Sensitivity analysis in seismic reliability of an urban self-anchored suspension bridge. (1st February 2022)

• Record Type: Journal Article
• Authors: Xia, Zhiyuan; Quek, Ser Tong; Li, Aiqun; Li, Jianhui; Duan, Maojun; Zhou, Guangpan; Shi, Huiyuan
• Is Part Of: Mechanical systems and signal processing. Volume 164(2022)
• Publication Date: 2022-02-01
• Subjects: Sensitivity analysis -- Seismic reliability -- Failure probability -- Self-anchored suspension bridge -- Subset simulation -- Explicit time domain method; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.108231
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A sampling-based method to solve sensitivity in seismic reliability was proposed. The proposed method considers the correlation of structural parameters. The application to a real self-anchored suspension bridge was conducted. The accuracy of the approach was acceptable compared by direct FEM. The method has higher efficiency in computing sensitivity for seismic reliability. Abstract: Seismic resistance and disaster prevention for self-anchored suspension bridge (SASB) are important, but the seismic reliability of this complex structure is time-consuming or low-accuracy based on existing methods, let alone the relative sensitivity analysis. A sampling-based hybrid methodology of sensitivity analysis in seismic reliability, combining subset simulation (SuS), explicit time domain method (ETDM), BP neural network (BPNN) and Pearson's Linear Correlation Coefficient (PLCC), is proposed herein. The separated treatment of low and high variabilities of structural and earthquake parameters based on ETDM with BPNN accelerates the computing efficiency. With the application to the SASB, sensitivities of structural parameters to seismic reliability are obtained, where three largest ones are ambient temperature, Young's modulus and density of girder. The failure probability of this bridge is mostly smaller than 1.0 × 10 -3, but it takes only about 10 ~ 15 min to obtain single failure probability with a deterministic parameter vector based on the proposed method, which is in lieu of hundreds of days based on Monte Carlo simulation. Hence, it is verified a sound approach with great accuracy and efficiency used in engineering structures.