تحلیل عدم قطعیت فرآیند اضمحلال روسازی آسفالتی مبتنی بر شاخص ناهمواری با استفاده از داده‌های LTPP

نوع مقاله : مقاله پژوهشی

نویسنده

دانشگاه ارومیه، ارومیه، ایران

چکیده

مدل‌های اضمحلال از اجزای مهم هر سیستم مدیریت روسازی (PMS) می‌باشند که امکان پیش‌بینی وضعیت روسازی را در زمان بهره‌برداری آن فراهم می‌کنند. اضمحلال روسازی فرآیندی بسیار پیچیده بوده و دارای عدم قطعیت زیادی است. مدل‌های احتمالاتی پیش‌بینی اضمحلال در مقایسه با مدل‌های قطعی امکان در نظر گرفتن این عدم قطعیت را دارا هستند. یکی از مهم‌ترین مدل‌های احتمالاتی پیش‌بینی اضمحلال، مدل منحنی روند است که مبتنی بر شاخص ناهمواری به عنوان یکی از مهم‌ترین شاخص‌های عملکردی روسازی می‌باشد. در این پژوهش از داده‌های ناهمواری روسازی قطعات GPS-1 و GPS-2 از پایگاه داده LTPP، که در واقع روسازی‌های آسفالتی در حال بهره‌برداری به ترتیب با اساس دانه‌ای و اساس تثبیت‌شده هستند، جهت تحلیل عدم قطعیت فرآیند اضمحلال روسازی استفاده شده است. برای این منظور از دو آزمون برازندگی مجذور کای (χ2) و کولموگروف – اسمیرنف (K-S) جهت تعیین توزیع احتمال وضعیت آینده روسازی نسبت به وضعیت فعلی آن در سال‌های مختلف استفاده شده و توزیع لاگ‌نرمال بیشترین مقدار همبستگی با توزیع واقعی داده‌ها را در بلندمدت ارائه کرده است. با داشتن این توزیع، مدل پیش‌بینی احتمالاتی اضمحلال روسازی مبتنی بر شاخص ناهمواری با استفاده از مدل منحنی روند توسعه یافته است. با بهره‌گیری از مدل توسعه داده شده، سیستم مدیریت روسازی می‌تواند وضعیت آینده روسازی را با ملاحظه عدم قطعیت فرآیند اضمحلال پیش‌بینی نماید و با تخصیص بودجه بهینه، وضعیت شبکه روسازی را در سطح ریسک معینی نگهداری کند و از تحمیل هزینه‌های گزاف ناشی از در نظر نگرفتن ریسک‌های احتمالی متاثر از عدم قطعیت وضعیت اضمحلال روسازی جلوگیری نماید.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Analysis of Uncertainties in Deterioration Process of Asphalt Pavements based on Roughness Index Using LTPP Data

نویسنده [English]

  • Nader Solatifar
Urmia University
چکیده [English]

Pavement deterioration models are the most important components of any Pavement Management System (PMS). These models could predict pavement condition at any time in its service life. Pavement deterioration is a very complicated and uncertain process. Probabilistic deterioration models in comparison with deterministic ones could take into account these uncertainties. One of the most important probabilistic pavement deterioration models, is the trend curve model that is based on pavement roughness. In this research, roughness data of GPS-1 and GPS-2 pavement sections, which are in-service asphalt pavements respectively with granular base and stabilized base layers, have been extracted from Long-Term Pavement Performance (LTPP) database. These data then were used for analyzing pavement deterioration uncertainties. For this purpose, Chi-square (χ2) and Kolmogorov-Smirnov (K-S) statistical tests were used to determine probability distribution of pavement future condition over its current condition ratio in different years. Results showed that lognormal distribution is more fitted with actual data in long-term pavement life. Having this distribution, pavement deterioration model was developed based on roughness index using trend curve model. Utilizing proposed model, the pavement management system could predict pavement future condition taking into account uncertainties of deterioration process and with optimal budget assignment, could maintain the network condition at a specified risk level. This could prevent of any future risk regarding the pavement deterioration uncertainties.

کلیدواژه‌ها [English]

  • Pavement Management System (PMS)
  • Pavement Deterioration
  • International Roughness Index (IRI)
  • Uncertainty
  • LTPP

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نشریه مهندسی عمران امیرکبیر
دوره 53، شماره 4
تیر 1400
صفحه 1259-1274

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