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Notice of Retraction: Stochastic process model of vehicle loads based on structural health monitoring data and maximum prediction of general renewal processes

  • Hui Li*
  • , Fujian Zhang
  • *Corresponding author for this work
  • School of Civil Engineering, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Vehicle loads are the most important live load on bridges. It's significant to study the maximum vehicle load in serving period for bridge design, maintenance and safetye-valuation. Stochastic process, such as Possion process or Erlang process, is a powerful model for understanding vehicle loads. While Possion process or Erlang process is only fit for vehicle load acting on one specific bridge, but not fit for the complex vehicle load cases. In this paper, the general gamma process model are used to calculate vehicle load maximum CDF for both loose status and dense status, and maximum CDF prediction method for general renewal processes are put forward to study vehicle load maximum and it's CDF. The numerical results show good agreement with the Yangtze River bridge health monitoring in-field data, which prove the suitability and practicability of the numerical simulation, and provide a reference for the actual project.

Original languageEnglish
Title of host publicationICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings
PublisherIEEE Computer Society
PagesV4704-V4708
ISBN (Print)9781424472369
DOIs
StatePublished - 2010
Externally publishedYes

Publication series

NameICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings
Volume4

Keywords

  • Maximum cumulative distribution function
  • Renewal stochastic process
  • Vehicle load

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