Akademik Veri Yönetim Sistemi
Structures, cilt.70, 2024 (SCI-Expanded)
This article explores the optimal design of curved steel structures with a focus on minimizing their weight by determining the most suitable cross-sections. Customized optimization algorithms were developed to identify structural designs that meet safety and durability requirements, adhering to design constraints set by the ASD-AISC specification. To ensure reliable results, the study employs a variety of metaheuristic optimization methods: Biogeography-Based Optimization (BBO), Dynamic Harmony Search (DHS), Wolf Colony Algorithm (WCA), and Honey Badger Algorithm (HBA). The Honey Badger Algorithm, a relatively new addition to the field, was used for the first time in the context of structural optimization for curved roof systems. This unique approach aims to evaluate its performance in civil engineering problems and compare it with other established algorithms. The major challenges of this study lie in the inherent complexity of dome structures, which involve a large number of elements and nonlinear constraints. The subdivision of the structure into smaller groups was necessary to manage the computational load, although this introduced additional complexities. Despite these challenges, the metaheuristic methods demonstrated their robustness in addressing such intricate engineering problems. Additionally, data retrieval is facilitated through Open Application Interface (OAPI) functions, enabling seamless data transfer between SAP 2000 and Visual Basic. The study's final design example involves a dome model with 2556 elements, which was both modeled and optimized. The results demonstrate the effectiveness of these optimization algorithms in achieving structurally sound and efficient designs. The insights gained from this study contribute to our understanding of optimized cross-sections in curved steel structures, offering valuable guidance for improving structural performance and minimizing material usage.