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dc.contributor.authorAckerman Jr, Paul J.en_US
dc.date.accessioned2014-09-05T08:01:05Z
dc.date.available2014-09-05T08:01:05Z
dc.date.issued2014-09-04en_US
dc.identifier.othervt_gsexam:3520en_US
dc.identifier.urihttp://hdl.handle.net/10919/50446
dc.description.abstractThe Asbestos Hazard Emergency Response Act (AHERA) requires public schools to manage asbestos containing materials. Twenty five years after AHERA was enacted public schools continue to struggle with documenting and managing asbestos containing material assets. In addition, the manufacturing of lead based paint (LBP) was banned over thirty years ago yet public schools continue to have to manage LBP assets with no guidelines specific to public schools. When compared to current civil infrastructure asset management systems, AHERA and the HUD guidelines lack a rating system based on visual inspection data. The development of a condition index algorithm and risk of failure model would provide school planners an efficient management tool to predict the future condition of asbestos containing material and lead based paint assets. As a result, school planners would be able to prioritize maintenance, repair, and abatement projects based on the risk to the indoor air quality of their facilities and more efficiently utilize their limited resources to mitigate such risks. This paper presents initial work toward the development of a visual condition index algorithm and a risk of failure model to support prioritization of maintenance, repair, and abatement projects. The condition assessment categories provided by AHERA and HUD were adapted and incorporated in an evaluation form created to assist in rating the various stages of accessibility, deterioration, and detection of typical ACM and LBP building components. The evaluation form can be utilized by inspection and school personnel when reclassifying ACM and LBP components during semi-annual inspections of their facilities and also ensure the repeatability of the condition assessment and risk of failure methodologies. A risk of failure model was developed utilizing the FMEA process, specifically the calculation of a risk priority number (RPN). Three schools were selected for a field pilot study to develop the accessibility, deterioration, detection, and RPN algorithms and evaluate for repeatability. The algorithms will provide a quantitative and consistent means for documenting the condition and RPN of asbestos containing material and lead based paint assets and allow the condition of these assets to be monitored and reclassified over a period of time.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectAsbestosen_US
dc.subjectLeaden_US
dc.subjectDeteriorationen_US
dc.subjectRisken_US
dc.titleCondition Assessment, Indices, and Risk-based Decision-making for Public School Infrastructure Managmenten_US
dc.typeDissertationen_US
dc.contributor.departmentCivil and Environmental Engineeringen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineCivil Engineeringen_US
dc.contributor.committeechairYoung-Corbett, Deborah Elspethen_US
dc.contributor.committeememberMcGinnis, Seanen_US
dc.contributor.committeememberFiori, Christine M.en_US
dc.contributor.committeememberGarvin, Michael J.en_US


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