• Geomechanics and Engineering
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• v.10 no.3
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• pp.269-284
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• 2016

Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising.

• Human Ecology Research
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• v.51 no.3
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• pp.321-331
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• 2013

The purpose of this study is to develop the scale to measure family health and to analyze the data collected by the survey in order to develop the educational program for healthy family. The sample of this study is taken by 522 housewives who are living in Seoul and are over the age of 40. The data are analyzed according to frequency, percentages, t-test, Pearson's correlation analysis, and Multinomial logistic Regression analysis. The results of this study are as follows. First, the scale measuring family health is developed through interviews with the respondents, preliminary survey, and comments reviewed from specialists. The responses to the scale are significantly different depending on whether they answered their family is healthy or not. Second, minimum family performances for family health are related to the category of social involvement of the family. Third, the types of healthy family are grouped by the responses related to the current state and the status of family health. The number of the type of the worst state-the worst status of family health is the largest, followed by the number of the type of the best state-the best status of family health. Fourth, the important and significant variables that affected the types of family health are psychological variables rather than personal and household-related variables of the respondents.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.5
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.6
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• pp.442-450
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• 2020

A small-signal modeling approach for a three-level boost (TLB) converter and a design methodology for a double-loop controller are proposed in this study. Conventional modeling of TLB converters involves three state variables. Moreover, TLB converters have two operation modes depending on the duty ratio. Consequently, complex mathematical calculations are required for controller design. This study proposes a simple system modeling method that uses two state variables, unlike previous methods that require three state variables. Analysis shows that the transfer functions of the two operation modes can be expressed as identical equations. This condition means that the linear feedback controller can be applied to all operational ranges, that is, for full duty ratios. The design method for a double-loop controller using a PI controller is presented in step-by-step sequences. Simulation and experimental verifications are conducted to verify the effectiveness of the small-signal analysis and control system design.

• Structural Engineering and Mechanics
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• v.85 no.3
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• pp.369-379
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• 2023

Reliability-Based Design Optimization (RBDO) is an appropriate framework for obtaining optimal designs by taking uncertainties into account. Large-scale problems with implicit limit state functions and problems with discrete design variables are two significant challenges to traditional RBDO methods. To overcome these challenges, this paper proposes a hybrid method to perform RBDO of structures that links Firefly Algorithm (FA) as an optimization tool to advanced (finite element) reliability methods. Furthermore, the Genetic Algorithm (GA) and the FA are compared based on the design cost (objective function) they achieve. In the proposed method, Weighted Simulation Method (WSM) is utilized to assess reliability constraints in the RBDO problems with explicit limit state functions. WSM is selected to reduce computational costs. To performing RBDO of structures with finite element modeling and implicit limit state functions, a First-Order Reliability Method (FORM) based on the Direct Differentiation Method (DDM) is utilized. Four numerical examples are considered to assess the effectiveness of the proposed method. The findings illustrate that the proposed RBDO method is applicable and efficient for RBDO problems with discrete and continuous design variables and finite element modeling.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.170.2-170
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• 2001

In this paper, the dynamic system modeling and the state sensitivity analysis of the spin-coater system for the reduction of the vibration are proposed. In the respect of modeling, the spin-coater system is composed of components of servomotor, belt, spindle, and a supported base. Each component is defined and combined modeling is derived to 3dimensional equations. Verification of modeling is verified by experimental values of actual system in the frequency domain. By direct differentiation the constraint equations with respect to kinematic design variables, such as eccentricity of spindle, moment of inertia, torsional stiffness and damping of supported base, sensitivity equations are derived to the verified state equations. Sensitivity of design variables could be used for vibration reduction and natural frequency shift in the frequency domain. Finally, dominant design variables ...

• Transactions of Materials Processing
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• v.16 no.1 s.91
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• pp.54-60
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• 2007

Optimum injection molding condition for a box mold was searched by the Response Surface Analysis(RSA) with the aid of process monitoring system(PMS). Process variables on the control panel of the injection molding machine such as barrel temperatures, screw speed profile, holding pressures, etc. cannot guarantee the uniformity of the material variables directly related with the state of the product in the mold cavity. In order to make sure the state of the resin in the cavity, pressures and temperatures in the cavity, runner and nozzle were monitored in the experiment with the PMS. To accomplish the consistency of the molding process, dependent variables such as the switchover point and holding time were searched with the PMS. With a proper objective function about deflection of the box-type product, the optimum injection molding condition was obtained.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.209-217
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• 2003

In this paper, the dynamic system modeling and the state sensitivity analysis of the spin-coater system are proposed for the reduction of the vibration. In the respect of modeling, the spin-coater system is considered to be composed of servomotor, spindle, supporting base and so on. Each component of model is combined and derived to 3 dimensional equations. The combined model is verified by experimental values of actual system in the frequency domain. By direct differentiation of the constraint equations with respect to kinematic design variables, such as eccentricity of spindle, moment of inertia, rotational stiffness and damping of supported base, sensitivity equations are derived to the verified state equations. Sensitivity of design variables could be used for vibration reduction and natural frequency shift in the frequency domain. Finally, dominant design variables are selected from the sensitivity analysis.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.826-827
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• 2006

Copper infiltration is demonstrated as a viable solution to achieve higher mechanical properties by filling the interconnected porosities of a ferrous structure with copper infiltrant. This paper will present the results of a design of experiments study based on the selected processing variables in the copper infiltration process. The variables are the following: Infiltrating temperatures, infiltrating time at pre-heat zone and hot zone, the green density of iron part, the migration of copper into the iron part at different processing conditions. The results show the flexibility of the infiltration process to attain certain mechanical properties by changing the processing conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.661-666
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• 2013

A state feedback controller with integration of output error is proposed for way-point tracking of an AUV (Autonomous Underwater Vehicle). For the steering control on the XY plane, the proposed controller uses three state variables (sway velocity, yaw rate, heading angle) and the integral of the steering error, and for the depth control on the XZ plane, it uses four state variables (pitch rate, depth, pitch angle) and the integral of the depth error. From the simulation using Matlab/Simulink, we verify that the performance of the proposed controller is satisfactory within an error range of 1m from the target way-point for arbitrarily chosen sets of consecutive way-points.