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Description
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
Description
In order to deploy autonomous multi-robot teams for humanitarian demining in Colombia, two key problems need to be addressed. First, a robotic controller with limited power that can completely cover a dynamic search area is needed. Second, the Colombian National Army (COLAR) needs to increase its science, technology and innovation (STI) capacity to help develop, build and maintain such robots. Using Thangavelautham's (2012, 2017) Artificial Neural Tissue (ANT) control algorithm, a robotic controller for an autonomous multi-robot team was developed. Trained by a simple genetic algorithm, ANT is an artificial neural network (ANN) controller with a sparse, coarse coding network architecture and adaptive activation functions. Starting from the exterior of open, basic geometric grid areas, computer simulations of an ANT multi-robot team with limited time steps, no central controller and limited a priori information, covered some areas completely in linear time, and other areas near completely in quasi-linear time, comparable to the theoretical cover time bounds of grid-based, ant pheromone, area coverage algorithms. To mitigate catastrophic forgetting, a new learning method for ANT, Lifelong Adaptive Neuronal Learning (LANL) was developed, where neural network weight parameters for a specific coverage task were frozen, and only the activation function and output behavior parameters were re-trained for a new coverage task. The performance of the LANL controllers were comparable to training all parameters ab initio, for a new ANT controller for the new coverage task.
To increase COLAR's STI capacity, a proposal for a new STI officer corps, Project ÉLITE (Equipo de Líderes en Investigación y Tecnología del Ejército) was developed, where officers enroll in a research intensive, master of science program in applied mathematics or physics in Colombia, and conduct research in the US during their final year. ÉLITE is inspired by the Israel Defense Forces Talpiot program.
To increase COLAR's STI capacity, a proposal for a new STI officer corps, Project ÉLITE (Equipo de Líderes en Investigación y Tecnología del Ejército) was developed, where officers enroll in a research intensive, master of science program in applied mathematics or physics in Colombia, and conduct research in the US during their final year. ÉLITE is inspired by the Israel Defense Forces Talpiot program.
ContributorsKwon, Byong (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Thangavelautham, Jekanthan (Committee member) / Seshaiyer, Padmanabhan (Committee member) / Arizona State University (Publisher)
Created2019