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Probabilistic Comparison of Sustainability of Pavement Maintenance Programs

Zeigham Nakhaei, Mohammad Hossein | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57476 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Tabatabaee, Nader
  7. Abstract:
  8. With the increasing importance of the sustainable development perspective, coupled evaluation of the environmental, economic, and functional performance of pavement maintenance programs needs to be considered. This task requires the use of data and models from different sources, which introduce uncertainty in the analysis. The use of probabilistic analysis may allow decision-makers to reach more realistic conclusions. To this end, all phases of the pavement life cycle, including material production, construction, use, and salvage at the end of life, should be considered. The effect of pavement-vehicle interaction (PVI) in the operation phase has received less attention from researchers. In this regard, the present study developed a probabilistic model based on Bayesian approach for three passenger vehicles, light trucks and heavy trucks to estimate the additional energy consumption of the vehicles due to pavement roughness and macro texture. This model considers three sources of uncertainty in a mathematical model, including inputs, model parameters, and model form. To generate the necessary data for model development, the EPA’s motor vehicle emission software, MOVES3.1, was used. In addition, the direct and indirect costs for both agencies and users were separated, leading to the development of a probabilistic sustainability evaluation framework for assessing maintenance programs. Within this framework, direct costs are analyzed using life cycle cost analysis (LCCA), while indirect costs are assessed through life cycle assessment (LCA) and pavement performance metrics. The selection of the optimal program is carried out using a Monte Carlo simulation combined with the Analytic Hierarchy Process (AHP). The Monte Carlo simulation incorporates uncertainties related to the discount rate, life cycle inventory (LCI), and PVI. To validate this framework, a case study was conducted that considered various maintenance programs, such as the application of a slurry seal or a thin asphalt overlay at different intervals over a 35-year analysis period. The results of the case study indicated that when both direct and indirect costs for agencies and users are given equal priority, the maintenance program with higher performance were selected as the optimal choice. This finding highlights the strong correlation between pavement performance and the direct and indirect costs of users
  9. Keywords:
  10. Preventive Maintenance ; Probability Analysis ; Sustainable Development ; Pavement-Vehicle Interaction ; Bayesian Analysis ; Life Cycle Cost Assessment

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