Development of an efficient and cost-effective bridge inspection system using unmanned aerial vehicles (UAVs)

Maintenance of deteriorating bridges is a pressing need throughout the U.S.. In the maintenance process, condition evaluation of this sector of the infrastructure is critical, as it informs repair decisions, load-rating and management of limited state resources. Throughout the Mountain-Plains region, the condition of nearly 25,000 bridges must be evaluated by state DOTs regularly. The cost of bridge inspection forms the basis of much of the bridge management budget for state DOTs (e.g. it varies from about $4.5 to $10 million annually for CDOT). Considering the need for frequent inspection of a large number of bridges in the state and the significant expense, this project proposed to develop an efficient and cost-effective bridge inspection system based on UAVs. The feasibility of UAV based data acquisition and damage identification/condition assessment for decision-making support will be investigated. A guideline for integrating the developed technology in current bridge inspection practice will be proposed.

Data-driven simulation of hurricane wind field

For accurate modeling of the cumulated damage of hurricane events to physical structures in community resilience analysis, the temporally and spatially varying wind field of a hurricane event needs to be estimated. However, wind field measurements from past events may not include the wind field data for every hour/minute, which are needed for carrying out time-dependent analysis. Also, for certain analyses (e.g., synthetic scenario analysis in resilience planning) the hurricane wind field needs to be simulated to model the damage to an arbitrary community of interest. In response to this need, this project proposes a novel data-driven simulation technique to simulate the temporally and spatially varying hurricane wind fields for hindcast and synthetic scenario analysis purpose. Due to its data-driven nature, the proposed technique can simulate realistic hurricane wind fields based on the observations of historical hurricane events. This technique is based on an asymmetric Holland model and has addressed two shortcomings of the existing Holland-type modes, i.e. the poor representation of wind field for inner core region and inability to model surface wind speed change due to roughness change from water to land. The developed models will be integrated into IN-CORE (a research web portal being developed by NIST center of excellence in resilience planning) as the hurricane wind simulation module.

Fragility model for hurricane-induced damage to tall building clusters with application to urban resilience analysis

The primary damage to tall buildings after hurricanes is mainly comprised of the non-structural damage to the cladding systems and façade, as well as the water intrusion through the building envelope resulting from that damage. The existing damage assessment models for mid/high-rise buildings often neglect the geometry of building clusters or simply assume a homogeneous configuration for simplification purposes. These simplified approaches likely introduce significant uncertainties for urban tall buildings whose geometries and distributions often vary. In this context, this project is to develop a new fragility model for hurricane-induced damage to tall buildings, which explicitly considers both the individual building geometries and complex surrounding environment of urban areas, so that the uncertainties associated with geometries of individual buildings and building clusters can be propagated through the community or urban model to better provide risk-informed decision support.