As the cost of designing and building new highway pavements increases and the number of new construction and major rehabilitation projects decreases, the importance of ensuring that a given pavement design performs as expected in the field becomes vital. To address this issue in other fields of civil engineering, reliability analysis has been used extensively. However, in the case of pavement structural design, the reliability component is usually neglected or overly simplified. To address this need, the current dissertation proposes a framework for estimating the reliability of a given pavement structure regardless of the pavement design or analysis procedure that is being used. As part of the dissertation, the framework is applied with the Mechanistic-Empirical Pavement Design Guide (MEPDG) and failure is considered as a function of rutting of the hot-mix asphalt (HMA) layer. The proposed methodology consists of fitting a response surface, in place of the time-demanding implicit limit state functions used within the MEPDG, in combination with an analytical approach to estimating reliability using second moment techniques: First-Order and Second-Order Reliability Methods (FORM and SORM) and simulation techniques: Monte Carlo and Latin Hypercube Simulation. In order to demonstrate the methodology, a three-layered pavement structure is selected consisting of a hot-mix asphalt (HMA) surface, a base layer, and subgrade. Several pavement design variables are treated as random; these include HMA and base layer thicknesses, base and subgrade modulus, and HMA layer binder and air void content. Information on the variability and correlation between these variables are obtained from the Long-Term Pavement Performance (LTPP) program, and likely distributions, coefficients of variation, and correlation between the variables are estimated. Additionally, several scenarios are defined to account for climatic differences (cool, warm, and hot climatic regions), truck traffic distributions (mostly consisting of single unit trucks versus mostly consisting of single trailer trucks), and the thickness of the HMA layer (thick versus thin). First and second order polynomial HMA rutting failure response surfaces with interaction terms are fit by running the MEPDG under a full factorial experimental design consisting of 3 levels of the aforementioned design variables. These response surfaces are then used to analyze the reliability of the given pavement structures under the different scenarios. Additionally, in order to check for the accuracy of the proposed framework, direct simulation using the MEPDG was performed for the different scenarios. Very small differences were found between the estimates based on response surfaces and direct simulation using the MEPDG, confirming the accurateness of the proposed procedure. Finally, sensitivity analysis on the number of MEPDG runs required to fit the response surfaces was performed and it was identified that reducing the experimental design by one level still results in response surfaces that properly fit the MEPDG, ensuring the applicability of the method for practical applications. / text

Planning road maintenance and development activities, prioritizing road construction, reconstruction and rehabilitation works, performing project economic evaluations, forecasting road operation expenditures and road user effect always requires prediction of pavement behaviour. For this purpose models of pavement deterioration are used. Commonly they are integrated in more sophisticated computational systems, known as Pavement Management systems (PMS) and Highway Development and Management systems (HDM). The implementation of these systems started in Lithuania shortly after the Re-establishment of the Independence. This was triggered by the violent drop in financing of the road sector, forcing to change obsolete road management strategy and planning approach. The need for project economic evaluations, transport modelling and long term pavement performance forecasts grew up after Lithuania joined the European Union and this brought the opportunity for financing road infrastructure projects from the EU funds. At present only on the Lithuanian state road network the total value of implemented projects, justified by evaluations and modelling with PMS, amounts to about 500 million Litas annually. Any Pavement Management System is just as good as the models within it, used for pavement deterioration prediction. The performed test calculations show that prediction models, currently used for this purpose in PMS we have in Lithuania, are of doubtful accuracy and have to be improved... [to full text]

No description available.