• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.1
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• pp.9-20
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• 2018

Due to integrated stochastic wind and wave loads, the supporting platform of a Floating Offshore Wind Turbine (FOWT) has to bear six Degrees of Freedom (DOF) motion, which makes the random cyclic loads acting on the structural components, for instance the tower base, more complicated than those on bottom-fixed or land-based wind turbines. These cyclic loads may cause unexpected fatigue damages on a FOWT. This paper presents a study on short-term fatigue damage at the tower base of a 5 MW FOWT with a spar-type platform. Fully coupled time-domain simulations code FAST is used and realistic environment conditions are considered to obtain the loads and structural stresses at the tower base. Then the cumulative fatigue damage is calculated based on rainflow counting method and Miner's rule. Moreover, the effects of the simulation length, the wind-wave misalignment, the wind-only condition and the wave-only condition on the fatigue damage are investigated. It is found that the wind and wave induced loads affect the tower base's axial stress separately and in a decoupled way, and the wave-induced fatigue damage is greater than that induced by the wind loads. Under the environment conditions with rated wind speed, the tower base experiences the highest fatigue damage when the joint probability of the wind and wave is included in the calculation. Moreover, it is also found that 1 h simulation length is sufficient to give an appropriate fatigue damage estimated life for FOWT.

• Wind and Structures
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• v.10 no.3
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• pp.269-285
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• 2007

This paper assesses the damage to high-set rectangular-plan houses with low-pitch gable roofs (built in the 1960 and 70s in the northern parts of Australia) to wind speeds experienced in tropical cyclones. The study estimates the likely failure mode and percentage of failure for a representative proportion of houses with increasing wind speed. Structural reliability concepts are used to determine the levels of damage. The wind load and the component connection strengths are treated as random variables with log-normal distributions. These variables are derived from experiments, structural analysis, damage investigations and experience. This study also incorporates progressive failures and considers the inter-dependency between the structural components in the house, when estimating the types and percentages of the overall failures in the population of these houses. The progressively increasing percentage of houses being subjected to high internal pressures resulting from damage to the envelope is considered. Results from this study also compare favourably with levels of damage and related modes of failure for high-set houses observed in post-cyclone damage surveys.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.130-139
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• 2017

The crop damage caused by strong wind was predicted using the wind speed data available from Korean Meteorological Administration (KMA). Wind speed data measured at 19 automatic weather stations in 2012 were compared with wind data available from the KMA's digital forecast. Linear regression equations were derived using the maximum value of wind speed measurements for the three-hour period prior to a given hour and the digital forecasts at the three-hour interval. Estimates of daily maximum wind speed were obtained from the regression equation finding the greatest value among the maximum wind speed at the three-hour interval. The estimation error for the daily maximum wind speed was expressed using normal distribution and Weibull distribution probability density function. The daily maximum wind speed was compared with the critical wind speed that could cause crop damage to determine the level of stages for wind damage, e.g., "watch" or "warning." Spatial interpolation of the regression coefficient for the maximum wind speed, the standard deviation of the estimation error at the automated weather stations, the parameters of Weibull distribution was performed. These interpolated values at the four synoptic weather stations including Suncheon, Namwon, Imsil, and Jangsu were used to estimate the daily maximum wind speed in 2012. The wind damage risk was determined using the critical wind speed of 10m/s under the assumption that the fruit of a pear variety Mansamgil would begin to drop at 10 m/s. The results indicated that the Weibull distribution was more effective than the normal distribution for the estimation error probability distribution for assessing wind damage risk.

• Structural Monitoring and Maintenance
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• v.5 no.4
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• pp.507-519
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• 2018

In this paper, damage assessment in wind-turbine towers using vibration-based artificial neural networks (ANNs) is numerically investigated. At first, a vibration-based ANNs algorithm is designed for damage detection in a wind turbine tower. The ANNs architecture consists of an input, an output, and hidden layers. Modal parameters of the wind turbine tower such as mode shapes and frequencies are utilized as the input and the output layer composes of element stiffness indices. Next, the finite element model of a real wind-turbine tower is established as the test structure. The natural frequencies and mode shapes of the test structure are computed under various damage cases of single and multiple damages to generate training patterns. Finally, the ANNs are trained using the generated training patterns and employed to detect damaged elements and severities in the test structure.

• Wind and Structures
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• v.19 no.3
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• pp.321-337
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• 2014

This study has developed an Enhanced Remote-Sensing (ERS) scale to improve the accuracy and efficiency of using remote-sensing images of residential building to predict their damage conditions. The new scale, by incorporating multiple damage states observable on remote-sensing imagery, substantially reduces measurement errors and increases the amount of information retained. A ground damage survey was conducted six days after the Joplin EF 5 tornado in 2011. A total of 1,400 one- and two-family residences (FR12) were selected and their damage states were evaluated based on Degree of Damage (DOD) in the Enhanced Fujita (EF) scale. A subsequent remote-sensing survey was performed to rate damages with the ERS scale using high-resolution aerial imagery. Results from Ordinary Least Square regression indicate that ERS-derived damage states could reliably predict the ground level damage with 94% of variance in DOD explained by ERS. The superior performance is mainly because ERS extracts more information. The regression model developed can be used for future rapid assessment of tornado damages. In addition, this study provides strong empirical evidence for the effectiveness of the ERS scale and remote-sensing technology for assessment of damages from tornadoes and other wind events.

• Wind and Structures
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• v.31 no.3
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• pp.217-227
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• 2020

Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

• Wind and Structures
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• v.13 no.2
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• pp.191-206
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• 2010

Windborne debris is a major cause of structural damage during severe windstorms and hurricanes owing to its direct impact on building envelopes as well as to the 'chain reaction' failure mechanism it induces by interacting with wind pressure damage. Estimation of debris risk is an important component in evaluating wind damage risk to residential developments. A debris risk model developed by the authors enables one to analytically aggregate damage threats to a building from different types of debris originating from neighboring buildings. This model is extended herein to a general debris risk analysis methodology that is then incorporated into a vulnerability model accounting for the temporal evolution of the interaction between pressure damage and debris damage during storm passage. The current paper (Part I) introduces the debris risk analysis methodology, establishing the mathematical modeling framework. Stochastic models are proposed to estimate the probability distributions of debris trajectory parameters used in the method. It is shown that model statistics can be estimated from available information from wind-tunnel experiments and post-damage surveys. The incorporation of the methodology into vulnerability modeling is described in Part II.

• Wind and Structures
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• v.3 no.1
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• pp.23-40
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• 2000

In the early morning hours of February 23rd, 1998, seven large tornadoes ravaged central Florida. A total of 42 people were killed and millions of dollars of damage was done. A strip mall and other commercial structures sustained considerable damage and several residential areas were completely destroyed. Based on field observations, the paper examines the causes and sequence of structural failure for the masonry single family homes. Wind speeds are estimated based on the observed damage, and compared to the meteorological data. Finally, recommendations are given that could help to eliminate or reduce similar failures in the future. It was found that with simple, cost effective measures, most if not all of the damage could have been prevented.

• Journal of the Korean Society of Safety
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• v.31 no.2
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• pp.127-132
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• 2016

In this study, the plan to construct a disaster information categorization system that can be objectively and efficiently performed was suggested in order to perform disaster management task systematically. Recently, the damage of natural disasters is gradually growing larger and faster, increasing the economic loss. Especially, as for the domestic storm damage, the damage from strong wind was found to be greater than the damage from torrential rain. Also, strong wind was found to be inflicting a great damage on human life, property and agricultural crops, so the necessity to study damage restoration from strong wind is increasing. Nevertheless, the damage items categorized in the domestic disaster year book are often comprehensive or unclear in criteria, and thus fail to reflect items or matters due to actual disaster damage. It is difficult to aggregate damage accurately such that it does not correspond to the national compensation scope or the damage amount is calculated according to subjective judgment of the investigator in charge. As such, if the disaster information management is inadequate by not applying accurate categorization criteria from damage amount calculation, there can be an issue with fairness when paying the damage support aid. Therefore, this study suggested a categorization plan for objective and efficient execution of disaster information management task in order to resolve such issues. It is expected that quick and efficient execution would be possible in disaster information management and task procedure domestically by constructing systematic categorization system related to disaster information.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.667-675
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• 2012

A damage estimation method for support structure of offshore wind turbine using modal parameters is presented for effective structural health monitoring. Natural frequencies and mode shapes for a support structure with monopile of an offshore wind turbine were calculated considering soil condition and added mass. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. Natural frequencies and mode shapes for 10 prospective damage cases were input to the trained neural network for damage estimation. The identified damage locations and severities agreed reasonably well with the accurate damages. Multi-damage cases could also be successfully estimated. Enhancement of estimation result using another parameters as input to neural network will be carried out by further study. Proposed method could be applied to other type of support structure of offshore wind turbine for structural health monitoring.