| description abstract | Postdisaster community scale recovery and resilience assessments have gained interest in the United States and around the world following natural and human-made disasters. Tornadoes are one of the most devastating natural disasters that occur in the United States every year with an annual average of more than 1,200 causing an impactful number of deaths as well as economic losses. The postdisaster recovery planning and process of communities can be enhanced by the use of risk-informed decision-making tools accounting for postdisaster vulnerability and restoration assessment in terms of repair time (functionality) and repair cost (economic losses). In this study, a methodology to probabilistically quantify building functionality through the development of functionality fragilities for use within broader community modeling is introduced. It is important when performing community resilience assessment studies to break down the components making up a community into their most fundamental components. Thus, it is proposed to generate stand-alone functionality fragilities (e.g., for different building types) and thereby not limit the process for optimizing risk-informed decision making, which may include options such as changes in permitting time, or removal of construction constraints. The proposed functionality methodology is composed of four steps while integrating concepts of performance based engineering, where functionality analyses are first performed for each major component in the building including both structural and nonstructural components (subassembly level) and then the results are combined in the form of statistical distributions to quantify the building (system level) functionality. The methodology is illustrated for a suite of 19 building types ranging from residential, schools, and hospitals, representing the building stock in the US communities needed to model a community that is heavily impacted by an extreme wind event (i.e., tornado). The post-tornado building direct economic losses are also probabilistically assessed for the 19 building archetypes. Repair times (functionality) and repair cost distribution curves summarized in this study may be further used in risk-informed decision making for investigation of policy implications, the effect of retrofit programs, and other changes to building codes. | |
