Year: 2025
Type: article
Abstract: Castellated beams have garnered increasing attention in various fields due to their aesthetically appealing design, diverse geometric shapes, environmental friendliness, and economic advantages in terms of time, cost, and performance. These beams particularly excel in resisting bending without increasing their weight. The novelty of this paper, is to optimize the performance of castellated beams by maximum vertical deflection, represented as the objective function. This is achieved by determining the optimal dimensions of the cross-section using three optimization algorithms: Gray Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Differential Evolution (DE). This study focuses on three different types of material for castellated beams: S235, S255, and S355. The results revealed that the PSO and DE algorithms produce very similar outcomes, while the GWO algorithm shows slightly different results. Overall, all three algorithms demonstrate good capability in engineering applications, with a slight preference for the PSO and DE algorithms.
Institution: İstanbul Gelişim Üniversitesi
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410085192