• Wind and Structures
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• v.13 no.3
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• pp.293-307
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• 2010

This paper describes a new method for the estimation of six complex aerodynamic admittance functions. The aerodynamic admittance functions relate buffeting forces to the incoming wind turbulent components, of which the estimation accuracy affects the prediction accuracy of the buffeting response of long-span bridges. There should be two aerodynamic admittance functions corresponding to the longitudinal and vertical turbulent components, respectively, for each gust buffeting force. Therefore, there are six aerodynamic admittance functions in all for the three buffeting forces. Sears function is a complex theoretical expression for the aerodynamic admittance function for a thin airfoil. Similarly, the aerodynamic admittance functions for a bridge deck should also be complex functions. This paper presents a separated frequency-by-frequency method for estimating the six complex aerodynamic admittance functions. A new experimental methodology using an active turbulence generator is developed to measure simultaneously all the six complex aerodynamic admittance functions. Wind tunnel tests of a thin plate model and a streamlined bridge section model are conducted in turbulent flow. The six complex aerodynamic admittance functions, determined by the developed methodology are compared with the Sears functions and Davenport's formula.

• Journal of Advanced Research in Ocean Engineering
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• v.2 no.4
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• pp.179-191
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• 2016

As the demand for renewable energy has increased following the worldwide agreement to act against global climate change and disaster, large-scale floating offshore wind systems have become a more viable solution. However, the cost of the whole system is still too high for practical realization. To make the cost of a floating wind system be more economical, a new concept of tension leg platform (TLP) type ocean floating wind system has been developed. To verify the performance of a 5-MW TLP type ocean floating wind power system designed by the Korea Advanced Institute of Science and Technology, the FAST simulation developed by the National Renewable Energy Laboratory is used. Further, 1/50 scale model tests have been carried out in the ocean engineering tank of the Research Institute of Medium and Small Shipbuilding, Korea. This paper compares the simulation and ocean engineering tank test results on motion prediction and tension assessment of the TLP anchor.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.667-674
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• 2013

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. This paper presents a new approach to coordination of battery energy storage in wind generation system for reducing the payment in frequency control market. The approach depends on the statistic data of wind generation and the prediction of frequency control market price to determine the optimal variation band which is then kept by the real-time charging and discharging of batteries, ultimately the minimum cost of frequency regulation can be obtained. The optimization problem is formulated as trade-off between the decrease in the regulation payment and the increase in the cost of using battery, and vice versus. The approach is applied to a study case and the results of simulation show its effectiveness.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.393-405
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• 2023

Accurate prediction of wind speed and power is vital for enhancing the efficiency of wind energy systems. Numerous solutions have been implemented to date, demonstrating their potential to improve forecasting. Among these, deep learning is perceived as a revolutionary approach in the field. However, despite their effectiveness, the noise present in the collected data remains a significant challenge. This noise has the potential to diminish the performance of these algorithms, leading to inaccurate predictions. In response to this, this study explores a novel feature engineering approach. This approach involves altering the data input shape in both Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) and Autoregressive models for various forecasting horizons. The results reveal substantial enhancements in model resilience against noise resulting from step increases in data. The approach could achieve an impressive 83% accuracy in predicting unseen data up to the 24th steps. Furthermore, this method consistently provides high accuracy for short, mid, and long-term forecasts, outperforming the performance of individual models. These findings pave the way for further research on noise reduction strategies at different forecasting horizons through shape-wise feature engineering.

• Wind and Structures
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• v.13 no.1
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• pp.57-82
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• 2010

The 486m-long roof of Shenzhen Citizens Centre is one of the world's longest spatial lattice roof structures. A comprehensive numerical study of wind effects on the long-span structure is presented in this paper. The discretizing and synthesizing of random flow generation technique (DSRFG) recently proposed by two of the authors (Huang and Li 2008) was adopted to produce a spatially correlated turbulent inflow field for the simulation study. The distributions and characteristics of wind loads on the roof were numerically evaluated by Computational Fluid Dynamics (CFD) methods, in which Large Eddy Simulation (LES) and Reynolds Averaged Navier-Stokes Equations (RANS) Model were employed. The main objective of this study is to explore a useful approach for estimations of wind effects on complex curved roof by CFD techniques. In parallel with the numerical investigation, simultaneous pressure measurements on the entire roof were made in a boundary layer wind tunnel to determine mean, fluctuating and peak pressure coefficient distributions, and spectra, spatial correlation coefficients and probability characteristics of pressure fluctuations. Numerical results were then compared with these experimentally determined data for validating the numerical methods. The comparative study demonstrated that the LES integrated with the DSRFG technique could provide satisfactory prediction of wind effects on the long-span roof with complex shape, especially on separation zones along leading eaves where the worst negative wind-induced pressures commonly occur. The recommended LES and inflow turbulence generation technique as well as associated numerical treatments are useful for structural engineers to assess wind effects on a long-span roof at its design stage.

• Journal of the Korean earth science society
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• v.26 no.1
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• pp.66-77
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• 2005

Aerological observation at Heuksando located in south-western part of Koran Peninsula has been started at 1 June 2003. In order to clarify the improvement of meteorological prediction quality. it is necessary to compare between aerological data observed at Gawngju and Heuksando and to make clear the influence of Heuksando data assimilation. Therefore numerical simulations were carried out with High resolution meterological prediction system based on MM5(The 5th Generation Mesoscale Model). The pattern of wind and temperature field observed at Heuksando and Gwangju are different due to land surface friction End Sensible heat flux at surface and the wind field Simulated With Gwangju and Heuksando aerological data agree well with observation wind field. Although the amount of precipitation in these experiments is underestimated. the area and starting time of precipitation around Honam province in case with Heuksando data is more reliable that without the data.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.80-83
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• 2008

The characteristics of the spread of a forest fire are generally related to the attributes of combustibles, geographical features, and meteorological conditions, such as wind conditions. The most common methodology used to create a prediction model for the spread of forest fires, based on the numerical analysis of the development stages of a forest fire, is an analysis of heat energy transmission by the stage of heat transmission. When a forest fire breaks out, the analysis of the transmission velocity of heat energy is quantifiable by the spread velocity of flame movement through a physical and chemical analysis at every stage of the fire development from flame production and heat transmission to its termination. In this study, the formula used for the 1-dimensional surface forest fire behavior prediction model, derived from a numerical analysis of the surface flame spread rate of solid combustibles, is introduced. The formula for the 1-dimensional surface forest fire behavior prediction model is the estimated equation of the flame spread velocity, depending on the condition of wind velocity on the ground. Experimental and theoretical equations on flame duration, flame height, flame temperature, ignition temperature of surface fuels, etc., has been applied to the device of this formula. As a result of a comparison between the ROS(rate of spread) from this formula and ROSs from various equations of other models or experimental values, a trend suggesting an increasing curved line of the exponent function under 3m/s or less wind velocity condition was identified. As a result of a comparison between experimental values and numerically analyzed values for fallen pine tree leaves, the flame spread velocity reveals has a error of less than 20%.

• Ocean and Polar Research
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• v.31 no.4
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• pp.369-377
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• 2009

Performance of the Korea Ocean Research and Development Institute (KORDI) operational storm surge prediction system for the Korean coast is presented here. Results for storm surge hindcasts and forecasts calculations were analyzed. The KORDI storm surge system consists of two important components. The first component is atmospheric models, based on US Army Corps of Engineers (CE) wind model and the Weather Research and Forecasting (WRF) model, and the second components is the KORDI-storm surge model (KORDI-S). The atmospheric inputs are calculated by the CE wind model for typhoon period and by the WRF model for non-typhoon period. The KORDI-S calculates the storm surges using the atmospheric inputs and has 3-step nesting grids with the smallest horizontal resolution of ${\sim}$300 m. The system runs twice daily for a 72-hour storm surge prediction. It successfully reproduced storm surge signals around the Korean Peninsula for a selection of four major typhoons, which recorded the maximum storm surge heights ranging from 104 to 212 cm. The operational capability of this system was tested for forecasts of Typhoon Nari in 2007 and a low-pressure event on August 27, 2009. This system responded correctly to the given typhoon information for Typhoon Nari. In particular, for the low-pressure event the system warned of storm surge occurrence approximately 68 hours ahead.

• Journal of computational fluids engineering
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• v.11 no.3 s.34
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• pp.59-63
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• 2006

Accurate prediction of a supersonic missile base drag continues to defy even well-rounded CFD codes. In an effort to address the accuracy and predictability of the base drags, the influence of grid system and competitive turbulence models on the base drag is analyzed. Characteristics of some turbulence models is reviewed through incompressible turbulent flow over a flat plate, and performance for the base drag prediction of several turbulence models such as Baldwin-Loman(B-L), Spalart-Allmaras(S-A), k-$\varepsilon$, k-$\omega$ model is assessed. When compressibility correction is injected into the S-A model, prediction accuracy of the base drag is enhanced. The NSWC wind tunnel test data are utilized for comparison of CFD and semi-empirical codes on the accuracy of base drag predictability: they are about equal, but CFD tends to perform better. It is also found that, as angle of attack of a missile with control fins increases, even the best CFD analysis tool we have lacks the accuracy needed for the base drag prediction.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.4
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• pp.45-55
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• 2003

Weather conditions have played a vital role in a war. Many historical records reported that the miss use of weather information is the main reason of the lost a war. In this study we demonstrated the possibility of applying the numerical weather prediction system(NWPS) for military operations. The NWPS consists of PC-cluster as a super computer, data assimilation system ingesting many remote sensing observation, and graphic systems. High resolution prediction in NWPS can provide useful weather information such as wind, temperature, sea fog and so on for military operations.