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    Optimum design of liquefied petroleum gas (LPG) composite cylinders by genetic algorithm research method
    (Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü, 2024) Mouchane, Brahim; Baştürk, Süleyman
    The optimum design of composite cylinders is crucial for achieving a balance between structural integrity, weight reduction, and cost-effectiveness propelled by the widespread utilization of fiber-reinforced composite materials in numerous engineering applications. This study presents a novel procedure by employing the Genetic Algorithm (GA) research method to optimize the design parameters of LPG composite cylinders. The Genetic Algorithm, inspired by natural selection and genetic principles, is employed to search the design space efficiently. The optimization process considers various factors, including material properties, cylinder geometry, and safety standards, to achieve a composite cylinder design that maximizes performance while meeting regulatory requirements. The objective is to find the composite cylinder's optimum ply angle and stacking sequence while maintaining the necessary strength and safety margins. The Genetic Algorithm explores the solution space through iterative generations of candidate designs, evolving toward the optimal configuration. The algorithm integrates fitness functions that assess the first-ply failure using classical laminate theory, ensuring convergence toward an optimal solution. The findings illustrate the efficacy of employing the Genetic Algorithm to attain an optimal design for maximizing failure pressure under mechanical and thermal loads. This study explores various criteria and materials for hybrid and non-hybrid composite cylinders, evaluating the best design based on cylinder structural efficiency.
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    Optimum design of liquefied petroleum gas (LPG) composite hybrid and non-hybrid cylinders by genetic algorithm for maximum failure pressure
    (Springer Science and Business Media B.V., 2025) Mouchane, Brahim; Baştürk, Süleyman
    Optimizing the design of composite cylinders is crucial for balancing structural integrity, weight reduction, and cost-effectiveness, especially with the widespread use of fiber-reinforced materials in many engineering applications. This study presents a novel approach using Genetic Algorithms to optimize liquefied petroleum gas (LPG) composite cylinders for maximum failure pressure by MATLAB software. Inspired by natural selection, the Genetic Algorithm efficiently explores design variations, considering different materials and cylinder geometries. The main goal of this study is to find the best ply angle and stacking sequence to maximize failure pressure for hybrid and non-hybrid composite cylinders. The maximum stress and Tsai–Wu criteria are used together to predict failure. The algorithm converges towards an optimal design through iterative generations, evaluated using fitness functions based on classical laminate theory. The results demonstrate the effectiveness of this approach in achieving an optimal design under mechanical and thermal loads. The optimization process exhibits strong sensitivity to the selected failure criterion, with the Tsai-Wu and Maximum Stress theories generating fundamentally different optimal configurations. For example, design I under mechanical loads, the Tsai-Wu failure criterion based GA finds that the optimal solution for carbon epoxy is [-89/-50/56/-50/-51/-503/563/-50/56/-50/57/-502/565/57/-502/56]s. In contrast, for the maximum stress failure criterion based GA, the optimal solution is [512 /-50/512/-502/51/-50/51/-50/522/-502/523/-502/52/-50/51/-503]s. The analysis under combined mechanical and thermal loading highlights significant performance constraints driven by temperature variations, uncovering distinct operational regimes. Within a limited thermal range, several viable stacking sequences are achievable; however, outside this window, only simplified—yet less optimal—designs remain feasible. For example, carbon epoxy, both GA identified that [9026]s is the optimal configuration. Numerical findings provide insights for hybrid and non-hybrid composite cylinders, assessing the best design based on cylinder structural efficiency and the cylinder cost.