Wind Hazard Research Articles

Spatiotemporal characteristics of high winds in Jilin Province during 1982–2021

AbstractHigh winds are a type of catastrophic weather characterized by wind speeds over 10.8 m·s−1, occurring in all seasons, and have become more frequent, impacting crop growth, agricultural production and quality of life. It is crucial to understand the spatial and temporal distribution patterns of high winds, as well as their speed and other characteristics, for logical planning of agricultural production and the creation of disaster resilience measures. This study applied the climate tendency, accumulative anomalies, theory of run, Mann–Kendall trend and Theil–Sen median to analyse the spatial and temporal distribution characteristics of the average wind speed and high wind days in Jilin Province, the probability of occurrence of high winds of various magnitudes in different eras, and the gale concentration degree (GCD) throughout Jilin Province for a total of 40 years from 1982 to 2021. The average wind speed and number of high wind days in Jilin Province have decreased over the past 40 years, and this trend has slowed over time. The average GCD in Jilin Province has shown an increasing trend over the last 40 years, with the average GCD being highest in Liouhe and lowest in Linjiang. In general, level six high winds were the main wind hazard level in Jilin Province, with the highest frequency occurring in different seasons and decades. In addition, the occurrence of high wind days is affected by global climate change and different underlying surfaces, which leads to maize and yield reduction. Research on the spatiotemporal distribution of high winds can provide important suggestions for the prevention and management of high wind disasters.

Modeling the Resilience of Power Distribution Systems Subjected to Extreme Winds Considering Tree Failures: An Integrated Framework

Overhead electrical power distribution systems (PDS) are very susceptible to extreme wind hazards. Power outages can cause catastrophic consequences, including economic losses, loss of critical services, and disruption to daily life. Therefore, it is very important to model the resilience of PDS against extreme winds to support disaster planning. While several frameworks currently exist to assess the resilience of PDS subjected to extreme winds, these frameworks do not systematically consider the tree-failure risk. In other words, there is no integrated framework that can simultaneously consider tree failures, PDS component failures induced by falling trees, resilience assessment, and evaluation of resilience enhancement with vegetation management. Therefore, this study proposed an integrated simulation framework to model the resilience of PDS against extreme winds, which includes tree fragility modeling, PDS fragility modeling, PDS component failure estimation, system performance evaluation, system restoration modeling, and resilience enhancement evaluation. The framework is demonstrated with a power distribution network in Oklahoma. The results show that the estimated system resilience will reduce if tree failures are considered. Crown thinning can effectively enhance the system’s resilience, but the effectiveness is affected by both wind speed and direction.

Comparative study of typhoon wind hazard estimation in coastal region of China using different wind field parameter models

Radius to maximum wind speed (Rmax) and Holland pressure profile parameter (B) are two key parameters for parametric typhoon or hurricane wind field modelling and hazard estimation. They are difficult to be observed or estimated for all historical storms and therefore always unavailable in most best track datasets. The statistical models were developed to correlate these two parameters with other available parameters based on limited real observation data and widely employed in typhoon hazard estimation. The applicability of these models to different ocean regions remains questionable. In this study, series of statistical models of Rmax and B are revisited and classified based on their regions of application, i.e., Gulf of Mexico and Atlantic Basin (GM&AB), South Pacific (SP), Bay of Bengal (BB) and Western North Pacific (WNP, 0°N-60°N, 100°E−180°E). Moreover, recursive models of Rmax and B in WNP are also introduced. The comparison of variation characteristics of different models for these two key parameters along with the change of typhoon surface central pressure deficit ΔPs are conducted. The stochastic typhoon tracking and intensity models are then coupled with an analytical wind field model to estimate the typhoon wind hazard of five coastal cities of China. The probability of exceedance and return period curves of wind speed are compared using different Rmax and B parameter models. The use of different Rmax and B models is shown to have significant effects on wind hazard curves. The extreme wind speeds estimated using parameter models from GM&AB and wind field model in this study are almost consistent with each other. Different models in WNP produce significant differences of wind hazard curve. The new findings in this study provide a forward step to the rational estimation of typhoon wind hazard in WNP by using the appropriate wind field parameter models.

Reconstructing urban wind flows for urban air mobility using reduced-order data assimilation

Advancements in uncrewed aircrafts and communications technologies have led to a wave of interest and investment in unmanned aircraft systems (UASs) and urban air mobility (UAM) vehicles over the past decade. To support this emerging aviation application, concepts for UAS/UAM traffic management (UTM) systems have been explored. Accurately characterizing and predicting the microscale weather conditions, winds in particular, will be critical to safe and efficient operations of the small UASs/UAM aircrafts within the UTM. This study implements a reduced order data assimilation approach to reduce discrepancies between the predicted urban wind speed with computational fluid dynamics (CFD) Reynolds-averaged Navier Stokes (RANS) model with real-world, limited and sparse observations. The developed data assimilation system is UrbanDA. These observations are simulated using a large eddy simulation (LES). The data assimilation approach is based on the time-independent variational framework and uses space reduction to reduce the memory cost of the process. This approach leads to error reduction throughout the simulated domain and the reconstructed field is different than the initial guess by ingesting wind speeds at sensor locations and hence taking into account flow unsteadiness in a time when only the mean flow quantities are resolved. Different locations where wind sensors can be installed are discussed in terms of their impact on the resulting wind field. It is shown that near-wall locations, near turbulence generation areas with high wind speeds have the highest impact. Approximating the model error with its principal mode provides a better agreement with the truth and the hazardous areas for UAS navigation increases by more than 10% as wind hazards resulting from buildings wakes are better simulated through this process.

Climate change effects on loss assessment and mitigation of residential buildings due to hurricane wind

Hurricanes are considered as one of the most devastating natural hazards. Their induced risk is expected to significantly increase with the changing climate conditions. Residential buildings are specifically highly vulnerable to hurricane winds. Therefore, accurate assessment of hurricane induced losses under changing climate conditions is crucial to assist in the development of the best mitigation strategies. In this paper, a stochastic hurricane risk assessment framework accounting for several climate scenarios is developed to assess the hurricane-induced losses of residential buildings located in hurricane-prone regions. Specifically, a total of 10,000 years of synthetic storms will be generated for both ‘observed climate’ and ‘future climate’. The future climate models correspond to the worst-case scenario SSP5-8.5 and are simulated based on two global climate models. Then a physics-based wind model is coupled with the synthetic tracks to generate the hazard probabilities. To accurately capture the upper tail effects, the Gaussian kernel density estimation function is proposed in this study. The effects of the variability of climate change models on the wind hazard and its induced losses are quantitatively evaluated. The average annual regional loss is selected as the decision variable. The framework is applied to a one-story single-family wood frame residential building in three different cities, namely Atlantic City, Miami and Galveston. Three mitigation strategies are evaluated, with varying degrees of structural mitigation, by comparing the corresponding losses incurred under different climate change scenarios. It is shown that, due to the disproportionate variation of hurricane intensity and frequency over the coastal areas, the estimated annual losses with the consideration of several mitigation strategies change unevenly from one location to another. Also, the selection of inappropriate probability density function to estimate the wind distribution might underestimate the hurricane-induced loss which is mainly due to its incapability to accurately capture the upper tail ends of the wind distribution.

North Atlantic Tropical Cyclone Size and Storm Surge Reconstructions From 1950‐Present

AbstractTropical cyclones (TCs) are one of the greatest threats to coastal communities along the US Atlantic and Gulf coasts due to their extreme wind, rainfall and storm surge. Analyzing historical TC climatology and modeling TC hazards can provide valuable insight to planners and decision makers. However, detailed TC size information is typically only available from 1988 onward, preventing accurate wind, rainfall, and storm surge modeling for TCs occurring earlier in the historical record. To overcome temporally limited TC size data, we develop a database of size estimates that are based on reanalysis data and a physics‐based model. Specifically, we utilize ERA5 reanalysis data to estimate the TC outer size, and a physics‐based TC wind model to estimate the radius of maximum wind. We evaluate our TC size estimates using two high‐resolution wind data sets as well as Best Track information for a wide variety of TCs. Using the estimated size information plus the TC track and intensity, we reconstruct historical storm tides from 1950 to 2020 using a basin‐scale hydrodynamic model and show that our reconstructions agree well with observed peak storm tide and storm surge. Finally, we demonstrate that incorporating an expanded set of historical modeled storm tides beginning in 1950 can enhance our understanding of US coastal hazard. Our newly developed database of TC sizes and associated storm tides/surges can aid in understanding North Atlantic TC climatology and modeling TC wind, storm surge, and rainfall hazard along the US Atlantic and Gulf coasts.

From social and natural vulnerability to human-centered climate resilient coastal cities

Anthropogenic climate change is increasingly affecting every city in the world, including through more intense weather and climate extremes. Climate impacts and risks are magnified in cities, which are home to more than half the world's population. Projections show one billion people will live in areas at risk of coastal hazards by 2050. Sea level rise jeopardizes cities to complicated wind, water, and coastal hazards. Potential impacts on wellbeing include damage to housing, transportation, and energy infrastructure as well as human health. Yet, attention thus far has focused on incremental adaptation responses, with a focus more on infrastructure and technology transitions in coastal cities. Comprehensive transformative actions that specifically incorporate behavioral, cultural and institutional options are largely neglected. In this perspective, we emphasize that immediate and massive effort and involvement from individuals to social entities across sectors, institutions, and systems is required for a transformation toward climate-resilient coastal cities. We conclude by emphasizing that dichotomies between ambitious adaptation and mitigation actions need to be bridged to enhance resilience to warming in coastal cities, and that this requires appropriate multi-level governance mechanisms to coordinate across agents and sectors.

A Novel Integrated Optimization-Driven Design Framework for Minimum-Weight Lateral-Load Resisting Systems in Wind-Sensitive Buildings Equipped with Dynamic Vibration Absorbers

The increasing rate of urbanization in recent decades has resulted in a global surge in the construction of slender high-rise buildings. These structures are prone to excessive wind-induced lateral vibrations in the crosswind direction owing to vortex shedding effects, causing occupant discomfort and, ultimately, dynamic serviceability failure. To reconcile the worldwide accelerated trend in constructing tall buildings with the sustainable building sector agenda, this paper proposes a novel bi-objective integrated design framework that leverages dynamic vibration absorbers (DVAs) to minimize the required material usage in the wind load-resisting structural systems (WLSSs) of occupant comfort-governed tall buildings. The framework couples structural sizing optimization for minimum-weight WLSS design (objective 1), with optimal DVA tuning for floor acceleration minimization to satisfy codified wind comfort design requirements by using the smallest DVA inertia (objective 2). Furthermore, a versatile numerical strategy is devised for the efficient solution of the proposed bi-objective optimization problem. For illustration, the framework is applied to a 15-storey steel building equipped with one of two different DVAs: a widely considered top-floor tuned mass damper (TMD) and an innovative ground-floor tuned inerter damper (TID). The derived Pareto optimal integrated (WLSS-plus-DVA) designs demonstrate that significant reduction in both structural steel usage and embodied carbon emissions can be achieved using either one of the two DVAs with moderate inertia. It is concluded that the proposed optimization-driven design framework and numerical solution strategy offer an alternative innovative approach to achieve material-efficient high-rise buildings under wind hazards.

Tropical cyclone wind hazard assessment for Donghaitang wind farm (Zhejiang Province, China): Case study

Currently, offshore and coastal wind power resources are growing rapidly around the world, especially in China. However, systematic research on the hazard assessment of wind farms under tropical cyclone conditions remains lacking. This study simulated the wind field of tropical cyclones based on a parameterized tropical cyclone wind field model, and analyzed the characteristics of historical tropical cyclones in Donghaitang wind farm (Zhejiang, China). Four extreme tropical cyclone hazard factors including the maximum wind speed (Vmax), maximum duration of wind direction change (Tmax), maximum cumulative wind direction change (Δθmax) and maximum rate of change in wind direction (ΔDmax) were proposed and examined. Then a comprehensive hazard assessment model for wind farms based on the analytic hierarchy process was established, and the risk to the Donghaitang wind farm represented by tropical cyclones during 1949–2021 was evaluated. Results showed that the number and intensity of tropical cyclones made landfall near the coast of Donghaitang wind farm gradually increased with time, which results in a gradual increase in the composite tropical cyclone risk level of the Donghaitang wind farm with time. The numbers and risk levels of tropical cyclones traveling northwestward were much larger than those traveling northward or northeastward. Moreover, the average composite risk index for tropical cyclones passing to the left of the wind farm was 14.3% higher than that for tropical cyclones passing to the right. The large values of Vmax and ΔDmax are main reasons for the high risk of the wind farm, while the other two hazard factors (Tmax, Δθmax) proposed to account for the wind turbine backup power are also of great importance in the design, selection and operation stages of offshore wind turbines. The findings of this study could provide support for hazard assessment of offshore and coastal wind farms exposed to tropical cyclones, including macro site selection of wind farms and type selection of wind turbines.

A novel framework to study community-level social and physical impacts of hurricane-induced winds through synthetic scenario analysis

Strong hurricane winds often cause severe infrastructure damage and pose social and economic consequences in coastal communities. In the context of community resilience planning, estimating such impacts can facilitate developing more risk-informed mitigation plans in the community of interest. This study presents a new framework for synthetically simulating scenario-hurricane winds using a parametric wind field model for predicting community-level building damage, direct economic loss, and social consequences. The proposed synthetic scenario approach uses historical hurricane data and adjusts its original trajectory to create synthetic change scenarios and estimates peak gust wind speed at the location of each building. In this research, a stochastic damage simulation algorithm is applied to assess the buildings’ physical damage. The algorithm assigns a damage level to each building using the corresponding damage-based fragility functions, predicted maximum gust speed at the building’s location, and a randomly generated number. The monetary loss to the building inventory due to its physical damage is determined using FEMA’s direct loss ratios and buildings’ replacement costs considering uncertainty. To assess the social impacts of the physical damage exposure, three likely post-disaster social disruptions are measured, including household dislocation, employment disruption, and school closures. The framework is demonstrated by its application to the hurricane-prone community of Onslow County, North Carolina. The novel contribution of the developed framework, aside from the introduced approach for spatial predicting hurricane-induced wind hazards, is its ability to illuminate some aspects of the social consequences of substantial physical damages to the building inventory in a coastal community due to the hurricane-induced winds. These advancements enable community planners and decision-makers to make more risk-informed decisions for improving coastal community resilience.

Community Perspectives on Simulation and Data Needs for the Study of Natural Hazard Impacts and Recovery

With the aim of fostering the development of robust tools to simulate the impact of natural hazards on structures, lifelines, and communities, the Natural Hazards Engineering Research Infrastructure Computational Modeling and Simulation Center gathered 60 researchers, developers, and practitioners working in natural hazards engineering (NHE) for a workshop to prioritize research questions and identify community needs for data and computational simulation capabilities. Participants used their wide-ranging expertise in earthquake, coastal, and wind hazards from engineering, planning, data sciences, and social sciences perspectives to identify five major thrusts of recommended future work, including detailed suggestions for each: (1) development of housing and household recovery models; (2) integration of existing models into flexible computational workflows; (3) investment in the collection of high-value open data; (4) commitment to sharing and utilizing high-value data; and (5) development of versatile, multidisciplinary testbed studies. Participant responses and workshop data were analyzed with the help of an ontology that the authors designed to support data classification in a broad range of NHE applications. The paper also includes observations and suggestions for planning and conducting interactive workshops of this type.

Attribution of observed extreme marine wind speeds and associated hazards to midlatitude cyclone conveyor belt jets near the British Isles

AbstractExtreme wind speeds, gusts, and wind wave heights associated with midlatitude cyclones pose a hazard to shipping lanes and offshore infrastructure operating in the North Atlantic Ocean seas surrounding the British Isles. Several studies have assessed the variability of wind and waves in this region using reanalyses, but few have used surface observations of extreme wind speeds and wave heights. Here, we use a network of marine surface stations to derive the 2012–2020 climatology of daily maximum wind speed events. An algorithm is used to attribute the extreme wind events, characterized as exceeding the 20 and 25 m·s−1 thresholds, to the cyclone warm conveyor belt (WCB), and early (CCBa) and returning (CCBb) cold conveyor belt jets; cyclones are matched with up to 90% of extreme wind events. The CCBb is most frequently associated with the strong wind speeds, accounting for 46 and 59% of the events exceeding the two thresholds, respectively. The CCBb also leads to the largest number of compound wind and wave hazard events (37 out of 87). Although the WCB is associated with the second largest number of extreme wind events, the CCBa accounts for the second largest number of compound extreme wind and wave events (24). The ERA5 reanalysis underestimates the observed extreme wind speeds, and associated gusts and wind‐wave heights, during extreme wind events for all the conveyor belt jets. The wind speeds and associated gusts are most underestimated, by median values of 4.5 and 5.5 m·s−1, respectively, and similar percentage error (), when associated with the CCBb; however, the wind‐wave heights are most underestimated, by a median of 3.4 m, when associated with the CCBa. Hence, while the marine CCBb jet, found in mature cyclones, is both most hazardous and underestimated in the ERA5 near the British Isles, the CCBa jet can be nearly as hazardous when considering compound wind‐wave events.

Assessing the effects of China's Three-North Shelter Forest Program over 40 years.

Forests provide vital ecosystem services such as soil and water conservation, climate regulation, and carbon storage. Large-scale afforestation programs are being attempted in many countries to improve environmental conditions in deteriorated or unfavorable locations. China's Three Northern Protected Forest Program (TNSFP), accounting for 42.40 % of China's total land area, is the world's largest afforestation program to date. The TNSFP has continued providing critical ecosystem services to humans over 73 years (1978-2050) with a total investment of CNY 93.3 billion. To facilitate understanding of the TNSFP's contribution, the effects of the TNSFP for last 43 years were comprehensively evaluated by using integrated review of structured literature, bibliometric analysis, and thematic analysis. We incorporated and expanded the direct ecosystem services evidence of the TNSFP from wind and sand control, soil erosion control and carbon sequestration to indirect economic benefits, e.g. increasing crop yield and promoting economic development. We found that over the past 40 years of TNSFP construction, wind and sand hazards and soil erosion in China's Three-North areas have been effectively controlled, and forest carbon sequestration, grain production and economic output have steadily increased. The ecosystem services provided by the TNSFP are highly consistent with the thrust of the UN Sustainable Development Goals, and the TNSFP has contributed to the realization of SDG2, SDG8, SDG13, and SDG15. Although achieving tremendous ecological, economic, and social benefits, the TNSFP still has knowledge gaps in its scientific basis. And the limited local engagement and insufficient investment highly hinder the TNSFP from playing its multiple functions. We suggest several urgent actions and directions to address these limitations. This review could help researchers gain insight into key areas of ecological restoration in the TNSFP, providing a reference for future research in the TNSFP construction in China and other regions of the world embarking on similar journeys.

Evaluating the Increasing Trend of Strength and Severe Wind Hazard of Philippine Typhoons Using the Holland-B Parameter and Regional Cyclonic Wind Field Modeling

For the Philippines, a country exposed to multiple natural hazards, such as severe winds, sustainable development includes resiliency. A severe wind hazard is raised by tropical cyclones in the Western Pacific, known as typhoons, which frequent the Philippines. Therefore, adequately evaluating wind hazards and their impact is crucial for sustainable building design. Acknowledging the effects of climate change on said hazards requires adaptation to their consequences, which necessitates a deeper understanding of the changing behavior of typhoons in recent years. For this study, detailed wind information from the Japanese Meteorological Agency from 1977 to 2021, the Holland-B parameter, and the radius of maximum wind speed for each typhoon, are determined for simulation of the regional cyclonic wind field. The analysis of the Holland-B parameters, which represent the steepness of the pressure gradient and tropical cyclone convection, suggests that the Holland-B parameters have been increasing since 2011. The evaluation of the maximum regional wind fields and the return period wind fields caused by typhoons also indicate an increasing trend in severe wind hazards. Seasonality for the location of severe wind hazards is also observed, with Visayas and Mindanao experiencing an increase (decrease) during the Northeast (Southwest) Monsoon season and Luzon experiencing an increase (decrease) during the Southwest (Northeast) Monsoon season.

Joint wind and ice hazard for transmission lines in mountainous terrain

This paper focuses on analyzing the ice and wind conditions for a high voltage transmission line system going over mountainous terrain in British Columbia, Canada. After analyzing sixteen surrounding weather stations, an Artificial Neural Network (ANN) is performed for wind speed predictions, the Inverse Distance Weighted Interpolation method (IDW) is used for temperature estimations, and the K Nearest Neighbor Imputation (KNNI) is performed for precipitation rate on the unsampled site of interest. In-cloud icing is estimated using a simple empirical equation proposed by Makkonen & Ahti (1995), in addition to the ice accretion model proposed by Makkonen (2000). The weather data from the described procedure is compared with data from a Weather Research and Forecast model (WRF) reported in previous studies. The wind speed and ice accretion data are fitted to the Weibull and Generalized Pareto distributions, respectively, and five hundred years of data pairs are simulated in addition to the historical data based on those distributions. Finally, hazard contours are drawn, and the results are compared with the combined wind and ice values proposed in the National Standard of Canada (CSA-C22.3) for different reliability levels.

Wind and Seismic Response Control of Dynamically Similar Adjacent Buildings Connected Using Magneto-Rheological Dampers

Wind and/or earthquake-imposed loadings on two dynamically similar adjacent buildings cause vigorous shaking that can be mitigated using energy dissipating devices. Here, the vibration response control in such adjacent structures interconnected with semi-active magneto-rheological (MR) dampers is studied, which could also be used as a retrofitting measure in existing structures apart from employing them in new constructions. The semi-active nature of the MR damper is modeled using the popular Lyapunov control algorithm owing to its least computational efforts among the other considered control algorithms. The semi-active performance of the MR damper is compared with its two passive states, e.g., passive-off and passive-on, in which voltage applied to the damper is kept constant throughout the occurrence of a hazard, to establish its effectiveness even during the probable electric power failure during the wind or seismic hazards. The performance of the MR damper, in terms of structural response reduction, is compared with other popular energy dissipating devices, such as viscous and friction dampers. Four damper arrangements have been considered to arrive at the most effective configuration for interconnecting the two adjoining structures. Structural responses are recorded in terms of storey displacement, storey acceleration, and storey shear forces. Coupling the two adjacent dynamically similar buildings results in over a 50% reduction in the structural vibration against both wind and earthquake hazards, and this is achieved by not necessarily connecting all the floors of the structures with dampers. The comparative analysis indicates that the semi-active MR damper is more effective for response control than the other passive dampers.

Minimising damage to houses by designing for high internal pressures

Internal pressurisation of buildings during a severe wind event, such as a tropical cyclone or thunderstorm, can often cause severe structural failures, as observed during damage investigations. Wind loading standards worldwide provide design data for internal pressure design. However, the implementation of these data often depends on the location of the building in relation to the levels of wind hazard in the relevant country. Recent observations during Tropical Cyclone (TC) Seroja in an intermediate wind region (wind region B) in Western Australia indicated the need for the design for full internal pressures of buildings in this wind region. This paper presents an overview of the damage investigation conducted after TC Seroja that highlights significant damage to buildings due to the lack of design for internal pressures. Additionally, a case study of a house modelled using the vulnerability analysis software VAWS is presented showing the improvements in the performance of buildings designed for internal pressures. TheVAWS models showed that both the design for full internal pressure and the use of debris rated shutters were both effective at reducing the level of serious structural damage and making houses more resilient. The robustness and resilience of buildings increase significantly if they are designed for high internal pressure because the failure of a window or door (a local failure) will not lead to a major structural failure.

BIM-GIS integration approach for high-fidelity wind hazard modeling at the community-level

Wind hazards often result in significant damage to the built environment cascading into impacts on the socio-economic systems within a community. The increasing frequency and intensity of hurricane hazards highlight the importance of developing high-resolution wind hazard models to better predict the consequences. Although previous studies have investigated hurricane-induced wind hazards in terms of hazard modeling and the subsequent vulnerability of buildings and infrastructure, these studies have not yet investigated applications of computational fluid dynamics (CFD) at the community-level. Therefore, in this study, a novel approach was developed to generate CFD models at the community-level by integrating building information modeling (BIM) and geographical information systems (GIS) to automate the generation of a high-resolution 3-D community model to be used as an input for a digital wind tunnel. This was done by harnessing the current advances in BIM and GIS applications and maximizing their capabilities by developing an algorithm that automates the 3-D geometry generation of communities with a detailed discretization of each building within the community. The 3-D community model was developed using the GIS shapefile of the buildings’ footprint and a parametric BIM model that uses a number of building parameters such as footprint dimensions, roof shape, foundation type, and the number of stories. Then, an algorithm was developed to automate the creation of the BIM model for each building within the community based on the prescribed building’s characteristics. The developed community model was used as an input for a numerical wind tunnel that uses CFD to account for the detailed wind pressure at each building after including the impacts of aerodynamics interference at the community-level. This novel BIM-GIS integration approach provides, for the first time, the next generation of high-resolution community-level CFD wind hazard modeling which aims to shift the current practice of wind hazard simulation at the community-level.

Simplified models for uncertainty quantification of extreme events using Monte Carlo technique

The accurate prediction of extreme events based on measured data is an important task because it can facilitate infrastructure reliability design, risk assessment, and disaster mitigation. However, owing to limited sample size, considerable uncertainties are introduced to extreme value predictions with respect to different probabilities of exceedance. This paper proposes an uncertainty quantification analysis algorithm for extreme value statistics using the Monte Carlo technique. The study is focused on three widely used probability distributions fitted by the maximum likelihood method: generalized extreme value, generalized Pareto, and Pearson Type III. Three simplified models of the standard error for extreme value quantiles are explicitly developed as a function of the sample size, return period, and distribution parameters. These models eliminate the constraints resulting from the assumption of normality as well as provide more straightforward and accurate expressions that are convenient for engineering applications. The results indicate that the standard error increases with the return period as well as the shape and scale parameters of the distribution; however, it decreases with the sample size. The developed simplified models were applied to extreme event analyses of wind speed and precipitation at several typical sites. To clarify the practicability and rationality of the method, a wind hazard map for non-typhoon winds was developed for mainland China.

Design of temporary, conditional, general and highly influential buildings for tropical cyclones and severe local storms

This paper first discusses the causes of damage to buildings and structures due to various types of winds including daily winds and some extremely strong winds. Regarding devastating wind-induced disasters due to tropical cyclones (TC), the importance of combined effects of wind and water hazards is emphasized. It also points out human errors hidden in damage scenarios, especially for large buildings. The importance of cladding/component design, the significance of debris impacts, and the effects of sudden changes in internal pressures are also emphasized. The design principles for buildings and structures are also examined, and the crucial differences among building performances against TCs and severe local storms such as tornadoes and downbursts are discussed. Design load levels for temporary buildings including scaffoldings and construction offices and for conditional buildings and structures including cranes, movable roofs and so on are also discussed. Next, design issues of tornado effects on highly important and highly influential buildings such as nuclear power plants are discussed. Finally, to cope with the future increasing trend of wind-related disasters, the importance of decarbonization and full-scale storm simulators are emphasized.