Desde a implantação das primeiras obras, há indicações de que seus construtores já apresentavam conhecimentos acerca da influência da drenagem no desempenho dos pavimentos. Muitos países, onde os custos rodoviários são avaliados criteriosamente ao longo de toda a vida de serviço do pavimento, vêm desenvolvendo pesquisas objetivando a consideração dos efeitos prejudiciais da água em excesso no interior de sua estrutura. Métodos consagrados como, por exemplo, o da AASHTO, já consideram a influência da eficiência do sistema de drenagem no dimensionamento das estruturas de pavimentos. Neste trabalho, são apresentados um breve histórico e uma análise dos métodos de dimensionamento nacionais e estrangeiros, com vistas às considerações da influência do sistema de drenagem e da variação sazonal do teor de umidade no desempenho estrutural dos pavimentos. Fazendo-se uso do Falling Weight Defectometer, foi realizado levantamento deflectométrico em trecho experimental, com extensão aproximada de 900 m, direcionado para a avaliação da variação dos módulos resilientes das camadas e do comportamento estrutural diante da infiltração d\'água pela borda do pavimento. A partir dos dados obtidos no segmento experimental, pôde-se avaliar a magnitude desses parâmetros e assim efetuar, através de modelos analíticos que expressam os métodos de dimensionamento vigentes no país, a estimativa de redução da vida útil do pavimento analisado. Finalmente, propõe-se a introdução de um parâmetro de ajuste da espessura, denominado Fator de Ajuste de Drenagem, para consideração das condições adversas de drenagem no procedimento de dimensionamento de estruturas de pavimentos flexíveis preconizado pelo DNER. / Since the implementation of the first roads, there are indications that constructors already had knowledge concerning drainage influence in the pavement performance. Many countries, where highway administration costs are criteriously available along pavement lifetime, have been developing researches regarding considerations about harmful effects from excessive water in the pavement structure. Renowned methods such as AASHTO, already consider the influence of drainage system efficiency in the pavement structures design. In this work, brief historic and an analysis about national and foreign design methods are presented, taking into account considerations concerning influence of drainage system and seasonal variations of moisture content in the structural pavement performance. Employing the Falling Weight Deflectometer, deflection measurements were carried out in a test section, about 900 m long, in order to evaluate the resilient modulus layers and the structural behavior variations due to water infiltration from pavement edge. From experimental sections data obtained, it was possible to evaluate the magnitude of these parameters and then realize, through analytical models that represent the actual national design methods, the reduction estimate of evaluated pavement lifetime. Finally, this work propose the introduction of a thickness adjustment parameter, called Drainage Adjustment Factor, to consider the adverse drainage conditions in the flexible pavement structure design procedure advocated by DNER.

While cement treatment is a proven method for improving the strength and durability of soils and aggregates, cement hydration causes shrinkage strains in the cement-treated base (CTB) that can lead to reflection cracking in asphalt surfaces. Cracking may then cause increased pavement roughness and lead to poor ride quality. The overall purpose of this research was to utilize data collected through the Long-Term Pavement Performance (LTPP) program to investigate the use and classification of CTB layers and evaluate the relative impact of cement content on the development of roughness and cracking in asphalt concrete (AC) pavements constructed using CTB layers. The data included 52 LTPP test sites, which represented 13 different states and one Canadian province, with cement contents ranging from 3.0 to 9.5 percent by weight of dry aggregate. Statistical procedures were utilized to identify the factors that were most correlated to the observed pavement performance and to develop prediction equations that transportation agencies can use to estimate the amount of roughness for a given pavement at a given age and the amount of distress associated with a particular crack severity level for a given pavement. The data collected for this study suggest that wide ranges of cement contents are used to stabilize soils within individual American Association of State Highway and Transportation Officials soil classifications. The data also suggest that CTBs comprising flexible pavement structures are constructed mainly on rural facilities. A backward-selection model development technique was used to develop sets of prediction equations for roughness and cracking. Age, AC thickness, CTB thickness, and cement content were determined to be significant predictors of International Roughness Index, while age, air freezing index, AC thickness, CTB thickness, cement content, and traffic loads in thousands of equivalent single-axle loads were determined to be significant predictors of low-severity, medium-severity, and high-severity block, fatigue, longitudinal (wheel-path and non-wheel-path), and transverse cracking in AC pavements constructed using CTB layers. Investigation of the relationships between CTB modulus and the development of roughness and cracking is recommended for further study.

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Current pavement performance prediction models are based on the parameters such as climate, traffic, environment, material properties, etc. while all these factors are playing important roles in the performance of pavements, the quality of construction and production are also as important as the other factors. The designed properties of Hot Mix Asphalt (HMA) pavements, known as flexible pavements, are subjected to change during production and construction stages. Therefore, most of the times the final product is not the exact reflection of the design. In almost any highway project, these changes are common and likely to occur from different sources, by various causes, and at any stage. These changes often have considerable impacts on the long-term performance of a project. The uncertainty of the traffic and environmental factors, as well as the variability of material properties and pavement structural systems, are obstacles for precise prediction of pavement performance. Therefore, it is essential to adopt a hybrid approach in pavement performance prediction and design; in which deterministic values work along with stochastic ones. Despite the advancement of technology, it is natural to observe variability during the production and construction stages of flexible pavements. Quality control programs are trying to minimize and control these variations and keep them at the desired levels. Utilizing the information gathered at the production and construction stages is beneficial for managers and researchers. This information enables performing analysis and investigations of pavements based on the as-produced and as-constructed values, rather than focusing on design values. This study describes a geo-relational framework to connect the pavement life-cycle information. This framework allows more intelligent and data-driven decisions for the pavements. The constructed geo-relational database can pave the way for artificial intelligence tools to help both researchers and practitioners having more accurate pavement design, quality control programs, and maintenance activities. This study utilizes data collected as part of quality control programs to develop more accurate deterioration and performance models. This data is not only providing the true perspective of actual measurements from different pavement properties but also answers how they are distributed over the length of the pavement. This study develops and utilizes different distribution functions of pavement properties and incorporate them into the general performance prediction models. These prediction models consist of different elements that are working together to produce an accurate and detailed prediction of performance. The model predicts occurrence and intensity of four common flexible pavement distresses; such as rutting, alligator, longitudinal and transverse cracking along with the total deterioration rate at different ages and locations of pavement based on material properties, traffic, and climate of a given highway. The uniqueness of the suggested models compared to the conventional pavement models in the literature is that; it carries out a multiscale and multiphysics approach which is believed to be essential for analyzing a complex system such as flexible pavements. This approach encompasses the discretization of the system into subsystems to employ the proper computational tools required to treat them. This approach is suitable for problems with a wide range of spatial and temporal scales as well as a wide variety of different coupled physical phenomena such as pavements. Moreover, the suggested framework in this study relies on using stochastic and machine learning techniques in the analysis along with the conventional deterministic methods. In addition, this study utilizes mechanical testing to provide better insights into the behavior of the pavement. A series of performance tests are conducted on field core samples with a variety of different material properties at different ages. These tests allow connecting the lab test results with the field performance survey and the material, environmental and loading properties. Moreover, the mix volumetrics extracted from the cores assisted verifying the distribution function models. Finally, the deterioration of flexible pavements as a result of four different distresses is individually investigated and based on the findings; different models are suggested. Dividing the roadway into small sections allowed predicting finer resolution of performance. These models are proposed to assist the highway agencies s in their pavement management process and quality control programs. The resulting models showed a strong ability to predict field performance at any age during the pavements service life. The results of this study highlighted the benefits of highway agencies in adopting a geo-relational framework for their pavement network. This study provides information and guidance to evolve towards data-driven pavement life cycle management consisted of quality pre-construction, quality during construction, and deterioration post-construction. / Civil Engineering

Using geotextiles in secondary roads to stabilize weak subgrades has been a well accepted practice over the past thirty years. However, from an economical point of view, a complete life cycle cost analysis (LCCA), which includes not only costs to agencies but also costs to users, is urgently needed to assess the benefits of using geotextile in secondary road flexible pavement. In this study, a comprehensive life cycle cost analysis framework was developed and used to quantify the initial and the future cost of 25 representative design alternatives. A 50 year analysis cycle was used to compute the cost-effectiveness ratio for the design methods. Four flexible pavement design features were selected to test the degree of influence of the frame's variables. The analysis evaluated these variables and examined their impact on the results. The study concludes that the cost effectiveness ratio from the two design methods shows that the lowest cost-effectiveness ratio using Al-Qadi's design method is 1.7 and the highest is 3.2. The average is 2.6. For Perkins' design method, the lowest value is 1.01 and the highest value is 5.7. The average is 2.1. The study also shows when user costs are considered, the greater TBR value may not result in the most effective life-cycle cost. Hence, for an optimum secondary road flexible pavement design with geotextile incorporated in the system, a life cycle cost analysis that includes user cost must be performed. / Master of Science