Structural Optimization of Composite Panel with Lamination Parameters and Equivalent Stiffness Laminate Method

2014 ◽  
Vol 496-500 ◽  
pp. 429-435
Author(s):  
Xiao Ping Zhong ◽  
Peng Jin
Keyword(s):  
Genetic Algorithm ◽  
Structural Optimization ◽  
Composite Structure ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Composite Panel ◽  
Analysis Tool ◽  
Equivalent Stiffness ◽  
Lamination Parameters ◽  
Design Variables

Firstly, a two-level optimization procedure for composite structure is investigated with lamination parameters as design variables and MSC.Nastran as analysis tool. The details using lamination parameters as MSC.Nastran input parameters are presented. Secondly, with a proper equivalent stiffness laminate built to substitute for the lamination parameters, a two-level optimization method based on the equivalent stiffness laminate is proposed. Compared with the lamination parameters-based method, the layer thicknesses of the equivalent stiffness laminate are adopted as continuous design variables at the first level. The corresponding lamination parameters are calculated from the optimal layer thicknesses. At the second level, genetic algorithm (GA) is applied to identify an optimal laminate configuration to target the lamination parameters obtained. The numerical example shows that the proposed method without considering constraints of lamination parameters can obtain better optimal results.

Aeroelastic Tailoring of Blended Composite Panels with Lamination Parameters

2013 ◽  
Vol 401-403 ◽  
pp. 571-577
Author(s):  
Peng Jin ◽  
Bi Feng Song ◽  
Xiao Ping Zhong
Keyword(s):  
Performance Improvement ◽  
Optimization Method ◽  
Composite Panel ◽  
Composite Panels ◽  
Parallel Genetic Algorithm ◽  
Lamination Parameters ◽  
Aeroelastic Tailoring ◽  
Region Division ◽  
Design Variables ◽  
Composite Wing

An optimization method for blended composite panels with aeroelastic constraint is presented in this paper. On the basis of composite panel sub-region division, the lamination parameters of a guide laminate and length indicator of each ply of the guide laminate are introduced as design variables using parallel genetic algorithm (GA) for optimization. For each individual, the inverse problem of obtaining laminate configuration to target the lamination parameters is solved by another GA. The method of defining design variables can reduce the number of design variables obviously compared with previous work. And the numerical results indicate that the present method is capable of producing fully blended designs of composite wing with aeroelastic performance improvement and weight reduction.

Topology Optimization of Compliant Mechanisms Using Hybrid Discretization Model

2010 ◽  
Vol 132 (11) ◽  
Author(s):  
Hong Zhou
Keyword(s):  
Topology Optimization ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Diagonal Element ◽  
Initial Guess ◽  
Stress Constraint ◽  
Design Variables ◽  
Hybrid Discretization

The hybrid discretization model for topology optimization of compliant mechanisms is introduced in this paper. The design domain is discretized into quadrilateral design cells. Each design cell is further subdivided into triangular analysis cells. This hybrid discretization model allows any two contiguous design cells to be connected by four triangular analysis cells whether they are in the horizontal, vertical, or diagonal direction. Topological anomalies such as checkerboard patterns, diagonal element chains, and de facto hinges are completely eliminated. In the proposed topology optimization method, design variables are all binary, and every analysis cell is either solid or void to prevent the gray cell problem that is usually caused by intermediate material states. Stress constraint is directly imposed on each analysis cell to make the synthesized compliant mechanism safe. Genetic algorithm is used to search the optimum and to avoid the need to choose the initial guess solution and conduct sensitivity analysis. The obtained topology solutions have no point connection, unsmooth boundary, and zigzag member. No post-processing is needed for topology uncertainty caused by point connection or a gray cell. The introduced hybrid discretization model and the proposed topology optimization procedure are illustrated by two classical synthesis examples of compliant mechanisms.

Optimum Autofrettage and Shrink-Fit Combination in Multi-Layer Cylinders

2005 ◽  
Vol 128 (2) ◽  
pp. 196-200 ◽  
Author(s):  
Hamid Jahed ◽  
Behrooz Farshi ◽  
Morvarid Karimi
Keyword(s):  
Fatigue Life ◽  
Life Expectancy ◽  
Crack Depth ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Stress Constraints ◽  
Simplex Search ◽  
Design Variables ◽  
Significant Life ◽  
Shrink Fit

The interest in the use of layered cylinders that combine autofrettage and shrink fit in order to extend fatigue lifetimes is increasing. As the number of layers increases, the sequential order of assembly and the size of each layer become more important. To achieve the most benefical result, a design optimization method is required. In this investigation, the optimum design of a three-layered vessel for maximum fatigue life expectancy under the combined effects of autofrettage and shrink fit has been considered. To obtain optimum size of each layer and to optimize the initial stress distribution, the numerical optimization procedure known as the Simplex search method is employed here. The thickness of each layer, shrink-fit pressures, and autofrettage percentages are treated as design variables. Under stress constraints, the operational sequences for assembly of a layered vessel have been formulated in order to lead to optimum results, defined as maximum life expectancy. The fatigue life consideration is based on ASME code provisions and standards for high pressure vessel technology, which define the allowable final crack depth for multilayer vessels. The proposed procedure has been carried out on a number of examples. The results show that, with proper combination of operations significant life enhancement can be achieved using the optimization procedure.

Genetic algorithm-based optimization design method of the Formula SAE racing car’s rear wing

2017 ◽  
Vol 232 (7) ◽  
pp. 1255-1269 ◽  
Author(s):  
Hui Wang ◽  
Qiuyang Bai ◽  
Xufei Hao ◽  
Lin Hua ◽  
Zhenghua Meng
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Design Method ◽  
Optimal Solution ◽  
Optimization Procedure ◽  
Formula Sae ◽  
Design Variables ◽  
Rear Wing ◽  
Sample Points ◽  
Lift And Drag

The aerodynamic devices play an important role on the performance of the Formula SAE racing car. The rear wing is the most significant and popular element, which offers primary down force and optimizes the wake. In traditional rear wing optimization, the optimization variables are first selected, and separately enumerated according to the analyzing experience of the racing car’s external flow field, and thus the optimal design is chosen by comparison. This method is complicated, and even might lose some key sample points. In this paper, the attack angle of the rear wing and the relative position parameters are set as design variables; then the design variables’ combination is determined by the DOE experimental design method. The aerodynamic lift and drag of the racing car for these variables’ combinations are obtained by the computational fluid dynamics method. With these sample points, the approximation model is produced by the response surface method. For the sake of gaining the best lift to drag ( FL/ FD) ratio, i.e. maximum down force and the minimum drag force, the optimal solution is found by the genetic algorithm. The result shows that the established optimization procedure can optimize the rear wing’s aerodynamic characteristic on the racing car effectively and have application values in the practical engineering.

A new laminates encoding scheme for the genetic algorithm-based optimization of stiffened composite panels

2014 ◽  
Vol 31 (1) ◽  
pp. 33-47
Author(s):  
Aleksandr Cherniaev
Keyword(s):  
Genetic Algorithm ◽  
Minimum Weight ◽  
Composite Panel ◽  
Computational Time ◽  
Stiffened Panel ◽  
Composite Panels ◽  
Encoding Scheme ◽  
Content Type ◽  
Design Variables ◽  
Stiffened Composite Panels

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.

scholarly journals Improved Immune Genetic Algorithm to Optimize the Design of Wing Structure of Competition Aircraft

2021 ◽  
Vol 2137 (1) ◽  
pp. 012075
Author(s):  
Xi Feng ◽  
Yafeng Zhang
Keyword(s):  
Genetic Algorithm ◽  
Aircraft Design ◽  
Flight Test ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Immune Genetic Algorithm ◽  
Maximum Deformation ◽  
Design Variables ◽  
Wing Structure

Abstract An improved immune genetic algorithm is used to design and optimize the wing structure parameters of a competition aircraft. According to the requirements of aircraft design, multi-objective optimization index is established. On this basis, the basic steps of using immune algorithm to optimize the main design parameters of aircraft wing structure are proposed, and the optimization of the wing parameters of a competition aircraft is used as an example for simulation calculation. The design variables in the optimization are the size of the wing components, and the optimization goal is to minimize the weight of the wing and the maximum deformation of the wing structure. Research shows that compared with traditional optimization methods; the improved immune genetic algorithm is a very effective optimization method. At the same time, a prototype is made to check the validity and feasibility of the design. Flight test results show that the optimization method is very effective. Although the method is proposed for competition aircraft, it is also applicable to other types of aircraft.

Genetic Algorithm for Material Cost Minimization of External Strengthening System with Fiber Reinforced Polymer

2012 ◽  
Vol 468-471 ◽  
pp. 1817-1822
Author(s):  
Md. Moshiur Rahman ◽  
Mohd Zamin Jumaat ◽  
Md. Akter Hosen
Keyword(s):  
Genetic Algorithm ◽  
Cost Minimization ◽  
Optimization Procedure ◽  
Minimum Cost ◽  
Optimization Method ◽  
Epoxy Adhesive ◽  
Fiber Reinforced Polymer ◽  
Fiber Reinforced ◽  
Limit States ◽  
Reinforced Polymer

An optimization procedural method for designing fiber reinforced polymer (FRP) plate for strengthening reinforced concrete beam is presented. The optimization procedure is formulated to find the design variables leading to the minimum cost of structural strengthening system using CFRP plate with constraints imposed based on TR55 code provisions. Genetic algorithm based approach is utilized to solve the optimization task. The cost of FRP plate and epoxy adhesive is included in the formulation of the objective function. The ultimate limit states and the serviceability limit states are included in formulation of constraints. A numerical example is given to show the validity of the proposed optimization method.

The Modified Quadrilateral Discretization Model for the Topology Optimization of Compliant Mechanisms

2011 ◽  
Vol 133 (11) ◽  
Author(s):  
Hong Zhou ◽  
Pranjal P. Killekar
Keyword(s):  
Topology Optimization ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Optimization Procedure ◽  
Local Stress ◽  
Optimization Method ◽  
Stress Constraint ◽  
Cell Problem ◽  
Design Variables ◽  
Design Cell

The modified quadrilateral discretization model for the topology optimization of compliant mechanisms is introduced in this paper. The design domain is discretized into quadrilateral design cells. There is a certain location shift between two neighboring rows of quadrilateral design cells. This modified quadrilateral discretization model allows any two contiguous design cells to share an edge whether they are in the horizontal, vertical, or diagonal direction. Point connection is completely eliminated. In the proposed topology optimization method, design variables are all binary, and every design cell is either solid or void to prevent gray cell problem that is usually caused by intermediate material states. Local stress constraint is directly imposed on each analysis cell to make the synthesized compliant mechanism safe. Genetic algorithm is used to search the optimum. No postprocessing is required for topology uncertainty caused by either point connection or gray cell. The presented modified quadrilateral discretization model and the proposed topology optimization procedure are demonstrated by two synthesis examples of compliant mechanisms.

An Aerodynamic Optimization Procedure for the Preliminary Design of Centrifugal Compressor Stages

2008 ◽  
Author(s):  
Omar Elshamy ◽  
Nidal Ghizawi ◽  
Ce´line Yon ◽  
Simone Pazzi ◽  
Denis Guenard
Keyword(s):  
Centrifugal Compressor ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Computational Time ◽  
Preliminary Design ◽  
Trial And Error ◽  
Aerodynamic Optimization ◽  
Peak Efficiency ◽  
Stage Design ◽  
Design Variables

This paper presents an automated aerodynamic optimization procedure for the preliminary design of centrifugal compressors. The proposed procedure interfaces a well-validated prediction tool with a GE in-house developed optimization code (PEZ). In GE Oil & Gas this tool is used to predict the performance of a single centrifugal compressor stage the outline of which requires more than thirty geometric parameters to be set. In the early phase of a new stage design, the designer manually varies all related parameters in the framework of a trial-and-error approach. The optimization procedure eliminates the inconvenience of a vast amount of manually launched simulations required by variations of the large number of design variables. Additionally, this procedure can perform trade-off studies and sensitivity analysis. In this case the optimization plan consists of a differential evolution (DE) genetic algorithm followed by a simplex-based optimization method (AMOEBA). The procedure was challenged with several existing designs by setting different objective/constraints combinations. The optimizer was often able to improve the predicted performance, as for an old 2D design where it was possible to increase the peak efficiency of approximately 2.6%. Also, the algorithm proved able to maximize the polytropic head (+12% with respect to baseline), while keeping unaltered both surge and choke limits. The computational time was about 40 hours per case on a Windows workstation (3.20 GHz, 3.5 GB RAM).

The Modified Quadrilateral Discretization Model for the Topology Optimization of Compliant Mechanisms

2011 ◽  
Author(s):  
Hong Zhou ◽  
Pranjal P. Killekar
Keyword(s):  
Topology Optimization ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Optimization Procedure ◽  
Local Stress ◽  
Optimization Method ◽  
Initial Guess ◽  
Stress Constraint ◽  
Design Variables ◽  
Conduct Sensitivity Analysis

The modified quadrilateral discretization model for the topology optimization of compliant mechanisms is introduced in this paper. The design domain is discretized into quadrilateral design cells. There is a certain location shift between two neighboring rows of quadrilateral design cells. This modified quadrilateral discretization model allows any two contiguous design cells to share an edge whether they are in the horizontal, vertical or diagonal direction. Point connection is completely eliminated. In the proposed topology optimization method, design variables are all binary and every design cell is either solid or void to prevent grey cell problem that is usually caused by intermediate material states. Local stress constraint is directly imposed on each analysis cell to make the synthesized compliant mechanism safe. Genetic algorithm is used to search the optimum and avoid the need to select the initial guess solution and conduct sensitivity analysis. No postprocessing is needed for topology uncertainty caused by point connection or grey cell. The presented modified quadrilateral discretization model and the proposed topology optimization procedure are demonstrated by two synthesis examples of compliant mechanisms.

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