Skip to main navigation Skip to search Skip to main content

Quantitative risk assessment of road posed by levee slope failure: A novel framework integrating Monte Carlo simulation and material point method

  • Harbin Institute of Technology Shenzhen
  • Nanjing Hydraulic Research Institute

Research output: Contribution to journalArticlepeer-review

Abstract

The frequent occurrence of extreme rainfall events often triggers levee slope failure (LSF), which, due to the “levee effect”, significantly damages the roads behind the levee. This paper presents a novel framework for the quantitative risk assessment of roads posed by LSF. Within the framework, the innovative integration of Monte Carlo simulation (MCS) and Material point method (MPM) provides a unique solution for simulating the complicated dynamic relationship between LSF and road destruction. MCS generates precise failure scenarios for MPM simulations, overcoming the limitations of traditional approaches in addressing uncertainty in complex scenario systems. With its technical superiority in capturing post-failure deformations, MPM offers critical insights for assessing road exposure and vulnerability. The framework also accounts for indirect losses from road disruptions, which have long been overlooked. The application of the framework to the risk assessment of the road behind the Shijiao Levee in the Pearl River Basin fully demonstrates its practicality and robustness. Compared to traditional risk assessment methods, the proposed framework provides a more refined dynamic evaluation, facilitating the formulation of more effective disaster mitigation strategies.

Original languageEnglish
Article number108148
JournalEngineering Geology
Volume353
DOIs
StatePublished - 25 Jun 2025
Externally publishedYes

Keywords

  • Levee slope failure
  • Material point method (MPM)
  • Monte Carlo simulation (MCS)
  • Risk assessment framework
  • Road risk

Fingerprint

Dive into the research topics of 'Quantitative risk assessment of road posed by levee slope failure: A novel framework integrating Monte Carlo simulation and material point method'. Together they form a unique fingerprint.

Cite this