Crumb rubber use in asphalt mixtures by means of wet process technology has been in place for several years in the United States with good performance record; however, it has some shortcomings such as maintaining high mixing and compaction temperatures in the field production. Organosilane (OS), a nanotechnology chemical substantially improves the bonding between aggregate and asphalt by modifying the aggregate structure from hydrophilic to hydrophobic contributing to increased moisture resistance of conventional asphalt mixtures. Use of Organosilane also reduces the mixing and compaction temperatures and facilitates similar compaction effort at lower temperatures. The objective of this research study was first to perform a Superpave mix design for Crumb Rubber Modified Binder (CRMB) gap-graded mixture with and without Organosilane; and secondly, analyse the performance of CRMB mixtures with and without Organosilane by conducting various laboratory tests. Performance Grade (PG) 64-22 binder was used to create the gap-graded Hot Mix Asphalt (HMA) mixtures for this study. Laboratory tests included rotational viscometer binder test and mixtures tests: dynamic modulus, flow number, tensile strength ratio, and C* fracture test. Results from the tests indicated that the addition of Organosilane facilitated easier compaction efforts despite reduced mixing and compaction temperatures. Organosilane also modestly increased the moisture susceptibility and resistance to crack propagation yet retaining equal rutting resistance of the CRMB mixtures.

Crumb rubber use in asphalt mixtures using wet process technology has been in practice for years in the United States with good performance history; however, it has some drawbacks that include the need for special blending equipment, high rubber-binder temperatures, and longer waiting time at mixing plants. Pre-treated crumb rubber technologies are emerging as a new method to produce asphalt rubber mixtures in the field. A new crumb rubber modifier known as Reacted and Activated Rubber (RAR) is one such technology. RAR (industrially known as “RARX”) acts like an Enhanced Elastomeric Asphalt Extender to improve the engineering properties of the binder and mixtures. It is intended to be used in a dry mixing process with the purpose of simplifying mixing at the asphalt plant. The objective of this research study was first to perform a Superpave mix design for determination of optimum asphalt content with 35% RAR by weight of binder; and secondly, analyse the performance of RAR modified mixtures prepared using the dry process against Crumb Rubber Modified (CRM) mixtures prepared using the wet process by conducting various laboratory tests. Performance Grade (PG) 64-22 binder was used to fabricate RAR and CRM mixtures and Performance Grade (PG) 70-10 was used to fabricate Control mixtures for this study. Laboratory tests included: Dynamic Modulus Test, Flow Number Test, Tensile Strength Ratio, Axial Cyclic Fatigue Test and C* Fracture Test. Observations from test results indicated that RAR mixes prepared through the dry process had excellent fatigue life, moisture resistance and cracking resistance compared to the other mixtures.

Asphalt binder is a complex viscoelastic hydrocarbon, whose performance depends upon interaction between its physical and chemical properties, both of which are equally important to the successful understanding of the material. Researchers have proposed various models linking linear viscoelastic (LVE) and microstructural parameters. However, none of these parameters provide insight into the relationship in the non- linear viscoelastic NLVE domain. The main goals of this dissertation are two fold. The first goal is to utilize the technique of Laser Desorption Mass Spectroscopy (LDMS) to relate the molecular structure of asphalt binders to its viscoelastic properties. The second goal of the study is to utilize different NLVE characterization tools and analysis procedures to get a clear understanding of the NLVE behavior of the asphalt binders. The goals of the study are divided into four objectives; 1) Performing the LDMS test on asphalt binder to develop at the molecular weight distributions for different asphalts, 2) Characterizing LVE properties of Arizona asphalt binders, 3) Development of relationship between molecular structure and linear viscoelasticity, 4) Understanding NLVE behavior of asphalt binders through three different characterization methods and analysis techniques.

In this research effort, a promising physico-chemical relationship is developed between number average molecular weight and width of relaxation spectrum by utilizing the data from LVE characterization and the molecular weight distribution from LDMS. The relationship states that as the molecular weight of asphalt binders increase, they require more time to relax the developed stresses. Also, NLVE characterization was carried out at intermediate and high temperatures using three different tests, time sweep fatigue test, repeated stress/strain sweep test and Multiple Stress Creep and Recovery (MSCR) test. For the intermediate temperature fatigue tests, damage characterization was conducted by applying the S-VECD model and it was found that aged binders possess greater fatigue resistance than unaged binders. Using the high temperature LAOS tests, distortion was observed in the stress-strain relationships and the data was analyzed using a Fourier transform based tool called MITlaos, which deconvolves stress strain data into harmonic constituents and aids in identification of non-linearity by detecting higher order harmonics. Using the peak intensities observed at higher harmonic orders, non-linearity was quantified through a parameter termed as “Q”, which in future applications can be used to relate to asphalt chemical parameters. Finally, the last NLVE characterization carried out was the MSCR test, where the focus was on the scrutiny of the Jnrdiff parameter. It was found that Jnrdiff is not a capable parameter to represent the stress-sensitivity of asphalt binders. The developed alternative parameter Jnrslope does a better job of not only being a representative parameter of stress sensitivity but also for temperature sensitivity.

The built environment is responsible for a significant portion of global waste generation.

Construction and demolition (C&D) waste requires significant landfill areas and costs

billions of dollars. New business models that reduce this waste may prove to be financially

beneficial and generally more sustainable. One such model is referred to as the “Circular

Economy” (CE), which promotes the efficient use of materials to minimize waste

generation and raw material consumption. CE is achieved by maximizing the life of

materials and components and by reclaiming the typically wasted value at the end of their

life. This thesis identifies the potential opportunities for using CE in the built environment.

It first calculates the magnitude of C&D waste and its main streams, highlights the top

C&D materials based on weight and value using data from various regions, identifies the

top C&D materials’ current recycling and reuse rates, and finally estimates a potential

financial benefit of $3.7 billion from redirecting C&D waste using the CE concept in the

United States.

Many coastal cities around the world are becoming increasingly vulnerable to natural disasters, particularly flooding driven by tropical storm and hurricane storm surge – typically the most destructive feature of these storms, generating significant economic damage and loss of life. This increase in vulnerability is driven by the interactions between a wide number of complex social and climatic factors, including population growth, irresponsible urban development, a decrease in essential service provision, sea level rise, and changing storm regimes. These issues are exacerbated by the short-term strategic planning that dominates political action and economic decision-making, resulting in many vulnerable coastal communities being particularly unprepared for large, infrequent storm surge events. This lack of preparedness manifests in several ways, but one of the most visible is the lack of comprehensive evacuation and rescue operation plans for use after major storm surge flooding occurs. Typical evacuation or rescue plans are built using a model of a region’s intact road network. While useful for pre-disaster purposes, the immediate aftermath of large floods sees enormous swaths of a given region’s road system flooded, rendering most of these plans largely useless. Post-storm evacuation and rescue requires large amounts of atypical travel through a region (i.e., across non-road surfaces). Traditional road network models (such as those that are used to generate evacuation routes) are unable to conceptualize this type of transportation, and so are of limited utility during post-disaster scenarios. To solve these problems, this dissertation introduces an alternative network conceptualization that preserves important on-network information but also accounts for the possibility of off-network travel during a disaster. Providing this in situ context is necessary to adequately model transportation through a post-storm landscape, one in which evacuees and rescuers are regularly departing from roads and one in which many roads are completely interdicted by flooding. This modeling approach is used to automatically generate routes through a flooded coastal urban area, as well as to identify potentially critical road segments in advance of an actual storm. These tools may help both emergency managers better prepare for large storms, and urban planners in their efforts to mitigate flood damage.

Environmental heat is a growing concern in cities as a consequence of rapid urbanization and climate change, threatening human health and urban vitality. The transportation system is naturally embedded in the issue of urban heat and human heat exposure. Research has established how heat poses a threat to urban inhabitants and how urban infrastructure design can lead to increased urban heat. Yet there are gaps in understanding how urban communities accumulate heat exposure, and how significantly the urban transportation system influences or exacerbates the many issues of urban heat. This dissertation focuses on advancing the understanding of how modern urban transportation influences urban heat and human heat exposure through three research objectives: 1) Investigate how human activity results in different outdoor heat exposure; 2) Quantify the growth and extent of urban parking infrastructure; and 3) Model and analyze how pavements and vehicles contribute to urban heat.

In the urban US, traveling outdoors (e.g. biking or walking) is the most frequent activity to cause heat exposure during hot periods. However, outdoor travel durations are often very short, and other longer activities such as outdoor housework and recreation contribute more to cumulative urban heat exposure. In Phoenix, parking and roadway pavement infrastructure contributes significantly to the urban heat balance, especially during summer afternoons, and vehicles only contribute significantly in local areas with high density rush hour vehicle travel. Future development of urban areas (especially those with concerns of extreme heat) should focus on ensuring access and mobility for its inhabitants without sacrificing thermal comfort. This may require urban redesign of transportation systems to be less auto-centric, but without clear pathways to mitigating impacts of urban heat, it may be difficult to promote transitions to travel modes that inherently necessitate heat exposure. Transportation planners and engineers need to be cognizant of the pathways to increased urban heat and human heat exposure when planning and designing urban transportation systems.

This study investigated the effect of environmental heat stress on physiological and performance measures during a ~4 mi time trial (TT) mountain hike in the Phoenix metropolitan area. Participants (n = 12; 7M/5F; age 21.6 ± 2.47 [SD]) climbed ‘A’ mountain (~1 mi) four times on a hot day (HOT; wet bulb globe temperature [WBGT] = 31.6°C) and again on a moderate day (MOD; WBGT = 19.0°C). Physiological and performance measures were made before and throughout the course of each hike. Mean pre-hike hydration status (urine specific gravity [USG]) indicated that participants began both HOT and MOD trials in a euhydrated state (1.016 ± 0.010 and 1.010 ± 0.008, respectively) and means did not differ significantly between trials (p = .085). Time trial performance was impaired by -11% (11.1 minutes) in the HOT trial (105 ± 21.7 min), compared to MOD (93.9 ± 13.1 min) (p = .013). Peak core temperatures were significantly higher in HOT (38.5 ± 0.36°C) versus MOD (38.0 ± 0.30°C) with progressively increasing differences between trials over time (p < .001). Peak ratings of perceived exertion were significantly higher in HOT (14.2 ± 2.38) compared to MOD (11.9 ± 2.02) (p = .007). Relative intensity (percent of age-predicted maximal heart rate [HR]), estimated absolute intensity (metabolic equivalents [METs]), and estimated energy expenditure (MET-h) were all increased in HOT, but not significantly so. The HOT condition reduced predicted maximal aerobic capacity (CRFp) by 6% (p = .026). Sweat rates differed significantly between HOT (1.38 ± 0.53 L/h) and MOD (0.84 ± 0.27 L/h) (p = .01). Percent body mass loss (PBML) did not differ significantly between HOT (1.06 ± 0.95%) and MOD (0.98 ± 0.84%) (p = .869). All repeated measures variables showed significant between-subjects effects (p < .05), indicating individual differences in response to test conditions. Heat stress was shown to negatively affect physiological and performance measures in recreational mountain hikers. However, considerable variation exists between individuals, and the degree of physiological and performance impairment is probably due, in part, to differences in aerobic fitness and acclimatization status rather than pre- or during-performance hydration status.

Pavement management systems and performance prediction modeling tools are essential for maintaining an efficient and cost effective roadway network. One indicator of pavement performance is the International Roughness Index (IRI), which is a measure of ride quality and also impacts road safety. Many transportation agencies use IRI to allocate annual maintenance and rehabilitation strategies to their road network.

The objective of the work in this study was to develop a methodology to evaluate and predict pavement roughness over the pavement service life. Unlike previous studies, a unique aspect of this work was the use of non-linear mathematical function, sigmoidal growth function, to model the IRI data and provide agencies with the information needed for decision making in asset management and funding allocation. The analysis included data from two major databases (case studies): Long Term Pavement Performance (LTPP) and the Minnesota Department of Transportation MnROAD research program. Each case study analyzed periodic IRI measurements, which were used to develop the sigmoidal models.

The analysis aimed to demonstrate several concepts; that the LTPP and MnROAD roughness data could be represented using the sigmoidal growth function, that periodic IRI measurements collected for road sections with similar characteristics could be processed to develop an IRI curve representing the pavement deterioration for this group, and that pavement deterioration using historical IRI data can provide insight on traffic loading, material, and climate effects. The results of the two case studies concluded that in general, pavement sections without drainage systems, narrower lanes, higher traffic, or measured in the outermost lane were observed to have more rapid deterioration trends than their counterparts.

Overall, this study demonstrated that the sigmoidal growth function is a viable option for roughness deterioration modeling. This research not only to demonstrated how historical roughness can be modeled, but also how the same framework could be applied to other measures of pavement performance which deteriorate in a similar manner, including distress severity, present serviceability rating, and friction loss. These sigmoidal models are regarded to provide better understanding of particular pavement network deterioration, which in turn can provide value in asset management and resource allocation planning.