Multi-Objective Structural Optimization of a Large-Scale Spherical Public Aquarium Using FEM, ANN, and Genetic Algorithms

Authors

https://doi.org/10.48313/mtei.v1i3.65

Abstract

This paper discusses the design process and multi-objective optimization of a large public spherical aquarium with a cuboid inner viewing tunnel. The structural geometry of the space frame, composed of steel combined with acrylic panels supported by reinforced concrete, is modeled using the Finite Element Method (FEM). The hydrostatic pressure acting on the surface, the load due to visitors, and the dynamic force due to impacts from aquatic animals are accounted for in the structural analysis. To minimize computational cost, an Artificial Neural Network (ANN) surrogate model is created using Finite Element Analysis (FEA) output. After creating an ANN model, the problem is solved using a multi-objective Genetic Algorithm (GA), and the safety factor is maximized by minimizing structural weight. This research shows that the proposed hybrid FEM-ANN-GA model effectively determines the optimal acrylic panel thickness that meets the safety criteria. The optimal solution achieved has a total structural weight of approximately 9569 tons.     

Keywords:

Large-scale public aquarium, Structural optimization, Finite element method, Artificial neural network, Genetic algorithm, Hydrostatic loading, Acrylic structure

References

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Published

2024-09-26

Issue

Vol. 1 No. 3 (2024): Mechanical Technology and Engineering Insights (MTEI)

Section

Articles

How to Cite

Masoomi, H. ., & Nejati, F. . (2024). Multi-Objective Structural Optimization of a Large-Scale Spherical Public Aquarium Using FEM, ANN, and Genetic Algorithms. Mechanical Technology and Engineering Insights, 1(3), 170-179. https://doi.org/10.48313/mtei.v1i3.65

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