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This dissertation presents a portable methodology for holistic planning and optimization of right of way infrastructure rehabilitation that was designed to generate monetary savings when compared to planning that only considers single infrastructure components. Holistic right of way infrastructure planning requires simultaneous consideration of the three right of way infrastructure

This dissertation presents a portable methodology for holistic planning and optimization of right of way infrastructure rehabilitation that was designed to generate monetary savings when compared to planning that only considers single infrastructure components. Holistic right of way infrastructure planning requires simultaneous consideration of the three right of way infrastructure components that are typically owned and operated under the same municipal umbrella: roads, sewer, and water. The traditional paradigm for the planning of right way asset management involves operating in silos where there is little collaboration amongst different utility departments in the planning of maintenance, rehabilitation, and renewal projects. By collaborating across utilities during the planning phase, savings can be achieved when collocated rehabilitation projects from different right of way infrastructure components are synchronized to occur at the same time. These savings are in the form of shared overhead and mobilization costs, and roadway projects providing open space for subsurface utilities. Individual component models and a holistic model that utilize evolutionary algorithms to optimize five year maintenance, rehabilitation, and renewal plans for the road, sewer, and water components were created and compared. The models were designed to be portable so that they could be used with any infrastructure condition rating, deterioration modeling, and criticality assessment systems that might already be in place with a municipality. The models attempt to minimize the overall component score, which is a function of the criticality and condition of the segments within each network, by prescribing asset management activities to different segments within a component network while subject to a constraining budget. The individual models were designed to represent the traditional decision making paradigm and were compared to the holistic model. In testing at three different budget levels, the holistic model outperformed the individual models in the ability to generate five year plans that optimized prescribed maintenance, rehabilitation and renewal for various segments in order to achieve the goal of improving the component score. The methodology also achieved the goal of being portable, in that it is compatible with any condition rating, deterioration, and criticality system.
ContributorsCarey, Brad David (Author) / Lueke, Jason S (Thesis advisor) / Ariaratnam, Samuel (Committee member) / Bashford, Howard (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The construction industry has been growing over the past few years, but it is facing numerous challenges, related to craft labor availability and declining productivity. At the same time, the industry has benefited from computational advancements by leveraging the use of Building Information Modeling (BIM) to create information rich 3D

The construction industry has been growing over the past few years, but it is facing numerous challenges, related to craft labor availability and declining productivity. At the same time, the industry has benefited from computational advancements by leveraging the use of Building Information Modeling (BIM) to create information rich 3D models to enhance the planning, designing, and construction of projects. Augmented Reality (AR) is one technology that could further leverage BIM, especially on the construction site. This research looks at the human performance attributes enabled using AR as the main information delivery tool in the various stages of construction. The results suggest that using AR for information delivery can enhance labor productivity and enable untrained personnel to complete key construction tasks. However, its usability decreases when higher accuracy levels are required. This work contributes to the body of knowledge by empirically testing and validating the performance effects of using AR during construction tasks and highlights the limitations of current generation AR technology related to the construction industry. This work serves as foundation of future industry-based AR applications and research into potential AR implementations.
ContributorsChalhoub, Jad M (Author) / Ayer, Steven K. (Thesis advisor) / Ariaratnam, Samuel T. (Committee member) / Atkinson, Robert K. (Committee member) / Arizona State University (Publisher)
Created2019