مهسا زندي

The present study focuses on exploring the effects of geometrical imperfections and different analysis methods on the optimum design of Double-Layer Grids (DLGs). A total of 12 notable meta-heuristic algorithms (MAs) are assessed and contrasted, and as a result, the Slime Mold Algorithm (SMA) is identified as the most effective approach for the size optimization of DLGs. To eva‎luate the influence of geometric imperfections and nonlinearity on the minimum weight design of DLGs, the optimization process is carried out by considering and disregarding geometric nonlinearity while incorporating three distinct forms of geometrical imperfections, namely local imperfections, global imperfections, and a combination of both. In light of the uncertain nature of geometrical imperfections, which may include the initial curvature of individual members and nodal installation errors, probabilistic distributions are used to define these imperfections randomly in direction and magnitude. To illustrate the importance of considering geometric imperfections and adopting geometric nonlinear behavior in the optimization process, this study analyzed three real-size DLGs. The results demonstrate that it is necessary to account for these imperfections to obtain a reliable optimal solution. The analysis also revealed that the initial curvature of members has a more significant impact on the optimal design of structures than the nodal installation error, indicating the need for greater attention to local imperfection issues in space structure construction. In addition, this study indicates a positive correlation between the size of the optimal DLG and its sensitivity to the analysis approach.

شبكه‌هاي‌ دولايه , بهينه‌سازي اندازه , الگوريتم‌هاي فراابتكاري , نواقص هندسي , رويكردهاي تحليل

Double-layer grid , Sizing optimization , Metaheuristic algorithms , Geometrical imperfections , Analysis approach

Mahsa Zandi

Dr. Majid Ilchi Ghazaan