A total of 1,625 tornadoes occurred in the United States in 2011, resulting in economic losses that exceeded $25 billion. Two tornado outbreaks stand out because they caused more than half of those losses. The tornadoes that cut through Tuscaloosa, Alabama, on April 27 and Joplin, Missouri, on May 22 were responsible for a combined 223 fatalities and more than 13,000 damaged buildings in the two cities. Although the economic losses associated with tornado damage are well documented, the writers argue that the overall impact should encompass longer term, broader considerations such as the social disruption and psychological effects that impact communities. This paper examines observations by tornado damage assessment teams led by the first author in these two medium-sized cities and suggests that the evolution of building codes and past approaches to construction have led to conditions that made this extent of damage possible. The authors outline a multidisciplinary path forward that incorporates engineering research and social and economic studies into a new design paradigm leading to building code changes and social practices that will improve resistance and mitigate future losses at a community level from tornadoes.
Infrastructure vulnerability has drawn significant attention in recent years, partly because of the occurrence of low-probability and high-consequence disruptive events such as 2017 hurricanes Harvey, Irma, and Maria, 2011 Tuscaloosa and Joplin tornadoes, and 2015 Gorkha, Nepal, and 2017 Central Mexico earthquakes. Civil infrastructure systems support social welfare, thus viability and sustained operation is critical. A variety of frameworks, models, and tools exist for advancing infrastructure vulnerability research. Nevertheless, providing accurate vulnerability measurement remains challenging. This paper presents a state-of-the-art data collection and information extraction methodology to document infrastructure at high granularity to assess preevent vulnerability and postevent damage in the face of disasters. The methods establish a baseline of preevent infrastructure functionality that can be used to measure impacts and temporal recovery following a disaster. The Extreme Events Web Viewer (EEWV) presented as part of the methodology is a GIS-based web repository storing spatial and temporal data describing communities before and after disasters and facilitating data analysis techniques. This web platform can store multiple geolocated data formats including photographs and 360° videos. A tool for automated extraction of photography from 360° video data at locations of interest specified in the EEWV was created to streamline data utility. The extracted imagery provides a manageable data set to efficiently document characteristics of the built and natural environment. The methodology was tested to locate buildings vulnerable to flood and storm surge on Dauphin Island, Alabama. Approximately 1,950 buildings were passively documented with vehicle-mounted 360° video. Extracted building images were used to train a deep learning neural network to predict whether a building was elevated or nonelevated. The model was validated, and methods for iterative neural network training are described. The methodology, from rapidly collecting large passive datasets, storing the data in an open repository, extracting manageable datasets, and obtaining information from data through deep learning, will facilitate vulnerability and postdisaster analyses as well as longitudinal recovery measurement.
Renovation of an existing building is an accomplished stem of the construction industry because it supplies financial diversification for construction stakeholders. Although several construction planning tools and stakeholder alignment exercises have been developed, no tool exists to assist project owners to decide between renovating an existing building and new construction with a comprehensive decision criteria. The objective of this research is to create and test a renovation versus new building support decision tool for construction project stakeholders. The renovation versus new building support decision tool was created based on an extensive review of existing support tools and construction industry needs. The created tool was implemented to evaluate decisions of educational facilities by university officials experienced in project management. Results show the tool was effective in identifying relevant topics for discussion and guiding a group of stakeholders through an exercise in decision-making. Specifically, the tool was implemented by construction management personnel for university facilities currently under construction to evaluate the decision to renovate an existing building or new construction. The main contribution of this research is a framework and support decision tool readily implementable for construction project stakeholders desiring to determine if renovation or new construction is the optimal path for their specific objectives.
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