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Using numerical modeling for asset management of buried prestressed concrete cylinder pipes
Author(s) -
Hajali Masood,
Abi Shdid Caesar
Publication year - 2021
Publication title -
structural concrete
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.912
H-Index - 34
eISSN - 1751-7648
pISSN - 1464-4177
DOI - 10.1002/suco.202000238
Subject(s) - asset management , prestressed concrete , asset (computer security) , cylinder , nonlinear system , field (mathematics) , structural engineering , key (lock) , engineering , reliability engineering , civil engineering , computer science , mechanical engineering , finance , physics , computer security , mathematics , quantum mechanics , pure mathematics , economics
Prestressed Concrete Cylinder Pipes (PCCP) form the backbone of water and wastewater infrastructure networks in North America. Failure of buried PCCP is a common occurrence due to structural deterioration or manufacturing defects. To mitigate the serious effects of such failures, owners and operators of these networks use risk curves to predict the failure of PCCP when given a certain level of deterioration by field inspectors. The current problem lies in the fact that asset management using such risk curves lacks accuracy and requires costly and time‐consuming field inspections. A solution is presented in this study that bypasses the need for such risk curves by using computational modeling in conjunction with flow measurement devices installed inside pipe networks. The three‐dimensional computational model uses nonlinear finite elements to simulate the behavior of buried PCCP under combined internal and external loading. The method is validated using experimental test results of full‐scale PCCP specimens. Comparison of several key structural health indicators shows close agreement of the developed model with experimental results. The study demonstrates that the developed approach can predict with relative accuracy and time efficiency the deterioration levels of different pipe segments under realistic loading conditions. This approach eliminates the need for risk curves that require time consuming and costly field inspections, and allows for more effective asset management through on‐time maintenance and replacement of such important infrastructure facilities by their public and private owners.