• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.142-145
• /
• 2006

The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the NOAA HWind wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

• Wind and Structures
• /
• v.9 no.5
• /
• pp.397-412
• /
• 2006

This paper presents the wind excited acceleration responses of a 50 m guyed mast under the action of Typhoon Dujuan. The response of the structure is reconstructed from using a full finite element model and an equivalent beam-column model. The wind load is modelled based on the measured wind speed and recommendations for high-rise structures. The nonlinear time response analysis is conducted using the Newton Raphson iteration procedure. Comparative studies on the measured and computed frequencies and acceleration responses show that the torsional vibration of the structure is significant particularly in the higher vibration modes after the first few bending modes. The equivalent model, in general, gives less accurate amplitude predictions than the full model because of the omission of torsional stiffness of the mast in the vibration analysis, but the root-mean-square value is close to the measured value in general with an error of less than 10%.

• Asian Journal of Atmospheric Environment
• /
• v.5 no.1
• /
• pp.1-7
• /
• 2011

This study assesses the dispersion and emission rates of odor form industrial area source. CALPUFF and AERMOD Gaussian models were used for predicting downwind odor concentration and calculating odor emission rates. The studied region was Seobu industrial complex in Korea. Odor samples were collected five days over a year period in 2006. In-site meteorological data (wind direction and wind speed) were used to predict concentration. The BOOT statistical examination software was used to analyze the data. Comparison between the predicted and field sampled downwind concentration using BOOT analysis indicates that the CALPUFF model prediction is a little better than AERMOD prediction for average downwind odor concentrations. Predicted concentrations of AERMOD model have a little larger scatter than that of CALPUFF model. The results also show odor emission rates of Seobu industrial complex area were an order of 10 smaller than that of beef cattle feed lots.

• Wind and Structures
• /
• v.18 no.5
• /
• pp.549-566
• /
• 2014

In spite of progress in the numerical simulation of typhoon wind field in atmospheric boundary layer (ABL), using typhoon wind field model in conjunction with Monte Carlo simulation method can only accurately evaluate typhoon wind field over a general terrain. This method is not enough for a reliable evaluation of typhoon wind field over the actual complex terrain with surface roughness and topography variations. To predict typhoon wind field over the actual complex terrain in ABL, a hybrid numerical simulation method combined typhoon simulation used the typhoon wind field model proposed by Meng et al. (1995) and CFD simulation in which the Reynolds averaged Navier-Stokes (RANS) equations and k-${\varepsilon}$ turbulence model are used. Typhoon wind filed during typhoon Dujuan and Imbudo are simulated using the hybrid numerical simulation method, and compared with the results predicted by the typhoon wind field model and the wind field measurement data collected by Fugro Geotechnical Services (FGS) in Hong Kong at the bridge site from the field monitoring system of wind turbulence parameters (FMS-WTP) to validate the feasibility and accuracy of the hybrid numerical simulation method. The comparison demonstrates that the hybrid numerical simulation method gives more accurate prediction to typhoon wind speed and direction, because the effect of topography is taken into account in the hybrid numerical simulation method.

• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.3
• /
• pp.219-228
• /
• 1998

In the present investigation, a numerical model developed for the prediction of the wind flow over complex terrain is validated by comparing with the field experiments. For the solution of the Reynolds - Averaged Clavier- stokes equations which are the governing equations of the microscale atmospheric flow, the model is constructed based on the finite-volume formulation and the SIMPLEC pressure-correction algorithm for the hydrodynamic computation. The boundary- fitted coordinate system is employed for the detailed depiction of topography. The boundary conditions and the modified turbulence constants suitable for an atmospheric boundary- layer are applied together with the k- s turbulence model. The full- scale experiments of Cooper's Ridge, Kettles Hill and Askervein Hill are chosen as the validation cases . Comparisons of the mean flow field between the field measurements and the predicted results show good agreement. In the simulation of the wind flow over Askervein Hill , the numerical model predicts the three dimensional flow separation in the downslope of the hill including the blockage effect due to neighboring hills . Such a flow behavior has not been simulated by the theoretical predictions. Therefore, the present model may offer the most accurate prediction of flow behavior in the leeside of the hill among the existing theoretical and numerical predictions.

• Journal of Environmental Science International
• /
• v.18 no.8
• /
• pp.885-897
• /
• 2009

In order to make sure the impact of spatial resolution of wind energy map on the estimation of wind power density in the Korean Peninsula, the comparison studies on the characteristics of wind energy map with three different spatial resolutions were carried out. Numerical model used in the establishment of wind map is MM5 (5th generation Mesoscale Model) with RBAPS (Regional Data Assimilation and Prediction System) as initial and boundary data. Analyzed Period are four months (March, August, October, and December), which are representative of four seasons. Since high spatial resolution of wind map make the undulation of topography be clear, wind pattern in high resolution wind map is correspond well with topography pattern and maximum value of wind speed is also increase. Indication of island and mountains in wind energy map depends on the its spatial resolution, so wind patterns in Heuksan island and Jiri mountains are clearly different in high and low resolutions. And area averaged power density can be changed by estimation method of wind speed for unit area in the numerical model and by treatment of air density. Therefore the studiable resolution for the topography should be evaluated and set before the estimation of wind resources in the Korean Peninsula.

• International Journal of Advanced Culture Technology
• /
• v.6 no.4
• /
• pp.190-194
• /
• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• Korean Journal of Agricultural Science
• /
• v.47 no.4
• /
• pp.1029-1037
• /
• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.49 no.3
• /
• pp.167-174
• /
• 2021

Computational Fluid Dynamics (CFD) was performed under low-speed wind tunnel test conditions using a 29.7% scale model of the NASA common research model. A wind tunnel test was conducted to measure the aerodynamic coefficient of the CRM with Belly sting model support configuration at a low Reynolds number of 0.3×106 and it was compared with the aerodynamic coefficient of CFD analysis. In order to verify the validation of the analysis, a computational analysis under the conditions of the advance research was performed and compared. The interference effect of the Belly sting model support affected not only the fuselage but also the main and tail wings.

• Plant Journal
• /
• v.17 no.4
• /
• pp.41-52
• /
• 2021

In this study, the PV output and module temperature values were predicted using the Meteorological Agency data and compared with actual data, weather, solar radiation, ambient temperature, and wind speed. The forecast accuracy by weather was the lowest in the data on a clear day, which had the most data of the day when it was snowing or the sun was hit at dawn. The predicted accuracy of the module temperature and the amount of power generation according to the amount of insolation decreased as the amount of insolation increased, and the predicted accuracy according to the ambient temperature decreased as the module temperature increased as the ambient temperature increased and the amount of power generated lowered the ambient temperature. As for wind speed, the predicted accuracy decreased as the wind speed increased for both module temperature and power generation, but it was difficult to define the correlation because wind speed was insignificant than the influence of other weather conditions.