Matching Items (116)
Description
With a rapidly decreasing amount of resources for construction, wood and bamboo have been suggested as renewable materials for increased use in the future to attain sustainability. Through a literature review, bamboo and wood growth, manufacturing and structural attributes were compared and then scored in a weighted matrix to determine the option that shows the higher rate of sustainability. In regards to the growth phase, which includes water usage, land usage, growth time, bamboo and wood showed similar characteristics overall, with wood scoring 1.11% higher than bamboo. Manufacturing, which captures the extraction and milling processes, is experiencing use of wood at levels four times those of bamboo, as bamboo production has not reached the efficiency of wood within the United States. Structural use proved to display bamboo’s power, as it scored 30% higher than wood. Overall, bamboo received a score 15% greater than that of wood, identifying this fast growing plant as the comparatively more sustainable construction material.
ContributorsThies, Jett Martin (Author) / Ward, Kristen (Thesis director) / Halden, Rolf (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Civil, Environmental and Sustainable Eng Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Transit ridership is declining in most cities throughout America. Public transportation needs to be improved in order for cities to handle urban growth, reduce carbon footprint, and increase mobility across income groups. In order to determine what causes changes in transit ridership, I performed a descriptive analysis of five metro areas in the United States. I studied changes in transit ridership in Dallas, Denver, Minneapolis, Phoenix, and Seattle from 2013 through 2017 to determine where public transportation works and where it does not work. I used employment, commute, and demographic data to determine what affects transit ridership. Each metro area was studied as a separate case because the selected cities are difficult to compare directly. The Seattle metro area was the only metro to increase transit ridership throughout the period of the study. The Minneapolis metro area experienced a slight decline in transit ridership, while Phoenix and Denver declined significantly. The Dallas metro area declined most of the five cities studied. The denser metro areas fared much better than the less dense areas. In order to increase transit ridership cities should increase the density of their city and avoid sprawl. Certain factors led to declines in ridership in certain metro areas but not all. For example, gentrification contributed to ridership decline in Denver and Minneapolis, but Seattle gentrified and increased ridership. Dallas and Phoenix experienced low-levels of gentrification but experienced declining ridership. Therefore, organizations such as the American Public Transportation Association (APTA) who attempt to find the single factor causing the decline in transit ridership, or the one factor that will increase ridership are misguided. Above all, this thesis shows that there is no single factor causing the ridership decline in each metro area, and it is wise to study each metro area as a separate case.
ContributorsBarro, Joshua Andrew (Co-author) / Barro, Joshua (Co-author) / King, David (Thesis director) / Salon, Deborah (Committee member) / School of Politics and Global Studies (Contributor) / Walter Cronkite School of Journalism & Mass Comm (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Productivity in the construction industry is an essential measure of production efficiency and economic progress, quantified by craft laborers' time spent directly adding value to a project. In order to better understand craft labor productivity as an aspect of lean construction, an activity analysis was conducted at the Arizona State University Palo Verde Main engineering dormitory construction site in December of 2016. The objective of this analysis on craft labor productivity in construction projects was to gather data regarding the efficiency of craft labor workers, make conclusions about the effects of time of day and other site-specific factors on labor productivity, as well as suggest improvements to implement in the construction process. Analysis suggests that supporting tasks, such as traveling or materials handling, constitute the majority of craft labors' efforts on the job site with the highest percentages occurring at the beginning and end of the work day. Direct work and delays were approximately equal at about 20% each hour with the highest peak occurring at lunchtime between 10:00 am and 11:00 am. The top suggestion to improve construction productivity would be to perform an extensive site utilization analysis due to the confined nature of this job site. Despite the limitations of an activity analysis to provide a complete prospective of all the factors that can affect craft labor productivity as well as the small number of days of data acquisition, this analysis provides a basic overview of the productivity at the Palo Verde Main construction site. Through this research, construction managers can more effectively generate site plans and schedules to increase labor productivity.
ContributorsFord, Emily Lucile (Author) / Grau, David (Thesis director) / Chong, Oswald (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The overall energy consumption around the United States has not been reduced even with the advancement of technology over the past decades. Deficiencies exist between design and actual energy performances. Energy Infrastructure Systems (EIS) are impacted when the amount of energy production cannot be accurately and efficiently forecasted. Inaccurate engineering assumptions can result when there is a lack of understanding on how energy systems can operate in real-world applications. Energy systems are complex, which results in unknown system behaviors, due to an unknown structural system model. Currently, there exists a lack of data mining techniques in reverse engineering, which are needed to develop efficient structural system models. In this project, a new type of reverse engineering algorithm has been applied to a year's worth of energy data collected from an ASU research building called MacroTechnology Works, to identify the structural system model. Developing and understanding structural system models is the first step in creating accurate predictive analytics for energy production. The associative network of the building's data will be highlighted to accurately depict the structural model. This structural model will enhance energy infrastructure systems' energy efficiency, reduce energy waste, and narrow the gaps between energy infrastructure design, planning, operation and management (DPOM).
ContributorsCamarena, Raquel Jimenez (Author) / Chong, Oswald (Thesis director) / Ye, Nong (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Building construction, design and maintenance is a sector of engineering where improved efficiency will have immense impacts on resource consumption and environmental health. This research closely examines the Leadership in Environment and Energy Design (LEED) rating system and the International Green Construction Code (IgCC). The IgCC is a model code, written with the same structure as many building codes. It is a standard that can be enforced if a city's government decides to adopt it. When IgCC is enforced, the buildings either meet all of the requirements set forth in the document or it fails to meet the code standards. The LEED Rating System, on the other hand, is not a building code. LEED certified buildings are built according to the standards of their local jurisdiction and in addition to that, building owners can chose to pursue a LEED certification. This is a rating system that awards points based on the sustainable measures achieved by a building. A comparison of these green building systems highlights their accomplishments in terms of reduced electricity usage, usage of low-impact materials, indoor environmental quality and other innovative features. It was determined that in general IgCC is more holistic, stringent approach to green building. At the same time the LEED rating system a wider variety of green building options. In addition, building data from LEED certified buildings was complied and analyzed to understand important trends. Both of these methods are progressing towards low-impact, efficient infrastructure and a side-by-side comparison, as done in this research, shed light on the strengths and weaknesses of each method, allowing for future improvements.
ContributorsCampbell, Kaleigh Ruth (Author) / Chong, Oswald (Thesis director) / Parrish, Kristen (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This paper describes the research done to quantify the relationship between external air temperature and energy consumption and internal air temperature and energy consumption. The study was conducted on a LEED Gold certified building, College Avenue Commons, located on Arizona State University's Tempe campus. It includes information on the background of previous studies in the area, some that agree with the research hypotheses and some that take a different path. Real-time data was collected hourly for energy consumption and external air temperature. Intermittent internal air temperature was collected by undergraduate researcher, Charles Banke. Regression analysis was used to prove two research hypotheses. The authors found no correlation between external air temperature and energy consumption, nor did they find a relationship between internal air temperature and energy consumption. This paper also includes recommendations for future work to improve the study.
ContributorsBanke, Charles Michael (Author) / Chong, Oswald (Thesis director) / Parrish, Kristen (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The Chinese Construction Industry has grown to be one of the largest construction markets in the world within the last 10 years. The size of the Chinese Construction Industry is on par with many developed nations, despite it being a developing country. Despite its rapid growth, the productivity and profitability of the Chinese Construction Industry is low compared to similar sized construction industries (United States, United Kingdom, etc.). In addition to the low efficiency of the Chinese Construction Industry, there is minimal documentation available showing the performance of the Chinese Construction Industry (projects completed on time, on budget, and customer satisfaction ratings).
The purpose of this research is to investigate potential solutions that could address the poor efficiency and performance of the Chinese Construction Industry. This research is divided into three phases; first, a literature review to identify countries that have similar construction industries to the Chinese Construction Industry. The second phase is to compare the risks and identify solutions that are proposed to increase the performance of similar construction industries and the Chinese Construction Industry. The third phase is to create a survey from the literature-based information to validate the concepts with the Chinese Construction Industry professionals and stakeholders.
The purpose of this research is to investigate potential solutions that could address the poor efficiency and performance of the Chinese Construction Industry. This research is divided into three phases; first, a literature review to identify countries that have similar construction industries to the Chinese Construction Industry. The second phase is to compare the risks and identify solutions that are proposed to increase the performance of similar construction industries and the Chinese Construction Industry. The third phase is to create a survey from the literature-based information to validate the concepts with the Chinese Construction Industry professionals and stakeholders.
ContributorsChen, Yutian (Author) / Chong, Oswald (Thesis advisor) / Kashiwagi, Dean T. (Committee member) / Badger, Willliam (Committee member) / Arizona State University (Publisher)
Created2020
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
The imaging and detection of specific cell types deep in biological tissue is critical for the diagnosis of cancer and the study of biological phenomena. Current high-resolution optical imaging techniques are depth limited due to the high degree of optical scattering that occurs in tissues. To address these limitations, photoacoustic (PA) techniques have emerged as noninvasive methods for the imaging and detection of specific biological structures at extended depths in vivo. In addition, near-infrared (NIR) contrast agents have further increased the depth at which PA imaging can be achieved in biological tissues. The goal of this research is to combine novel PA imaging and NIR labeling strategies for the diagnosis of disease and for the detection of neuronal subtypes. Central Hypothesis: Utilizing custom-designed PA systems and NIR labeling techniques will enable the detection of specific cell types in vitro and in mammalian brain slices. Work presented in this dissertation addresses the following: (Chapter 2): The custom photoacoustic flow cytometry system combined with NIR absorbing copper sulfide nanoparticles for the detection of ovarian circulating tumor cells (CTCs) at physiologically relevant concentrations. Results obtained from this Chapter provide a unique tool for the future detection of ovarian CTCs in patient samples at the point of care. (Chapter 3): The custom photoacoustic microscopy (PAM) system can detect genetically encoded near-infrared fluorescent proteins (iRFPs) in cells in vitro. Results obtained from this Chapter can significantly increase the depth at which neurons and cellular processes can be targeted and imaged in vitro. (Chapter 4): Utilizing the Cre/lox recombination system with AAV vectors will enable selective tagging of dopaminergic neurons with iRFP for detection in brain slices using PAM. Thus, providing a new means of increasing the depth at which neuronal subtypes can be imaged and detected in the mammalian brain. Significance: Knowledge gained from this research could have significant impacts on the PA detection of ovarian cancer and extend the depth at which neuronal subtypes are imaged in the mammalian brain.
ContributorsLusk, Joel F. (Author) / Smith, Barbara S. (Thesis advisor) / Halden, Rolf (Committee member) / Anderson, Trent (Committee member) / Arizona State University (Publisher)
Created2022
Description
This dissertation consists of three chapters that investigate the rapid adoption and complex implementation of city commitments to transition to 100% renewable energy (100RE). The first paper uses a two-stage, mixed methods approach to examine 100RE commitments across the US, combining a multivariate regression of demographic, institutional, and policy factors in adoption and six interview-based state case studies to discuss implementation. Adoption of this non-binding commitment progressed rapidly for city councils around the US. Results show that many cities passed 100RE commitments with no implementation plan and minimal understanding of implementation challenges. This analysis highlights that many cities will need new institutions and administrative capacities for successful implementation of these ambitious new policies. While many cities abandoned the commitment soon after adoption, collaboration allowed cities in a few states to break through and pursue implementation, examined further in the next two studies. The second paper is a qualitative case study examining policymaking for the Utah Community Renewable Energy Act. Process tracing methods are used to identify causal factors in enacting this legislation at the state level and complementary resolutions at the local level. This Act was passed through the leadership and financial backing of major cities and committed the investor-owned utility to fulfill any city 100RE resolutions passed through 2019. Finally, the third paper is a mixed-methods, descriptive case study of the benefits of Community Choice Aggregation (CCA) in California, which many cities are using to fulfill their 100RE commitments. Cities have adopted CCAs to increase their local voice in the energy process, while fulfilling climate and energy goals. Overall, this research shows that change in the investor-owned utility electricity system is in fact possible from the city scale, though many cities will need institutional innovation to implement these policies and achieve the change they desire. While cities with greater resources are better positioned to make an impact, smaller cities can collaborate to similarly influence the energy system. Communities are interested in lowering energy costs for customers where possible, but the central motivations in these cases were the pursuit of sustainability and increasing local voice in energy decision-making.
ContributorsKunkel, Leah Christine (Author) / Breetz, Hanna L (Thesis advisor) / Parker, Nathan (Committee member) / Salon, Deborah (Committee member) / Arizona State University (Publisher)
Created2022