Research on the reliability assessment method of bridges incorporating transversely distributed damage information

As the throat of transportation system, bridge structure is a lifeline project related to the coordinated development of society and economy.Based on fuzzy mathematical theory, this paper adopts Gaussian subordinate degree function to quantitatively characterize the damage detection information of articulation joints, combines Latin hypercubic sampling method and response surface method, and proposes a reliability assessment method for bridges integrating transversely distributed damage information, and analyzes the bridge of a certain structure as an engineering case, compares the failure probability corresponding to the model outputs and the real damage degree under different damage degrees, and analyzes the change of reliability indexes with the damage degree under articulation joint damage and main plate damage conditions, respectively.Under the conditions of articulation joint damage and main plate damage, the changes of reliability indexes with the damage degree are analyzed.The results show that the narrower the width of the damage interval is, the closer the failure probability is to the value corresponding to the real damage degree, and the reliability of the bridge decreases with the increase of the articulation damage and the main plate damage, which illustrates the objectivity and reasonableness of the method proposed in this paper.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-16
DOI
https://doi.org/10.61091/jcmcc127b-487
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the reliability assessment method of bridges incorporating transversely distributed damage information

1 links
Journal of Combinatorial Mathematics and Combinatorial Computing
Structural Health Monitoring Techniques
article

Research on the reliability assessment method of bridges incorporating transversely distributed damage information

article en

Abstract

As the throat of transportation system, bridge structure is a lifeline project related to the coordinated development of society and economy.Based on fuzzy mathematical theory, this paper adopts Gaussian subordinate degree function to quantitatively characterize the damage detection information of articulation joints, combines Latin hypercubic sampling method and response surface method, and proposes a reliability assessment method for bridges integrating transversely distributed damage information, and analyzes the bridge of a certain structure as an engineering case, compares the failure probability corresponding to the model outputs and the real damage degree under different damage degrees, and analyzes the change of reliability indexes with the damage degree under articulation joint damage and main plate damage conditions, respectively.Under the conditions of articulation joint damage and main plate damage, the changes of reliability indexes with the damage degree are analyzed.The results show that the narrower the width of the damage interval is, the closer the failure probability is to the value corresponding to the real damage degree, and the reliability of the bridge decreases with the increase of the articulation damage and the main plate damage, which illustrates the objectivity and reasonableness of the method proposed in this paper.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127b
Openalex Percentile: Top 91%
Structural Health Monitoring Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.