Skip to main navigation Skip to search Skip to main content

Probability evaluation method for cable safety of long span suspension bridges under extreme wind load

  • Jun Hu*
  • , Jinping Ou
  • *Corresponding author for this work
  • Dalian University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The cable is the main load-bearing component of suspension bridge and its safety assessment under extreme wind load is a key issue to the structure. Take a long-span suspension bridge in the East Sea China as an example, the standard of extreme wind load for structural safety evaluation is established; the wire's strength model is established by the type I extreme value distribution; cable's safety assessment function under wind load is established and the Monte Carlo method is used to get the cable's reliability and reliable indicators. The bridge's re-service term is taken for 90 years as an example, the results indicate that the wire's serial effects can't be ignored, the cable's reliable indicator decreases as the number of broken wires increases in approximately the linear attenuation relations, the critical percentage of broken wires is about 10%.

Original languageEnglish
Title of host publicationAdvances in Structures
Pages3223-3229
Number of pages7
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 International Conference on Structures and Building Materials, ICSBM 2011 - Guangzhou, China
Duration: 7 Jan 20119 Jan 2011

Publication series

NameAdvanced Materials Research
Volume163-167
ISSN (Print)1022-6680

Conference

Conference2011 International Conference on Structures and Building Materials, ICSBM 2011
Country/TerritoryChina
CityGuangzhou
Period7/01/119/01/11

Keywords

  • Extreme wind
  • Monte carlo method
  • Safety evaluation
  • Suspension cable

Fingerprint

Dive into the research topics of 'Probability evaluation method for cable safety of long span suspension bridges under extreme wind load'. Together they form a unique fingerprint.

Cite this