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Traditional asphalt mix design procedures are empirical and need random and lengthy trials in a laboratory, which can cost much labor, material resources, and finance. The initiative (Material Genome initiative) was launched by President Obama to revitalize American manufacturing. To achieve the objective of the MGI, three major tools which are computational techniques, laboratory experiments, and data analytics methods are supposed to have interacted. Designing asphalt mixture with laboratory and computation simulation methods has developed in recent decades. With the development of data science, establishing a new design platform for asphalt mixture based on data-driven methods is urgent. A balanced mix design, defined as an asphalt mix design simultaneously considering the ability of asphalt mixture to resist pavement distress, such as rutting, cracking, IRI (international roughness index), etc., is still the trend of future asphalt mix design. The service life of asphalt pavement mainly depends on the properties of the asphalt mixture. Whether asphalt mixture has good properties also depends on advanced asphalt mix design methods. Scientific mix design methods can improve engineering properties of asphalt mixture, further extending pavement life and preventing early distress of flexible pavement. Additionally, in traditional asphalt mix design procedures, the capability to resist pavement distress (rutting, IRI, and fatigue cracking) of a mixture is always evaluated based on laboratory performance tests (Hamburg wheel tracking device, Asphalt Pavement Analyzer, repeated flexural bending, etc.). However, there is an inevitable difference between laboratory tests and the real circumstance where asphalt mixture experiences because the pavement condition (traffic, climate, pavement structure) is varying and complex. The successful application examples of machine learning (ML) in all kinds of fields make it possible to establish the predictive models of pavement distress, with the inputs which contain asphalt concrete materials properties involved in the mix design process. Therefore, this study utilized historical data acquired from laboratory records, the LTPP dataset, and the NCHRP 1-37A report, data analytics and processing methods, as well as ML models to establish pavement distress predictive models, and then developed an automated and balanced mix design procedure, further lying a foundation to achieve an MGI mix design in the future. Specifically, the main research content can be divided into three parts:1. Established ML models to capture the relationship between properties of the binder, aggregates properties, gradation, asphalt content (effective and absorbed asphalt content), gyration numbers, and mixture volumetric properties for developing cost-saving Superpave and Marshall mix design methods; 2. Developed pavement distress (rutting, IRI, and fatigue cracking) predictive models, based on the inputs of asphalt concrete properties, other pavement materials information, pavement structure, climate, and traffic; 3. Proposed and verified an intelligent and balanced asphalt mix design procedure by combining the mixture properties prediction module, pavement distress predictive models and criteria, and non-dominated Sorting genetic algorithm-Ⅱ (NSGA-Ⅱ). It was discovered determining total asphalt content through predicting effective and absorbed asphalt content indirectly with ML models was more accurate than predicting total asphalt content directly with ML models; Pavement distress predictive models can achieve better predictive results than the calibrated prediction models of Mechanistic-Empirical Pavement Design Guide (MEPDG); The design results for an actual project of surface asphalt course suggested that compared to the traditional ones, the asphalt contents of the 12.5 mm and 19 mm Nominal Maximum Aggregate Size (NMAS) mixtures designed by the automated mix design procedure drop by 7.6% and 13.2%, respectively; the percent passing 2.36 mm sieve of the two types of mixtures designed by the proposed mix design procedure fall by 17.8% and 10.3%, respectively. / Doctor of Philosophy / About 96% of roads are paved with asphalt mixture. Asphalt mixture consists of asphalt, aggregates, and additives. Asphalt mix design refers to the process to determine the proper proportion of aggregates, asphalt, and additives. Traditional asphalt mix design procedures in laboratories are empirical and cost much labor, material resources, and finance. Pavement distresses, for example, cracks are important indicators to assess pavement condition. With the development of data science, machine learning (ML) has been applied to various fields by predicting desired targets. The multi-objective optimization refers to determining the optimal solution of a multiple objectives problem. The study applied ML methods to predict asphalt mixture components' proportions and pavement distress with historical experimental data and pavement condition records from literature and an open-source database. Specifically, the main research content can be divided into three parts:1. Established ML models to predict the proportion of asphalt when aggregates are given; 2. Built ML models to predict pavement distress from pavement materials information, pavement structure, climate, and traffic; 3. Develop a digital asphalt mix design procedure by combining the pavement distress prediction models and a multi-objective optimization algorithm.

Asphalt mix design includes the determination of a gradation, asphalt content, other volumetric properties, the evaluation of mechanical properties and moisture damage potentials. In this study, a computational method is developed to aid mix design. Discrete element method (DEM) was used to simulate the formation of skeleton and voids structures of asphalt concrete of different gradations of aggregates. The optimum gradation could be determined by manipulating the particle locations and orientations and placing smaller particles in the voids among larger particles. This method aims at an optimum gradation, which has been achieved through experimental methods. However, this method takes the mechanical properties or performance of the mixture into consideration, such as inter-aggregate contacts and local stability. A simple visco-elastic model was applied to model the contacts between asphalt binder and aggregates. The surface texture of an aggregate particle can be taken into consideration in the inter-particle contact model. The void content before compactions was used to judge the relative merits of a gradation. Once a gradation is selected, the Voids in Mineral Aggregate (VMA) can be determined. For a certain air void content, the mastics volume or the binder volume or the asphalt content can be determined via a digital compression test. The surface area of all the aggregates and the film thickness can be then calculated. The asphalt content can also be determined using an alternative approach that is based on modeling the inter-particle contact with an asphalt binder layer. In this study, considering the necessity of preservation of the compaction temperature, the effect of various temperatures on Hot Mix Asphalt (HMA) samples properties has been evaluated. As well, to evaluate the effect of this parameter on different grading, two different grading have been used and samples were compacted at various temperatures. Air voids also influence pore water pressure and shrinkage of asphalt binder and mixture significantly. The shrinkage is measured on a digital model that represents beams in a steel mold and is defined as the linear autogenous deformation at horizontal direction. / Ph. D.

Over the past decades, several new technologies/materials (such as WMA, RAP, rubber, polymers, bio-binders…etc.) were incorporated into asphalt mixtures. However, current mix-design specifications evaluate all mixtures containing these different additives/technologies based on volumetric. Further, RAP incorporation in asphalt mixtures is still limited, and the influence of lowered production temperatures on RAP contribution in RAP-WMA mixtures is understudied. To tackle these issues, this study presents a comprehensive evaluation of the effect of production factors ( RAP content and source, binder grade, and production temperatures) on the effective binder in WMA-RAP mixtures, and the role of the effective binder in controlling mixture performance.The experimental program included evaluation of the compaction, cracking, and rutting performance of WMA-RAP mixtures produced with a different combination of the production factors. The Semi-Circular Bend (SCB) test at intermediate temperatures was used for cracking evaluation, while the Indirect Tension Test at High Temperatures (IDT-HT) was used for rutting evaluation. Further, the study included rheological characterization of extracted binder from the mixtures to investigate the role of the effective binder on cracking performance. The results showed that the effective binder properties are changed significantly with changes in the production factors, as measured by the extracted binder rheological properties. Also, the properties of the effective binder showed a direct control of the mixture performance as measured by the IDT-HT strength and the flexibility index obtained from the SCB test. Binder selection limits were developed for lab-produced WMA-RAP mixtures based on the Glover-Rowe parameter. Finally, a validation study was conducted using data from four different projects, including a field project in Texas, FHWA’s accelerated loading facility, a laboratory mixture study in Wisconsin, and a New Hampshire DOT study to confirm the refine the findings of this study. / Civil Engineering

La presente investigación hace mención al análisis en laboratorio con respecto a la colocación de asfalto a una temperatura menor a seis grados centígrados, teniendo en consideración que el Perú cuenta con diferentes tipos de climas a lo largo y ancho de su territorio, esto hace que la producción de asfalto y su colocación sea una dificultad para cualquier tipo de proyecto de carreteras, la cual nos dirige a una realidad en la producción de asfalto en caliente, ya que sabiendo las normas y manuales con las que actualmente contamos hace que la colocación sea imposible a una temperatura menor a seis grados centígrados. La investigación se focaliza en un análisis cualitativo – cuantitativo la cual debe cumplir con los parámetros de calidad (Ensayos), manual de carreteras (EG - 2013) y proceso constructivo (método Marshall) la realización de la propuesta de mezcla asfáltica va a variar en el porcentaje de diferentes tipos de filler que hemos considerado para la investigación (cal, cemento portland tipo I y sílice). Para los ensayos se realizaron probetas sin ningún tipo de aditivos, las probetas una vez preparadas a 140ºC se sometieron a congelamiento dando como resultado, de los tres tipos de filler, que la mezcla asfáltica en caliente con incorporación de cemento portland tipo I a un 5,90% de cemento asfáltico es el óptimo cumpliendo con los parámetros y especificaciones técnicas del manual de carreteras. / The present investigation mentions the laboratory analysis regarding the placement of asphalt at a temperature below six degrees centigrade, taking into account that Peru has different types of climates throughout its territory, this makes the asphalt production and its placement is a difficulty for any type of road project, which leads us to a reality in the production of hot asphalt, since knowing the standards we currently have, that makes placement impossible to a temperature below six degrees centigrade. The research is focused on a qualitative - quantitative analysis which must comply with the quality parameters (Tests), road manual (EG - 2013) and constructive process (Marshall method) the realization of the asphalt mix proposal will vary in the percentage of different types of filler that we have considered for the research (lime, portland cement type I and silica). For the tests, test tubes were carried out without any type of additives, once the test tubes were prepared at 140ºC, they were subjected to freezing, resulting, of the three types of filler, that the hot asphalt mix with incorporation of portland cement type I at a 5,90% asphalt cement is the optimal one complying with the parameters and technical specifications of the road manual. / Tesis

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