• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.17-22
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• 2004

A space launch vehicle departs the ground in a low speed, soon reaches a transonic and a supersonic speed, and then flies in a hypersonic speed into the space. Therefore, the design of a launch vehicle should include the prediction of aerodynamic characteristics for all speed regimes, ranging from subsonic to hypersonic speed. Generally, Empirical and analytical methods and wind tunnel tests are used for the prediction of aerodynamic characteristics. This research presents considerable factors for aerodynamic analysis of a launch vehicle using CFD. This investigation was conducted to determine effects of wake over the base section on the aerodynamic characteristics of a launch vehicle and also performed to determine effects of the sting which exist to support wind tunnel test model.

• Wind and Structures
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• v.9 no.5
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• pp.387-396
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• 2006

This paper presents the wind characteristics of Typhoon Dujuan as measured at a 50 m guyed mast in Hong Kong. The basic wind speed, wind direction and turbulent intensity are studied at two measurement levels of the structure. The power spectral density of the typhoon is compared with the von Karman prediction, and the coherence between wind speeds at the two measurement levels is found to This paper presents the wind characteristics of Typhoon Dujuan as measured at a 50 m guyed mast in Hong Kong. The basic wind speed, wind direction and turbulent intensity are studied at two measurement levels of the structure. The power spectral density of the typhoon is compared with the von Karman prediction, and the coherence between wind speeds at the two measurement levels is found to compare with Davenport's prediction. The effect of typhoon Dujuan on the response of the structure will be discussed in a companion paper (Law, et al. 2006).with Davenport's prediction. The effect of typhoon Dujuan on the response of the structure will be discussed in a companion paper (Law, et al. 2006).

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.327-333
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• 2019

Wind speed data constitute important weather information for aircrafts flying at low altitudes, such as drones. Currently, the accuracy of low altitude wind predictions is much lower than that of high-altitude wind predictions. Deep neural networks are proposed in this study as a method to improve wind speed forecast information. Deep neural networks mimic the learning process of the interactions among neurons in the brain, and it is used in various fields, such as recognition of image, sound, and texts, image and natural language processing, and pattern recognition in time-series. In this study, the deep neural network model is constructed using the wind prediction values generated by the numerical model as an input to improve the wind speed forecasts. Using the ground wind speed forecast data collected at the Boseong Meteorological Observation Tower, wind speed forecast values obtained by the numerical model are compared with those obtained by the model proposed in this study for the verification of the validity and compatibility of the proposed model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.652-655
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• 2008

Despite of the laminar-turbulent transition region co-exist with fully turbulence region around the leading edge of an airfoil, still lots of researchers apply to fully turbulence models to predict aerodynamic characteristics. It is well known that fully turbulent model such as standard k-${\varepsilon}$ model couldn't predict the complex stall and the separation behavior on an airfoil accurately, it usually leads to over prediction of the aerodynamic characteristics such as lift and drag forces. So, we apply correlation based transition model to predict aerodynamic performance of the NREL (National Renewable Energy Laboratory) Phase IV wind turbine. And also, compare the computed results from transition model with experimental measurement and fully turbulence results. Results are presented for a range of wind speed, for a NREL Phase IV wind turbine rotor. Low speed shaft torque, power, root bending moment, aerodynamic coefficients of 2D airfoil and several flow field figures results included in this study. As a result, the low speed shaft torque predicted by transitional turbulence model is very good agree with the experimental measurement in whole operating conditions but fully turbulent model(k-${\varepsilon}$) over predict the shaft torque after 7m/s. Root bending moment is also good agreement between the prediction and experiments for most of the operating conditions, especially with the transition model.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.290-292
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• 2008

we applied Wind Field Module of PHRLM so that disaster prevention agency concerned can effectively estimate the possible strong wind damages by typhoon. In this study, therefore, we estimated wind speed at 300m level using 700hPa wind according to the research method by Franklin(2003), PHRLM(2003), and Vickery and Skerlj(2005). Then we calculated wind speed at 10m level using the estimated wind speed at 300m level, and finally, peak 3.second gust on surface. The case period is from 18LST August 31 to 03LST September 1, 2002, when the typhoon Rusa in 2002 was the most intense. Among disaster prediction models in the US, Wind Field Module of PHRLM in Florida was used for the 2002 typhoon Rusa case. As a result, peak 3.second gust on the surface increased $10\sim20%$ in the typhoon's 700hPa wind speed.

• Journal of the Korean Solar Energy Society
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• v.37 no.1
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• pp.25-38
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• 2017

Climate change and environmental pollution are becoming serious due to the use of fossil energy. For this reason, renewable energy systems are increasing, especially photovoltaic systems being more popular. The photovoltaic system has characteristics that are affected by ambient weather conditions such as insolation, outside temperature, wind speed. Particularly, it has been confirmed that the performance of the photovoltaic system decreases as the module temperature increases. In order to grasp the influence of the module temperature in advance, several researchers have proposed the prediction models on the module temperature. In this paper, we predicted the module temperature using the aforementioned prediction model on the basis of the weather conditions in Incheon, South Korea during July and August. The influence of weather conditions (i.e. insolation, outside temperature, and wind speed) on the accuracy of the prediction models was also evaluated using the standard statistical metrics such as RMSE, MAD, and MAPE. The results show that the prediction accuracy is reduced by 3.9 times and 1.9 times as the insolation and outside temperature increased respectively. On the other hand, the accuracy increased by 6.3 times as the wind speed increased.

• Wind and Structures
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• v.30 no.4
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• pp.393-403
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• 2020

One of the growing concerns of the wind energy production is wind ramp events. To improve the wind ramp event forecasts, the nonlinear Kalman filter bias correction method was applied to 24-h wind speed forecasts issued from the WRF model at 70-m height in Zhangbei wind farm, Hebei Province, China for a two-year period. The Kalman filter shows the remarkable ability of improving forecast skill for real-time wind speed forecasts by decreasing RMSE by 32% from 3.26 m s_-1 to 2.21 m s_-1, reducing BIAS almost to zero, and improving correlation from 0.58 to 0.82. The bias correction improves the forecast skill especially in wind speed intervals sensitive to wind power prediction. The fact shows that the Kalman filter is especially suitable for wind power prediction. Moreover, the bias correction method performs well under abrupt weather transition. As to the overall performance for improving the forecast skill of ramp events, the Kalman filter shows noticeable improvements based on POD and TSS. The bias correction increases the POD score of up-ramps from 0.27 to 0.39 and from 0.26 to 0.38 for down-ramps. After bias correction, the TSS score is significantly promoted from 0.12 to 0.26 for up-ramps and from 0.13 to 0.25 for down-ramps.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.85-88
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• 2008

Damage from typhoon disaster can be mitigated by grasping and dealing with the damage promptly for the regions in typhoon track. What is this work, a technique to analyzed dangerousness of typhoon should be presupposed. This study estimated 10m level wind speed using 700hPa wind by typhoon, referring to GPS dropwindsonde study of Franklin(2003). For 700hPa wind, 30km resolution data of Regional Data Assimilation Prediction System(RDAPS) were used. For roughness length in estimating wind of 10m level, landuse data of USGS are employed. For 10m level wind speed of Typhoon Rusa in 2002, we sampled AWS point of $7.4\sim30km$ distant from typhoon center and compare them with observational data. The results show that the 10m level wind speed is the estimation of maximum wind speed which can appear in surface by typhoon and it cannot be compared with general hourly observational data. Wind load on domestic buildings relies on probability distributions of extreme wind speed. Hence, calculated 10m level wind speed is useful for estimating the damage structure from typhoon.

• Journal of Environmental Science International
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• v.31 no.7
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• pp.617-635
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• 2022

The effect of coupled data assimilation (DA) on the meteorological prediction in the west coastal region of Korea was evaluated using a coupled atmosphere-ocean model (e.g., COAWST) in the spring (March 17-26) of 2019. We performed two sets of simulation experiments: (1) with the coupled DA (i.e., COAWST_DA) and (2) without the coupled DA (i.e., COAWST_BASE). Overall, compared with the COAWST_BASE simulation, the COAWST_DA simulation showed good agreement in the spatial and temporal variations of meteorological variables (sea surface temperature, air temperature, wind speed, and relative humidity) with those of the observations. In particular, the effect of the coupled DA on wind speed was greatly improved. This might be primarily due to the prediction improvement of the sea surface temperature resulting from the coupled DA in the study area. In addition, the improvement of meteorological prediction in COAWST_DA simulation was also confirmed by the comparative analysis between SST and other meteorological variables (sea surface wind speed and pressure variation).