Browsing by Subject "Infrastructure management"
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Item Applicability of agent-based model to managing roadway infrastructure(2013-12) Li, Chen, active 2013; Zhang, Zhanmin, 1962-In a roadway network, infrastructure conditions determine efficient network operation and traveler safety, and thus roadway engineers need a sophisticated plan to monitor and maintain network performance. Developing a comprehensive maintenance and rehabilitation (M&R) strategy for an infrastructure system, specifically a roadway network, is a complicated process because of the system uncertainties and multiple parties involved. Traditional approaches are mostly top-down, and restrict the decision-making process. In contrast, agent-based models, a bottom-up approach, could well simulate and analyze the autonomy of each party and their interactions in the infrastructure network. In this thesis, an agent-based model prototype was developed to simulate the operations of a small roadway network with a high degree of simplification. The objective of this study is to assess the applicability of agent-based modeling for infrastructure management problems through the following four aspects: (1) to simulate the user route selection process in the network; (2) to analyze the impact of users’ choices on the congestion levels and structural conditions of roadway sections; (3) to help the engineer to determine M&R strategies under a certain budget; and (4) to investigate the impact due to different fare rates of the toll road section on the infrastructure conditions in the network. This prototype detected traffic flow, and gave appropriate M&R advice to each roadway segment. To improve this model, more investigation should be conducted to increase the level of sophistication for the interaction rules between agents, the route selection, and the budget allocation algorithm. Upon completion, this model can be applied to existing road networks to assist roadway engineers in managing the network with an efficient M&R plan and toll rate.Item Development of infrastructure asset management software solutions for municipalities in South Africa(2009-05-15) von Holdt, Christopher JamesThis Record of Study presents the development of infrastructure asset management software solutions for municipalities in South Africa. The study was performed within a multidisciplinary engineering consulting company in South Africa with an interest in expanding its infrastructure asset management consultancy services in the local government market. South Africa faces a large backlog in the delivery of basic services to communities; existing infrastructure is showing signs of advanced aging; and municipalities are inadequately staffed to effectively provide services with limited funding. The company identified the opportunity to support South African municipalities with the delivery of sustainable infrastructure services through the implementation of infrastructure asset management best practice. The provision of these services required the development of infrastructure asset management software that satisfies the needs of municipalities. Infrastructure asset management practice around the world and in the context of municipalities in South Africa was reviewed to gain an understanding of the specific requirements of the asset management software solution. The software functionality was conceptualized and the technical requirements were identified to aid development. Finally, a business plan was prepared to assess the commercial viability of the software and to guide its introduction into the market.Item Optimal infrastructure maintenance scheduling problem under budget uncertainty(2011-08) Gao, Lu; Zhang, Zhanmin, 1962-; Caldas, Carlos; Donald, Stephen; Machemehl, Randy B.; Murphy, Michael R.; Walton, C. MichaelThis research addresses the infrastructure maintenance scheduling problems under budget uncertainty. Infrastructure agencies usually face budget uncertainties that will eventually lead to suboptimal planning if maintenance decisions are made without taking the uncertainty into consideration. It is important for decision makers to adopt maintenance scheduling policies that take future budget uncertainty into consideration. The author proposes a multistage, stochastic linear programming model to address this problem. The author also develops solution procedures using the augmented Lagrangian decomposition algorithm and scenario reduction method. A case study exploring the computational characteristics of the proposed methods is conducted and the benefit of using the stochastic programming approach is discussed. In the case study, the road network in Dallas District is used with data taken from the Texas Department of Transportation’s Pavement Management Information System. The case study results reveal that the stochastic programming solutions tend to allocate more resources to preventive maintenance than deterministic solutions that ignore the uncertainty information. The proposed methodology can help decision makers effectively obtain optimal maintenance plan under budget uncertainty.Item Stockpile reduction : the key to transition and infrastructure management at Los Alamos(2010-08) Gubernatis, David Charles; Nichols, Steven P.; Kautz, Douglas D.; Kornreich, Drew E.Since the end of World War II the United States has grown and maintained a stockpile of nuclear weapons in the interest of preserving world peace, and with the specific intent to provide unparalleled national security to its citizens. It was a commonly held view during this time that a large diverse stockpile was a fundamental key to national security. However, in today’s ever-changing environment, Los Alamos National Laboratory finds itself with an infrastructure unable to quickly adapt to new national security needs and threats. Burdened by the management of a Cold-War-era stockpile, nuclear operations at Los Alamos will benefit from a reduced stockpile initiative. Contrary to previously held beliefs, Los Alamos can be the prime beneficiary to such an approach, and use such a monumental shift in strategy to modernize infrastructure, revitalize critical staff, and effectively manage critical materials and facilities while simultaneously reducing waste and environmental impacts to better support national security needs.