Matching Items (15)
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- All Subjects: Civil Engineering
- Genre: Doctoral Dissertation
- Creators: Bearup, Wylie
- Creators: Tang, Pingbo
Description
Alternative Project Delivery Methods (APDMs), namely Design Build (DB) and Construction Manager at Risk (CMAR), grew out of the need to find a more efficient project delivery approach than the traditional Design Bid Build (DBB) form of delivery. After decades of extensive APDM use, there have been many studies focused on the use of APDMs and project outcomes. Few of these studies have reached a level of statistical significance to make conclusive observations about APDMs. This research effort completes a comprehensive study for use in the horizontal transportation construction market, providing a better basis for decisions on project delivery method selection, improving understanding of best practices for APDM use, and reporting outcomes from the largest collection of APDM project data to date. The study is the result of an online survey of project owners and design teams from 17 states representing 83 projects nationally. Project data collected represents almost six billion US dollars. The study performs an analysis of the transportation APDM market and answers questions dealing with national APDM usage, motivators for APDM selection, the relation of APDM to pre-construction services, and the use of industry best practices. Top motivators for delivery method selection: the project schedule or the urgency of the project, the ability to predict and control cost, and finding the best method to allocate risk, as well as other factors were identified and analyzed. Analysis of project data was used to compare to commonly held assumptions about the project delivery methods, confirming some assumptions and refuting others. Project data showed that APDM projects had the lowest overall cost growth. DB projects had higher schedule growth. CMAR projects had low design schedule growth but high construction schedule growth. DBB showed very little schedule growth and the highest cost growth of the delivery methods studied. Best practices in project delivery were studied: team alignment, front end planning, and risk assessment were identified as practices most critical to project success. The study contributes and improves on existing research on APDM project selection and outcomes and fills many of the gaps in research identified by previous research efforts and industry leaders.
ContributorsBingham, Evan Dale (Author) / Gibson Jr., G. Edward (Thesis advisor) / El Asmar, Mounir (Thesis advisor) / Bearup, Wylie (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
Implementing Building Information Modeling (BIM) in construction projects has many potential benefits, but issues of projects can hinder its realization in practice. Although BIM involves using the technology, more than four-fifths of the recurring issues in current BIM-based construction projects are related to the people and processes (i.e., the non-technological elements of BIM). Therefore, in addition to the technological skills required for using BIM, educators should also prepare university graduates with the non-technological skills required for managing the people and processes of BIM. This research’s objective is to develop a learning module that teaches the non-technological skills for addressing common, people- and process-related, issues in BIM-based construction projects. To achieve this objective, this research outlines the steps taken to create the learning module and identify its impact on a BIM course. The contribution of this research is in the understanding of the pedagogical value of the developed problem-based learning module and documenting the learning module’s development process.
ContributorsAbdul Rahman, Abdul Rahimi Bin (Author) / Ayer, Steven K (Thesis advisor) / Tang, Pingbo (Committee member) / Wiezel, Avi (Committee member) / Arizona State University (Publisher)
Created2018
Description
The United States building sector was the most significant carbon emission contributor (over 40%). The United States government is trying to decrease carbon emissions by enacting policies, but emissions increased by approximately 7 percent in the U.S. between 1990 and 2013. To reduce emissions, investigating the factors affecting carbon emissions should be a priority. Therefore, in this dissertation, this research examine the relationship between carbon emissions and the factors affecting them from macro and micro perspectives. From a macroscopic perspective, the relationship between carbon dioxide, energy resource consumption, energy prices, GDP (gross domestic product), waste generation, and recycling waste generation in the building and waste sectors has been verified. From a microscopic perspective, the impact of non-permanent electric appliances and stationary and non-stationary occupancy has been investigated. To verify the relationships, various kinds of statistical and data mining techniques were applied, such as the Granger causality test, linear and logarithmic correlation, and regression method. The results show that natural gas and electricity prices are higher than others, as coal impacts their consumption, and electricity and coal consumption were found to cause significant carbon emissions. Also, waste generation and recycling significantly increase and decrease emissions from the waste sector, respectively. Moreover, non-permanent appliances such as desktop computers and monitors consume a lot of electricity, and significant energy saving potential has been shown. Lastly, a linear relationship exists between buildings’ electricity use and total occupancy, but no significant relationship exists between occupancy and thermal loads, such as cooling and heating loads. These findings will potentially provide policymakers with a better understanding of and insights into carbon emission manipulation in the building sector.
ContributorsLee, Seungtaek (Author) / Chong, Oswald (Thesis advisor) / Sullivan, Kenneth (Committee member) / Tang, Pingbo (Committee member) / Arizona State University (Publisher)
Created2018
Description
The demand for new highway infrastructure, the need to repair aging infrastructure, and the drive to optimize public expenditures on infrastructure have led transportation agencies toward alternative contracting methods (ACMs) such as design-build (DB) and construction manager/general contractor (CM/GC). U.S. transportation agencies have substantial experience with traditional design-bid-build delivery. To promote ACMs, the Federal Highway Administration and the National Cooperative Highway Research Program (NCRHP) have published ACM guidance documents. However, the published material and research tend to focus on pre-award activities. The need for guidance on ACM post-award activities is confirmed in NCHRP’s request for a guidebook focusing on ACM contract administration (NCHRP 2016).
This dissertation fills the crucial knowledge gap in contract administration functions and tools for DB and CM/GC highway project delivery. First, this research identifies and models contract administration functions in DBB, CM/GC, and DB using integrated definition modeling (IDEF0). Second, this research identifies and analyzes DB and CM/GC tools for contract administration by conducting 30 ACM project case studies involving over 90 ACM practitioners. Recommendations on appropriate use regarding project phase, complexity, and size were gathered from 16 ACM practitioners. Third, the alternative technical concepts tool was studied. Data from 30 DB projects was analyzed to explore the timing of DB procurement and DB initial award performance in relation to the project influence curve. Types of innovations derived from ATCs are discussed. Considerable industry input at multiple stages grounds this research in professional practice.
Results indicate that the involvement of the contractor during the design phase for both DB and CM/GC delivery creates unique contract administration functions that need unique tools. Thirty-six DB and CM/GC tools for contract administration are identified with recommendations for effective implementation. While strong initial award performance is achievable in DB projects, initial award performance in this sample of projects is only loosely tied to the level of percent base design at procurement. Cost savings typically come from multiple ATCs, and innovations tend to be incremental rather than systemic, disruptive, or radical. Opportunity for innovation on DB highway projects is influenced by project characteristics and engaging the DB entity after pre-project planning.
This dissertation fills the crucial knowledge gap in contract administration functions and tools for DB and CM/GC highway project delivery. First, this research identifies and models contract administration functions in DBB, CM/GC, and DB using integrated definition modeling (IDEF0). Second, this research identifies and analyzes DB and CM/GC tools for contract administration by conducting 30 ACM project case studies involving over 90 ACM practitioners. Recommendations on appropriate use regarding project phase, complexity, and size were gathered from 16 ACM practitioners. Third, the alternative technical concepts tool was studied. Data from 30 DB projects was analyzed to explore the timing of DB procurement and DB initial award performance in relation to the project influence curve. Types of innovations derived from ATCs are discussed. Considerable industry input at multiple stages grounds this research in professional practice.
Results indicate that the involvement of the contractor during the design phase for both DB and CM/GC delivery creates unique contract administration functions that need unique tools. Thirty-six DB and CM/GC tools for contract administration are identified with recommendations for effective implementation. While strong initial award performance is achievable in DB projects, initial award performance in this sample of projects is only loosely tied to the level of percent base design at procurement. Cost savings typically come from multiple ATCs, and innovations tend to be incremental rather than systemic, disruptive, or radical. Opportunity for innovation on DB highway projects is influenced by project characteristics and engaging the DB entity after pre-project planning.
ContributorsPapajohn, Dean (Author) / El Asmar, Mounir (Thesis advisor) / Gibson, G. Edward (Committee member) / Bearup, Wylie (Committee member) / Molenaar, Keith R. (Committee member) / Arizona State University (Publisher)
Created2019
Description
The rate of urbanization has been impacted by global economic growth. A strong economy results in more people moving to already crowded urban centers to take advantage of increased employment opportunities often resulting in sprawling of the urban area. More natural land resources are being exploited to accommodate these anthropogenic activities. Subsequently, numerous natural land resources such as green areas or porous soil, which are less flood-prone and more permeable are being converted into buildings, parking lots, roads and underground utilities that are less permeable to stormwater runoff from rain events. With the diminishing of the natural landscape that can drain stormwater during a rainfall event, urban underground drainage systems are being designed and built to tackle the excess runoff resulting from urbanization. However, the construction of a drainage system is expensive and usually involves massive land excavations and tremendous environmental disturbances. The option for constructing an underground drainage system is even more difficult in dense urban environments due to the complicated underground environments, creating a need for low footprint solutions. This need has led to emerging opportunities for low impact development (LID) methods or green infrastructures, which are viewed as an environmentally friendly alternative for dealing with stormwater runoff. LID mimics the pre-development environment to retain the stormwater runoff through infiltration, retention, detention and evaporation. Despite a significant amount of prior research having been conducted to analyze the performance of runoff volume reduction and peak flow decrement of various green infrastructures, little is known about the economic benefits of using LID practices.
This dissertation fills the gap in the knowledge regarding the life-cycle-cost effectiveness of green infrastructure in current urban developments. This study’s two research objectives are:
(1) Develop a life cycle cost calculation template to analyze the cost benefits of using LID compared to the traditional drainage system
(2) Quantify the cost benefits based on the real-world construction projects
A thorough literature review led to the data collection of the hydrological benefits of using LIDs in conjunction with overviewing three real-world construction projects to quantify the cost benefits of LIDs.
This dissertation fills the gap in the knowledge regarding the life-cycle-cost effectiveness of green infrastructure in current urban developments. This study’s two research objectives are:
(1) Develop a life cycle cost calculation template to analyze the cost benefits of using LID compared to the traditional drainage system
(2) Quantify the cost benefits based on the real-world construction projects
A thorough literature review led to the data collection of the hydrological benefits of using LIDs in conjunction with overviewing three real-world construction projects to quantify the cost benefits of LIDs.
ContributorsZhang, Pengfei (Author) / Ariaratnam, Samuel T (Thesis advisor) / Vivoni, Enrique R (Committee member) / Bearup, Wylie (Committee member) / Arizona State University (Publisher)
Created2019
Description
Planning efforts conducted during the early stages of a construction project, known
as front end planning (FEP), have a large impact on project success and significant
influence on the configuration of the final project. As a key component of FEP, front end
engineering design (FEED) plays an essential role in the overall success of large industrial
projects. The primary objective of this dissertation focuses on FEED maturity and accuracy
and its impact on project performance. The author was a member of the Construction
Industry Institute (CII) Research Team (RT) 331, which was tasked to develop the FEED
Maturity and Accuracy Total Rating System (FEED MATRS), pronounced “feed matters.”
This dissertation provides the motivation, methodology, data analysis, research findings
(which include significant correlations between the maturity and accuracy of FEED and
project performance), applicability and contributions to academia and industry. A scientific
research methodology was employed in this dissertation that included a literature review,
focus groups, an industry survey, data collection workshops, in-progress projects testing,
and statistical analysis of project performance. The results presented in this dissertation are
based on input from 128 experts in 57 organizations and a data sample of 33 completed
and 11 on-going large industrial projects representing over $13.9 billion of total installed
cost. The contributions of this work include: (1) developing a tested FEED definition for
the large industrial projects sector, (2) determining the industry’s state of practice for
measuring FEED deliverables, (3) developing an objective and scalable two-dimensional
method to measure FEED maturity and accuracy, and (4) quantifying that projects with
high FEED maturity and accuracy outperformed projects with low FEED maturity and
accuracy by 24 percent in terms of cost growth, in relation to the approved budget.
as front end planning (FEP), have a large impact on project success and significant
influence on the configuration of the final project. As a key component of FEP, front end
engineering design (FEED) plays an essential role in the overall success of large industrial
projects. The primary objective of this dissertation focuses on FEED maturity and accuracy
and its impact on project performance. The author was a member of the Construction
Industry Institute (CII) Research Team (RT) 331, which was tasked to develop the FEED
Maturity and Accuracy Total Rating System (FEED MATRS), pronounced “feed matters.”
This dissertation provides the motivation, methodology, data analysis, research findings
(which include significant correlations between the maturity and accuracy of FEED and
project performance), applicability and contributions to academia and industry. A scientific
research methodology was employed in this dissertation that included a literature review,
focus groups, an industry survey, data collection workshops, in-progress projects testing,
and statistical analysis of project performance. The results presented in this dissertation are
based on input from 128 experts in 57 organizations and a data sample of 33 completed
and 11 on-going large industrial projects representing over $13.9 billion of total installed
cost. The contributions of this work include: (1) developing a tested FEED definition for
the large industrial projects sector, (2) determining the industry’s state of practice for
measuring FEED deliverables, (3) developing an objective and scalable two-dimensional
method to measure FEED maturity and accuracy, and (4) quantifying that projects with
high FEED maturity and accuracy outperformed projects with low FEED maturity and
accuracy by 24 percent in terms of cost growth, in relation to the approved budget.
ContributorsYussef, Abdulrahman (Author) / Gibson, Jr., G. Edward (Thesis advisor) / El Asmar, Mounir (Thesis advisor) / Bearup, Wylie (Committee member) / Wiezel, Avi (Committee member) / Arizona State University (Publisher)
Created2019
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
Emerging information and communication technology (ICT) has had an enormous effect on the building architecture, engineering, construction and operation (AECO) fields in recent decades. The effects have resonated in several disciplines, such as project information flow, design representation and communication, and Building Information Modeling (BIM) approaches. However, these effects can potentially impact communication and coordination of the virtual design contents in both design and construction phases. Therefore, and with the great potential for emerging technologies in construction projects, it is essential to understand how these technologies influence virtual design information within the organizations as well as individuals’ behaviors. This research focusses on understanding current emerging technologies and its impacts on projects virtual design information and communication among projects stakeholders within the AECO organizations.
ContributorsAlsafouri, Suleiman (Author) / Ayer, Steven (Thesis advisor) / Tang, Pingbo (Committee member) / Atkinson, Robert (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