• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.3
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• pp.29-39
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• 1992

We investigate a systematic design procedure of automatic rule generation of fuzzy logic based controllers for highly nonlinear dynamic systems such as an engine dynamic modle. By "automatic rule generation" we mean autonomous clustering or collection of such meaningful transitional relations from one conditional subspace to another. During the design procedure, we also consider optimaly control strategies such as minimum squared error, near minimum time, minimum energy or combined performance critiera. Fuzzy feedback control systems designed by our method have the properties of closed-loop stability, robustness under parameter variabitions, and a certain degree of optimality. Most of all, the main advantage of the proposed approach is that reliability can be potentially increased even if a large grain of uncertainty is involved within the control system under consideration. A numerical example is shown in which we apply our strategic fuzzy controller dwsign to a highly nonlinear model of engine idling speed control.d control.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.244-244
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• 2023

Both the frequency and the magnitude of hydrometeorological extreme events such as severe floods and droughts are increasing. In order to prevent a damage from the climatic disaster, hydrological models are often simulated under various meteorological conditions. While performing the simulations, a synthetic data generated through time series models which maintains the key statistical characteristics of the sample data are widely applied. However, the synthetic data can easily maintains both the average and the variance of the sample data, but the quantile is not maintained well. In this study, we proposes a data generation method which maintains the quantile of the sample data well. The equations of the former maintenance of variance extension (MOVE) are expanded to maintain quantile rather than the average or the variance of the sample data. The equations are derived and the coefficients are determined based on the characteristics of the sample data that we aim to preserve. Monte Carlo simulation is utilized to assess the performance of the proposed data generation method. A time series data (data length of 500) is regarded as the sample data and selected randomly from the sample data to create the data set (data length of 30) for simulation. Data length of the selected data set is expanded from 30 to 500 by using the proposed method. Then, the average, the variance, and the quantile difference between the sample data, and the expanded data are evaluated with relative root mean square error for each simulation. As a result of the simulation, each equation which is designed to maintain the characteristic of data performs well. Moreover, expanded data can preserve the quantile of sample data more precisely than that those expanded through the conventional time series model.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.406-418
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• 2020

In this study, a nonlinear wave simulation code is developed using a higher-order spectral (HOS) method. The HOS method is very efficient because it can determine the solution of the boundary value problem using fast Fourier transform (FFT) without matrix operation. Based on the HOS order, the vertical velocity of the free surface boundary was estimated and applied to the nonlinear free surface boundary condition. Time integration was carried out using the fourth order Runge-Kutta method, which is known to be stable for nonlinear free-surface problems. Numerical stability against the aliasing effect was guaranteed by using the zero-padding method. In addition to simulating the initial wave field distribution, a nonlinear adjusted region for wave generation and a damping region for wave absorption were introduced for wave generation simulation. To validate the developed simulation code, the adjusted simulation was carried out and its results were compared to the eighth order Stokes theory. Long-time simulations were carried out on the irregular wave field distribution, and nonlinear wave propagation characteristics were observed from the results of the simulations. Nonlinear adjusted and damping regions were introduced to implement a numerical wave tank that successfully generated nonlinear regular waves. According to the variation in the mean wave steepness, irregular wave simulations were carried out in the numerical wave tank. The simulation results indicated an increase in the nonlinear interaction between the wave components, which was numerically verified as the mean wave steepness. The results of this study demonstrate that the HOS method is an accurate and efficient method for predicting the nonlinear interaction between waves, which increases with wave steepness.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.335-346
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• 2016

This study produced the parameter maps of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall generation model across South Korea and developed and validated the web application that automates the process of rainfall generation based on the produced parameter maps. To achieve this purpose, three deferent sets of parameters of the MBLRP model were estimated at 62 ground gage locations in South Korea depending on the distinct purpose of the synthetic rainfall time series to be used in hydrologic modeling (i.e. flood modeling, runoff modeling, and general purpose). The estimated parameters were spatially interpolated using the Ordinary Kriging method to produce the parameter maps across South Korea. Then, a web application has been developed to automate the process of synthetic rainfall generation based on the parameter maps. For validation, the synthetic rainfall time series has been created using the web application and then various rainfall statistics including mean, variance, autocorrelation, probability of zero rainfall, extreme rainfall, extreme flood, and runoff depth were calculated, then these values were compared to the ones based on the observed rainfall time series. The mean, variance, autocorrelation, and probability of zero rainfall of the synthetic rainfall were similar to the ones of the observed rainfall while the extreme rainfall and extreme flood value were smaller than the ones derived from the observed rainfall by the degree of 16%-40%. Lastly, the web application developed in this study automates the entire process of synthetic rainfall generation, so we expect the application to be used in a variety of hydrologic analysis needing rainfall data.

• Journal of Wind Energy
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• v.14 no.1
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• pp.37-43
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• 2023

In this study, synthetic time series wind data was generated numerically using a second-order Markov chain. One year of wind data in 2020 measured by the AWS on Wido Island was used to investigate the statistics for measured wind data. Both the transition probability matrix and the cumulative transition probability matrix for annual hourly mean wind speed were obtained through statistical analysis. Probability density distribution along the wind speed and autocorrelation according to time were compared with the first- and the second-order Markov chains with various lengths of time series wind data. Probability density distributions for measured wind data and synthetic wind data using the first- and the second-order Markov chains were also compared to each other. For the case of the second-order Markov chain, some improvement of the autocorrelation was verified. It turns out that the autocorrelation converges to zero according to increasing the wind speed when the data size is sufficiently large. The generation of artificial wind data is expected to be useful as input data for virtual digital twin wind turbines.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.107-117
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• 2005

A distributed hardware-in-the-loop simulation (HILS) platform is developed for designing an automotive engine control system. The HILS equipment consists of a widely used PC and commercial-off-the-shelf (COTS) I/O boards instead of a powerful computing system and custom-made I/O boards. The distributed structure of the HILS system supplements the lack of computing power. These features make the HILS equipment more cost-effective and flexible. The HILS uses an automatic code generation extension, REAL-TIME WORKSHOP$^{ (RTW$^{) of MATLAB$^{ tool-chain and RT-LAB$^{, which enables distributed simulation as well as the detection and generation of digital event between simulation time steps. The mean value engine model, which is used in control design phase, is imported into this HILS. The engine model is supplemented with some I/O subsystems and I/O boards to interface actual input and output signals in real-time. The I/O subsystems are designed to imitate real sensor signals with high fidelity as well as to convert the raw data of the I/O boards to the appropriate forms for proper interfaces. A lot of attention is paid to the generation of a precise crank/ earn signal which has the problem of quantization in a conventional fixed time step simulation. The detection of injection! command signal which occurs between simulation time steps are also successfully compensated. In order to prove the feasibility of the proposed environment, a simple PI controller for an air-to-fuel ratio (AFR) control is used. The proposed HILS environment and I/O systems are shown to be an efficient tool to develop various control functions and to validate the software and hardware of the engine control system.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.611-622
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• 2018

Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.

• Wind and Structures
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• v.38 no.2
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• pp.129-146
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• 2024

Aiming at the problem of non-stationary wind field simulation of downbursts, a non-stationary down-burst generation system was designed by adding a nozzle and program control valve to the inlet of the original wall jet model. The computational fluid dynamics (CFD) method was used to simulate the downburst. Firstly, the two-dimensional (2D) model was used to study the outflow situation, and the database of working conditions was formed. Then the combined superposition of working conditions was carried out to simulate the full-scale measured downburst. The three-dimensional (3D) large eddy simulation (LES) was used for further verification based on this superposition condition. Finally, the wind tunnel test is used to further verify. The results show that after the valve is opened, the wind ve-locity at low altitude increases rapidly, then stays stable, and the wind velocity at each point fluctuates. The velocity of the 2D model matches the wind velocity trend of the measured downburst well. The 3D model matches the measured downburst flow in terms of wind velocity and pulsation characteris-tics. The time-varying mean wind velocity of the wind tunnel test is in better agreement with the meas-ured time-varying mean wind velocity of the downburst. The power spectrum of fluctuating wind ve-locity at different vertical heights for the test condition also agrees well with the von Karman spectrum, and conforms to the "-5/3" law. The vertical profile of the maximum time-varying average wind veloci-ty obtained from the test shows the basic characteristics of the typical wind profile of the downburst. The effectiveness of the downburst generation system is verified.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.2
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• pp.108-113
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• 2021

Detrimental effects of inbreeding have been studied by many researchers for a long time. However, only a few studies have shown the occurrence of inbreeding depression due to evolutionary changes as a purging process. In this study, two different populations (inbreeding and outbreeding) of Drosophila melanogaster were compared to assess inbreeding effects on artificial population bottlenecks. For inbreeding conditions, a couple of D. melanogaster (one virgin and one male) were selected from an inbred population and cultured in a vial. For outbreeding conditions, a couple of D. melanogaster were selected from different populations and cultured in a vial. There were significant differences in body lengths of adults, but not in other parameters such as the total number of adults, the rate of survival, and the rate of wing mutants. The mean body length of adults of outbreeding populations was longer than that of inbreeding populations in the first generation (G1; P = 0.004), but not in the second generation (G2; P = 0.066). Although the other three parameters (total number of adults, rate of survival, and rate of wing mutants) showed differences in their mean values between inbreeding and outbreeding populations, these differences were not statistically significant. This might be due to genetic purging. This study demonstrated one additional experimental case related to inbreeding depression in artificial bottlenecked populations. Further studies are necessary to confirm the clear interaction between inbreeding depression and genetic purging using more generations and replicates (or samples) of D. melanogaster.

• Atmosphere
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• v.18 no.3
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• pp.171-182
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• 2008

In this study, we analyzed the spatial and temporal distribution of wind resources over Korea based on hourly observational data recorded over a period of 5 years from 457 stations belonging to Korea Meteorological Administration (KMA). The surface and 850 hPa wind data obtained from the Korea Local Analysis and Prediction System (KLAPS) and the Regional Data Assimilation and Prediction System (RDAPS) over a period of 1 year are used as supplementary data sources. Wind speed is generally high over seashores, mountains, and islands. In 62 (13.5%) stations, mean wind speeds for 5 years are greater than $3ms^{-1}$. The effects of seasonal wind, land-sea breeze, and mountain-valley winds on wind resources over Korea are evaluated as follows: First, wind is weak during summer, particularly over the Sobaek Mountains. However, over the coastal region of the Gyeongnam-province, strong southwesterly winds are observed during summer owing to monsoon currents. Second, the wind speed decreases during night-time, particularly over the west coast, where the direction of the land breeze is opposite to that of the large-scale westerlies. Third, winds are not always strong over seashores and highly elevated areas. The wind speed is weaker over the seashore of the Gyeonggi-province than over the other seashores. High wind speed has been observed only at 5 stations out of the 22 high-altitude stations. Detailed information on the wind resources conditions at the 21 stations (15 inland stations and 6 island stations) with high wind speed in Korea, such as the mean wind speed, frequency of wind speed available (WSA) for electricity generation, shape and scale parameters of Weibull distribution, constancy of wind direction, and wind power density (WPD), have also been provided. Among total stations in Korea, the best possible wind resources for electricity generation are available at Gosan in Jeju Island (mean wind speed: $7.77ms^{-1}$, WSA: 92.6%, WPD: $683.9Wm^{-2}$) and at Mt. Gudeok in Busan (mean wind speed: $5.66ms^{-1}$, WSA: 91.0%, WPD: $215.7Wm^{-2}$).