GP provided significant time gain in deriving sets of equations for thermal stress analysis of plates with current boundary conditions.
📌 3 Key Takeaways
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Objective & Hypothesis:In this study, the sets of equation were extracted by Genetic Programming (GP) for thermal stress analysis of one-dimensional functionally graded rectangular plates.
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Key Findings & Data:The models achieved these levels 100 times faster than the finite difference method by using GP.
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Conclusion & Impact:GP provided significant time gain in deriving sets of equations for thermal stress analysis of plates with current boundary conditions.
In this study, the sets of equation were extracted by Genetic Programming (GP) for thermal stress analysis of one-dimensional functionally graded rectangular plates. First, thermal stress analyses were performed using a finite difference method for a sufficient number of compositional gradient exponents. Then, equation sets were obtained by the GP using the maximum and minimum equivalent stress levels obtained from these analyses. Appropriate models are produced for equivalent stress levels at compositional gradient exponents. The models achieved these levels 100 times faster than the finite difference method by using GP. GP provided significant time gain in deriving sets of equations for thermal stress analysis of plates with current boundary conditions.
DEMİRBAŞ, M. D., ÇAKIR, D., ARSLAN, S., ÖZTÜRK, C. (2018). Equivalent Stress Analysis of Functionally Graded Rectangular Plates by Genetic Programming. International Scientific and Vocational Studies Journal, Cilt: 2 - Sayı: 1, 67–80. https://ajindex.com/articles/769839
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