A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Computer-aided dynamic structural optimization using an advanced swarm algorithm
Abstract Natural frequencies, which are relatively easy parameters to obtain, provide efficient information about the dynamic behavior of structures. Controlling these parameters can help to minimize the destructive effect of dynamic loads on structures. However, the optimal design of the size and shape of truss structures with controlling dynamic constraints is an expensive problem. While frequency constraints are nonlinear and non-convex, handling natural frequencies as constraints is a challenging task, which prevents the phenomenon of resonance, large deformations, and destruction of a structure. Also, reducing the vibration amplitude of a structure would reduce the stress and deflections. In this paper, the Improved Marine Predators Algorithm (IMPA) is proposed and implemented for size and shape optimization of truss structures subject to natural frequency constraints. In this method, a Novel CF (NCF) factor is introduced to control the predator's step size when looking for prey. To evaluate the performance of IMPA, the optimum weight of structures under dynamic constraints was computationally investigated. To demonstrate the efficiency and robustness of IMPA, 37-bar truss bridge, 52-bar dome, 72-bar space truss, 120-bar dome, 200-bar planar truss, and 600-bar dome truss were optimized. Compared to other state-of-the-art algorithms, the results indicate that IMPA performs better in solving these nonlinear structural optimization problems.
Highlights Marine Predators Algorithm Improved based on a new strategy. A novel formula is proposed for CF factor. engineering problems with dynamic constraints are investigated to prove the capabilities of new swarm algorithm. The results are compared with state-of-the-art swarm algorithms.
Computer-aided dynamic structural optimization using an advanced swarm algorithm
Abstract Natural frequencies, which are relatively easy parameters to obtain, provide efficient information about the dynamic behavior of structures. Controlling these parameters can help to minimize the destructive effect of dynamic loads on structures. However, the optimal design of the size and shape of truss structures with controlling dynamic constraints is an expensive problem. While frequency constraints are nonlinear and non-convex, handling natural frequencies as constraints is a challenging task, which prevents the phenomenon of resonance, large deformations, and destruction of a structure. Also, reducing the vibration amplitude of a structure would reduce the stress and deflections. In this paper, the Improved Marine Predators Algorithm (IMPA) is proposed and implemented for size and shape optimization of truss structures subject to natural frequency constraints. In this method, a Novel CF (NCF) factor is introduced to control the predator's step size when looking for prey. To evaluate the performance of IMPA, the optimum weight of structures under dynamic constraints was computationally investigated. To demonstrate the efficiency and robustness of IMPA, 37-bar truss bridge, 52-bar dome, 72-bar space truss, 120-bar dome, 200-bar planar truss, and 600-bar dome truss were optimized. Compared to other state-of-the-art algorithms, the results indicate that IMPA performs better in solving these nonlinear structural optimization problems.
Highlights Marine Predators Algorithm Improved based on a new strategy. A novel formula is proposed for CF factor. engineering problems with dynamic constraints are investigated to prove the capabilities of new swarm algorithm. The results are compared with state-of-the-art swarm algorithms.
Computer-aided dynamic structural optimization using an advanced swarm algorithm
Goodarzimehr, Vahid (author) / Talatahari, Siamak (author) / Shojaee, Saeed (author) / Gandomi, Amir H. (author)
Engineering Structures ; 300
2023-11-12
Article (Journal)
Electronic Resource
English
Water Distribution System Computer‐Aided Design by Agent Swarm Optimization
| Online Contents | 2014
An optimum structural computer-aided design using hybrid genetic algorithm
| British Library Conference Proceedings | 2006
A Hybrid Particle Swarm—Gradient Algorithm for Global Structural Optimization
| Online Contents | 2011