• International Journal of High-Rise Buildings
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• v.12 no.4
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• pp.287-297
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• 2023

This paper briefly discusses current issues in wind engineering, including the enhancement of aerodynamic database and AI-assisted design, aerodynamic characteristics of tall buildings with atypical building shapes, application of computation fluid dynamics to wind engineering, evaluation of aerodynamic force coefficients based on a probabilistic method, estimation of tornadic wind speed (JEF scale) and effect of the Ekman Spiral on tall buildings.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.873-881
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• 2014

Speed sensorless modes of operation are becoming standard solution in the area of electric drives. This paper presents flux estimator and speed estimator for the speed sensorless vector control of induction motors. The proposed sensorless methods are based on the model reference adaptive system (MRAS) observer and adaptive speed observer (ASO). The proposed speed estimation algorithm can be employed in the power control of grid connected induction generator for wind power applications. Two proposed schemes are verified through computer simulation PSIM and compared their simulation results.

• New & Renewable Energy
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• v.10 no.2
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• Wind and Structures
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• v.31 no.5
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• pp.419-430
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• 2020

Weibull distribution is a conspicuous distribution known for its accuracy and its usage for wind energy analysis. The two and three parameter Weibull distributions are adopted in this study to fit wind speed data. The daily mean wind speed data of Ennore, Tamil Nadu, India has been used to validate the procedure. The parameters are estimated using maximum likelihood method, least square method and moment method. Four statistical tests namely Root mean square error, R2 test, Kolmogorov-Smirnov test and Anderson-Darling test are employed to inspect the fitness of Weibull probability density functions. The value of shape factor, scale factor, wind speed and wind power are determined at a height of 100m using extrapolation of numerical equations. Also, the value of capacity factor is calculated mathematically. This study provides a way to evaluate feasible locations for wind energy assessment, which can be used at any windy site throughout the world.

• Spatial Information Research
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• v.19 no.5
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• pp.47-52
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• 2011

Recently damage scale by local winds and typhoon has dramatically increased. Korea has the terrain over 70% of the land and the planning of the wind load is necessary to estimate reflecting appropriately the change of the wind-speed according to the characteristic of the terrain and in the Korean Building Code(2009), this is stated and it reflects to the design process. However, in order to estimate the topographic factor of the wind speed considering the topographic characteristics in the structure design actually, it has many difficult points including the local topographic survey, etc. In this paper, the Digital Elevation Model(DEM) is created using TIN interpolation method in the form of the digital map and then the interface was designed and implemented which can automatically estimate the topographic factor of wind speed by using ESRI(R)ArcObjectTM and the Visual Basic programing language. By applying it to the terrain which positioned in the downtown area, the practicality of the topographic factor of wind speed estimation interface was checked.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.869-877
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• 2016

Necessity has compelled man to improve upon the art of tapping wind energy for power generation; an apt reliever of strain exerted on the non-renewable fossil fuel. The power generation in a Wind Farm (WF) depends on site and wind velocity which varies with time and season which in turn determine wind power modeling. It implies, the development of an accurate wind speed model to predict wind power fluctuations at a particular site is significant. In this paper, Box-Jenkins ARIMA (Auto Regressive Integrated Moving Average) time series model for wind speed is developed for a 99MW wind farm in the southern region of India. Because of the uncertainty in wind power developed, the economic viability and reliability of power generation is significant. Life Cycle Costing (LCC) method is used to determine the economic viability of WF generated power. Reliability models of WF are developed with the help of load curve of the utility grid and Capacity Outage Probability Table (COPT). ARIMA wind speed model is used for developing COPT. The values of annual reliability indices and variations of risk index of the WF with system peak load are calculated. Such reliability models of large WF can be used in generation system planning.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.491-500
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• 2022

It has been noted that an accurate estimation of wind loads on offshore structures such as an FLNG (Liquefied Natural Gas Floating P roduction Storage Offloading Units, LNG FPSOs) with a large topside plays an important role in the safety design of hull and mooring system. Therefore, the present study aims to develop a computational model for estimating the wind load acting on an FLNG. In particular, it is the sequel to the previous research by the author. The numerical computation model in the present study was modified based on the previous research. Numerical analysis for estimating wind loads was performed in two conditions for an interval of wind direction (α), 15° over the range of 0° to 360°. One condition is uniform wind speed and the other is the NPD model reflecting the wind speed profile. At first, the effect of sand-grain roughness on the speed profile of the NPD model was studied. Based on the developed NPD model, mesh convergence tests were carried out for 3 wind headings, i.e. head, quartering, and beam. Finally, wind loads on 6-degrees of freedom were numerically estimated and compared by two boundary conditions, uniform speed, and the NPD model. In the present study, a commercial RANS-based viscous solver, STAR-CCM+ (ver. 17.02) was adopted. In summary, wind loads in surge and yaw from the wind speed profile boundary condition were increased by 20.35% and 34.27% at most. Particularly, the interval mean of sway (45° < α <135°, 225° < α < 315°) and roll (60° < α < 135°, 225° < α < 270°) increased by 15.60% and 10.89% against the uniform wind speed (10m/s) boundary condition.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.209-216
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• 2009

The structural stability as well as economical efficiency of the wind sensitive structures are strongly dependant on accurate evaluation of the design wind speed. Present study demonstrates a useful wind data obtained at the wind monitoring tower in the Kwangyang Suspension Bridge site. Moreover the Measure-Correlate-Predict (MCP) method has been applied to estimate the long-term wind data at the bridge site based on the wind data at the local weather station. The measured data indicate that the turbulent intensities and roughness exponents are strongly affected by the wind direction and surrounding topography. The new design wind speed based on MCP method is 20m/s lower than that at the original estimation, and the resulting design wind load is only 36% of the old prediction. The field measurement of wind data is recommended to ensure the economical and secure design of the wind sensitive structures because the measured wind data reveal much different from the estimated one due to local topography.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3E
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• pp.69-76
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• 2008

Measurements of bubble size and distribution in the surface layer of the sea, wind speed, and variation of ocean environments were made continually over a four-day period in an experiment conducted in the South Sea of Korea during 17-20 September 2007. Theoretical background of bubble population model indicates that bubble population is a function of the depth, range and wind speed and bubble effects on sound speed shows that sound speed varies with frequency. Observational evidence exhibited that the middle size bubble population fit the model very well, however, smaller ones can not follow the model probably due to their short lifetime. Meanwhile, there is also a hysteresis effect of void fraction. Observational evidence also indicates that strong changes in sound speed are produced by the presence of swarms of micro bubbles especially from 7 kHz to 50 kHz, and calculation results are consistent with the measured data in the high frequency band, but inconsistent in the low frequency band. Based on the measurements of the sound speed and high frequency transmission configuration in the bubble layer, we present an estimation of underwater acoustic channel capacity in the bubble layer.