الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
The civil infrastructure including highways, bridges, and water/sewer systems, is crucial for economic growth and prosperity. Sustaining the safety and operability of infrastructure networks is a complex task due to the harsh operational environment and the limited repair budgets. Among the various infrastructure systems, sewer pipelines networks represent a great challenge due to their diverse components that have different repair requirements. While many asset management systems have been introduced in the literature. Ideally, an asset management system would include important functions such as condition assessment, deterioration prediction, repair selection, and component prioritization for repair along a planning horizon. Existing systems, however, may not adequately cover all these functions and lack optimization features that are suitable for large scale networks.
The research problem: asset management system would include important functions such as condition assessment, deterioration prediction, repair selection, and component prioritization for repair along a planning horizon. Existing systems, however, may not adequately cover all these functions and lack optimization features that are suitable for large scale networks.
And then the research aims: This research introduces a comprehensive asset management framework to support the efficient planning of maintenance and repair programs for sewer pipelines. The proposed framework has unique focus on tracking the dynamics of defects in gravity pipelines and in optimally repairing these defects.
Steps of study: The framework introduces the following novel developments: 1) a simple approach to support speedy and less subjective assessment of the current condition of defects associated with gravity sewer pipelines; 2) a Markov chain approach for pipelines-dependent prediction of future conditions along the planning horizon; and 3) a procedure for determining the least-cost strategy to repair pipeline deficiencies in each year of the planning horizon considering practical constraints and user preferences..
The study concludes: The framework has been implemented in user-friendly prototype and its performance tested using data obtained from Shoha sewer network in Dakhlia. The system proved to be practical and capable of optimizing repair funds for gravity sewer pipelines, simultaneously, using mathematical optimization, and for a much larger number using the genetic algorithms technique. The system as such, will aid consultants and owner organizations administering large inventory of sewer network (e.g., municipalities and governmental agencies) in making appropriate decisions that ensure the sustainable operation of the infrastructure assets with least cost.