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Urban scaling analysis has introduced a new scientific paradigm to the study of cities. With it, the notions of size, heterogeneity and structure have taken a leading role. These notions are assumed to be behind the causes for why cities differ from one another, sometimes wildly. However, the mechanisms by which size, heterogeneity and structure shape the general statistical patterns that describe urban economic output are still unclear. Given the rapid rate of urbanization around the globe, we need precise and formal mathematical understandings of these matters. In this context, I perform in this dissertation probabilistic, distributional and computational explorations of (i) how the broadness, or narrowness, of the distribution of individual productivities within cities determines what and how we measure urban systemic output, (ii) how urban scaling may be expressed as a statistical statement when urban metrics display strong stochasticity, (iii) how the processes of aggregation constrain the variability of total urban output, and (iv) how the structure of urban skills diversification within cities induces a multiplicative process in the production of urban output.
ContributorsGómez-Liévano, Andrés (Author) / Lobo, Jose (Thesis advisor) / Muneepeerakul, Rachata (Thesis advisor) / Bettencourt, Luis M. A. (Committee member) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2014
Description
As a developing nation, China is currently faced with the challenge of providing
safe, reliable and adequate energy resources to the county's growing urban areas as well as to its expanding rural populations. To meet this demand, the country has initiated massive construction projects to expand its national energy infrastructure, particularly in the form of natural gas pipeline. The most notable of these projects is the ongoing West-East Gas Pipeline Project. This project is currently in its third phase, which will supply clean and efficient natural gas to nearly sixty million users located in the densely populated Yangtze River Delta.
Trenchless Technologies, in particular the construction method of Horizontal
Directional Drilling (HDD), have played a critical role in executing this project by
providing economical, practical and environmentally responsible ways to install buried pipeline systems. HDD has proven to be the most popular method selected to overcome challenges along the path of the pipeline, which include mountainous terrain, extensive farmland and numerous bodies of water. The Yangtze River, among other large-scale water bodies, have proven to be the most difficult obstacle for the pipeline installation as it widens and changes course numerous times along its path to the East China Sea. The purpose of this study is to examine those practices being used in China in order to compare those to those long used practices in the North American in order to understand the advantages of Chinese advancements.
Developing countries would benefit from the Chinese advancements for large-scale HDD installation. In developed areas, such as North America, studying Chinese execution may allow for new ideas to help to improve long established methods. These factors combined further solidify China's role as the global leader in trenchless technology methods and provide the opportunity for Chinese HDD contractors to contribute to the world's knowledge for best practices of the Horizontal Directional Drilling method.
safe, reliable and adequate energy resources to the county's growing urban areas as well as to its expanding rural populations. To meet this demand, the country has initiated massive construction projects to expand its national energy infrastructure, particularly in the form of natural gas pipeline. The most notable of these projects is the ongoing West-East Gas Pipeline Project. This project is currently in its third phase, which will supply clean and efficient natural gas to nearly sixty million users located in the densely populated Yangtze River Delta.
Trenchless Technologies, in particular the construction method of Horizontal
Directional Drilling (HDD), have played a critical role in executing this project by
providing economical, practical and environmentally responsible ways to install buried pipeline systems. HDD has proven to be the most popular method selected to overcome challenges along the path of the pipeline, which include mountainous terrain, extensive farmland and numerous bodies of water. The Yangtze River, among other large-scale water bodies, have proven to be the most difficult obstacle for the pipeline installation as it widens and changes course numerous times along its path to the East China Sea. The purpose of this study is to examine those practices being used in China in order to compare those to those long used practices in the North American in order to understand the advantages of Chinese advancements.
Developing countries would benefit from the Chinese advancements for large-scale HDD installation. In developed areas, such as North America, studying Chinese execution may allow for new ideas to help to improve long established methods. These factors combined further solidify China's role as the global leader in trenchless technology methods and provide the opportunity for Chinese HDD contractors to contribute to the world's knowledge for best practices of the Horizontal Directional Drilling method.
ContributorsCarlin, Maureen Cassin (Author) / Ariaratnam, Samuel T (Thesis advisor) / Chong, Oswald (Committee member) / Bearup, Wylie (Committee member) / Arizona State University (Publisher)
Created2014
Description
The increased number of novel pathogens that potentially threaten the human population has motivated the development of mathematical and computational modeling approaches for forecasting epidemic impact and understanding key environmental characteristics that influence the spread of diseases. Yet, in the case that substantial uncertainty surrounds the transmission process during a rapidly developing infectious disease outbreak, complex mechanistic models may be too difficult to be calibrated quick enough for policy makers to make informed decisions. Simple phenomenological models that rely on a small number of parameters can provide an initial platform for assessing the epidemic trajectory, estimating the reproduction number and quantifying the disease burden from the early epidemic phase.
Chapter 1 provides background information and motivation for infectious disease forecasting and outlines the rest of the thesis.
In chapter 2, logistic patch models are used to assess and forecast the 2013-2015 West Africa Zaire ebolavirus epidemic. In particular, this chapter is concerned with comparing and contrasting the effects that spatial heterogeneity has on the forecasting performance of the cumulative infected case counts reported during the epidemic.
In chapter 3, two simple phenomenological models inspired from population biology are used to assess the Research and Policy for Infectious Disease Dynamics (RAPIDD) Ebola Challenge; a simulated epidemic that generated 4 infectious disease scenarios. Because of the nature of the synthetically generated data, model predictions are compared to exact epidemiological quantities used in the simulation.
In chapter 4, these models are applied to the 1904 Plague epidemic that occurred in Bombay. This chapter provides evidence that these simple models may be applicable to infectious diseases no matter the disease transmission mechanism.
Chapter 5, uses the patch models from chapter 2 to explore how migration in the 1904 Plague epidemic changes the final epidemic size.
The final chapter is an interdisciplinary project concerning within-host dynamics of cereal yellow dwarf virus-RPV, a plant pathogen from a virus group that infects over 150 grass species. Motivated by environmental nutrient enrichment due to anthropological activities, mathematical models are employed to investigate the relevance of resource competition to pathogen and host dynamics.
Chapter 1 provides background information and motivation for infectious disease forecasting and outlines the rest of the thesis.
In chapter 2, logistic patch models are used to assess and forecast the 2013-2015 West Africa Zaire ebolavirus epidemic. In particular, this chapter is concerned with comparing and contrasting the effects that spatial heterogeneity has on the forecasting performance of the cumulative infected case counts reported during the epidemic.
In chapter 3, two simple phenomenological models inspired from population biology are used to assess the Research and Policy for Infectious Disease Dynamics (RAPIDD) Ebola Challenge; a simulated epidemic that generated 4 infectious disease scenarios. Because of the nature of the synthetically generated data, model predictions are compared to exact epidemiological quantities used in the simulation.
In chapter 4, these models are applied to the 1904 Plague epidemic that occurred in Bombay. This chapter provides evidence that these simple models may be applicable to infectious diseases no matter the disease transmission mechanism.
Chapter 5, uses the patch models from chapter 2 to explore how migration in the 1904 Plague epidemic changes the final epidemic size.
The final chapter is an interdisciplinary project concerning within-host dynamics of cereal yellow dwarf virus-RPV, a plant pathogen from a virus group that infects over 150 grass species. Motivated by environmental nutrient enrichment due to anthropological activities, mathematical models are employed to investigate the relevance of resource competition to pathogen and host dynamics.
ContributorsPell, Bruce (Author) / Kuang, Yang (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Nagy, John (Committee member) / Kostelich, Eric (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2016
Description
The solar energy sector has been growing rapidly over the past decade. Growth in renewable electricity generation using photovoltaic (PV) systems is accompanied by an increased awareness of the fault conditions developing during the operational lifetime of these systems. While the annual energy losses caused by faults in PV systems could reach up to 18.9% of their total capacity, emerging technologies and models are driving for greater efficiency to assure the reliability of a product under its actual application. The objectives of this dissertation consist of (1) reviewing the state of the art and practice of prognostics and health management for the Direct Current (DC) side of photovoltaic systems; (2) assessing the corrosion of the driven posts supporting PV structures in utility scale plants; and (3) assessing the probabilistic risk associated with the failure of polymeric materials that are used in tracker and fixed tilt systems.
As photovoltaic systems age under relatively harsh and changing environmental conditions, several potential fault conditions can develop during the operational lifetime including corrosion of supporting structures and failures of polymeric materials. The ability to accurately predict the remaining useful life of photovoltaic systems is critical for plants ‘continuous operation. This research contributes to the body of knowledge of PV systems reliability by: (1) developing a meta-model of the expected service life of mounting structures; (2) creating decision frameworks and tools to support practitioners in mitigating risks; (3) and supporting material selection for fielded and future photovoltaic systems. The newly developed frameworks were validated by a global solar company.
As photovoltaic systems age under relatively harsh and changing environmental conditions, several potential fault conditions can develop during the operational lifetime including corrosion of supporting structures and failures of polymeric materials. The ability to accurately predict the remaining useful life of photovoltaic systems is critical for plants ‘continuous operation. This research contributes to the body of knowledge of PV systems reliability by: (1) developing a meta-model of the expected service life of mounting structures; (2) creating decision frameworks and tools to support practitioners in mitigating risks; (3) and supporting material selection for fielded and future photovoltaic systems. The newly developed frameworks were validated by a global solar company.
ContributorsChokor, Abbas (Author) / El Asmar, Mounir (Thesis advisor) / Chong, Oswald (Committee member) / Ernzen, James (Committee member) / Arizona State University (Publisher)
Created2017
Description
Civil infrastructures undergo frequent spatial changes such as deviations between as-designed model and as-is condition, rigid body motions of the structure, and deformations of individual elements of the structure, etc. These spatial changes can occur during the design phase, the construction phase, or during the service life of a structure. Inability to accurately detect and analyze the impact of such changes may miss opportunities for early detections of pending structural integrity and stability issues. Commercial Building Information Modeling (BIM) tools could hardly track differences between as-designed and as-built conditions as they mainly focus on design changes and rely on project managers to manually update and analyze the impact of field changes on the project performance. Structural engineers collect detailed onsite data of a civil infrastructure to perform manual updates of the model for structural analysis, but such approach tends to become tedious and complicated while handling large civil infrastructures.
Previous studies started collecting detailed geometric data generated by 3D laser scanners for defect detection and geometric change analysis of structures. However, previous studies have not yet systematically examined methods for exploring the correlation between the detected geometric changes and their relation to the behaviors of the structural system. Manually checking every possible loading combination leading to the observed geometric change is tedious and sometimes error-prone. The work presented in this dissertation develops a spatial change analysis framework that utilizes spatiotemporal data collected using 3D laser scanning technology and the as-designed models of the structures to automatically detect, classify, and correlate the spatial changes of a structure. The change detection part of the developed framework is computationally efficient and can automatically detect spatial changes between as-designed model and as-built data or between two sets of as-built data collected using 3D laser scanning technology. Then a spatial change classification algorithm automatically classifies the detected spatial changes as global (rigid body motion) and local deformations (tension, compression). Finally, a change correlation technique utilizes a qualitative shape-based reasoning approach for identifying correlated deformations of structure elements connected at joints that contradicts the joint equilibrium. Those contradicting deformations can help to eliminate improbable loading combinations therefore guiding the loading path analysis of the structure.
Previous studies started collecting detailed geometric data generated by 3D laser scanners for defect detection and geometric change analysis of structures. However, previous studies have not yet systematically examined methods for exploring the correlation between the detected geometric changes and their relation to the behaviors of the structural system. Manually checking every possible loading combination leading to the observed geometric change is tedious and sometimes error-prone. The work presented in this dissertation develops a spatial change analysis framework that utilizes spatiotemporal data collected using 3D laser scanning technology and the as-designed models of the structures to automatically detect, classify, and correlate the spatial changes of a structure. The change detection part of the developed framework is computationally efficient and can automatically detect spatial changes between as-designed model and as-built data or between two sets of as-built data collected using 3D laser scanning technology. Then a spatial change classification algorithm automatically classifies the detected spatial changes as global (rigid body motion) and local deformations (tension, compression). Finally, a change correlation technique utilizes a qualitative shape-based reasoning approach for identifying correlated deformations of structure elements connected at joints that contradicts the joint equilibrium. Those contradicting deformations can help to eliminate improbable loading combinations therefore guiding the loading path analysis of the structure.
ContributorsKalasapudi, Vamsi Sai (Author) / Tang, Pingbo (Thesis advisor) / Chong, Oswald (Committee member) / Hjelmstad, Keith (Committee member) / Arizona State University (Publisher)
Created2017
Description
The performance of the Alpha Sprayed Polyurethane Foam (SPF) roofing system is perceived as not an economical option when compared to a 20-year modified bitumen roofing system. Today, the majority of roofs are being replaced, rather than newly installed. The coating manufacturer, Neogard, implemented the Alpha roofing program to identify the best contractors in the industry and to measure their roof performance. The Alpha roof system has shown consistent high performance on over 230 million square feet of surveyed roof. The author proposes to identify if the Alpha roof system is renewable, has proven performance that competes with the traditional modified roofing system, and is a more economical option by evaluating an Alpha roof system installation and the performance of a 29-year-old Alpha roof system. The Dallas Independent School District utilized the Alpha program for William Lipscomb Elementary School in 2016. Dallas Fort Worth Urethane installed the Alpha SPF roof system with high customer satisfaction ratings. This roofing installation showed the value of the Alpha roof system by saving over 20% on costs for the installation and will save approximately 69% of costs on the recoating of the roof in 20 years. The Casa View Elementary School roof system was installed with a Neogard Permathane roof system in 1987. This roof was hail tested with ten drops from 17 feet 9 inches of 1-3/4-inch steel ball (9 out of 10 passed) and four drops from 17 feet 9 inches with a 3-inch diameter steel ball (2 out of 4 passed). The analysis of the passing and failing core samples show that the thickness of the top and base Alpha SPF coating is one of the major differences in a roof passing or failing the FM-SH hail test. Over the 40-year service life, the main difference of purchasing a 61,000 square feet Alpha SPF roof versus modified bitumen roof are savings of approximately $1,067,500. Past hail tests on Alpha SPF roof systems show its cost effectiveness with high customer satisfaction (9.8 out of 10), an over 40-year service life after a $6.00/SF recoat and savings of over $1M for DISD.
ContributorsZulanas, Charles J., IV (Author) / Kashiwagi, Dean T. (Thesis advisor) / Kashiwagi, Jacob S (Thesis advisor) / Chong, Oswald (Committee member) / Arizona State University (Publisher)
Created2017
Description
Regulatory agencies, such as the Occupational Safety and Health Administration (OSHA), and the National Institute of Occupational Safety and Health (NIOSH), recognize that decisions regarding occupational health are often economically driven, with worker health only a secondary concern (Ruttenberg, 2014). To investigate the four National Occupational Research Agenda (NORA) long-standing health concerns—welding fumes, crystalline silica, noise, and musculoskeletal disorders—a mixed methods research is conducted. Fourfold structuration, a holistic communication process with roots in indigenous/ancient knowledge, is used to organize data and facilitate making tangible relationships of health to productivity and profits that are abstract and often stated by industries, such as construction, as difficult to quantify. From both construction trade worker and occupational health and safety expert interviews data/codes are developed. For the qualitative method, the codes are organized into a constructivist grounded theory depicting the construction industry with regard to its foundation – profits. A theoretical exercise translating the qualitative codes into potential productivity losses is presented as a way for quantifying the abstract relationships of health to productivity. For the quantitative study, the data/codes are used to develop a comprehensive list of practices, barriers to, and catalysts for addressing health in construction. A significant quantitative finding is that occupational health and safety (OSH) experts are not traditionally involved at the highest levels of the OSHA Hierarchy of Controls, where the greatest opportunity to prevent exposure to health hazards is possible. Organized via a holistic framework, this research emphasizes our primary responsibility to each other as highlighted in recent NIOSH worker health agendas.
ContributorsTello, Linda Marguerite (Author) / Grau, David (Thesis advisor) / Koro-Ljungberg, Mirka (Committee member) / Hanemann, Michael (Committee member) / Chong, Oswald (Committee member) / Arizona State University (Publisher)
Created2017
Description
Construction industry performance (schedule, budget, and customer satisfaction) has not improved over the last 20 years. This investigation proposes that academic/industry research using actual project data may have more impact on improving industry performance than traditional survey-based research. The authors utilize the CIB and CIB W117 platforms to proliferate the concept of academic/industry test results to increase the impact on the construction industry. The authors propose to use the existing journal and then share the journal papers on an online platform (ResearchGate.net) ensuring a faster proliferation of the key academic/industry test results into the academic research community. The mechanism of the academic/industry test results will have more of an impact on industry practices than the traditional publication systems, which concentrate on literature reviews and surveys to collect industry opinions and analyze the information to change industry practices. The proliferation of industry research results will create transparency in the construction industry and the academic research community.
ContributorsGastelum, David (Author) / Kashiwagi, Dean T. (Thesis advisor) / Chong, Oswald (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2017
Description
Resilient acquisition of timely, detailed job site information plays a pivotal role in maintaining the productivity and safety of construction projects that have busy schedules, dynamic workspaces, and unexpected events. In the field, construction information acquisition often involves three types of activities including sensor-based inspection, manual inspection, and communication. Human interventions play critical roles in these three types of field information acquisition activities. A resilient information acquisition system is needed for safer and more productive construction. The use of various automation technologies could help improve human performance by proactively providing the needed knowledge of using equipment, improve the situation awareness in multi-person collaborations, and reduce the mental workload of operators and inspectors.
Unfortunately, limited studies consider human factors in automation techniques for construction field information acquisition. Fully utilization of the automation techniques requires a systematical synthesis of the interactions between human, tasks, and construction workspace to reduce the complexity of information acquisition tasks so that human can finish these tasks with reliability. Overall, such a synthesis of human factors in field data collection and analysis is paving the path towards “Human-Centered Automation” (HCA) in construction management. HCA could form a computational framework that supports resilient field data collection considering human factors and unexpected events on dynamic job sites.
This dissertation presented an HCA framework for resilient construction field information acquisition and results of examining three HCA approaches that support three use cases of construction field data collection and analysis. The first HCA approach is an automated data collection planning method that can assist 3D laser scan planning of construction inspectors to achieve comprehensive and efficient data collection. The second HCA approach is a Bayesian model-based approach that automatically aggregates the common sense of people from the internet to identify job site risks from a large number of job site pictures. The third HCA approach is an automatic communication protocol optimization approach that maximizes the team situation awareness of construction workers and leads to the early detection of workflow delays and critical path changes. Data collection and simulation experiments extensively validate these three HCA approaches.
Unfortunately, limited studies consider human factors in automation techniques for construction field information acquisition. Fully utilization of the automation techniques requires a systematical synthesis of the interactions between human, tasks, and construction workspace to reduce the complexity of information acquisition tasks so that human can finish these tasks with reliability. Overall, such a synthesis of human factors in field data collection and analysis is paving the path towards “Human-Centered Automation” (HCA) in construction management. HCA could form a computational framework that supports resilient field data collection considering human factors and unexpected events on dynamic job sites.
This dissertation presented an HCA framework for resilient construction field information acquisition and results of examining three HCA approaches that support three use cases of construction field data collection and analysis. The first HCA approach is an automated data collection planning method that can assist 3D laser scan planning of construction inspectors to achieve comprehensive and efficient data collection. The second HCA approach is a Bayesian model-based approach that automatically aggregates the common sense of people from the internet to identify job site risks from a large number of job site pictures. The third HCA approach is an automatic communication protocol optimization approach that maximizes the team situation awareness of construction workers and leads to the early detection of workflow delays and critical path changes. Data collection and simulation experiments extensively validate these three HCA approaches.
ContributorsZhang, Cheng (Author) / Tang, Pingbo (Thesis advisor) / Cooke, Nancy J. (Committee member) / Chong, Oswald (Committee member) / Arizona State University (Publisher)
Created2017
Description
Background: While prior studies have quantified the mortality burden of the 1957 H2N2 influenza pandemic at broad geographic regions in the United States, little is known about the pandemic impact at a local level. Here we focus on analyzing the transmissibility and mortality burden of this pandemic in Arizona, a setting where the dry climate was promoted as reducing respiratory illness transmission yet tuberculosis prevalence was high.
Methods: Using archival death certificates from 1954 to 1961, we quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 H2N2 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and assumed generation intervals of 3 and 4 days. Local newspaper articles published during 1957–1958 were also examined.
Results: Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 16.59 in the elderly (≥65 years). All other age groups exhibit very low excess-mortality and the typical U-shaped age-pattern was absent. However, the standardized mortality ratio was greatest (4.06) among children and young adolescents (5–14 years) from October 1957-March 1958, based on mortality rates of respiratory deaths. Transmissibility was greatest during the same 1957–1958 period, when the mean reproduction number was estimated at 1.08–1.11, assuming 3- or 4-day generation intervals with exponential or fixed distributions.
Conclusions: Maricopa County exhibited very low mortality impact associated with the 1957 influenza pandemic. Understanding the relatively low excess-mortality rates and transmissibility in Maricopa County during this historic pandemic may help public health officials prepare for and mitigate future outbreaks of influenza.
ContributorsCobos, April (Author) / Nelson, Clinton (Author) / Jehn, Megan (Author) / Viboud, Cecile (Author) / Chowell-Puente, Gerardo (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-08-11