A Performance-Based Wind Engineering Framework for Engineered Building Systems Subject to Hurricanes

Over the past decade, significant research efforts have been dedicated to the development of performance-based wind engineering (PBWE). Notwithstanding these efforts, frameworks that integrate the damage assessment of the structural and envelope system are still lacking. In response to this need, the authors have recently proposed a PBWE framework that holistically treats envelope and structural damages through progressive multi-demand fragility models that capture the inherent coupling in the demands and damages. Similar to other PBWE methodologies, this framework is based on describing the hurricane hazard through a nominal straight and stationary wind event with constant rainfall and one-hour duration. This study aims to develop a PBWE framework based on a full description of the hurricane hazard in which the entire evolution of the storm track and time-dependent wind/rain fields is simulated. Hurricane-induced pressures impacting the building envelope are captured through the introduction of a non-stationary/-straight/-Gaussian wind pressure model. Time-dependent wind-driven rain is modeled through a computational fluid dynamics Eulerian multiphase framework with interpolation schemes for the rapid computation of wind-driven rain intensities over the building surface. Through the development of a conditional stochastic simulation algorithm, the envelope performance is efficiently characterized through probabilistic metrics associated with rare events of design interest. The framework is demonstrated through analyzing a 45-story archetype building located in Miami, FL, for which the envelope performance is estimated in terms of a suite of probabilistic damage and loss metrics. A comparative study is carried out in order to provide insights into the differences that can occur due to the use of nominal hurricane models.

A RESILIENCE-BASED ASSESSMENT OF THE PERFORMANCE OF RESIDENTIAL COMMUNITIES SUBJECT TO HURRICANE HAZARD

Hurricanes are among the most devastating and costliest natural hazards. This devastating impact urged governments and policymakers to implement mitigation plans and strategies that can enhance the community’s resilience against hurricanes. A fundamental step to gauge the performance and effectiveness of these mitigations plans is to develop computational frameworks that can provide a probabilistic assessment of the resilience of the community. Therefore, this paper presents a framework to probabilistically estimate the resilience of residential wooden buildings against hurricane winds. The framework estimates the post-hurricane damage due to dynamic wind pressure and the impact of windborne debris using an engineering-based hurricane vulnerability. The building recovery function is then estimated by integrating the estimated damage with a building-level recovery model. By aggregating building recovery functions, the community recovery function is obtained. The Monte Carlo simulation method is used to account for uncertainties related to the hazard intensity, community vulnerability, and recovery process. The framework is applied to a residential neighborhood in Miami, FL. This framework can help decision-makers to compare current community resilience with target levels, identify the gap, and set strategies to improve community resilience.

Hurricane risk assessment of offshore wind turbines under changing climate

<p>Offshore wind energy is attracting increasing attention across the North America. However, the offshore wind turbines along the East Coast are extremely vulnerable to hurricane-induced hazards. The vulnerability to hurricanes is expected to change due to global warming’s effects. This study quantifies the risk of floating wind turbines (FWTs) subjected to hurricane hazards under current and future climate scenarios. The hurricane hazard estimation is achieved using a hurricane track model which generates a large synthetic database of hurricanes allowing for accurate risk estimation. The structural response of the FWTs during each hurricane event is obtained using an efficient physics-based 3-D model. The case study results involving a parked FWT indicate that the change in hurricane-induced risk, evaluated in terms of the magnification factor, to the FWTs would significantly increase with the intensity measure.</p>