Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
An Approach for Data Analysis, Evaluation and Correction: A Case Study from Man-Made River Project in Libya
Authors: Nasser M. Amaitik, Nabil A. Alfagi
Abstract:
The world-s largest Pre-stressed Concrete Cylinder Pipe (PCCP) water supply project had a series of pipe failures which occurred between 1999 and 2001. This has led the Man-Made River Authority (MMRA), the authority in charge of the implementation and operation of the project, to setup a rehabilitation plan for the conveyance system while maintaining the uninterrupted flow of water to consumers. At the same time, MMRA recognized the need for a long term management tool that would facilitate repair and maintenance decisions and enable taking the appropriate preventive measures through continuous monitoring and estimation of the remaining life of each pipe. This management tool is known as the Pipe Risk Management System (PRMS) and now in operation at MMRA. Both the rehabilitation plan and the PRMS require the availability of complete and accurate pipe construction and manufacturing data This paper describes a systematic approach of data collection, analysis, evaluation and correction for the construction and manufacturing data files of phase I pipes which are the platform for the PRMS database and any other related decision support system.Keywords: Asbuilt, History, IMD, MMRA, PDBMS & PRMS
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330515
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2020References:
[1] O. Essamin and M. Holley, "Great Man Made River Authority (GMRA): The Role of Acoustic Monitoring in the Management of the World's Largest Prestressed Concrete Cylinder Pipe Project," Proceedings of the American Society of Civil Engineers (ASCE), the International Pipelines Conference, Aug., 1-4, 2004, San Diego, California, USA.
[2] N. M. Amaitik, and S. M. Amaitik, "Development of PCCP Wire Breaks Prediction Model Using Artificial Neural Networks," Proceedings of the American Society of Civil Engineers (ASCE), the International Pipelines Conference, Jul., 22-25, 2008, Atlanta, Georgia, USA.