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Laboratory assessment of crack resistance and propagation in asphalt concrete is a difficult task that challenges researchers and engineers. Several fracture mechanics based laboratory tests currently exist; however, these tests and subsequent analysis methods rely on elastic behavior assumptions and do not consider the time-dependent nature of asphalt concrete. The

Laboratory assessment of crack resistance and propagation in asphalt concrete is a difficult task that challenges researchers and engineers. Several fracture mechanics based laboratory tests currently exist; however, these tests and subsequent analysis methods rely on elastic behavior assumptions and do not consider the time-dependent nature of asphalt concrete. The C* Line Integral test has shown promise to capture crack resistance and propagation within asphalt concrete. In addition, the fracture mechanics based C* parameter considers the time-dependent creep behavior of the materials. However, previous research was limited and lacked standardized test procedure and detailed data analysis methods were not fully presented. This dissertation describes the development and refinement of the C* Fracture Test (CFT) based on concepts of the C* line integral test. The CFT is a promising test to assess crack propagation and fracture resistance especially in modified mixtures. A detailed CFT test protocol was developed based on a laboratory study of different specimen sizes and test conditions. CFT numerical simulations agreed with laboratory results and indicated that the maximum horizontal tensile stress (Mode I) occurs at the crack tip but diminishes at longer crack lengths when shear stress (Mode II) becomes present. Using CFT test results and the principles of time-temperature superposition, a crack growth rate master curve was successfully developed to describe crack growth over a range of test temperatures. This master curve can be applied to pavement design and analysis to describe crack propagation as a function of traffic conditions and pavement temperatures. Several plant mixtures were subjected to the CFT and results showed differences in resistance to crack propagation, especially when comparing an asphalt rubber mixture to a conventional one. Results indicated that crack propagation is ideally captured within a given range of dynamic modulus values. Crack growth rates and C* prediction models were successfully developed for all unmodified mixtures in the CFT database. These models can be used to predict creep crack propagation and the C* parameter when laboratory testing is not feasible. Finally, a conceptual approach to incorporate crack growth rate and the C* parameter into pavement design and analysis was presented.
ContributorsStempihar, Jeffrey (Author) / Kaloush, Kamil (Thesis advisor) / Witczak, Matthew (Committee member) / Mamlouk, Michael (Committee member) / Arizona State University (Publisher)
Created2013
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Description

One of the main requirements of designing perpetual pavements is to determine the endurance limit of Hot Mix Asphalt (HMA). The purpose of this study was to validate the endurance limit for HMA using laboratory beam fatigue tests. A mathematical procedure was developed to determine the endurance limit of HMA

One of the main requirements of designing perpetual pavements is to determine the endurance limit of Hot Mix Asphalt (HMA). The purpose of this study was to validate the endurance limit for HMA using laboratory beam fatigue tests. A mathematical procedure was developed to determine the endurance limit of HMA due to healing that occurs during the rest periods between loading cycles. Relating healing to endurance limit makes this procedure unique compared to previous research projects that investigated these concepts separately. An extensive laboratory testing program, including 468 beam tests, was conducted according to AASHTO T321-03 test procedure. Six factors that affect the fatigue response of HMA were evaluated: binder type, binder content, air voids, test temperature, rest period and applied strain. The endurance limit was determined when no accumulated damage occurred indicating complete healing. Based on the test results, a first generation predictive model was developed to relate stiffness ratio to material properties. A second generation stiffness ratio model was also developed by replacing four factors (binder type, binder content, air voids, and temperature) with the initial stiffness of the mixture, which is a basic material property. The model also accounts for the nonlinear effects of the rest period and the applied strain on the healing and endurance limit. A third generation model was then developed by incorporation the number of loading cycles at different locations along the fatigue degradation curve for each test in order to account for the nonlinearity between stiffness ratio and loading cycles. In addition to predicting endurance limit, the model has the ability to predict the number of cycles to failure at any rest period and stiffness combination. The model was used to predict fatigue relationship curves for tests with rest period and determining the K1, K2, and K3 fatigue cracking coefficients. The three generation models predicted close endurance limit values ranging from 22 to 204 micro strains. After developing the third generation stiffness ratio model, the predicted endurance limit values were integrated in the strain-Nf fatigue relationships as a step toward incorporating the endurance limit in the MEPDG software. The results of this study can be used to design perpetual pavements that can sustain a large number of loads if traffic volumes and vehicle weights are controlled.

ContributorsSouliman, Mena (Author) / Mamlouk, Michael S. (Thesis advisor) / Witczak, Matthew W. (Thesis advisor) / Kaloush, Kamil (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The fatigue resistance of asphalt concrete (AC) plays an important role in the service life of a pavement. For predicting the fatigue life of AC, there are several existing empirical and mechanistic models. However, the assessment and quantification of the ‘reliability’ of the predictions from these models is a substantial

The fatigue resistance of asphalt concrete (AC) plays an important role in the service life of a pavement. For predicting the fatigue life of AC, there are several existing empirical and mechanistic models. However, the assessment and quantification of the ‘reliability’ of the predictions from these models is a substantial knowledge gap. The importance of reliability in AC material performance predictions becomes all the more important in light of limited monetary and material resources. The goal of this dissertation research is to address these shortcomings by developing a framework for incorporating reliability into the prediction of mechanical models for AC and to improve the reliability of AC material performance prediction by using Fine Aggregate Matrix (FAM) phase data. The goal of the study is divided into four objectives; 1) development of a reliability framework for fatigue life prediction of AC materials using the simplified viscoelastic continuum damage (S-VECD) model, 2) development of test protocols for FAM in similar loading conditions as AC, 3) evaluation of the mechanical linkages between the AC and FAM mix through upscaling analysis, and 4) investigation of the hypothesis that the reliability of fatigue life prediction of AC can be improved with FAM data modeling.

In this research effort, a reliability framework is developed using Monte Carlo simulation for predicting the fatigue life of AC material using the S-VECD model. The reliability analysis reveals that the fatigue life prediction is very sensitive to the uncertainty in the input variables. FAM testing in similar loading conditions as AC, and upscaling of AC modulus and damage response using FAM properties from a relatively simple homogenized continuum approach shows promising results. The FAM phase fatigue life prediction and upscaling of FAM results to AC show more reliable fatigue life prediction than the fatigue life prediction of AC material using its experimental data. To assess the sensitivity of fatigue life prediction model to uncertainty in the input variables, a parametric sensitivity study is conducted on the S-VECD model. Overall, the findings from this research show promising results both in terms of upscaling FAM to AC properties and the reliability of fatigue prediction in AC using experimental data on FAM.
ContributorsGudipudi, Padmini Priyadarsini (Author) / Underwood, Benjamin S (Thesis advisor) / Kaloush, Kamil (Committee member) / Mamlouk, Michael (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2016
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Description
The combination of rapid urban growth and climate change places stringent constraints on multisector sustainability of cities. Green infrastructure provides a great potential for mitigating anthropogenic-induced urban environmental problems; nevertheless, studies at city and regional scales are inhibited by the deficiency in modelling the complex transport coupled water and energy

The combination of rapid urban growth and climate change places stringent constraints on multisector sustainability of cities. Green infrastructure provides a great potential for mitigating anthropogenic-induced urban environmental problems; nevertheless, studies at city and regional scales are inhibited by the deficiency in modelling the complex transport coupled water and energy inside urban canopies. This dissertation is devoted to incorporating hydrological processes and urban green infrastructure into an integrated atmosphere-urban modelling system, with the goal to improve the reliability and predictability of existing numerical tools. Based on the enhanced numerical tool, the effects of urban green infrastructure on environmental sustainability of cities are examined.

Findings indicate that the deployment of green roofs will cool the urban environment in daytime and warm it at night, via evapotranspiration and soil insulation. At the annual scale, green roofs are effective in decreasing building energy demands for both summer cooling and winter heating. For cities in arid and semiarid environments, an optimal trade-off between water and energy resources can be achieved via innovative design of smart urban irrigation schemes, enabled by meticulous analysis of the water-energy nexus. Using water-saving plants alleviates water shortage induced by population growth, but comes at the price of an exacerbated urban thermal environment. Realizing the potential water buffering capacity of urban green infrastructure is crucial for the long-term water sustainability and subsequently multisector sustainability of cities. Environmental performance of urban green infrastructure is determined by land-atmosphere interactions, geographic and meteorological conditions, and hence it is recommended that analysis should be conducted on a city-by-city basis before actual implementation of green infrastructure.
ContributorsYang, Jiachuan (Author) / Wang, Zhihua (Thesis advisor) / Kaloush, Kamil (Committee member) / Myint, Soe (Committee member) / Huang, Huei-Ping (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2016
Description

Better methods are necessary to fully account for anthropogenic impacts on ecosystems and the essential services provided by ecosystems that sustain human life. Current methods for assessing sustainability, such as life cycle assessment (LCA), typically focus on easily quantifiable indicators such as air emissions with no accounting for the essential

Better methods are necessary to fully account for anthropogenic impacts on ecosystems and the essential services provided by ecosystems that sustain human life. Current methods for assessing sustainability, such as life cycle assessment (LCA), typically focus on easily quantifiable indicators such as air emissions with no accounting for the essential ecosystem benefits that support human or industrial processes. For this reason, more comprehensive, transparent, and robust methods are necessary for holistic understanding of urban technosphere and ecosphere systems, including their interfaces. Incorporating ecosystem service indicators into LCA is an important step in spanning this knowledge gap.

For urban systems, many built environment processes have been investigated but need to be expanded with life cycle assessment for understanding ecosphere impacts. To pilot these new methods, a material inventory of the building infrastructure of Phoenix, Arizona can be coupled with LCA to gain perspective on the impacts assessment for built structures in Phoenix. This inventory will identify the origins of materials stocks, and the solid and air emissions waste associated with their raw material extraction, processing, and construction and identify key areas of future research necessary to fully account for ecosystem services in urban sustainability assessments. Based on this preliminary study, the ecosystem service impacts of metropolitan Phoenix stretch far beyond the county boundaries. A life cycle accounting of the Phoenix’s embedded building materials will inform policy and decision makers, assist with community education, and inform the urban sustainability community of consequences.

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Description

The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods

The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.

Created2021-09