Publication Date

Spring 2016

Advisor(s) - Committee Chair

Steven Fernandez (Director), Keith Andrew, Michael Carini, and Ivan Novikov

Degree Program

Department of Physics and Astronomy

Degree Type

Master of Science

Abstract

Climate change studies and examinations of increasing sea levels and temperatures show storm intensity and frequency are increasing. As these storms are increasing in intensity and frequency, the effects of these storms must be monitored to determine the probable damages or impacts to critical infrastructure [2, 35]. These storms suddenly create new demands and requirements upon already stressed critical infrastructure sectors [1]. A combined and interdisciplinary effort must be made to identify these stresses and to mitigate any failures. This effort is needed so that the 21st Century Smart Grid is robust and resilient enough to ensure that the grid is secured against all hazards. This project focuses on anticipating loss of above ground electrical power due to extreme wind speeds. This thesis selected a study region of Indiana, Illinois, Kentucky, and Tennessee to investigate the skill of fragility curve generation for this region, during Hurricane Irene, in the Fall of 2011. Three published fragility techniques are compared within the Midwest study region to determine the best skilled technique for the low wind speeds experienced in this region in August 2011. The three techniques studied are: 1) Powerline Technique [6], a correlation between “as published” state based construction standards and surface wind speeds sustained for greater than one minute; 2) the ANL Headout Technique [37], a correlation of Hurricane Irene three second wind gusts with DOE situation reports of outages; and 3) the Walker Technique [1], a correlation of utility reported outages in the Eastern Seaboard counties with three second surface gusts. The deliverable outcomes for this project include: 1) metrics for determining the method best for the study region, from the archival data during Hurricane Irene timeframe; 2) a fragility curve methodology description for each technique; and 3) a mathematical representation for each technique suitable for inclusion in automated forecast algorithms. Overall, this project combines situational awareness modeling to provide distinct fragility techniques that can be used by the public and private sectors to improve emergency management, restoration processes, and critical infrastructure all-hands-preparedness. This work was supported by Western Kentucky University (WKU) and the National Oceanic Atmospheric Administration (NOAA)

Disciplines

Atmospheric Sciences | Geographic Information Sciences

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