest difference between vertical reaction and allowable reaction at any pile. Several different allowable reactions with a given number of such piles may be intended for a grillage. The design parameters for the problem are positions of the piles. The feasible space of design parameters is determined by two constraints. First, during the optimization process piles can move only along the connecting beams. Therefore, the two-dimensional grillage is “unfolded” to a one-dimensional construct, and the supports are allowed to range through this space freely. Second, the minimum allowable distance between two adjacent piles is introduced due to the specific capacities of pile driver.The initial data for the problem are the following: the geometrical scheme of the grillage, the cross-section and material data of connecting beams, minimum possible distance between adjacent supports, characteristics of piles, and the loading data given in the form of concentrated loads or trapezoidal distributed loadings. The results of solution are the required number of piles and their positions.The entire optimization problem is solved in two steps. First, the grillage is transformed to a one-dimensional construct, and the optimizer decides about a routine solution (i.e. the positions of piles in this construct). Second, the backward transformation returns the pile positions into the two-dimensional grillage, and the “black-box” finite element program returns the corresponding objective function value. On the basis of this value the optimizer predicts the new positions of piles, etc. The finite element program idealizes the connecting beams as the beam elements and the piles – as the finite element mesh nodes with a given boundary conditions in form of vertical and rotational stiffnesses. The optimizing program is an elitist genetic algorithm or a random local search algorithm. At the beginning of problem solution the genetic algorithm is employed. In the optimization problems under consideration, the genetic algorithms usually demonstrate very fast convergence at the beginning of solution and slow non-monotonic convergence to a certain local solution point after some number of generations. When the further solution with a genetic algorithm refuses to improve the achieved answer, i.e. a certain local solution is obtained; the specific random search algorithm is used. The moment, at which the transition from genetic algorithm to the local search is optimal, is sought in the paper analyzing the experimental data. Thus, the hybrid genetic algorithm that combines the genetic algorithm itself and the local search is suggested for the optimization of grillages.


1985 ◽  
Vol 107 (1) ◽  
pp. 88-93 ◽  
Author(s):  
Juhachi Oda

Problems considered here are that of minimizing the weight of beams, which are subjected to a uniform bending moment and reinforced by the fibers distributed in the direction of beam axis. The beam is simplified as a multilaminate structure, of which the fiber volume percent Vfi of each lamina is considered as the design variables. To formulate this design problem the bending theory of multilaminate beam and the law of mixture for the composite material strength are applied. Furthermore, the sequential linear programming and the sequential unconstrianed minimization techniques are used to obtain the design solutions numerically.


2014 ◽  
Vol 31 (1) ◽  
pp. 33-47
Author(s):  
Aleksandr Cherniaev

Purpose – The genetic algorithm (GA) technique is widely used for the optimization of stiffened composite panels. It is based on sequential execution of a number of specific operators, including the encoding of particular design variables. For instance, in the case of a stiffened composite panel, the design variables that need to be encoded are: the number of plies and their stacking sequences in the panel skin and stiffeners. This paper aims to present a novel, implicit, heuristic approach for encoding composite laminates and, through its use, demonstrates an improvement in the optimization process. Design/methodology/approach – The stiffened panel optimization has been formulated as a constrained discrete minimum-weight design problem. GAs, which use both new encoding schemes and those previously described in the literature, have been used to find near-optimal solutions to the formulated problem. The influence of the new encoding scheme on the searching capabilities of the GA has been investigated using comparative analysis of the optimization results. Findings – The new encoding scheme allows the definition of stacking sequences in composites using shorter symbolic representations as compared with standard encoding operators and, as a result of this, a reduction in the problem design space. According to numerical experiments performed in this work, this feature enables GA to obtain near-optimal designs using smaller population sizes than those required if standard encoding schemes are used. Originality/value – The approach to encoding laminates presented in this paper is based on the original heuristics. In the context of GA-based optimization of stiffened composite panels, the use of the new approach rather than the standard encoding technique can lead to a significant reduction in computational time employed.


2016 ◽  
Vol 3 (1) ◽  
Author(s):  
M. Abouhamzeh ◽  
M. Sadighi

AbstractIn this paper, the buckling load optimisation is performed on sandwich cylindrical panels. A finite element program is developed in MATLAB to solve the governing differential equations of the global buckling of the structure. In order to find the optimal solution, the genetic algorithm Toolbox in MATLAB is implemented. Verifications are made for both the buckling finite element code and also the results from the genetic algorithm by comparisons to the results available in literature. Sandwich cylindrical panels are optimised for the buckling strength with isotropic or orthotropic cores with different boundary conditions. Results are presented in terms of stacking sequence of fibers in the face sheets and core to face sheet thickness ratio.


2019 ◽  
Vol 304 ◽  
pp. 01018
Author(s):  
Lada Zudova ◽  
Victor Fomin ◽  
Danil Fomin ◽  
Konstantin Zudov

The algorithm of optimization of the hybrid structural layout for the wing box has been developed. The wing box consisted of two parts; one of them (heavily loaded) had hybrid (lattice-truss) layouts, the other had conventional (black metal) layout. These parts was connected by use of interface structure. The basic objectives were sizing of load-bearing elements for each of the layouts, and to search for the interface position, providing minimum weight of the wing box structure. These tasks were solved with use of genetic algorithm. At searching for the interface optimal position the results of parametric FEM calculations were additionally used. A rational variant (65-73%) of the relative length of the wing box zone with lattice-truss structural layout has been obtained for the aircraft of regional airlines. This variant meets the constraints, and has the weight benefit (13-17%) compared with conventional structural layout.


2002 ◽  
Vol 124 (2) ◽  
pp. 397-408 ◽  
Author(s):  
J. S. Chung ◽  
S. M. Hwang

A genetic algorithm based approach is presented for process optimal design in forging. In this approach, the optimal design problem is formulated on the basis of the integrated thermo-mechanical finite element process model so as to cover diverse design variables and objective functions, and a genetic algorithm is adopted for conducting design iteration for optimization. The process model, the formulation for process optimal design, and the genetic algorithm are described in detail. The approach is applied to several selected process design problems in cold and hot forging.


Author(s):  
S J Guo ◽  
J R Bannerjee ◽  
C W Cheung

This paper presents an analytical study on optimization of a laminated composite wing structure for achieving a maximum flutter speed and a minimum weight without strength penalty. The investigation is carried out within the range of incompressible airflow and subsonic speed. In the first stage of the optimization, attention has been paid mainly to the effect on flutter speed of the bending, torsion and, more importantly, the bending-torsional coupling rigidity, which is usually associated with asymmetric laminate lay-up. The study has shown that the torsional rigidity plays a dominant role, while the coupling rigidity has also quite a significant effect on the flutter speed. In the second stage of the optimization, attention has been paid to the weight and laminate strength of the wing structure, which is affected by the variation in laminate lay-up in the first stage. Results from a thin-walled wing box made of laminated composite material show that up to 18 per cent increase in flutter speed and 13 per cent reduction in weight can be achieved without compromising the strength. The investigation has shown that a careful choice of initial lay-up and design variables leads to a desirable bending, torsional and coupling rigidities, with the provision of an efficient approach when achieving a maximum flutter speed with a minimum mass of a composite wing.


2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.


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