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.
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Description
Over the last two decades, Alternative Project Delivery Methods (APDM), such as Design-Build (DB), have become more popular in the construction industry, specifically in the U.S., and the competition for APDM projects has risen among construction companies. The Engineering News Record (ENR) magazine analyzes DB firms and publishes the list of the top 100 every year. According to ENR articles and many scientific papers, the implementation of DB method has grown drastically over the last decade, however, information about growth trends depending on firm size and segment is lacking. Also missing is knowledge the future market trends over the next five years. Furthermore, public agencies and DB firms may be worried that DB projects do not distribute wealth equally among DB firms. Using the top 100 firms deemed representative of the DB market, the author has divided the market into volumes based on rankings to analyze the total DB market revenue growth. A comparison between international and domestic revenues indicated that the top five DB firms have 64% more involvement in the international market compared to the domestic market. Furthermore, while the research shows increasing market share only for the top five firms, the author has found that (1) a large portion of their market share is due to a large growth in their international market, and (2) revenues for all volumes of the DB market have increased. Moreover, regression and time series analyses allow for the forecasting of the DB market growth, which the author anticipate to move from about $100B to about $150B in 2020.
ContributorsVashani, Hossein (Author) / El Asmar, Mounir (Thesis advisor) / Ernzen, James (Committee member) / Bearup, Wylie (Committee member) / Arizona State University (Publisher)
Created2014
Description
Front end planning (FEP) is an essential and valuable process that helps identify risks early in the capital project planning phases. With effective FEP, risks can potentially be mitigated through development of detailed scope definition and subsequent efficient project resource use. The thesis describes the FEP process that has been developed over the past twenty years by the Construction Industry Institute (CII). Specifically, it details the FEP tools developed for early project planning and the data gathered to analyze the tools used within the CII community. Data from a March 2011 survey are given showing the tools commonly used, how those tools are used and the common barriers faced that prohibit successful FEP implementation. The findings from in-depth interviews are also shared in the thesis. The interviews were used to gather detail responses from organizations on the implementation of their FEP processes. In total, out of the 116 CII organizations, 59 completed the survey and over 75 percent of the respondents used at least one CII tool in their front end planning processes. Of the 59 survey respondents, 12 organizations participated in the in-depth interviews. The thesis concludes that CII organizations continue to find value in CII FEP tools due to the increase tool usage. Also the thesis concludes that organizations must have strong management commitment, smart succession planning and a standardized planning process to increase the likelihood of successful FEP strategies.
ContributorsBosfield, Roberta Patrice (Author) / Gibson, G.Edward (Thesis advisor) / Wiezel, Avi (Committee member) / Ernzen, James (Committee member) / Arizona State University (Publisher)
Created2012
Description
The construction industry is becoming more aware of its impact on the environment. It has become more sensitive to how it operates and how it can reduce the carbon footprint of the construction process. This research identifies the source of and quantities of the carbon emissions created by an operating modular home fabrication plant in producing, transporting and installing modular structures. This study demonstrates how to measure the carbon footprint created in the production of a modular home. It quantifies and reports the results on a home, on a single module and on a per square foot basis. The primary conclusions of this study are: a) electricity was found to be the largest energy source used in this fabrication process; b) the modular fabrication process consumes a significant amount of electrical energy per month; c) production volume has a bearing on the carbon footprint of each home since the carbon footprint for each period is allocated to every home produced in that period; and d) transportation of fabricated modules and set-up add to the carbon footprint. Further, a carbon calculator was produced and is included with the study. The tool calculates the impact of energy consumption on the carbon footprint of a modular factory or a modular home. It may be expanded to other process driven fabrication entities. This research is valuable to developers and builders who wish to measure the carbon impact of a modular new home delivery system. The study also provides a methodology for modular home fabricators to measure the carbon footprint of their factories and factory production.
ContributorsKawecki, Leonard Robert (Author) / Bashford, Howard H (Thesis advisor) / Davis, Joseph (Committee member) / Ernzen, James (Committee member) / Arizona State University (Publisher)
Created2010
Description
Large-scale civil infrastructure systems are critical for the functioning and development of any society. However, these systems are often vulnerable to degradation and the effects of aging, necessitating consistent monitoring and maintenance. Current methods for infrastructure maintenance primarily rely on human intervention and need the implementation of advanced sensing and computing technologies in field operations and maintenance (O&M) tasks. This research aimed to address these gaps and provide novel contributions. Specifically, the objectives of this study were to leverage artificial intelligence models to enhance point cloud noise processing, to automate tree species detection using Mask R-CNN, and to integrate imagery data and LiDAR datasets for real-time terrain analysis. First, the study proposed leverages neural networks to eliminate unwanted noise from point cloud datasets, enhancing the accuracy and reliability of infrastructure data. Secondly, the research integrated Mask R-CNN into automated tree species detection. This component offers an efficient solution to identify and classify vegetation surrounding infrastructure, enabling infrastructure managers to devise proactive vegetation management strategies, thereby reducing risks associated with tree-related incidents. Lastly, the study fused image and LiDAR datasets to support real-time terrain analysis. This integrated approach provides a comprehensive understanding of terrain characteristics, allowing infrastructure managers to assess slope, elevation, and other relevant factors, facilitating proactive maintenance interventions and mitigating risks associated with erosion. These contributions collectively underscore the potential of artificial intelligence models in advancing the operations and maintenance practices of large civil infrastructure systems. By leveraging these models, infrastructure managers can optimize decision-making processes, streamline maintenance efforts, and enhance critical infrastructure networks' overall resilience and sustainability.
ContributorsPaladugu, Bala Sai Krishna (Author) / Grau, David (Thesis advisor) / Ernzen, James (Committee member) / Standage, Richard (Committee member) / Arizona State University (Publisher)
Created2023