ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Nighttime visibility of pavement markings is provided by glass beads embedded into the striping surface. The glass beads take light from the vehicle headlamps and reflect it back to the driver. This phenomenon is known as retroreflection. Literature suggests that the amount of the bead embedded into the striping surface has a profound impact on the intensity of the retroreflected light. In order to gain insight into how the glass beads provide retroreflection, an experiment was carried out to produce paint stripes with glass beads and measure the retroreflection. Samples were created at various application rates and embedment depths, in an attempt to verify the optimal embedment and observe the effect of application rate on retroreflection. The experiment was conducted using large, airport quality beads and small, road quality beads. Image analysis was used to calculate the degree to which beads were embedded and in an attempt to quantify bead distribution on the stripe surface. The results from the large beads showed that retroreflection was maximized when the beads were embedded approximately seventy percent by bead volume. The results also showed that as the application rate increased, the retroreflection increased, up to a point and then decreased. A model was developed to estimate the retroreflectivity given the amount of beads, bead spacing, and distribution of bead embedment. Results from the small beads were less conclusive, but did demonstrate that the larger beads are better at providing retroreflection. Avenues for future work in this area were identified as the experiment was conducted.
The activity-based approach to travel demand analysis and modeling, which has been developed over the past 30 years, has received tremendous success in transportation planning and policy analysis issues, capturing the multi-way joint relationships among socio-demographic, economic, land use characteristics, activity participation, and travel behavior. The development of synthesizing population with an array of socio-demographic and socio-economic attributes has drawn remarkable attention due to privacy and cost constraints in collecting and disclosing full scale data. Although, there has been enormous progress in producing synthetic population, there has been less progress in the development of population evolution modeling arena to forecast future year population. The objective of this dissertation is to develop a well-structured full-fledged demographic evolution modeling system, capturing migration dynamics and evolution of person level attributes, introducing the concept of new household formations and apprehending the dynamics of household level long-term choices over time. A comprehensive study has been conducted on demography, sociology, anthropology, economics and transportation engineering area to better understand the dynamics of evolutionary activities over time and their impacts in travel behavior. This dissertation describes the methodology and the conceptual framework, and the development of model components. Demographic, socio-economic, and land use data from American Community Survey, National Household Travel Survey, Census PUMS, United States Time Series Economic Dynamic data and United States Center for Disease Control and Prevention have been used in this research. The entire modeling system has been implemented and coded using programming language to develop the population evolution module named `PopEvol' into a computer simulation environment. The module then has been demonstrated for a portion of Maricopa County area in Arizona to predict the milestone year population to check the accuracy of forecasting. The module has also been used to evolve the base year population for next 15 years and the evolutionary trend has been investigated.
This study investigates the mastic level structure of asphalt concrete containing RAP materials. Locally sourced RAP material was screened and sieved to separate the coated fines (passing #200) from the remaining sizes. These binder coated fines were mixed with virgin filler at proportions commensurate with 0%, 10%, 30%, 50% and 100% RAP dosage levels. Mastics were prepared with these blended fillers and a PG 64-22 binder at a filler content of 27% by volume. Rheological experiments were conducted on the resulting composites as well as the constituents, virgin binder, solvent extracted RAP binder. The results from the dynamic modulus experiments showed an expected increase in stiffness with increase in dosage levels. These results were used to model the hypothesized structure of the composite. The study presented discusses the different micromechanical models employed, their applicability and suitability to correctly predict the blended mastic composite. The percentage of blending between virgin and RAP binder estimated using Herve and Zaoui model decreased with increase in RAP content.
Institutions of higher education, particularly those with large student enrollments, constitute special generators that contribute in a variety of ways to the travel demand in a region. Despite the importance of university population travel characteristics in understanding and modeling activity-travel patterns and mode choice behavior in a region, such populations remain under-studied. As metropolitan planning organizations continue to improve their regional travel models by incorporating processes and parameters specific to major regional special generators, university population travel characteristics need to be measured and special submodels that capture their behavior need to be developed. The research presented herein begins by documenting the design and administration of a comprehensive university student online travel and mode use survey that was administered at Arizona State University (ASU) in the Greater Phoenix region of Arizona. The dissertation research offers a detailed statistical analysis of student travel behavior for different student market segments. A framework is then presented for incorporating university student travel into a regional travel demand model. The application of the framework to the ASU student population is documented in detail. A comprehensive university student submodel was estimated and calibrated for integration with the full regional travel model system. Finally, student attitudes toward travel are analyzed and used as explanatory factors in multinomial logit models of mode choice. This analysis presents an examination of the extent to which attitudes play a role in explaining mode choice behavior of university students in an urban setting. The research provides evidence that student travel patterns vary substantially from those of the rest of the population, and should therefore be considered separately when forecasting travel demand and formulating transport policy in areas where universities are major contributors to regional travel.
A network-sensitive integrated travel model for simulating impacts of real-time traveler information
Real-time information systems are being used widely around the world to mitigate the adverse impacts of congestion and events that contribute to network delay. It is important that transportation modeling tools be able to accurately model the impacts of real-time information provision. Such planning tools allow the simulation of the impacts of various real-time information systems, and the design of traveler information systems that can minimize impacts of congestion and network disruptions. Such modeling tools would also be helpful in planning emergency response services as well as evacuation scenarios in the event of a natural disaster. Transportation modeling tools currently in use are quite limited in their ability to model the impacts of real-time information provision on travel demand and route choices. This dissertation research focuses on enhancing a previously developed integrated transportation modeling system dubbed SimTRAVEL (Simulator of Transport, Routes, Activities, Vehicles, Emissions, and Land) to incorporate capabilities that allow the simulation of the impacts of real-time traveler information systems on activity-travel demand. The first enhancement made to the SimTRAVEL framework involves the ability to reflect the effects of providing information on prevailing (as opposed to historical) network conditions on activity-travel behavior choices. In addition, the model system is enhanced to accommodate multiple user information classes (pre-trip and enroute) simultaneously. The second major contribution involves advancing the methodological framework to model enroute decision making processes where a traveler may alter his or her travel choices (such as destination choice) while enroute to an intended destination. Travelers who are provided up-to-date network information may choose to alter their destination in response to congested conditions, or completely abandon and reschedule an activity that offers some degree of flexibility. In this dissertation research, the model framework is developed and an illustrative demonstration of the capabilities of the enhanced model system is provided using a subregion of the Greater Phoenix metropolitan area in Arizona. The results show that the model is able to simulate adjustments in travel choices that may result from the introduction of real-time traveler information. The efficacy of the integrated travel model system is also demonstrated through the application of the enhanced model system to evaluate transportation policy scenarios.
ure of merit (zT) due to quantum connement eects. Improving the eciency of
thermoelectric devices allows for the development of better, more economical waste
heat recovery systems. Such systems may be used as bottoming or co-generation
cycles in conjunction with conventional power cycles to recover some of the wasted
heat. Thermal conductivity measurement systems are an important part of the char-
acterization processes of thermoelectric materials. These systems must possess the
capability of accurately measuring the thermal conductivity of both bulk and thin-lm
samples at dierent ambient temperatures.
This paper discusses the construction, validation, and improvement of a thermal
conductivity measurement platform based on the 3-Omega technique. Room temperature
measurements of thermal conductivity done on control samples with known properties
such as undoped bulk silicon (Si), bulk gallium arsenide (GaAs), and silicon dioxide
(SiO2) thin lms yielded 150 W=m􀀀K, 50 W=m􀀀K, and 1:46 W=m􀀀K respectively.
These quantities were all within 8% of literature values. In addition, the thermal
conductivity of bulk SiO2 was measured as a function of temperature in a Helium-
4 cryostat from 75K to 250K. The results showed good agreement with literature
values that all fell within the error range of each measurement. The uncertainty in
the measurements ranged from 19% at 75K to 30% at 250K. Finally, the system
was used to measure the room temperature thermal conductivity of a nanocomposite
composed of cadmium selenide, CdSe, nanocrystals in an indium selenide, In2Se3,
matrix as a function of the concentration of In2Se3. The observed trend was in
qualitative agreement with the expected behavior.
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