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    District Level Preventive Maintenance Treatment Selection Tool for Use in Virginia

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    Hosten_AM_T_2013.pdf (1.215Mb)
    Downloads: 1347
    Date
    2013-02-06
    Author
    Hosten, Akyiaa Makeda
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    Abstract
    Preventive maintenance has the potential to improve network condition by retarding future pavement deterioration. The Virginia Department of Transportation uses its pavement management system to determine maintenance targets for each district. The districts then use these recommendations to select pavements that will receive maintenance and the types of treatments that will be applied. Each district has a different approach to preventive maintenance. There was a need for more consistent preventive maintenance practices across the state. This thesis outlines guidelines for the implementation of a preventive maintenance policy. Preventive maintenance treatments currently being used within Virginia include chip seal, slurry seal, microsurfacing, and thin hot mix asphalt overlays. Historical pavement condition data was obtained from the VDOT PMS for these treatments and treatment performance models were developed. A district level treatment selection tool was developed to assist the district level decision making process. A prioritized list of pavement sections was generated, maximizing the cost-effectiveness of the selected treatments subject to budgetary constraints set by the central office. The treatment selection tool was then run for each pavement classification in each district. The results of this analysis were presented. Although the recommended budget for each district was very close to the targets set by the central office, the recommended lane miles for each district were about half the targets set by the central office.  It is believed that the unit costs used in this analysis were higher than those used in the VDOT PMS analysis. This selection tool has the potential to be a very powerful decision support tool if the unit costs are representative of what the expected treatment costs are for each district.
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    http://hdl.handle.net/10919/19264
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    • Masters Theses [21068]

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