Toward a Comprehensive Pavement Reliability Analysis Approach

Yared Dinegdae*, Abubeker Ahmed, Sigurdur Erlingsson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Reliability has been incorporated in pavement design tools to account for input variability influence on predicted performance. As they are not based on a probabilistic method of uncertainty propagation, the reliability analysis methodologies that are currently implemented in pavement performance tools lack rigor and robustness. This paper investigates the potential of three reliability analysis methodologies for pavement application: the Pavement ME reliability analysis methodology, Monte Carlo simulation (MCS), and the first-order reliability method (FORM). The MCS and FORM involve a response surface method for the generation of a second-order surrogate model. The investigation was performed using inputs and performance data from accelerated pavement testing structures. Inputs that were identified as significant were characterized as random variables and their associated variability was established using measured structural and material properties. Pavement performance with respect to rutting was predicted using the ERAPave performance prediction tool, while MCS was used to generate the actual variability of the distress. The reliability analysis results have shown that a comprehensive reliability analysis methodology is required that effectively captures input variabilities and the error associated with surrogate models.

Original languageEnglish
Pages (from-to)680-692
Number of pages13
JournalTransportation Research Record
Volume2677
Issue number7
DOIs
Publication statusPublished - 21 Feb 2023

Bibliographical note

Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2023.

Other keywords

  • ERAPave PP
  • FORM
  • MCS
  • pavement ME
  • reliability
  • RSM
  • variability

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