A Statistical Methodology for Evaluating the Residual Life of Water Mains
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This paper provides a method for evaluating a residual life of water mains using a proportional hazard model(PHM). The survival time of individual pipe is defined as the elapsed time since installation until a break rate of individual pipe exceeds the Threshol Break Rate. A break rate of an individual pipe is estimated by using the General Pipe Break Model(GPBM). In order to use the GPBM effectively, improvement of the GPBM is presented in this paper by utilizing additional break data that is the cumulative number of pipe break of 0 for the time of installation and adjusting a value of weighting factor(WF). The residual lives and hazard ratios of the case study pipes of which the cumulative number of pipe breaks is more than one is estimated by using the estimated survival function. It is found that the average residual lives of the steel and cast iron pipes are about 25.1 and 21 years, respectively. The hazard rate of the cast iron pipes is found to be higher than the steel pipes until 20 years since installation. However, the hazard rate of the cast iron pipes become lower than the hazard rates of the steel pipes after 20 years since installation.Keywords:
Mains electricity
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The probabilities of failure for cast iron (CI), ductile iron (DI), polyvinyl chloride (PVC), and concrete cylinder (CC) pipes were analyzed to determine the pipe type that failed most consistently at the Honolulu Board of Water Supply (HBWS). In understanding the process of the probability of failure over time, expected failure rates were calculated. A pipe type with a low and consistent probability of pipe failure was preferred for asset management over one that displayed a high and volatile probability of failure. The probability of failure was derived from the failure rate, assuming a Poisson distribution. The data for each pipe type was analyzed and compared by using control charts, operating characteristic (OC) curves, and process capability indexes. The results of the control charts showed that CC pipes were the most stable. According to the OC curves, in which the hypothesis created was that the probability of failure was less than the upper specification limit, CI pipes had the highest probability of accepting the hypothesis when true. PVC pipes showed a low probability of accepting the hypothesis within the specification limits, but also a low probability of false acceptance of the hypothesis. Finally, process capability analysis found that CI and PVC pipes were able to meet their desired failure specification limits. Overall results are mixed—CI pipes performed the best according to OC curves and process capability analysis; PVC pipes were seen as the worst through the use of control charts and OC curves; CC pipes were the most stable according to control charts, but the worst in process capability. A rank order structuring of failure expectations concluded that CI pipes were the best, whereas PVC pipes were the worst. However, this finding does not translate into recommendations for pipe design. It was observed that actual failure rates and expectation analysis are distinct aspects; the expected performance of a pipe is independent of its actual performance.
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The drinking water network serving are up to 100 years old in Korea. Therefore, pipelines suffer various degrees of deterioration due to aggressive environments. Water supply system is one of the major urban infrastructures based on activities of mankind. Its most expensive facility is the water distribution network which is an important component in both quantitative and qualitative sides. Therefore, its effective maintenance and operation (M&O) has essential effect on sustaining human life. Moreover, factors of pipe deterioration and models to predict failure and optimal rehabilitation time are needed to support network management strategies. This study has performed to set up the determination of optimal rehabilitation time for Cast Iron Pipes (CIP) with diameter less than 300 mm. And the determination model for optimal rehabilitation time was developed by using cost analysis and deterioration evaluation on rehabilitation alternatives. In the result from the application of the field, the renovation time was faster about 10 years than the replacement time. Especially, as the difference between rehabilitation and replacement time on E-CIP was about from 3 to 5 years, and it was thought that the replacement was effective on E-CIP. To model sensitivity analysis, the discount rate of coefficient was fixed at 0.08, and the values of initial year break rate(N(t0)) and growth rate coefficient(A) were adjusted in values of 0.0009, 0.0018, 0.0027, and 0.05, 0.10, 0.15 respectively. When the values of N(t0) and A was increased, the results from the time of rehabilitation and replacement was faster. It was thought that N(t0), 0.018 was reliable values on the applied pipeline through the result of the study. In case of A, the values of A above 0.1 was thought to be proper.
Pipe network analysis
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It is important to set up the predictive models for pipe replacement time in water distribution system.Through scientific management and technology rehabilitation and replacement to network,the rate of pipe break could be reduced and the security of water distribution systems would be enhanced.In this paper,the predictive model of replacement times is obtained by taking the threshold break rate into the Shamir and Howard's exponential break rate model,parametric analysis is carried out to examine the sensitivity of the optimal replacement by the example.Optimal replacement time prediction is based on minimization of the total cost during a predetermined service period.The results show that the optimal replacement values of discount rate are fairly sensitive and very sensitive to the values of growth rate coefficient A.The replacement time can be delayed by decreasing the value of coefficient A.The value of coefficient A should vary with pipe diameter,age,pressure,type and soil corrosivity.
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The service life of thick-walled power plant components exposed to creep, as is the case with pipelines of fresh- and re-heated steam, depend on the exhaustion rate of the material. Plant operation at elevated temperatures and at temperatures below designed temperatures all relates to the material exhaustion rate, thus complicating remaining life assessment, whereas the operating temperature variation is a most common cause in the mismatching of real service- and design life. Apart from temperature, the tube wall stress is a significant variable for remaining life assessment, whose calculation depends on the selected procedure, due to the complex pipeline configuration. In this paper, a remaining life assessment is performed according to the Larson-Miller parametric relation for a ?324?36 pipe bend element of a fresh steam-pipeline, made of steel class 1Cr0.3Mo0.25V, after 160 000 hours of operation. The temperature history of the pipeline, altogether with the pipe bend, is determined based on continuous temperature monitoring records. Compared results of remaining life assessment are displayed for monitored temperature records and for designed operating temperature in the same time period. The stress calculation in the pipe bend wall is performed by three methods that are usually applied so to emphasize the differences in the obtained results of remaining life assessment.
Service life
Operating temperature
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The energy performance of water mains is rarely used as a criterion for pipe rehabilitation decisions, yet there is a need to identify the worst‐performing pipes to target investment wisely. This study links pipe characteristics with energy performance to understand how traditional pipe replacement thresholds perform in terms of energy. A cross‐correlation analysis between pipe characteristics and pipe energy performance metrics, using a benchmarking data set of more than 20,000 water mains from 17 distribution systems, showed that unit head loss is closely related to net energy efficiency and the energy lost to friction (ELTF) in pipes, along with flow. Under average flow conditions, 3.2% of the pipes exceeded 3 m/km (ft/1,000 ft) of unit head loss, with 1.1% exceeding the more stringent 10 m/km threshold. Over 90% of pipes have a unit head loss below 1 m/km, which corresponds to an ELTF of 1.9%.
Hydraulic head
Mains electricity
Friction loss
Pipe network analysis
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