• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1930-1939
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• 2015

Wind power planning aims to locate and size wind farms optimally. Traditionally, wind power planners tend to choose the wind farms with the richest wind resources to maximize the energy benefit. However, the capacity benefit of wind power should also be considered in large-scale clustered wind farm planning because the correlation among the wind farms exerts an obvious influence on the capacity benefit brought about by the combined wind power. This paper proposes a planning model considering both the energy and the capacity benefit of the wind farms. The capacity benefit is evaluated by the wind power capacity credit. The Ordinal Optimization (OO) Theory, capable of handling problems with non-analytical forms, is applied to address the model. To verify the feasibility and advantages of the model, the proposed model is compared with a widely used genetic algorithm (GA) via a modified IEEE RTS-79 system and the real world case of Ningxia, China. The results show that the diversity of the wind farm enhances the capacity credit of wind power.

• Wind and Structures
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• v.36 no.2
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• pp.121-131
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• 2023

Aiming at the problem that fatigue characteristics of metal roof rely on local physical tests and lacks the cyclic load sequence matching with regional climate, this paper proposed a method of constructing the fatigue load spectrum based on integration of wind load model, measured data of long-span metal roof and climate statistical data. According to the turbulence characteristics of wind, the wind load model is established from the aspects of turbulence intensity, power spectral density and wind pressure coefficient. Considering the influence of roof configuration on wind pressure distribution, the parameters are modified through fusing the measured data with least squares method to approximate the actual wind pressure load of the roof system. Furthermore, with regards to the wind climate characteristics of building location, Weibull model is adopted to analyze the regional meteorological data to obtain the probability density distribution of wind velocity used for calculating wind load, so as to establish the cyclic wind load sequence with the attributes of regional climate and building configuration. Finally, taking a workshop's metal roof as an example, the wind load spectrum is constructed according to this method, and the fatigue simulation and residual life prediction are implemented based on the experimental data. The forecasting result is lightly higher than the design standards, consistent with general principles of its conservative safety design scale, which shows that the presented method is validated for the fatigue characteristics study and health assessment of metal roof.

• Wind and Structures
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• v.25 no.1
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• pp.1-24
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• 2017

This paper presents a 1:25 multi-freedom aero-elastic model for a high lighting pole at the Zhoushan stadium. To validate the similarity characteristics of the model, a free vibration test was performed before the formal test. Beat phenomenon was found and eliminated by synthesis of vibration in the X and Y directions, and the damping ratio of the model was identified by the free decay method. The dynamic characteristics of the model were examined and compared with the real structure; the similarity results were favorable. From the test results, the major along-wind dynamic response was the first vibration component. The along-wind wind vibration coefficient was calculated by the China code and Eurocode. When the peak factor equaled 3.5, the coefficient calculated by the China code was close to the experimental result while Eurocode had a slight overestimation of the coefficient. The wind vibration coefficient during typhoon flow was analyzed, and a magnification factor was suggested in typhoon-prone areas. By analyzing the power spectrum of the dynamic cross-wind base shear force, it was found that a second-order vortex-excited resonance existed. The cross-wind response in the test was smaller than Eurocode estimation. The aerodynamic damping ratio was calculated by random decrement technique and the results showed that aerodynamic damping ratios were mostly positive at the design wind speed, which means that the wind-induced galloping phenomenon is predicted not to occur at design wind speeds.

• Wind and Structures
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• v.9 no.6
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• pp.473-492
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• 2006

This paper presents numerical results of pedestrian-level wind environment around the base of a row of tall buildings by CFD. Four configurations of building arrangement are computed including a single square tall building. Computed results of pedestrian-level wind flow patterns and wind speeds are compared to previous wind tunnel measurement data to enable an assessment of CFD predictions. The CFD model uses the finite-volume method with RNG $k-{\varepsilon}$ model for turbulence closure. It is found that the numerical results can reproduce key features of pedestrian-level wind environment such as corner streams around corners of upwind building, sheltered zones behind buildings and channeled high-speed flow through a building gap. However, there are some differences between CFD results and wind tunnel data in the wind speed distribution and locations of highest wind speeds inside the corner streams. In locations of high ground-level wind speeds, CFD values match wind tunnel data within ${\pm}10%$.

• Journal of Industrial Technology
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• v.24 no.B
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• pp.29-36
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• 2004

The wind and wind-induced dynamic wind pressures fluctuate irregularly according to time and space. In this study, the proper orthogonal decomposition(POD) technique is applied to wind pressures acting on a tall tower model, and the following results are found: the along-wind and across-wind forces can be reconstructed by only four dominant POD modes, and the reconstructed errors are 4.71% and 22%, respectively for across-wind and along-wind directions. The physical meanings for dominant modes are also presented in the paper. The POD analysis can compress complex wind pressure data only by a few dominant modes and interpret spatio-temporal characteristics of wind pressure by novel way while existing statistical methods do not have such benefits.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.5-9
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• 2010

A numerical wind tunnel simulation is performed in order to predict wind loads acting on a building. The aim of the present study is to suggest a guideline for the numerical wind tunnel analysis, which could provide more detail wind load distributions compared to the wind code and expensive wind tunnel experiments. To validate the present numerical simulation, wind-induced loads on a 6 m cube model is predicted. Atmospheric boundary layer is used as a inlet boundary condition. Various effect of numerical methods are investigated such as size of computational domain, grid density, turbulence model and discretization scheme. The appropriate procedure for the numerical wind tunnel analysis is suggested through the present study.

• Journal of the Korean Solar Energy Society
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• v.26 no.2
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• pp.27-34
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• 2006

In this paper, a forecasting model of wind speed at Walryong Site, Jeju Island is presented, which has been developed and evaluated as a first step toward establishing Korea Forecasting Model of Wind Power Generation. The forecasting model is constructed based on neural network and is trained with wind speed data observed at Cosan Weather Station located near by Walryong Site. Due to short period of measurements at Walryong Site for training statistical model Gosan Weather Station's long-term data are substituted and then transplanted to Walryong Site by using Measure-Correlate-Predict technique. One to three-hour advance forecasting of wind speed show good agreements with the monitoring data of Walryong site with the correlation factors 0.96 and 0.88, respectively.

• Journal of Ocean Engineering and Technology
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• v.24 no.6
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• pp.7-15
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• 2010

Analyses of wind wave characteristics near the Korean marginal seas were performed in 2008 and 2009 by comparisons of an operational wind wave forecast model and ocean buoy data. In order to evaluate the model performance, its results were compared with the observed data from an ocean buoy. The model used in this study was very good at predicting the characteristics of wind waves near the Korean Peninsula, with correlation coefficients between the model and observations of over 0.8. The averaged Root Mean Square Error (RMSE) for 48 hrs of forecasting between the modeled and observed waves and storm surges/tide were 0.540 m and 0.609 m in 2008 and 2009, respectively. In the spatial and seasonal analysis of wind waves, long waves were found in July and September at the southern coast of Korea in 2008, while in 2009 long waves were found in the winter season at the eastern coast of Korea. Simulated significant wave heights showed evident variations caused by Typhoons in the summer season. When Typhoons Kalmaegi and Morakot in 2008 and 2009 approached to Korean Peninsula, the accuracy of the model predictions was good compared to the annual mean value.

• Journal of The Korean Astronomical Society
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• v.37 no.1
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• pp.55-59
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• 2004

We have developed a two fluid solar wind model from the Sun to 1 AU. Its basic equations are mass, momentum and energy conservations. In these equations, we include a wave mechanism of heating the corona and accelerating the wind. The two fluid model takes into account the power spectrum of Alfvenic wave fluctuation. Model computations have been made to fit observational constraints such as electron($T_e$) and proton($T_p$) temperatures and solar wind speed(V) at 1 AU. As a result, we obtained physical quantities of solar wind as follows: $T_e$ is $7.4{\times}10^5$ K and density(n) is $1.7 {\times}10^7\;cm^{-3}$ in the corona. At 1 AU $T_e$ is $2.1 {\times} 10^5$ K and n is $0.3 cm^{-3}$, and V is $511 km\;s^{-1}$. Our model well explains the heating of protons in the corona and the acceleration of the solar wind.

• Wind and Structures
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• v.36 no.6
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• pp.379-392
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• 2023

Structural health monitoring is used to ensure the well-being of civil structures by detecting damage and estimating deterioration. Wind flow applies external loads to high-rise buildings, with the horizontal force component of the wind causing structural displacements in high-rise buildings. This study proposes a deep learning-based predictive model for measuring lateral displacement response in high-rise buildings. The proposed long short-term memory model functions as a sequence generator to generate displacements on building floors depending on the displacement statistics collected on the top floor. The model was trained with wind-induced displacement data for the top floor of a high-rise building as input. The outcomes demonstrate that the model can forecast wind-induced displacement on the remaining floors of a building. Further, displacement was predicted for each floor of the high-rise buildings at wind flow angles of 0° and 45°. The proposed model accurately predicted a high-rise building model's story drift and lateral displacement. The outcomes of this proposed work are anticipated to serve as a guide for assessing the overall lateral displacement of high-rise buildings.