Revista IBRACON de Estruturas e Materiais (Oct 2024)

Probabilistic bridge deterioration prediction models based on Markov matrices using real and simulated data from deterministic models

  • Christian Alexandre Feitosa de Souza,
  • José Maria Franco de Carvalho,
  • Ana Carolina Perreira Martins,
  • Fernando Gussão Bellon,
  • Matheus Sant’Anna Andrade,
  • Diogo Silva de Oliveira,
  • José Carlos Lopes Ribeiro,
  • Kleos Magalhães Lens Cesar Jr

DOI
https://doi.org/10.1590/s1983-41952024000100015
Journal volume & issue
Vol. 17, no. 1

Abstract

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Abstract This study uses real and simulated information from 885 bridges in Brazil. A total of 2,655 available inspection data were collected from the database, and 37,170 additional data were simulated from deterministic deterioration prediction models developed in previous studies. The probabilistic Markov matrices-based models obtained include one covering all the bridges, specific models for non-aggressive and aggressive environments, and models for Average Daily Traffic (ADT) of less than and more than 4,000. Validation showed good metrics, with a coefficient of determination of 0.6268, a mean absolute error and mean squared error below 0.5, and an accuracy of 66.25%. Finally, these tools enable more accurate forecasting, and a better understanding of the risks associated with the deterioration of structures for safe and cost-effective bridge management.

Keywords