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Failure of underground pipe <br />becomes very evident <br />when sinkholes form to <br />swallow up cars, which <br />happened in the city of Fort <br />Lauderdale, Fla. <br />a statistical distribution, <br />such as abell-shaped <br />curve. Within this dis- <br />tribution, the average life <br />of most pipes makes up <br />the middle of the distri- <br />bution and the ex- <br />tremes-represented by <br />the "tails" of the distribution <br />curve-are either shorter or longer <br />than the average. <br />'This bell-shaped curve of life ex- <br />pectancy stretches out replacement <br />investment needs over a longer period <br />of time than would be the case if all <br />pipes had exactly the same life <br />expectancy. Stretching out reinvest- <br />ment needs sounds good, but the total <br />picture is a bit more complicated. <br />Most water systems installed <br />additional pipes as the utility <br />expanded. Every installment of pipe <br />assets will have its own bell-shaped <br />curve of replacement needs. The suc- <br />cession of bell-shaped curves will be <br />staggered over time, and the distri- <br />butions will overlap. To get an accu- <br />rate picture of total replacement <br />needs, the overlapping curves must <br />be added together. <br />The result is a replacement invest- <br />ment forecast, or echo wave, that <br />reflects the original waves of con- <br />struction and expansion in a water <br />system. In the past, the expansion <br />rate of pipe networks was a result of <br />population growth, which tended to <br />ebb and flow as waves of growth <br />swept over US cities. Combining the <br />demographic patterns of original con- <br />struction work with the bell-shaped <br />curves of expected pipe life produces <br />a graph like the one in Figure 2. This <br />graph illustrates the relationship <br />between the original waves of con- <br />struction and the echo waves of <br />replacement for each class of pipe <br />assets. The resulting ramplike shape <br />of reinvestment results because most <br />system expansion occurred during the <br />latter part of the previous century <br />(i.e., most pipes are less than ~0 years <br />old) and because even the oldest pipes <br />have long lives (life expectancy for <br />many of the oldest pipes is more than <br />100 years because of the thick-walled <br />design of the early iron pipes). <br />Two key variables determine the <br />echo wave of pipe reinvestment <br />needs; one is known, and the other is <br />unknown. The original pipe instal- <br />lation pattern is fixed and known; it <br />can be inferred reasonably well from <br />data on historic population growth <br />trends even if there are no utility <br />records. The second variable-the <br />bell-shaped distribution of pipe life <br />for each annual cohort group of pipe <br />assets-is not known with precision. <br />1Vloreover, it is not fixed but rather <br />evolving as individual pipes continue <br />to wear out, and it is changeable <br />because of maintenance interventions. <br />Asset management focuses on this <br />"pipe life" variable in an attempt to <br />optimize the rate of reinvestment in <br />terms of total life-cycle costs (flat- <br />tening the ramp) while maintaining <br />the level of asset performance <br />required to deliver the desired level of <br />service to customers. <br />In addition to physical failures <br />such as main breaks, pipe perfor- <br />mance is affected by line pressure, <br />water chemistry, and microbiology. <br />CROMWELL ET AL °9:4 JOURNAL AWWA ~ APRIL 2007 113 <br />