Browsing by Subject "Transportation agencies"
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Item Evaluation of recycled material performance in highway applications and optimization of their use(Texas Tech University, 2004-05) Rana, A. S. M. AshekIn the United States, solid waste is being generated at an increasing rate, and its disposal is becoming a huge problem for the communities involved. Solid waste comprises of a broad range of materials. Currently, the primary solid waste disposal methods are incineration and landfilling. Although incineration helps reduce the volume of waste, the resulting ash still ends up in landfills. Furthermore, concerns have been raised about the negative effects of incineration on air quality. Highway construction typically involves the use of large quantities of natural resources such as construction aggregates. Furthermore, in many parts of the United States, good quality highway materials are in short supply. Cost of conventional materials continue to increase due to reasons such as depletion of natural resources, rising cost of mining, and high transportation costs. This, combined with the rising costs of waste disposal, has made recycling an attractive option to reduce the burden on landfills and also to save valuable natural resources. For several decades, transportation agencies have been conducting research on the use of recycled waste material in construction projects. However, a large number of these studies involved laboratory characterizations of recycled waste materials to develop technical specifications for their use. However, this is not a comprehensive approach to the problem, and it has not led to widespread use of recycled materials except for a very few cases. This dissertation evaluates recycled material use from engineering, economic, environmental and performance points of view to conduct an overall assessment of the feasibility of using such material in transportation projects. It includes long-term monitoring of projects constructed using several recycled materials. A framework to optimize the use of recycled materials is also developed using glass cullet as an example. This framework is based on laboratory evaluation, structural and economic analysis.Item Prioritization of highway maintenance functions using multi-attribute decision making with fuzzy pairwise comparison(2011-05) Liu, Wenxing, 1987-; Zhang, Zhanmin, 1962-; Machemehl, Randy B.As is the case for most of the Departments of Transportation in the U.S., the Texas Department of Transportation has been experiencing fluctuations of budget for maintaining and preserving its highway infrastructure over the recent years. If the maintenance budget shortfall lasts for an extended period of time, the condition of the highway network would be harmed directly or indirectly since some maintenance work would be deferred or cancelled. Thus, in order to control and minimize the risk caused by maintenance budget reductions, it is important for highway agencies to adjust their maintenance and rehabilitation policies to accommodate budget fluctuations. This thesis presents a methodological framework that helps highway agencies quantify the risks to highway networks, and revise the highway routine maintenance work plans to minimize the impact of budget fluctuations. The proposed methodology aims to assist highway agencies in prioritizing and selecting maintenance functions according to the risk of not performing a specific maintenance activity. Also, this methodology considers the subjective nature of decision makers’ assessments, allowing different levels of confidence and different attitudes toward risk to be captured as the uncertainty and imprecision involved in the decision making process. In the case study, the proposed methodology is tested with a set of data obtained from the Texas Department of Transportation. The result is compared with the outcome obtained from the crisp Analytical Hierarchy Process using the same set of data. The outcomes from the two methodologies are very close, validating the effectiveness of prioritizing highway maintenance functions using Multi-Attribute Analysis with Fuzzy Pairwise Comparison.