Sensitivity and Reliability Analysis of a Self-Anchored Suspension Bridge

This paper presents a sensitivity and reliability analysis of a self-anchored suspension bridge by applying a new hybrid method proposed by the authors based on integration of the Latin hypercube sampling technique (LHS), artificial neural network (ANN), first-order reliability method (FORM), Pearson’s linear correlation coefficient (PLCC), and Monte Carlo simulation with important sampling technique (MCS-IS). The framework consists of three stages of analysis: (1) selection of training, validation, and test datasets for establishing an ANN model by the LHS technique; (2) formulation of a performance function from the well-trained ANN model; and (3) sensitivity analysis using PLCC, identification of the most probabilistic failure point based on FORM, and estimation of the failure probability using the MCS-IS technique. Upon demonstration of its efficiency through analysis of a 12-story frame structure, the method is applied to sensitivity and reliability analysis of the Jiangxinzhou Bridge, a five-span self-anchored suspension bridge, in which both structural parameters and external loads are considered as random variables. The analysis identified a number of structural parameters, as well as external loads, that have a significant influence on structural serviceability and safety.

• Record URL:
  • https://doi.org/10.1061/(ASCE)BE.1943-5592.0000424
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/32947845
• Supplemental Notes:
  • Copyright © 2013 American Society of Civil Engineers.
• Authors:
  • Li, Jianhui
  • Li, AiQun
  • Feng, Maria Q
• Publication Date: 2013-8

Language

• English

Media Info

• Media Type: Print
• Features: References;
• Pagination: pp 703-711
• Serial:
  • Journal of Bridge Engineering
  • Volume: 18
  • Issue Number: 8
  • Publisher: American Society of Civil Engineers
  • ISSN: 1084-0702
  • Serial URL: http://ojps.aip.org/beo

Subject/Index Terms

• TRT Terms: Bridge anchorages; Bridge substructures; Bridge superstructures; Mathematical models; Mechanical failure; Monte Carlo method; Neural networks; Reliability; Sensitivity analysis; Serviceability; Statistical sampling; Structural health monitoring; Suspension bridges; Traffic loads
• Identifier Terms: Jiangxinzhou Bridge (China)
• Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation; I24: Design of Bridges and Retaining Walls; I60: Maintenance;

Filing Info

• Accession Number: 01493518
• Record Type: Publication
• Files: TRIS, ASCE
• Created Date: Sep 20 2013 4:26PM