Optimal dome design considering member-related design constraints

Abstract

This study proposes to optimize the design of geometrically nonlinear dome structures. A new Multi-objective Optimization Algorithm named Pareto Archived Genetic Algorithm (PAGA), which has an ability of integrating the nonlinear structural analysis with the provisions of American Petroleum Institute specification is employed to optimize the design of ellipse and sphere-shaped dome configurations. Thus, it is possible to investigate how the qualities of optimal designations vary considering the shape, size, and topology-related design variables. Furthermore, the computing efficiency of PAGA is evaluated considering six multi-objective optimization algorithms and eight quality measuring indicators. It is shown that PAGA has a capability of both exploring an increased number of pareto solutions and predicting a pareto front with a higher convergence degree. Moreover, the inclusion of shape-related design variables leads to a decrease in both the weights of dome structures and their load-carrying capacities. However, the designer easily determines the most requested optimal design through the archiving feature of PAGA. Thus, it is also demonstrated that the proposed optimal design procedure increases the correctness degree in the evaluation of optimal dome designs through the tradeoff analysis. Consequently, PAGA is recommended as an optimization tool for the design optimization of geometrically nonlinear dome structures.

Keywords

dome structure / geometric nonlinearity / multi-objective optimization / API RP2A-LRFD

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