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- Genre: Doctoral Dissertation
Description
Engineering education can provide students with the tools to address complex, multidisciplinary grand challenge problems in sustainable and global contexts. However, engineering education faces several challenges, including low diversity percentages, high attrition rates, and the need to better engage and prepare students for the role of a modern engineer. These challenges can be addressed by integrating sustainability grand challenges into engineering curriculum.
Two main strategies have emerged for integrating sustainability grand challenges. In the stand-alone course method, engineering programs establish one or two distinct courses that address sustainability grand challenges in depth. In the module method, engineering programs integrate sustainability grand challenges throughout existing courses. Neither method has been assessed in the literature.
This thesis aimed to develop sustainability modules, to create methods for evaluating the modules’ effectiveness on student cognitive and affective outcomes, to create methods for evaluating students’ cumulative sustainability knowledge, and to evaluate the stand-alone course method to integrate sustainability grand challenges into engineering curricula via active and experiential learning.
The Sustainable Metrics Module for teaching sustainability concepts and engaging and motivating diverse sets of students revealed that the activity portion of the module had the greatest impact on learning outcome retention.
The Game Design Module addressed methods for assessing student mastery of course content with student-developed games indicated that using board game design improved student performance and increased student satisfaction.
Evaluation of senior design capstone projects via novel comprehensive rubric to assess sustainability learned over students’ curriculum revealed that students’ performance is primarily driven by their instructor’s expectations. The rubric provided a universal tool for assessing students’ sustainability knowledge and could also be applied to sustainability-focused projects.
With this in mind, engineering educators should pursue modules that connect sustainability grand challenges to engineering concepts, because student performance improves and students report higher satisfaction. Instructors should utilize pedagogies that engage diverse students and impact concept retention, such as active and experiential learning. When evaluating the impact of sustainability in the curriculum, innovative assessment methods should be employed to understand student mastery and application of course concepts and the impacts that topics and experiences have on student satisfaction.
Two main strategies have emerged for integrating sustainability grand challenges. In the stand-alone course method, engineering programs establish one or two distinct courses that address sustainability grand challenges in depth. In the module method, engineering programs integrate sustainability grand challenges throughout existing courses. Neither method has been assessed in the literature.
This thesis aimed to develop sustainability modules, to create methods for evaluating the modules’ effectiveness on student cognitive and affective outcomes, to create methods for evaluating students’ cumulative sustainability knowledge, and to evaluate the stand-alone course method to integrate sustainability grand challenges into engineering curricula via active and experiential learning.
The Sustainable Metrics Module for teaching sustainability concepts and engaging and motivating diverse sets of students revealed that the activity portion of the module had the greatest impact on learning outcome retention.
The Game Design Module addressed methods for assessing student mastery of course content with student-developed games indicated that using board game design improved student performance and increased student satisfaction.
Evaluation of senior design capstone projects via novel comprehensive rubric to assess sustainability learned over students’ curriculum revealed that students’ performance is primarily driven by their instructor’s expectations. The rubric provided a universal tool for assessing students’ sustainability knowledge and could also be applied to sustainability-focused projects.
With this in mind, engineering educators should pursue modules that connect sustainability grand challenges to engineering concepts, because student performance improves and students report higher satisfaction. Instructors should utilize pedagogies that engage diverse students and impact concept retention, such as active and experiential learning. When evaluating the impact of sustainability in the curriculum, innovative assessment methods should be employed to understand student mastery and application of course concepts and the impacts that topics and experiences have on student satisfaction.
ContributorsAntaya, Claire Louise (Author) / Landis, Amy E. (Thesis advisor) / Parrish, Kristen (Thesis advisor) / Bilec, Melissa M (Committee member) / Besterfield-Sacre, Mary E (Committee member) / Allenby, Braden R. (Committee member) / Arizona State University (Publisher)
Created2015
Description
High performing and sustainable building certification bodies continue to update their requirements, leading to scope modification of certifications, and an increasing number of viable sources of environmental information for building materials. In conjunction, the Architecture, Engineering, and Construction (AEC) industry is seeing increasing demand for such environmental product information. The industry and certifications are moving from using single attribute environmental information about building materials to lifecycle based information to inform their design decisions.
This dissertation seeks to understand the current practices, and then focus on strategies to effectively utilize newer sources of environmental product information in high performance building design. The first phase of research used a survey of 119 U.S.-based AEC practitioners experienced in certified sustainable building projects to understand how the numerous sources of environmental information are currently used in the building design process. The second phase asked two focus groups of experienced AEC professionals to develop a Message Sequence Chart (MSC) that documents the conceptual design process for a recently designed building. Then, the focus group participants integrated a new sustainability requirement for building materials, Environmental Product Declarations (EPDs), into their project, and documented the adjustments to their specific design process in a second, modified MSC highlighting potential drivers for inclusion of EPDs. Finally, the author examines the broader applicability of these drivers through case studies. Specifically, 19 certified high-performance building (HPB) case studies, for reviewing the impact of three different potential drivers on the design team’s approach to considering environmental product information during conceptual design of a HPB, as well as the projects certification level.
LEED certification has changed the design of buildings, and the new information sources for building materials will inform the way the industry selects building materials. Meanwhile, these information sources will need to expand to include a growing number of products, and potentially more data as the industry’s understanding of the impacts of building materials develops. This research expands upon previous research on LEED certification to illustrates that owner engagement and commitment to the HPB process is a critical success factor for the use of environmental product information about building materials.
This dissertation seeks to understand the current practices, and then focus on strategies to effectively utilize newer sources of environmental product information in high performance building design. The first phase of research used a survey of 119 U.S.-based AEC practitioners experienced in certified sustainable building projects to understand how the numerous sources of environmental information are currently used in the building design process. The second phase asked two focus groups of experienced AEC professionals to develop a Message Sequence Chart (MSC) that documents the conceptual design process for a recently designed building. Then, the focus group participants integrated a new sustainability requirement for building materials, Environmental Product Declarations (EPDs), into their project, and documented the adjustments to their specific design process in a second, modified MSC highlighting potential drivers for inclusion of EPDs. Finally, the author examines the broader applicability of these drivers through case studies. Specifically, 19 certified high-performance building (HPB) case studies, for reviewing the impact of three different potential drivers on the design team’s approach to considering environmental product information during conceptual design of a HPB, as well as the projects certification level.
LEED certification has changed the design of buildings, and the new information sources for building materials will inform the way the industry selects building materials. Meanwhile, these information sources will need to expand to include a growing number of products, and potentially more data as the industry’s understanding of the impacts of building materials develops. This research expands upon previous research on LEED certification to illustrates that owner engagement and commitment to the HPB process is a critical success factor for the use of environmental product information about building materials.
ContributorsBurke, Rebekah (Author) / Parrish, Kristen (Thesis advisor) / Gibson, G. Edward (Committee member) / Allenby, Braden (Committee member) / Arizona State University (Publisher)
Created2018
Description
Recent studies have identified that contractors in the Saudi construction industry are not the main party that cause risks as owners and other parties have the major share of causing risks. However, with the identification that risks out of contractors’ control are a leading cause of low performance, there is a lack of efficient risk mitigation practices in Saudi to manage these risks. The main aim of this dissertation is to assess the current practices applied by contractors to minimize risk out of their control and develop a risk mitigation model to manage these risks. The main objectives of the study are: investigating the risks that are out of contractors’ control, assessing the contractors’ current risk mitigation and performance measurement practices, and finally developing and validating a risk mitigation model to minimize risks out of contractors’ control and measure performance of involved project parties. To achieve the study aim, a mixed methodological approach was adopted. Theoretical approaches were utilized to review previous research and to develop a conceptual risk mitigation framework followed by a practical approach that is considered with collecting data from contractors. The quantitative method was mainly used to meet the study objectives through distributing a survey in the form of a questionnaire. As a consolidation of the study findings, the top ranked risks that are out of contractors’ control were identified. Furthermore, the results identified that the contractors’ current risk management and performance measurement practices are not effective in minimizing projects risks caused by other parties and ineffective in measuring performance of all parties. The developed model focuses on increasing accountability of project parties through mitigating project parties’ activities and risks with measuring the deviations and identifying sources of deviations. Transparency is utilized in the model through sharing weekly updates of the activities and risks combined with updated information of performance measurements of all project parties. The study results showed that project risks can be minimized and projects’ performance can be increased if contractors shift their focus using the developed model from only managing their own activities and risks to managing all project parties’ activities and risks.
ContributorsAlgahtany, Mohammed (Author) / Sullivan, Kenneth (Thesis advisor) / Kashiwagi, Dean (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2018
Description
Recently, automation, shared use, and electrification are proposed and viewed as the “three revolutions” in the future transportation sector to significantly relieve traffic congestion, reduce pollutant emissions, and increase transportation system sustainability. Motivated by the three revolutions, this research targets on the passenger-focused scheduled transportation systems, where (1) the public transit systems provide high-quality ridesharing schedules/services and (2) the upcoming optimal activity planning systems offer the best vehicle routing and assignment for household daily scheduled activities.
The high quality of system observability is the fundamental guarantee for accurately predicting and controlling the system. The rich information from the emerging heterogeneous data sources is making it possible. This research proposes a modeling framework to systemically account for the multi-source sensor information in urban transit systems to quantify the estimated state uncertainty. A system of linear equations and inequalities is proposed to generate the information space. Also, the observation errors are further considered by a least square model. Then, a number of projection functions are introduced to match the relation between the unique information space and different system states, and its corresponding state estimate uncertainties are further quantified by calculating its maximum state range.
In addition to optimizing daily operations, the continuing advances in information technology provide precious individual travel behavior data and trip information for operational planning in transit systems. This research also proposes a new alternative modeling framework to systemically account for boundedly rational decision rules of travelers in a dynamic transit service network with tight capacity constraints. An agent-based single-level integer linear formulation is proposed and can be effectively by the Lagrangian decomposition.
The recently emerging trend of self-driving vehicles and information sharing technologies starts creating a revolutionary paradigm shift for traveler mobility applications. By considering a deterministic traveler decision making framework, this research addresses the challenges of how to optimally schedule household members’ daily scheduled activities under the complex household-level activity constraints by proposing a set of integer linear programming models. Meanwhile, in the microscopic car-following level, the trajectory optimization of autonomous vehicles is also studied by proposing a binary integer programming model.
The high quality of system observability is the fundamental guarantee for accurately predicting and controlling the system. The rich information from the emerging heterogeneous data sources is making it possible. This research proposes a modeling framework to systemically account for the multi-source sensor information in urban transit systems to quantify the estimated state uncertainty. A system of linear equations and inequalities is proposed to generate the information space. Also, the observation errors are further considered by a least square model. Then, a number of projection functions are introduced to match the relation between the unique information space and different system states, and its corresponding state estimate uncertainties are further quantified by calculating its maximum state range.
In addition to optimizing daily operations, the continuing advances in information technology provide precious individual travel behavior data and trip information for operational planning in transit systems. This research also proposes a new alternative modeling framework to systemically account for boundedly rational decision rules of travelers in a dynamic transit service network with tight capacity constraints. An agent-based single-level integer linear formulation is proposed and can be effectively by the Lagrangian decomposition.
The recently emerging trend of self-driving vehicles and information sharing technologies starts creating a revolutionary paradigm shift for traveler mobility applications. By considering a deterministic traveler decision making framework, this research addresses the challenges of how to optimally schedule household members’ daily scheduled activities under the complex household-level activity constraints by proposing a set of integer linear programming models. Meanwhile, in the microscopic car-following level, the trajectory optimization of autonomous vehicles is also studied by proposing a binary integer programming model.
ContributorsLiu, Jiangtao (Author) / Zhou, Xuesong (Thesis advisor) / Pendyala, Ram (Committee member) / Mirchandani, Pitu (Committee member) / Lou, Yingyan (Committee member) / Arizona State University (Publisher)
Created2018
Description
Flooding is a critical issue around the world, and the absence of comprehension of watershed hydrologic reaction results in lack of lead-time for flood forecasting and expensive harm to property and life. It happens when water flows due to extreme rainfall storm, dam breach or snowmelt exceeds the capacity of river system reservoirs and channels. The objective of this research was to develop a methodology for determining a time series operation for releases through control gates of river-reservoir systems during flooding events in a real-time using one- and/or two-dimensional modeling of flows through river-reservoir systems.
The optimization-simulation methodology interfaces several simulation-software coupled together with an optimization model solved by genetic algorithm coded in MATLAB. These software include the U.S. Army Corps of Engineers HEC-RAS linked the genetic algorithm in MATLAB to come up with an optimization-simulation model for time series gate openings to control downstream elevations. The model involves using the one- and two-dimensional ability in HEC-RAS to perform hydrodynamic routing with high-resolution raster Digital Elevation Models. Also, the model uses both real-time gridded- and gaged-rainfall data in addition to a model for forecasting future rainfall-data.
This new model has been developed to manage reservoir release schedules before, during, and after an extraordinary rainfall event that could cause extreme flooding. Further to observe and control downstream water surface elevations to avoid exceedance of threshold of flood levels in target cells in the downstream area of study, and to minimize the damage and direct effects in both the up and downstream.
The application of the complete optimization-simulation model was applied to a portion of the Cumberland River System in Nashville, Tennessee for the flooding event of May 2010. The objective of this application is to demonstrate the applicability of the model for minimizing flood damages for an actual flood event in real-time on an actual river basin. The purpose of the application in a real-time framework would be to minimize the flood damages at Nashville, Tennessee by keeping the flood stages under the 100-year flood stage. This application also compared the three unsteady flow simulation scenarios: one-dimensional, two-dimensional and combined one- and two-dimensional unsteady flow.
The optimization-simulation methodology interfaces several simulation-software coupled together with an optimization model solved by genetic algorithm coded in MATLAB. These software include the U.S. Army Corps of Engineers HEC-RAS linked the genetic algorithm in MATLAB to come up with an optimization-simulation model for time series gate openings to control downstream elevations. The model involves using the one- and two-dimensional ability in HEC-RAS to perform hydrodynamic routing with high-resolution raster Digital Elevation Models. Also, the model uses both real-time gridded- and gaged-rainfall data in addition to a model for forecasting future rainfall-data.
This new model has been developed to manage reservoir release schedules before, during, and after an extraordinary rainfall event that could cause extreme flooding. Further to observe and control downstream water surface elevations to avoid exceedance of threshold of flood levels in target cells in the downstream area of study, and to minimize the damage and direct effects in both the up and downstream.
The application of the complete optimization-simulation model was applied to a portion of the Cumberland River System in Nashville, Tennessee for the flooding event of May 2010. The objective of this application is to demonstrate the applicability of the model for minimizing flood damages for an actual flood event in real-time on an actual river basin. The purpose of the application in a real-time framework would be to minimize the flood damages at Nashville, Tennessee by keeping the flood stages under the 100-year flood stage. This application also compared the three unsteady flow simulation scenarios: one-dimensional, two-dimensional and combined one- and two-dimensional unsteady flow.
ContributorsAlbo-Salih, Hasan Hadi Kraidi (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2019
Description
Asphalt concrete is a non-homogenous viscoelastic material; its behavior depends on the properties of the asphalt binder and the aggregate skeleton. The two major distresses in flexible pavements, fatigue cracking and rutting, have different mechanisms in that the way binders and mixtures behavior are related differ. Further complicating the issues is that distresses in asphalt pavement are dependent on climate, pavement structure, and traffic loads, in addition to factors such as properties of the asphalt mixture itself. Hence, to characterize the multiscale mechanics associated with binder to mixture behaviors, researchers characterized the fatigue and rutting resistance of asphalt binders and mixtures in the laboratory, and established specifications related to how asphalt mixtures would perform in the field.
This dissertation tackles the linkages across length scales with respect to rutting and cracking. Through the literature reviewed, studies regarding the linear and non-linear viscoelastic properties of asphalt mixture and the corresponding bitumen were identified. There was a wealth of data in this area. In addition, the relationship between the laboratory mixture short-term aging and the binder aging conditions were studied, characterized and analyzed.
The literature review showed that there exists a shortage of knowledge that directly examines the relationships between the binder nonlinear viscoelastic damage behaviors and mixture performance. Addressing this knowledge gap is the basic objective of this research. Specifically, the relationships between the non-recoverable creep compliance at 3.2 kPa (Jnr3.2) and the percent of elastic recovery (R3.2) from the multiple stress creep and recovery (MSCR) test and mixture rutting; and between mixture fatigue and binder linear amplitude sweep (LAS) were studied.
Finally, an aging study was performed to ensure that the binder tests properties reflect the condition of the binder during the mixture test when evaluating binder-to-mixture properties. The propensity to oxidize measured by calculating the aging ratio of various aged conditions (RTFO, PAV, and STOA) were gathered and analyzed.
This dissertation tackles the linkages across length scales with respect to rutting and cracking. Through the literature reviewed, studies regarding the linear and non-linear viscoelastic properties of asphalt mixture and the corresponding bitumen were identified. There was a wealth of data in this area. In addition, the relationship between the laboratory mixture short-term aging and the binder aging conditions were studied, characterized and analyzed.
The literature review showed that there exists a shortage of knowledge that directly examines the relationships between the binder nonlinear viscoelastic damage behaviors and mixture performance. Addressing this knowledge gap is the basic objective of this research. Specifically, the relationships between the non-recoverable creep compliance at 3.2 kPa (Jnr3.2) and the percent of elastic recovery (R3.2) from the multiple stress creep and recovery (MSCR) test and mixture rutting; and between mixture fatigue and binder linear amplitude sweep (LAS) were studied.
Finally, an aging study was performed to ensure that the binder tests properties reflect the condition of the binder during the mixture test when evaluating binder-to-mixture properties. The propensity to oxidize measured by calculating the aging ratio of various aged conditions (RTFO, PAV, and STOA) were gathered and analyzed.
ContributorsSalim, Ramadan A (Author) / Underwood, Shane (Thesis advisor) / Kaloush, Kamil (Thesis advisor) / Mamlouk, Mike (Committee member) / Arizona State University (Publisher)
Created2019
Description
The success or failure of projects is not determined only by procedures, tasks, and technologies, but also by the project team and its effectiveness. In order to lead project teams towards successful outcomes, project managers must maintain high quality relationships in the workplace. When looking at employees’ relationships in the workplace, Social Exchange Theory introduces two types of exchanges: employee-organization and leader-member exchanges. While both types of exchanges focus exclusively on the employee’s longitudinal relationships, the interpersonal relationships among the team members are usually overlooked.
This research presents the results of a quantitative study of the interpersonal relationships of 327 project managers and assistant project managers in their workplace. Specifically, the study investigates if the quality of the relationship with particular stakeholders, such as one’s immediate supervisor (boss), peers, or subordinates, drives the individual’s quality of the relationship with other stakeholders.
Contrary to the expectations, in strictly hierarchical organizations (one direct supervisor), there is no significant correlation between the quality of relationships with the boss and the overall quality of the individual’s relationships. However, in the case of matrix organizations (two or three bosses), there are significant correlations between several variables such as the quality of the relationship, perceived importance and the time spent with each stakeholder, as well the inclination of the participant towards leadership actions. The driving relationship in matrix organizations is the one with “the most important peer”.
This research presents the results of a quantitative study of the interpersonal relationships of 327 project managers and assistant project managers in their workplace. Specifically, the study investigates if the quality of the relationship with particular stakeholders, such as one’s immediate supervisor (boss), peers, or subordinates, drives the individual’s quality of the relationship with other stakeholders.
Contrary to the expectations, in strictly hierarchical organizations (one direct supervisor), there is no significant correlation between the quality of relationships with the boss and the overall quality of the individual’s relationships. However, in the case of matrix organizations (two or three bosses), there are significant correlations between several variables such as the quality of the relationship, perceived importance and the time spent with each stakeholder, as well the inclination of the participant towards leadership actions. The driving relationship in matrix organizations is the one with “the most important peer”.
ContributorsK. Jamali, M. Hossein (Author) / Wiezel, Avi (Thesis advisor) / Sullivan, Kenneth T. (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2019
Description
Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). Previous research has made a number of important contributions to the challenging pickup and delivery problem along different formulation or solution approaches. However, there are a number of modeling and algorithmic challenges for a large-scale deployment of a vehicle routing and scheduling algorithm, especially for regional networks with various road capacity and traffic delay constraints on freeway bottlenecks and signal timing on urban streets. The main thrust of this research is constructing hyper-networks to implicitly impose complicated constraints of a vehicle routing problem (VRP) into the model within the network construction. This research introduces a new methodology based on hyper-networks to solve the very important vehicle routing problem for the case of generic ride-sharing problem. Then, the idea of hyper-networks is applied for (1) solving the pickup and delivery problem with synchronized transfers, (2) computing resource hyper-prisms for sustainable transportation planning in the field of time-geography, and (3) providing an integrated framework that fully captures the interactions between supply and demand dimensions of travel to model the implications of advanced technologies and mobility services on traveler behavior.
ContributorsMahmoudi, Monirehalsadat (Author) / Zhou, Xuesong (Thesis advisor) / Mirchandani, Pitu B. (Committee member) / Miller, Harvey J. (Committee member) / Pendyala, Ram M. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Resilience is emerging as the preferred way to improve the protection of infrastructure systems beyond established risk management practices. Massive damages experienced during tragedies like Hurricane Katrina showed that risk analysis is incapable to prevent unforeseen infrastructure failures and shifted expert focus towards resilience to absorb and recover from adverse events. Recent, exponential growth in research is now producing consensus on how to think about infrastructure resilience centered on definitions and models from influential organizations like the US National Academy of Sciences. Despite widespread efforts, massive infrastructure failures in 2017 demonstrate that resilience is still not working, raising the question: Are the ways people think about resilience producing resilient infrastructure systems?
This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.
Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.
This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.
Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.
ContributorsEisenberg, Daniel Alexander (Author) / Seager, Thomas P. (Thesis advisor) / Park, Jeryang (Thesis advisor) / Alderson, David L. (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2018
Description
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.
ContributorsGundla, Akshay (Author) / Underwood, Benjamin S (Thesis advisor) / Kaloush, Kamil (Thesis advisor) / Mamlouk, Michael S. (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2018