• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.52-59
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• 1999

Vegetation canopy plays an important role in $CO_2$/$H_2$O exchange between the biosphere and the atmosphere by controlling leaf stomata. In this study, rice (Oryza sativa L.), a staple crop in Asia was investigated to formulate its single leaf model of photosynthesis and stomatal conductance. Photosynthesis and stomatal conductance were measured with a portable infrared gas analyzer system. Other plant and meteorological variables were also measured. To evaluate empirical constants in this biochemical leaf model, nonlinear least squares technique was used. The maximum catalytic activity of enzyme and the maximum rate of electron transport were $ 100\mu$㏖ $m^{-2}$ $s^{-1}$ and $140 \mu$㏖ m$^{-2}$ s$^{-1}$ (@ 35$^{\circ}C$), respectively. The empirical constants, m and b, associated with stomatal conductance model were 9.7 and $0.06 m^{-2}$ $s^{-1}$ , respectively. On a leaf scale, agreements between the modeled and the measured values of photosynthesis and stomatal conductance were on average within 20%, and the simulation of diurnal variation was also satisfactory On a canopy scale, the Simple Biosphere model(SiB2) was tested using the derived parameters. The modeled energy fluxes were compared against the micrometeorologically measured fluxes over a rice canopy. Agreements between the modeled and the measured values of net radiation, sensible heat and latent heat fluxes, and $CO_2$ flux (i.e., net canopy photosynthesis) were on average within 25%.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.3-12
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• 1996

Sliding mode controller(SMC) is a simple but powerful nonlinear controller, because it guarantees the stability and the robustness. However, it leads to the high frequency chattering of the control input. Although the phenomenon can be avoided by introducing a thin boundary layer to the sliding surface, the method results in a steady state: error proportional to the boundary layer thickness. In this paper, we proposed a new sliding mode controller with self-tuning the thickness of a boundary layer. It uses a fuzzy rule base for tuning the thickness of a boundary layer. That is, the thickness is increased to some degree to reject a discontinuous control input at the initial state and then it is decreased as the states approaches to the steady states for improving the tracking performance. In order to assure the control performance, we perf'ormed the computer simulation using an inverted pendulum system as a controlled plant.

• Journal of the Korea Concrete Institute
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• v.27 no.2
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• pp.169-176
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• 2015

Since the size effect law announced currently has been based on the normal weight concrete, for light weight concrete having different fracture characteristics, its application is questionable. Accordingly, in this study, a model equation to predict the effect of dried unit weight of the concrete on size effect of its compressive strength was developed and a database using existing research results was created. After determining the experimental constants of prediction models of Ba${\check{z}}$ant based on nonlinear fracture mechanics, Kim and Eo, and this study using the database, their results are mutually compared. Finally, it was found that the prediction model of this study considered dried unit weight of concrete predicted well the test results for light weight concrete than that of the models of Ba${\check{z}}$ant and Kim and Eo.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.151-157
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• 2013

This paper proposes an online adaptive fuzzy controller for a wind energy conversion system (WECS) that is intrinsically highly nonlinear plant. In real application, to obtain exact system parameters such as power coefficient, many measuring instruments and off-line implementations are required, which is very difficult to perform. This shortcoming can be avoided by introducing fuzzy system in the controller design in this paper. The proposed adaptive fuzzy control scheme using self-structuring algorithm requires no system parameters to meet control objectives. Even the structure of the fuzzy system is automatically grows on-line, which distinguishes our proposed algorithm over the previously proposed fuzzy control schemes. Combining derivative estimator for wind velocity, the whole closed-loop system is shown to be stable in the sense of Lyapunov.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.21-25
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• 2002

Activated sludge processes are widely used in biological wastewater treatment processes. The main motivation of this research is to develop an intelligent control strategy for activated sludge process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent rate, weather conditions, and so on. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP model based on Matlab/Simulink is designed in this paper. The performance of the model is tested by IWA (International Water Association) and COST (European Cooperation in the filed of Scientific and Technical Research) data that include steady-state results during 14 days. In this paper, fuzzy logic control approach is applied to control the DO (dissolved oxygen) concentration. The fuzzy logic controller that includes two inputs and one output can adjust air flowrate. Also, this paper introduces the remote monitoring and control system that is applied for the CSTR (Continuously Stirred Tank Reactor) wastewater treatment system. The CSTR plant has a local control and the remote monitoring system which is contained communication parts which consist of LAN (Local Area Network) network and CDMA (Code Division Multiple Access) wireless module. Remote control and monitoring systems are constructed in the laboratory.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.3
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• pp.245-259
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• 1994

This paper is concerned with the development of a three-dimensional numerical model for coastal circulation and heat transport with improved prediction ability. The model uses fully nonlinear, time-dependent three-dimensional, $\sigma$-transformed equations of motion and equation of heat transport The model was verified with experimental data for wind-driven current in a one-dimensional channel and thermal jets flowing into stagnant waters and applied for unsteady flow induced by tide and thermal jets in coastal waters around Kori nuclear power plant. The model results were in good agreements with experimental data sets for wind-driven current and thermal jet, and field observed data sets in coastal waters. This study has shown that the $\kappa$-$\varepsilon$ turbulence model is applicable to various coastal conditions without any modification of turbulence constants.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.862-870
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• 2011

In this paper, we introduce a new topology of Radial Basis Function-based Polynomial Neural Networks (RPNN) that is based on a genetically optimized multi-layer perceptron with Radial Polynomial Neurons (RPNs). This study offers a comprehensive design methodology involving mechanisms of optimization algorithms, especially Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization (PSO) algorithms. In contrast to the typical architectures encountered in Polynomial Neural Networks (PNNs), our main objective is to develop a design strategy of RPNNs as follows : (a) The architecture of the proposed network consists of Radial Polynomial Neurons (RPNs). In here, the RPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Fuzzy C-Means (FCM) clustering method. The RPN dwells on the concepts of a collection of radial basis function and the function-based nonlinear (polynomial) processing. (b) The PSO-based design procedure being applied at each layer of RPNN leads to the selection of preferred nodes of the network (RPNs) whose local characteristics (such as the number of input variables, a collection of the specific subset of input variables, the order of the polynomial, and the number of clusters as well as a fuzzification coefficient in the FCM clustering) can be easily adjusted. The performance of the RPNN is quantified through the experimentation where we use a number of modeling benchmarks - NOx emission process data of gas turbine power plant and learning machine data(Automobile Miles Per Gallon Data) already experimented with in fuzzy or neurofuzzy modeling. A comparative analysis reveals that the proposed RPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of the Earthquake Engineering Society of Korea
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• v.26 no.1
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• pp.13-22
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• 2022

This study proposes a low-cycle fatigue life derived from measurement points on pipe elbows, which are components that are vulnerable to seismic load in the interface piping systems of nuclear power plants that use seismic isolation systems. In order to quantitatively define limit states regarding leakage, i.e., actual failure caused by low-cycle fatigue, in-plane cyclic loading tests were performed using a sine wave of constant amplitude. The test specimens consisted of SCH40 6-inch carbon steel pipe elbows and straight pipes, and an image processing method was used to measure the nonlinear behavior of the test specimens. The leakage lines caused by low-cycle fatigue and the low-cycle fatigue curves were compared and analyzed using the relationship between the relative deformation angles, which were measured based on each of the measurement points on the straight pipe, and the moment, which was measured at the center of the pipe elbow. Damage indices based on the combination of ductility and dissipation energy at each measurement point were used to quantitatively express the time at which leakage occurs due to through-wall cracking in the pipe elbow.

• Korean journal of applied entomology
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• v.55 no.2
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• pp.149-160
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• 2016

Temperature-dependent development and fecundity of apterious Rhopalosiphum padi (L.) (Hemiptera: Aphididae) were examined at six constant temperatures (10, 15, 20, 25, 30 and $35{\pm}1.0^{\circ}C$, RH 50-70%, 16L:8D). Development time of nymphs decreased with increasing temperature and ranged from 42.9 days at $10^{\circ}C$ to 4.7 days at $30^{\circ}C$. The nymphs did not develop until adult at $35^{\circ}C$ because the nymphs died during the 2nd instar. The lower threshold temperature and thermal constant of nymph were estimated as $8.3^{\circ}C$ and 101.6 degree days, respectively. The relationships between development rates of nymph and temperatures were well described by the nonlinear model of Lactin 2. The distribution of development times of each stage was successfully fitted to the Weibull function. The longevity of apterious adults decreased with increasing temperature ranging from 24.0 days at $15^{\circ}C$ to 4.3 days at $30^{\circ}C$, with abnormally short longevity of 11.1 days at $10^{\circ}C$. R. padi showed the highest fecundity at $20^{\circ}C$ (38.2) and the lowest fecundity at $10^{\circ}C$ (3.9). In this study, we provided component sub-models for the oviposition model of R. padi: total fecundity, age-specific cumulative oviposition rate, and age-specific survival rate as well as adult aging rate based on the adult physiological age.

• Korean journal of applied entomology
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• v.55 no.2
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• pp.119-128
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• 2016

This study was conducted to develop temperature-driven models for a population model of turnip aphid, Lipaphis erysimi: nymphal development rate models and apterious adult's oviposition (larviparous) model. Nymphal development and the longevity and fecundity of adults were examined on cabbage at six constant temperatures (10, 15, 20, 25, 30, $35{\pm}1^{\circ}C$, 16L:8D). L. erysimi nymphs did not survive at $10^{\circ}C$. Development time of nymphs increased with increasing temperature up to $30^{\circ}C$ and thereafter slightly decreased, ranging from 18.5 d at $15^{\circ}C$ to 5.9 d at $30^{\circ}C$. The lower threshold temperature and thermal constant were estimated as $7.9^{\circ}C$ and 126.3 degree days, respectively. The nonlinear model of Lactin 2 fitted well for the relationship between the development rate and temperature of small (1+2 instar), large (3+4 instar) and total nymph (all instars). The Weibull function provided a good fit for the distribution of development times of each stage. Temperature affected the longevity and fecundity of L. erysimi. Adult longevity decreased as the temperature increased and ranged from 24.4 d at $20^{\circ}C$ to 16.4 d at $30.0^{\circ}C$ with abnormal longevity 18.2 d at $15^{\circ}C$, which was used to estimate adult aging rate model for the calculation of adult physiological age. L. erysimi showed a maximum fecundity of 91.6 eggs per female at $20^{\circ}C$. In this study, we provided three temperature-dependent components for an oviposition model of L. erysimi: total fecundity, age-specific cumulative oviposition rate, and age-specific survival rate.