• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.6
• /
• pp.39-47
• /
• 1998

A fourth-order $\Sigma$-$\Delta$ modulator is designed and implemented in 0.6 $\mu\textrm{m}$ CMOS technology. The modulator is verified by introducing nonlinear factors such as DC gain and slew rate in system model that determines the transfer function in S-domain and in time-domain. Dynamic range is more than 110 dB and the peak SM is 102.6 dB at a clock rate of 2.8224 MHz for voiceband signal. The structure of a ∑-$\Delta$ modulator is a modified fourth-order ∑-$\Delta$ modulator using direct feedback loop method, which improves performance and consumes less power. The transmission zero for noise is located in the first-second integrator loop, which reduces entire size of capacitors, reduces the active area of the chip, improves the performance, and reduces power dissipation. The system is stable because the output variation with respect to unit time is small compared with that of the third integrator. It is easy to implement because the size of the capacitor in the first integrator, and the size of the third integrator is small because we use the noise reduction technique. This paper represents a new design method by modeling that conceptually decides transfer function in S-domain and in Z-domain, determines the cutoff frequency of signal, maximizes signal power in each integrator, and decides optimal transmission-zero frequency for noise. The active area of the prototype chip is 5.25$\textrm{mm}^2$, and it dissipates 10 mW of power from a 5V supply.

• Journal of Korea Water Resources Association
• /
• v.41 no.8
• /
• pp.761-772
• /
• 2008

The object of this study is to develop the model that solves the numerically difficult problems in hydraulic engineering and to demonstrate the applicability of this model by means of various test examples, such as, verification in the gradually varied unsteady condition, three steady flow problems with the change of bottom slope with exact solution, and frictional bed with analytical solution. The governing equation of this model is the integral form of the Saint-Venant equation satisfying the conservation laws, and finite volume method with the Riemann solver is used. The evaluation of the mass and momentum flux with the HLL Riemann approximate solver is executed. MUSCL-Hancock scheme is used to achieve the second order accuracy in space and time. This study introduce the new and simple technique to discretize the source terms of gravity and hydrostatic pressure force due to longitudinal width variation for the balance of quantity between nonlinear flux and source terms. The results show that the developed model's implementation is accurate, robust and highly stable in various flow conditions with source terms, and this model is reliable for one-dimensional applications in hydraulic engineering.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.2
• /
• pp.325-333
• /
• 2016

This paper proposes controller design algorithms for a ceramic soldering iron temperature control system, and reports their effectiveness in a control experiment. Because the responses of the ceramic soldering iron temperature to the control input are non-linear and very slow, precise modeling and controller design is difficult. In this study, the temperature characteristics of a ceramic soldering iron are represented by TSK fuzzy models consisting of TSK fuzzy rules. In the fuzzy rules, the premise variable is the control input and the consequences are the transfer functions. The transfer functions in the fuzzy model were obtained from the step input responses. As the responses of the ceramic soldering iron temperature are very slow, it is difficult to obtain the complete step input responses. This paper proposes a genetic algorithm to obtain the transfer functions from an incomplete step input responses, and showed its effectiveness in examples. This paper also reports a fuzzy controller design method from the TSK fuzzy model and examples. The proposed methods were applied to the temperature control experiments of ceramic iron. The TSK fuzzy model consisted of 7 TSK fuzzy rules, and the consequences were PI controllers. The experimental results of the proposed fuzzy PI controller were superior to the linear controller and were as good as in previous studies using a fuzzy PID controller.

• Journal of Wetlands Research
• /
• v.18 no.3
• /
• pp.313-323
• /
• 2016

Water temperature affects physical and biological processes in ecologies on river system and is important conditions for growth rate and spawning of fish species. The objective of this study is to compare models for water temperature during the summer season for the Fourchue River (St-Alexandre-de-Kamouraska, Quebec, Canada). For this, three different models, which are CEQUEAU, Auto-regressive Moving Average with eXogenous input and Nonlinear Autoregressive with eXogenous input, were applied and compared. Also, future water temperature in the Fourchue river were simulated and analyzed its result based on the CMIP5 climate models, RCP 2.6, 4.5, 8.5 climate change scenarios. As the result of the study, the water temperature in the Fourchue river are actually changed and median water temperature will increase $0.2{\sim}0.7^{\circ}C$ in June and could decrease by $0.2{\sim}1.1^{\circ}C$ in September. Also, the UILT ($24.9^{\circ}C$) for brook trout are also likely to occurred for several days.

• Journal of the Korea Concrete Institute
• /
• v.24 no.2
• /
• pp.157-164
• /
• 2012

This study evaluates the shear performance of reinforced concrete beams with recycled coarse aggregates. A total of six specimens with various replacement ratios of recycled coarse aggregates (0%, 50%, and 100%) and different amount of shear reinforcement were cast and tested in this study. A finite element analysis was performed to predict the shear behavior of the specimens with natural or recycled coarse aggregates. The FE analysis was performed using a two-dimensional nonlinear FE analysis program based on the disturbed stress field model (DSFM), which is an extension of the modified compression field theory (MCFT). Experimental results showed that the specimens with 50% and 100% replacement ratios of recycled coarse aggregates had the similar shear strength compared to the specimen with natural aggregates, regardless of the replacement ratios of recycled coarse aggregates and the amount of the shear reinforcement. Furthermore, the comparison between experimental and analytical results showed that the proposed numerical modeling methods and the analytical model, DSFM, can be successfully used to predict the shear behavior of reinforced concrete beams with recycled coarse aggregates.

• Korean journal of applied entomology
• /
• v.35 no.2
• /
• pp.119-125
• /
• 1996

Temperature-dependent development study for overwintered eggs of Pseudococcus comstocki (Kuwana) wasconducted to develop a forecasting model for egg hatch date. Hatch times of overwintered eggs were comparedat five constant temperatures (10, 15, 20, 25, 27$^{\circ}$C) and different collection dates. A nonlinear, four-parameterdevelopmental model with high temperature inhibition accurately described (R2=0.9948) mean developmentalrates of all temperatures. Variation in developmental times was modeled(~~=0.972w9)it h a cumulative Weibullfunction. Least-squares linear regression (rate=O.O06358[Temp.]-0.07566)d escribed development in the linearregion (15-25$^{\circ}$C) of the development curve. The low development threshold temperature was estimated 11.9"Cand 154.14 degree-days were required for complete development. The linear degree-day model (thermal summation)and rate summation model (Wagner et al. 1985) were validated using field phenology data. In degreedaymodels, mean-minus-base method, sine wave method, and rectangle method were used in estimation of dailythermal units. Mean-minus-base method was 18 to 28d late, sine wave method was 11 to 14d late, rectanglemethod was 3 to 5d late, and rate summation model was 2 to 3d late in predicting 50% hatch of overwinteredeggs. hatch of overwintered eggs.

• Wind and Structures
• /
• v.30 no.4
• /
• pp.433-450
• /
• 2020

The strong turbulence characteristic of typhoon not only will significantly change flow field characteristics surrounding the large-scale wind turbine and aerodynamic force distribution on surface, but also may cause morphological evolution of coast dune and thereby form sand storms. A 5MW horizontal-axis wind turbine in a wind power plant of southeastern coastal areas in China was chosen to investigate the distribution law of additional loads caused by wind-sand coupling movement of coast dune at landing of strong typhoons. Firstly, a mesoscale Weather Research and Forecasting (WRF) mode was introduced in for high spatial resolution simulation of typhoon "Megi". Wind speed profile on the boundary layer of typhoon was gained through fitting based on nonlinear least squares and then it was integrated into the user-defined function (UDF) as an entry condition of small-scaled CFD numerical simulation. On this basis, a synchronous iterative modeling of wind field and sand particle combination was carried out by using a continuous phase and discrete phase. Influencing laws of typhoon and normal wind on moving characteristics of sand particles, equivalent pressure distribution mode of structural surface and characteristics of lift resistance coefficient were compared. Results demonstrated that: Compared with normal wind, mesoscale typhoon intensifies the 3D aerodynamic distribution mode on structural surface of wind turbine significantly. Different from wind loads, sand loads mainly impact on 30° ranges at two sides of the lower windward region on the tower. The ratio between sand loads and wind load reaches 3.937% and the maximum sand pressure coefficient is 0.09. The coupling impact effect of strong typhoon and large sand particles is more significant, in which the resistance coefficient of tower is increased by 9.80% to the maximum extent. The maximum resistance coefficient in typhoon field is 13.79% higher than that in the normal wind field.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.9
• /
• pp.1041-1050
• /
• 2011

An elasto-plastic finite element method using the theory of strain gradient plasticity is proposed to evaluate the size dependency of structural plasticity that occurs when the configuration size decreases to micron scale. For this method, we suggest a low-order plane and three-dimensional displacement-based elements, eliminating the need for a high order, many degrees of freedom, a mixed element, or super elements, which have been considered necessary in previous researches. The proposed method can be performed in the framework of nonlinear incremental analysis in which plastic strains are calculated and averaged at nodes. These strains are then interpolated and differentiated for gradient calculation. We adopted a strain-gradient-hardening constitutive equation from the Taylor dislocation model, which requires the plastic strain gradient. The developed finite elements are tested numerically on the basis of typical size-effect problems such as micro-bending, micro-torsion, and micro-voids. With respect to the strain gradient plasticity, i.e., the size effects, the results obtained by using the proposed method, which are simple in their calculation, are in good agreement with the experimental results cited in previously published papers.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.6
• /
• pp.349-357
• /
• 2019

Finite element method (FEM) is utilized in the development of products to realistically analyze and predict the mechanical behavior of materials in various fields. However, the approach based on the numerical analysis of glass fiber reinforced plastic (GFRP) composites, for which the fiber orientation and strain rate affect the mechanical properties, has proven to be challenging. The purpose of this study is to define and evaluate the mechanical properties of glass fiber reinforced plastic composites using the numerical analysis models of Digimat, a linear, nonlinear multi-scale modeling program for various composite materials such as polymers, rubber, metal, etc. In addition, the aim is to predict the behavior of realistic polymeric composites. In this regard, the tensile properties according to the fiber orientation and strain rate of polybutylene terephthalate (PBT) with short fiber weight fractions of 30wt% among various polymers were investigated using references. Information on the fiber orientation was calculated based on injection analysis using Moldflow software, and was utilized in the finite element model for tensile specimens via a mapping process. LS-Dyna, an explicit commercial finite element code, was used for coupled analysis using Digimat to study the tensile properties of composites according to the fiber orientation and strain rate of glass fibers. In addition, the drawbacks and advantages of LS-DYNA's various anisotropic material models were compared and evaluated for the analysis of glass fiber reinforced plastic composites.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.1
• /
• pp.9-14
• /
• 2004

Rational sense is affected by emotion. If we add the factor of estimated emotion by environment information into robots, we may get more intelligent and human-friendly robots. However, various sensory information and pattern classification are prescribed for robots to learn emotion so that the networks are suitable for the necessity of robots. Neural network has superior ability to extract character of system but neural network has defect of temporal cross talk and local minimum convergence. To solve the defects, many kinds of modular neural networks have been proposed because they divide a complex problem into simple several subproblems. The modular neural network, introduced by Jacobs and Jordan, shows an excellent ability of recomposition and recombination of complex work. On the other hand, the recurrent network acquires state representations and representations of state make the recurrent neural network suitable for diverse applications such as nonlinear prediction and modeling. In this paper, we applied recurrent network for the expert network in the modular neural network structure to learn data pattern based on emotional assessment. To show the performance of the proposed network, simulation of learning the environment and behavior pattern is proceeded with the real time implementation. The given problem is very complex and has too many cases to learn. The result will show the performance and good ability of the proposed network and will be compared with the result of other method, general modular neural network.