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Optimum Stacking Sequence Design of Composite Laminates for Maximum Buckling Load Capacity
In this chapter, metaheuristic algorithms are applied for maximizing the buckling capacity of laminated plates. Two loading types are considered as optimization problems: deterministic and uncertain loaded composite laminates. Furthermore, different cases with various panel aspect ratios, number of layers and materials are examined to provide the optimal configurations. To account for the uncertainty in loading, the anti-optimization approach is employed. Golden Section Search (GSS) is applied for finding a robust design based on worst-case biaxial compressive loading. The results are investigated from different perspectives and sensitivity analyses are performed.
Optimum Stacking Sequence Design of Composite Laminates for Maximum Buckling Load Capacity
In this chapter, metaheuristic algorithms are applied for maximizing the buckling capacity of laminated plates. Two loading types are considered as optimization problems: deterministic and uncertain loaded composite laminates. Furthermore, different cases with various panel aspect ratios, number of layers and materials are examined to provide the optimal configurations. To account for the uncertainty in loading, the anti-optimization approach is employed. Golden Section Search (GSS) is applied for finding a robust design based on worst-case biaxial compressive loading. The results are investigated from different perspectives and sensitivity analyses are performed.
Optimum Stacking Sequence Design of Composite Laminates for Maximum Buckling Load Capacity
Studies Comp.Intelligence
Kaveh, Ali (author) / Dadras Eslamlou, Armin (author)
Metaheuristic Optimization Algorithms in Civil Engineering: New Applications ; Chapter: 2 ; 9-50
2020-04-15
42 pages
Article/Chapter (Book)
Electronic Resource
English
British Library Online Contents | 2016
|British Library Online Contents | 2016
|British Library Online Contents | 2016
|British Library Online Contents | 2016
|British Library Online Contents | 2016
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