Dealing with uncertainty in sewer condition assessment: Impact on inspection programs

被引:15
|
作者
Roghani, Bardia [1 ]
Cherqui, Frederic [2 ]
Ahmadi, Mehdi [3 ]
Le Gauffre, Pascal [2 ]
Tabesh, Massoud [4 ]
机构
[1] Univ Tehran, Coll Engn, Sch Civil Engn, Tehran, Iran
[2] INSA Lyon, DEEP, F-69621 Villeurbanne, France
[3] SINTEF, Oslo, Norway
[4] Univ Tehran, Coll Engn, Sch Civil Engn, Ctr Excellence Engn & Management Civil Infrastruc, Tehran, Iran
关键词
Asset management; Uncertainty; Sewer inspection program; Deterioration model; Condition assessment; VISUAL INSPECTION; DECISION-SUPPORT; DETERIORATION; PERFORMANCE;
D O I
10.1016/j.autcon.2019.03.012
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Sewer condition prediction is a fundamental element of proactive maintenance programs. The prediction relies mostly on the assessed condition of inspected segments, generally based on CCTV reports. However, several sources of uncertainty affect the condition assessment and may lead to inefficient maintenance. The present article focuses on three main questions. 1. What is the impact of uncertainty in assessed condition on the prediction model? 2. Considering uncertainties in the assessed condition, is it necessary to collect data on the characteristics of many segments, or are a small number of influential variables enough to build the condition prediction model? 3. Is it better to overestimate (false positive) or underestimate (false negative) the deterioration of a segment? These questions were evaluated on a semi-virtual asset stock and the results confirm that uncertainties affect the inspection efficiency negatively. Results also show that errors leading to the overestimation of the deterioration have less negative impact. The study suggests that data from a small number of influential segments is adequate to inform the prediction model.
引用
收藏
页码:117 / 126
页数:10
相关论文
共 50 条
  • [21] Dealing with uncertainty in flood risk assessment of dike rings in the netherlands
    Van der Most, H
    Wehrung, M
    NATURAL HAZARDS, 2005, 36 (1-2) : 191 - 206
  • [22] A review of uncertainty effect in structural condition assessment
    Hao, Hong
    Xia, Yong
    9TH INTERNATIONAL CONFERENCE ON INSPECTION APPRAISAL REPAIRS & MAINTENANCE OF STRUCTURES, 2005, : 29 - 44
  • [23] Application of Regression-Based Machine Learning Algorithms in Sewer Condition Assessment for Ålesund City, Norway
    Nguyen, Lam Van
    Seidu, Razak
    WATER, 2022, 14 (24)
  • [24] Linking sewer condition assessment methods to asset managers' data-needs
    Noshahri, Hengameh
    Scholtenhuis, Leon L. olde
    Doree, Andre G.
    Dertien, Edwin C.
    AUTOMATION IN CONSTRUCTION, 2021, 131
  • [25] Application of uncertainty and variability in LCA: Part II: Dealing with parameter uncertainty and uncertainty due to choices in life cycle assessment
    Huijbregts M.A.J.
    The International Journal of Life Cycle Assessment, 1998, 3 (6) : 343 - 351
  • [26] PERIODIC INSPECTION AND CONDITION ASSESSMENT OF A CABLE-STAYED BRIDGE
    Shen, Min
    Yan, Ban-Fu
    Zeng, Xian-Bin
    4TH INTERNATIONAL SYMPOSIUM ON LIFETIME ENGINEERING OF CIVIL INFRASTRUCTURE, 2009, : 304 - 309
  • [27] Condition Assessment of the Cable Trench Based on an Intelligent Inspection Robot
    Jia, Zhiwei
    Tian, Yihong
    Liu, Zheng
    Fan, Shaosheng
    FRONTIERS IN ENERGY RESEARCH, 2022, 10
  • [28] Dealing With Uncertainty in Early Health Technology Assessment: An Exploration of Methods for Decision Making Under Deep Uncertainty
    Scholte, Mirre
    Marchau, Vincent A. W. J.
    Kwakkel, Jan H.
    Klijn, Catharina J. M.
    Rovers, Maroeska M.
    Grutters, Janneke P. C.
    VALUE IN HEALTH, 2023, 26 (05) : 694 - 703
  • [29] Development of track condition assessment model based on visual inspection
    Sadeghi, J. M.
    Askarinejad, H.
    STRUCTURE AND INFRASTRUCTURE ENGINEERING, 2011, 7 (12) : 895 - 905
  • [30] Uncertainty assessment of deterministic water quality model for a combined sewer system with the GLUE method
    Zhang, Wei
    Li, Tian
    Dai, Meihong
    DESALINATION AND WATER TREATMENT, 2016, 57 (32) : 14888 - 14896