• Wind and Structures
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• v.31 no.4
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• pp.363-371
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• 2020

Proper understanding of offshore wind speed variability is of essential importance in practice, which provides useful information to a wide range of coastal and marine activities. In this paper, long-term wind speed data recorded at various offshore stations are analyzed in the framework of fractal dimension analysis. Fractal analysis is a well-established data analysis tool, which is particularly suitable to determine the complexity in time series from a quantitative point of view. The fractal dimension is estimated using the conventional box-counting method. The results suggest that the wind speed data are generally fractals, which are likely to exhibit a persistent nature. The mean fractal dimension varies from 1.31 at an offshore weather station to 1.43 at an urban station, which is mainly associated with surface roughness condition. Monthly variability of fractal dimension at offshore stations is well-defined, which often possess larger values during hotter months and lower values during winter. This is partly attributed to the effect of thermal instability. In addition, with an increase in measurement interval, the mean and minimum fractal dimension decrease, whereas the maximum and coefficient of variation increase in parallel.

• Journal of Wind Energy
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• v.9 no.4
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• pp.40-46
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• 2018

In this study, a three-dimensional Navier-Stokes simulation around Wido Island was performed to analyze the wake effect behind an island. A 10 m/s wind speed and pressure boundary conditions were assigned for the inflow and outflow boundary conditions, respectively. Wido Island was modeled using GIS data. A prevailing wind from the north-northwest direction was determined based on QuikSCAT satellite data. A computational domain of $40km{\times}20km{\times}5km$ covering Wido Island was applied for numerical analysis. Sixty points were specified to extract the wind speed data. A wind speed profile inside the atmospheric boundary layer was compared with a wind profile using a simple power law. It turns out that the wake effect decreases the mean wind speed by 5% more or less, which corresponds to a 14% decrease in wind energy. Thus, the installation of a meteorological mast or development of a wind farm behind Wido Island is not highly recommended.

• Wind and Structures
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• v.17 no.2
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• pp.227-244
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• 2013

Non-stationary extreme winds such as thunderstorm downbursts are responsible for many structural damages. This research presents a time domain approach for estimating along-wind load effects on tall buildings using multiple wind speed time history samples, which are simulated from evolutionary power spectra density (EPSD) functions of non-stationary wind fluctuations using the method developed by the authors' earlier research. The influence of transient wind loads on various responses including time-varying mean, root-mean-square value and peak factor is also studied. Furthermore, a simplified model is proposed to describe the non-stationary wind fluctuation as a uniformly modulated process with a modulation function following the time-varying mean. Finally, the probabilistic extreme response and peak factor are quantified based on the up-crossing theory of non-stationary process. As compared to the time domain response analysis using limited samples of wind record, usually one sample, the analysis using multiple samples presented in this study will provide more statistical information of responses. The time domain simulation also facilitates consideration of nonlinearities of structural and wind load characteristics over previous frequency domain analysis.

• Wind and Structures
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• v.30 no.1
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• pp.55-67
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• 2020

Wind tunnel test is one of the most important means to study the flutter performance of bridges, but there are blockage effects in flutter test due to the size limitation of the wind tunnel. On the other hand, the size of computational domain can be defined by users in the numerical simulation. This paper presents a study on blockage effects of a simplified box girder by computation fluid dynamics (CFD) simulation, the blockage effects on the aerodynamic characteristics and flutter performance of a long-span suspension bridge are studied. The results show that the aerodynamic coefficients and the absolute value of mean pressure coefficient increase with the increase of the blockage ratio. And the aerodynamic coefficients can be corrected by the mean wind speed in the plane of leading edge of model. At each angle of attack, the critical flutter wind speed decreases as the blockage ratio increases, but the difference is that bending-torsion coupled flutter and torsional flutter occur at lower and larger angles of attack respectively. Finally, the correction formula of critical wind speed at 0° angle of attack is given, which can provide reference for wind resistance design of streamlined box girders in practical engineering.

• Wind and Structures
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• v.32 no.2
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• pp.89-104
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• 2021

Non-synoptic winds generated by tornadoes, downbursts or gust fronts exhibit significant non-stationarity and can cause significant wind load effect on flexible structures such as long-span bridges. However, conventional assumptions on stationarity used to evaluate the structural wind-induced vibration are inadequate. In this paper, an efficient frequency domain scheme based on fast CQC method, which can predict non-stationary buffeting random responses of long-span bridges, is presented, and then this approach is applied to evaluate the buffeting response of a long-span suspension bridge located in a complex mountainous wind environment as an example. In this study, the data-driven method based on one available measured wind speed sample is firstly presented to establish non-stationary wind models, including time-varying mean wind speed, time-varying intensity envelope function and uniformly modulated fluctuating spectrum. Then, a linear time-variant (LTV) system based on the proposed scheme can be generally applied to calculate the non-stationary buffeting responses. The effectiveness and accuracy of the proposed scheme are verified through Monte Carlo time domain simulation implemented in ANSYS platform. Also, the transient effect nature of the bridge responses is further illustrated by comparison of the non-stationary, quasistationary and steady-state cases. Finally, buffeting response analysis with traditional stationary treatment (10 min constant mean plus stationary wind fluctuation) is performed to illustrate the importance of the non-stationary characteristics embedded in original wind speed samples.

• Journal of Wind Energy
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• v.15 no.2
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• pp.10-22
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• 2024

This research is a comprehensive analysis of wind power prediction sensitivity using a Long Short-Term Memory (LSTM) deep learning neural network model, accounting for the inherent uncertainties in wind speed estimation. Utilizing a year's worth of operational data from an operational wind farm, the study forecasts the power output of both individual wind turbines and the farm collectively. Predictions were made daily at intervals of 10 minutes and 1 hour over a span of three months. The model's forecast accuracy was evaluated by comparing the root mean square error (RMSE), normalized RMSE (NRMSE), and correlation coefficients with actual power output data. Moreover, the research investigated how inaccuracies in wind speed inputs affect the power prediction sensitivity of the model. By simulating wind speed errors within a normal distribution range of 1% to 15%, the study analyzed their influence on the accuracy of power predictions. This investigation provided insights into the required wind speed prediction error rate to achieve an 8% power prediction error threshold, meeting the incentive standards for forecasting systems in renewable energy generation.

• Atmosphere
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• v.20 no.2
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• pp.63-71
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• 2010

In this study, we derived the wind speed at 50 m and 80 m above sea level from 567 stations over a period of 1 year and correlated to measured wind speed at 5 radiosonde sites. From these correlations, we derived and analyzed the spatial distribution of wind map over Korea based on hourly observational data recorded over a period of 5 years from 2004 to 2008. As a results, wind speed is generally high over seashores, mountains, and islands. Mean wind speed over Korea at 50 and 80 m above sea level for 5 years during 2004 to 2008 seasonally are highest at Spring, and then followed by Winter, Fall, and Summer. In 76 (14%) stations, mean wind speed at 80 m above sea level for 5 years during 2004 to 2008 are greater than $5ms^{-1}$. The prevailing winds over Korea at 80 m above sea level for 5 years during 2004 to 2008 are North (44%), Northwest (16%), and West (15%). In 99 stations, the % of wind faster than $5ms^{-1}$ was higher than 40%, and in 62 stations, the % of wind faster than $5ms^{-1}$ was higher than 50%. In 178 station, the % of prevailing winds was higher than 30%, and there are 7 stations which also have wind speeds over $5ms^{-1}$, ranking from highest to lowest, Dongsong, Daegwallyeong, Baekun Mt., Hyangrobong Mt., Sorak Mt., Gosan, and Misiryeong Mt..

• Wind and Structures
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• v.37 no.2
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• pp.117-131
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• 2023

Korea Design Standard (KDS) will be updated with two major revisions on the assessment of wind load and performance-based wind design (PBWD). Major changes on the wind load assessment are the wind load factor and basic wind speed. Wind load factor in KDS is reduced from 1.3 to 1, and mean recurrence interval (MRI) for basic wind speed increases from 100 years to 500 years considering the reduction of wind load factor. Additional modification is made including pressure coefficient, torsional moment coefficient and spectrum, and aeroelastic instability. Combined effect of the updates of KDS code on the assessment of wind load is discussed with the case study on the specified sites and building. PBWD is newly added in KDS code to consider the cases with various target performance, vortex-induced vibration, aeroelastic instability, or inelastic behavior. Proposed methods and target performance for PBWD in KDS code are introduced.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.417-421
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• 2006

A comparative study of wind speed spectrum based on the in-situ observation at the SeoHae bridge site is conducted. Wind speed and directions of the SeoHae bridge site is measured and analyzed. Mean wind speed and turbulence intensity are estimated. The power spectral density function of the fluctuating component of the wind velocity is estimated. Several wind spectrum models of gust wind turbulence are compared and discussed based on the estimated wind spectrum.

• Wind and Structures
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• v.13 no.6
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• pp.529-556
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• 2010

This paper investigates the correlation of wind characteristics monitored on a cable-stayed bridge. Total five anemoscopes are implemented into the bridge. Two out of 5 anemoscopes in inflow and two out of 5 anemoscopes in wake-flow along the longitudinal direction of the bridge are installed. Four anemoscopes are respectively distributed at two cross-sections. Another anemoscope is installed at the top of the tower. The correlation of mean wind speed and direction, power spectral density, the turbulent intensity and integral length of wind in flow at two cross-sections are investigated. In addition, considering the non-stationary characteristics of wind, the spatial correlation in time-frequency is analyzed using wavelet transform and different phenomenon from those obtained through FFT is observed. The time-frequency analysis further indicates that intermittence, coherence structures and self-similar structures are distinctly observed from fluctuant wind. The flow characteristics around the bridge deck at two positions are also investigated using the field measurement. The results indicate that the mean wind speed decrease when the flow passing through the deck, but the turbulence intensity become much larger and the turbulence integral lengths become much smaller compared with those of inflow. The relationship of RMS (root mean square) of wake-flow and the mean wind speed of inflow is approximately linear. The special structures of wake-flow in time-frequency domain are also analyzed using wavelet transform, which aids to reveal the forming process of wake-flow.