Data-Driven Model for Risk Assessment of Cable Fire in Utility Tunnels Using Evidential Reasoning Approach

• Published in: 东华大学学报（英文版） Vol. 40; no. 2; pp. 202 - 215
• Main Authors: PENG Xin, YAO Shuaiyu, HU Hao, DU Shouji
• Format: Journal Article
• Language: English
• Published: School of Naval Architecture,Ocean&Civil Engineering,Shanghai Jiao Tong University,Shanghai 200240,China 01.04.2023
• Subjects: risk assessment; evidential reasoning(ER); operation and maintenance(O&M); underground utility tunnel(UUT)
• ISSN: 1672-5220
• DOI: 10.19884/j.1672-5220.202111008

TP374.2; Cable fire is one of the most important events for operation and maintenance(O&M)safety in underground utility tunnels(UUTs).Since there are limited studies about cable fire risk assessment,a comprehensive assessment model is proposed to evaluate the cable fire risk in different UUT sections and improve O&M efficiency.Considering the uncertainties in the risk assessment,an evidential reasoning(ER)approach is used to combine quantitative sensor data and qualitative expert judgments.Meanwhile,a data transformation technique is contributed to transform continuous data into a five-grade distributed assessment.Then,a case study demonstrates how the model and the ER approach are established.The results show that in Shenzhen,China,the cable fire risk in District 8,B Road is the lowest,while more resources should be paid in District 3,C Road and District 25,C Road,which are selected as comparative roads.Based on the model,a data-driven O&M process is proposed to improve the O&M effectiveness,compared with traditional methods.This study contributes an effective ER-based cable fire evaluation model to improve the O&M efficiency of cable fire in UUTs.