Journal of Korean Society of Water and Wastewater (상하수도학회지)

The Korean Society of Water and Wastewater (대한상하수도학회)
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Estimation of sewer deterioration by Weibull distribution function

와이블 분포함수를 이용한 하수관로 노후도 추정

  • Kang, Byongjun (Environment Solution Partners Inc.) ;
  • Yoo, Soonyu (Department of Consilience, Korea Polytechnic University) ;
  • Park, Kyoohong (School of Civil and Environmental Engineering, Chung-Ang University)
  • 강병준 ((주)엔솔파트너스) ;
  • 유순유 (한국산업기술대학교 지식융합학부) ;
  • 박규홍 (중앙대학교 공과대학 사회기반시스템공학부)
  • Received : 2020.06.30
  • Accepted : 2020.07.26
  • Published : 2020.08.15
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Abstract

Sewer deterioration models are needed to forecast the remaining life expectancy of sewer networks by assessing their conditions. In this study, the serious defect (or condition state 3) occurrence probability, at which sewer rehabilitation program should be implemented, was evaluated using four probability distribution functions such as normal, lognormal, exponential, and Weibull distribution. A sample of 252 km of CCTV-inspected sewer pipe data in city Z was collected in the first place. Then the effective data (284 sewer sections of 8.15 km) with reliable information were extracted and classified into 3 groups considering the sub-catchment area, sewer material, and sewer pipe size. Anderson-Darling test was conducted to select the most fitted probability distribution of sewer defect occurrence as Weibull distribution. The shape parameters (β) and scale parameters (η) of Weibull distribution were estimated from the data set of 3 classified groups, including standard errors, 95% confidence intervals, and log-likelihood values. The plot of probability density function and cumulative distribution function were obtained using the estimated parameter values, which could be used to indicate the quantitative level of risk on occurrence of CS3. It was estimated that sewer data group 1, group 2, and group 3 has CS3 occurrence probability exceeding 50% at 13th-year, 11th-year, and 16th-year after the installation, respectively. For every data groups, the time exceeding the CS3 occurrence probability of 90% was also predicted to be 27th- to 30th-year after the installation.

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References

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