A Mechanistic Analysis Based Decision Support System for Scheduling Optimal Pipeline Replacement

Abstract

Failure of pipes in water distribution systems is a common occurrence especially in large cities. The failure of a pipe results in: loss of water; property damage; interruption of service; decreased system performance; and the financial cost of restoring the failed pipe. The cost of replacement and rehabilitation in the United States is estimated at 23 plus billion dollars. It is virtually impossible to replace all vulnerable pipes at the same time. As a result, there is a need for methods that can help in progressive system rehabilitation and replacement subject to budgetary constraints. If delaying is considered a good strategy due to the time value of money then, the timing of preventive maintenance becomes a crucial element for system maintenance and operation. The central under pinning element in the decision process for scheduling preventive maintenance is the deteriorating nature of a pipe under a given surrounding. By planning to replace pipes before they fail, proper planning can be put in place for securing of finances and labor force needed to rehabilitate the pipes. With this approach, service interruptions are minimized as the loss of service time is limited to the time used in replacing the pipe. In this research, a mechanistic model for assessing the stage of deterioration of an underground pipe is developed. The developed model consists of three sub-models namely, the Pipe Load Model (PLM), the Pipe Deterioration Model (PDM), and the Pipe Break Model (PBM). The PLM simulates the loads and stresses exerted on a buried water main. These loads include the earth load, traffic load, internal pressure, expansive soil loads, thermal, and frost loads. The PDM simulates the deterioration of the pipe due to corrosion resulting from the physical characteristics of the pipe environment. The pipe deterioration effect is modeled in two stages. First, the thinning of the pipe wall is modeled using a corrosion model. Second, the localized pit growth is used to determine the residual strength of the pipe based on the fracture toughness and the initial design strength of the pipe. The PBM assesses the vulnerability of a pipe at any time in terms of a critical safety factor. The safety factor is defined as the ratio of residual strength to applied stress. For a conservative estimate the multiplier effect due to thermal and frost loads are considered. For a chosen analysis period, say 50 years, the pipes with safety factors less than the critical safety factor are selected and ordered by their rank. Aided by the prioritized list of failure prone pipes, utilities can organize a replacement schedule that minimizes cost over time. Additionally a physically based regression model for determining the optimal replacement time of pipe is also presented. A methodology for assessing the consequences of accelerated and delayed replacement is also provided. The methodologies developed in this dissertation will enable utilities to formulate future budgetary needs compatible with the intended level of service. An application of the model and results are included in the dissertation.