Optimization of Stacking Sequence of Composite Laminates for Optimizing Buckling Load by Neural Network and Genetic Algorithm

Hajmohammad, Mohammad Hadi; Salari, Mostafa; Hashemi, Seyed Ali Asghar; Esfe, Mohammad Hemmat

doi:10.17485/ijst/2013/v6i8.22

Cited by 16 publications

(6 citation statements)

References 11 publications

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“…Then, when ply 3 is being chosen it is necessary to consider 2 9 and 4 8 simultaneously because 4 8 was chosen in the previous case and is fixed in this case. So if 4 8 is 90°, 3 9 can only become -45° or +45°. As for the minimum percentage constraint, this has been included with the lamination parameters constraints in the first stage.…”

Section: Addition Of Constraintsmentioning

confidence: 99%

“…Todoroki and Ishikawa [3] used a response surface to obtain the buckling load with reduced computational cost. Hajmohammad et al [4] employed an artificial neural network in their optimization to replace FEA when determining the buckling load of composite plates. An alternative to these methods is the exact finite strip approach for obtaining the buckling and postbuckling behaviour for prismatic plate assemblies [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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Two-level layup optimization of composite laminate using lamination parameters

Liu

Featherston

Kennedy

2019

Composite Structures

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This paper provides an efficient method for performing global layup optimization of composite laminates with buckling and manufacturing constraints. The optimization problem is divided into two stages and is based on the use of lamination parameters. During the first stage, exact finite strip analysis and continuous optimum design are employed for buckling optimization of the lamination parameters and laminate thickness. In the second stage, a logic-based procedure combining the branch and bound method with a global layerwise technique is employed to find the optimal stacking sequences to match the optimized lamination parameters obtained in the first stage. In order to ensure the optimized layup can be used in practice, four manufacturing constraints are added into the logical search process, and the feasible region for the lamination parameters with a manufacturing constraint which requires at least 10% of each of four possible ply orientations is studied. By comparing the logic-based method with the use of a genetic algorithm for searching stacking sequences under different requirements, the high efficiency and ability to achieve a global optimal result of the logic-based method are demonstrated.

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Section: Addition Of Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Two-level layup optimization of composite laminate using lamination parameters

Liu

Featherston

Kennedy

2019

Composite Structures

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“…More so, in some cases it is not very clear how to choose when to discontinue getting a good system. It is also uncertain how fit the LCA might generalize to diverse situations in these cases 83 . Most of the related LCA literatures show that some enhancements need to be done to suite a particular situation.…”

Section: Generalizationmentioning

confidence: 99%

A Survey of League Championship Algorithm: Prospects and Challenges

Abdulhamid¹,

Latiff²,

Madni³

et al. 2015

Indian Journal of Science and Technology

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The League Championship Algorithm (LCA) is sport-inspired optimization algorithm that was introduced by Ali Husseinzadeh Kashan in the year 2009. It has since drawn enormous interest among the researchers because of its potential efficiencyinsolvingmanyoptimizationproblemsandreal-worldapplications.TheLCAhasalsoshowngreat potentialsinsolvingnon-deterministicpolynomialtime(NP-complete)problems.Thissurveypresentsabriefsynopsisof theLCA literaturesinpeer-reviewedjournals,conferencesandbookchapters.Theseresearcharticlesarethen categorized according to indexing in the major academic databases (Web of Science, Scopus, IEEE Xplore and the Google Scholar). The analysis was also done to explore the prospects and the challenges of the algorithm and its acceptability among researchers. This systematic categorization can be used as a basis for future studies. Big Data and Data Mining Search technique 37 , resource allocation 38 , resource management 39 , etc. Mobile Computing and Sensor Networks Resource allocation 40 , energy conservation problem 41 , resource distribution 42 , search technique 43 , etc. Engineering Design Toy problem 44,45 , chaotic sequences 46 , Cognitive engineering design problem 47 , structural design problem 48 , etc. Networks and Distributed (i.e. parallel, grid and cloud) Systems Routing problem 49,50 , assignment problem 40,51 , resource allocation 52 and resource distribution 53 , etc. Graph Colouring Assignment problem 54,55 . Resource Constrained Projects Resource allocation 56,57 , resource distribution 58 and scheduling 59 . Machine Learning Learning of classification rules 60,61 , Learning the Structure of Bayesian Networks 62 , learning rules in a fuzzy system 63 and quadratic assignment problem 64 . University Timetable Resources allocation 65 and scheduling 66,67 . Subset Problems Multiple knapsack problem 68-70 , maximum independent set problem 71-73 , maximum clique problem 74,75 and redundancy allocation problem 76,77 , etc. Other Applications Open shop 78 and group shop scheduling 79 , permutation flow shop problem 80 , set covering problem 81 , 2D-HP Protein Folding 82 , etc.

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“…Hajmohammad et al, [6] use Genetic Algorithm combined with Neural Networks function to optimize buckling load subjected by varying stacking sequence. Zhao et al, [7] also optimized buckling load by varying stacking sequence but by using Permutation Search Algorithm.…”

Section: Introductionmentioning

confidence: 99%

Stress Analysis of Composite Aircraft Wing using Coupled Fluid-Structural Analysis

Ali

Haron

2021

CFDL

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Aircraft wings are designed with very low factor of safety to keep the aircraft weight minimum. Thus, for safe design of wings, stress analysis should be carried out under accurately estimated aerodynamic loads and this can be achieved only through coupled fluid-structure analysis. Moreover, modern aircraft wings are made of laminated composite structures and thus the purpose of this study is to employ ANSYS coupled fluid-structure analysis to find the best layup of composite wing of an aircraft that results in higher specific strength and specific stiffness. Firstly, Computational Fluid Dynamics (CFD) analysis has been carried out to find the actual aerodynamic load which is the pressure distribution around a three-dimensional wing. Then, this pressure distribution from CFD was used as a load input for detailed static structural analysis of the wing. Initially, strength and stiffness of an isotropic wing is evaluated and then the material of the wing was changed to composite laminates to achieve better structural performance with higher strength and stiffness to weight ratio. Stress analysis was carried out for different layups to predict the optimum layup that results in high strength and stiffness coupled with the least weight and it was found that the wing made of symmetric cross-ply laminate performs the best.

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Optimization of Stacking Sequence of Composite Laminates for Optimizing Buckling Load by Neural Network and Genetic Algorithm

Cited by 16 publications

References 11 publications

Two-level layup optimization of composite laminate using lamination parameters

Two-level layup optimization of composite laminate using lamination parameters

A Survey of League Championship Algorithm: Prospects and Challenges

Stress Analysis of Composite Aircraft Wing using Coupled Fluid-Structural Analysis

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