Development of hybrid optimization algorithm for structures furnished with seismic damper devices using the particle swarm optimization method and gravitational search algorithm

Ayyash, Najad; Hejazi, Farzad

Abstract

Previous studies about optimizing earthquake structural energy dissipation systems indicated that most existing techniques employ merely one or a few parameters as design variables in the optimization process, and thereby are only applicable only to simple, single, or multiple degree-of-freedom structures. The current approaches to optimization procedures take a specific damper with its properties and observe the effect of applying time history data to the building; however, there are many different dampers and isolators that can be used. Furthermore, there is a lack of studies regarding the optimum location for various viscous and wall dampers. The main aim of this study is hybridization of the particle swarm optimization (PSO) and gravitational search algorithm (GSA) to optimize the performance of earthquake energy dissipation systems (i.e., damper devices) simultaneously with optimizing the characteristics of the structure. Four types of structural dampers device are considered in this study: (i) variable stiffness bracing (VSB) system, (ii) rubber wall damper (RWD), (iii) nonlinear conical spring bracing (NCSB) device, (iv) and multi-action stiffener (MAS) device. Since many parameters may affect the design of seismic resistant structures, this study proposes a hybrid of PSO and GSA to develop a hybrid, multi-objective optimization method to resolve the aforementioned problems. The characteristics of the above-mentioned damper devices as well as the section size for structural beams and columns are considered as variables for development of the PSO-GSA optimization algorithm to minimize structural seismic response in terms of nodal displacement (in three directions) as well as plastic hinge formation in structural members simultaneously with the weight of the structure. After that, the optimization algorithm is implemented to identify the best position of the damper device in the structural frame to have the maximum effect and minimize the seismic structure response. To examine the performance of the proposed PSO-GSA optimization method, it has been applied to a three-story reinforced structure equipped with a seismic damper device. The results revealed that the method successfully optimized the earthquake energy dissipation systems and reduced the effects of earthquakes on structures, which significantly increase the building’s stability and safety during seismic excitation. The analysis results showed a reduction in the seismic response of the structure regarding the formation of plastic hinges in structural members as well as the displacement of each story to approximately 99.63%, 60.5%, 79.13% and 57.42% for the VSB device, RWD, NCSB device, and MAS device, respectively. This shows that using the PSO-GSA optimization algorithm and optimized damper devices in the structure resulted in no structural damage due to earthquake vibration.

• Journal Article Type: Article
• Acceptance Date: Feb 18, 2021
• Online Publication Date: Apr 20, 2022
• Publication Date: Apr 1, 2022
• Deposit Date: Nov 1, 2022
• Publicly Available Date: Apr 2, 2023
• Journal: Earthquake Engineering and Engineering Vibration
• Print ISSN: 1671-3664
• Electronic ISSN: 1993-503X
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 21
• Issue: 2
• Pages: 455-474
• DOI: https://doi.org/10.1007/s11803-022-2088-1
• Keywords: Mechanical Engineering; Geotechnical Engineering and Engineering Geology; Building and Construction; Civil and Structural Engineering; Hybrid optimization algorithm; Structures; Earthquake; Seismic damper devices; Particle swarm optimization method; Gravitational search algorithm
• Public URL: https://uwe-repository.worktribe.com/output/10112214
• Publisher URL: https://link.springer.com/article/10.1007/s11803-022-2088-1
• Additional Information: Received: 12 May 2020; Accepted: 18 February 2021; First Online: 20 April 2022