کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4927806 | 1431960 | 2017 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Probabilistic physical modelling of corroded cast iron pipes for lifetime prediction
ترجمه فارسی عنوان
مدل سازی فیزیکی احتمالی لوله های خورنده چدن برای پیش بینی طول عمر
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کلمات کلیدی
شکست خط لوله، پیش بینی استرس، خوردگی، مدلسازی فیزیکی، تجزیه و تحلیل احتمالی،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی عمران و سازه
چکیده انگلیسی
Cast iron was the dominant material for buried pipes for water networks prior to the 1970s in Australia and overseas. At present, many water utilities still have a significant amount of ageing cast iron pipes. Cast iron is a brittle material and when large diameter cast iron pipes (diameters above 300Â mm) further deteriorate, the consequences of failure can be substantial. Focusing on the likelihood of failure to assist risk assessment, this paper examines the performance of large-diameter cast iron pipes using probabilistic analysis, incorporating uncertainties of governing variables. Finite element analysis is first conducted to study the physical mechanism of buried pipes subjected to complex environmental conditions. The deterioration of cast iron pipes due to corrosion is considered on the basis of recent research. The uncertainties of governing variables, such as the physical properties of soil, cast iron, water pressure and corrosion patterns, in pipe failure risk assessment are considered. Using probabilistic physical modelling, the lifetime probability of failure is derived and a time-dependent sensitivity analysis is presented. The results of this probabilistic physical modelling are compared with cohorts of failure data from two Australian water utilities to examine the underlying trends from both physical modelling and statistical analysis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Structural Safety - Volume 64, January 2017, Pages 62-75
Journal: Structural Safety - Volume 64, January 2017, Pages 62-75
نویسندگان
Jian Ji, D.J. Robert, Chunshun Zhang, David Zhang, Jayantha Kodikara,