• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.258-265
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• 2017

At the early stage of the development of high speed propulsion systems, the designers suffer from the lack of both the quantity and the quality of test data. In that situation, the associated uncertainties could not be modeled as probabilistic distribution since probabilistic modelling requires large amount of data. In this paper, instead, the information provided by experts based on their experience and engineering knowledge was used to model uncertainty using the evidence theory. In designing the DCR(Dual Combustion Ramjet) engine, the combustion efficiencies, not well understood and little data existing, are assumed to have been provided by experts. And the uncertainties are quantified by Evidence theory. The quantified uncertainties are incorporated into the optimization. The design variables, area of inlet and area of combustor exit, have been found while satisfying reliability margins of thrust and thermal choking. The results show a reasonable design of the engine under the uncertain circumstances.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.201-204
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• 2002

Kansei design knowledge acquisition stage is a crucial stage in kansei designing process and kansei engineering (KE) methodology. In kansei engineering methodology, it is essential to extract design knowledge or rules on relationships between customer's kansei and product design element. We attempt to construct a more powerful melted for extracting the design rules from kansei expremental data. We constucted a kansei experiment concerning color kansei evaluation, and analyzed the sane data by both conventional quantification theory type I and rough set theory. Finally, we compared the effectiveness of both methods for extracting rules and examined the extensions of rough set theory in kansei engineering.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.327-330
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• 2007

This paper verifies that the normality assumption that the simulation output data, Project Completion Times (PCTs), follow normal distribution is not always acceptable and the existing belief may lead to misleading results. A risk quantification method, which measures the effect caused by the assumption, relative to the probability distribution of PCTs is implemented as an algorithm in MATLAB. To validate the reliability of the quantification, several series of simulation experiments have been carried out to analyze a set of simulation output data which are obtained from different type of Probability Distribution Function (PDF) assigned to activities'duration in a network. The method facilitates to find the effect of PDF type and its parameters. The procedure necessary for performing the risk quantification method is described in detail along with the findings. This paper contributes to improving the reliability of simulation based scheduling method, as well as increasing the accuracy of analysis results.

• Journal of Korean Society of Forest Science
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• v.88 no.2
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• pp.240-248
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• 1999

On the basis of data obtained from five forest roads collapsed due to a heavy rainfall of 1995 in Chunchon, Kangwon-do, this study was carried out to evaluate and predict the fill slope failure of forest roads with four factors of forest road structure and those of location condition by using Quantification theory(II). The results were summarized as follows ; In the structure factors of forest road, the fill slope failure was mainly occurred in longitudinal gradients less than $2^{\circ}$ or more than $4^{\circ}$, distance of surface-flow longer than 80m, fill slope length greater than 6m, and fill slope gradients steeper than $35^{\circ}$. In the factors of location condition, the failure was mainly occurred in ridge portion of road position, weathered rock and soft rock of constituent material, slope gradients in the range from $35^{\circ}$ to $45^{\circ}$, and concave and convex of longitudinal slope forms. The priority order for factors influencing on fill slope failure was ranked by fill slope length, constituent material, road position, and so on. And the rate of correct discrimination by analysis of fill slope failure was estimated at the high prediction of 86.5%.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.73-80
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• 1987

Various procedures for evaluation of traffic noise annoyance have been proposed. However, most of the studies of this type are restricted for improving traffic flow. In this paper, a method to predict the road traffic noise is proposed in terms of equivalent continuous A-Weighted sound pressure level (Leq), based on a probability model. First, distribution of the road traffic noise level are investigated. second, the weibull distribution parameters are estimated by using the quantification theory. Finally, a prediction model of the road traffic noise is proposed based on the weibull distribution model The predicted values of the Leq are closely matched the measured data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1470-1474
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• 2004

This paper addresses the development of inverse compensation techniques for a class of ferromagnetic transducers including magnetostrictive actuators. In this work, hysteresis is modeled through the domain wall theory originally proposed by Jiles and Atherton[1]. This model is based on the quantification of the energy required to translate domain walls pinned at inclusions in the material with the magnetization at a given field level specified through the solution of an ordinary differential equation. A complementary differential equation is then employed to compute the inverse which can be used to compensate for hysteresis and nonlinear dynamics in control design.

• ETRI Journal
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• v.14 no.3
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• pp.67-74
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• 1992

Discrete variable을 갖는 Mean Field Theory(MFT) neural network은 이미 많은 combinatorial optimization 문제에 적용되어져 왔다. 본 논문에서는 이를 확장하여 continuous variable을 갖는 mean field annealing을 제안하고, 이러한 network에서 integral로 표현되는 spin average를 mean field에 기초하여 어렵지 않게 구할 수 있는 one-variable stochastic simulated annealing을 제안하였다. 이런 방법으로 multi-body problem을 single-body problem으로 바꿀 수 있었다. 또한 이 방법을 이용한 응용으로서 통계학에서 잘 알려진 문제중의 하나인 quantification analysis 문제에 적용하여 타당성을 보였다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.241-246
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• 1999

In this study, to specify an evaluation of human sensibility, the types of color, intensity of illuminations and lights consisting work environmental condition are decided, and image data from examining the change of human sensibility followed by changes of the above three conditions are obtained. Using the factor analysis and quantification theory in multi-variate analysis type of Sensibility Ergonomics, determinating the structure of factors, specifying the relations of environmental conditions and factors can be done so that the structure of image on human sensibility space with the change of environmental conditions is analyzed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.3
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• pp.47-54
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• 1992

This paper presents an image processing method which emphasizes a certain perception feeling on a color image. A series of fuzzy image processing schemes are proposed, which transform an color image represented in the LCH coordinate system to the image with a certain perception feeling based on the rules and fuzzy inference. To obtain the rules, results of the sensory perception tests are applied to the quantification theory. The proposed schemes can be effectively utilized in the color copy system, since printed outputs possibly look better than originals.

• Structural Engineering and Mechanics
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• v.72 no.2
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• pp.203-216
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• 2019

Reliability analysis of composite structures considering random variation of involved parameters is quite important as composite materials revealed large statistical variations in their mechanical properties. The reliability analysis of such structures by the first order reliability method (FORM) and Monte Carlo Simulation (MCS) based approach involves repetitive evaluations of performance function. The response surface method (RSM) based metamodeling technique has emerged as an effective solution to such problems. In the application of metamodeling for uncertainty quantification and reliability analysis of composite structures; the finite element model is usually formulated by either classical laminate theory or first order shear deformation theory. But such theories show significant error in calculating the structural responses of composite structures. The present study attempted to apply the RSM based MCS for reliability analysis of composite shell structures where the surrogate model is constructed using higher order shear deformation theory (HSDT) of composite structures considering the uncertainties in the material properties, load, ply thickness and radius of curvature of the shell structure. The sensitivity of responses of the shell is also obtained by RSM and finite element method based direct approach to elucidate the advantages of RSM for response sensitivity analysis. The reliability results obtained by the proposed RSM based MCS and FORM are compared with the accurate reliability analysis results obtained by the direct MCS by considering two numerical examples.