• Journal of the Korean Chemical Society
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• v.47 no.2
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• pp.165-174
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• 2003

The purposes of this study were to investigate the correlation between the cognitive level and the probabilistic thinking level and to analyze the effects of the probability activities in Thinking Science (TS) program on the development of probabilistic thinking. The 219 7th grade students were sampled in the middle school and were divided into an experimental group and a control group. The probability activities in TS program were implemented to the experimental group, while only normal curriculum was conducted in the control group. The results of this study showed that most of 7th grade students were in the concrete operational stage and used both subjective and quantitative strategy simultaneously in probability problem solving. It was also found that the higher the cognitive level of the students, the higher the probabilistic thinking level of them. The sample space and the probability of an event in the constructs of probability were first developed as compared to the probability comparisons and the conditional probability. The probability activities encouraged the students to use quantitative strategy in probability problem solving and to recognize probability of an event. Especially, the effectiveness was relatively higher for the students in the mid concrete operational stage than those in any other stage.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.3
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• pp.1-10
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• 2008

The seismic performance of a structure designed without consideration of seismic loading can be effectively enhanced through seismic rehabilitation. The appropriate level of rehabilitation should be determined based on the decision criteria that minimize the anticipated earthquake-related losses. To estimate the anticipated losses, seismic risk analysis should be performed considering the probabilistic characteristics of the hazard and the structural damage. This study presents the decision procedure in which the probabilistic seismic demand model is utilized for the effective estimation and minimization of the total seismic losses through seismic rehabilitation. The probability density function and the cumulative distribution function of the structural damage for a specified time period are established in a closed form, and are combined with the loss functions to derive the expected seismic loss. The procedure presented in this study could be effectively used for making decisions on the seismic rehabilitation of structural systems.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.2
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• pp.62-72
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• 2019

Due to the difficulties in forecasting the intensity and the source location of tsunami the countermeasures prepared based on the deterministic approach fail to work properly. Thus, there is an increasing demand of the tsunami hazard analyses that consider the uncertainties of tsunami behavior in probabilistic approach. In this paper a fundamental study is conducted to perform the probabilistic tsunami hazard analysis (PTHA) for the tsunamis that caused the disaster to the east coast of Korea. A logic tree approach is employed to consider the uncertainties of the initial free surface displacement and the tsunami height distribution along the coast. The branches of the logic tree are constructed by reflecting characteristics of tsunamis that have attacked the east coast of Korea. The computational time is nonlinearly increasing if the number of branches increases in the process of extracting the fractile curves. Thus, an improved method valid even for the case of a huge number of branches is proposed to save the computational time. The performance of the discrete weight distribution method proposed first in this study is compared with those of the conventional sorting method and the Monte Carlo method. The present method is comparable to the conventional methods in its accuracy, and is efficient in the sense of computational time when compared with the conventional sorting method. The Monte Carlo method, however, is more efficient than the other two methods if the number of branches and the number of fault segments increase significantly.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.10a
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• pp.637-640
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• 2002

The deterioration of RC deck slabs has been a serious problem and high portion of budget has been a spent for repair and strengthening of deck slab. The concrete deck slabs are subject to direct application of vehicle loading and accumulation of fatigue damage. Besides, various environmental causes. In this paper, an probabilistic study is carried out to predict exact load effects and structural capacity of deck slab during its service life, and estimate an appropriate remaining life of deck slab. To achieve this purpose the live load model is developed using by influence line including deterioration of deck slab, and deterioration model of bridge deck slab is developed. In addition, the fatigue life of reinforced concrete deck slabs considering corrosion of reinforcement are estimated based on experimental formula. This study will help rational decisions for the management and repair of reinforced concrete deck slabs.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.27-32
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• 2008

The laminated composite materials have been applied to various mechanical structures due to their high performance to weight ratios. In this study, we suggest a stochastic finite element scheme for the probabilistic analysis of the composite laminated plates. The composite materials consist of two different materials which constitute the matrix and fiber. The material properties in the major and minor directions are determined depending on the volume fraction of these two materials. In this study, the elastic modulus and shear modulus are considered as random and the effect of these random properties on the behavior of the composite plate is investigated. We adopt the weighted integral scheme in the formulation, which has been recognized as the most accurate method in the statistical methodologies. For verification of the proposed scheme, Monte Carlo analysis is also performed for the comparison with the proposed scheme.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1983-1989
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• 2020

The human reliability analysis is a method by which, in general terms, the human impact to the safety and risk of a nuclear power plant operation can be modelled, quantified and analysed. It is an indispensable element of the PSA process within the nuclear industry nowadays. The paper herein presents a sensitivity study of the human reliability analysis performed on a real nuclear power plant-specific probabilistic safety assessment model. The analysis is performed on a pre-selected set of post-initiator operator actions. The purpose of the study is to investigate the impact of these operator actions on the plant risk by altering their corresponding human error probabilities in a wide spectrum. The results direct the fact that the future effort should be focused on maintaining the current human reliability level, i.e. not letting it worsen, rather than improving it.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.4
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• pp.439-445
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• 2017

Plunging breaker slamming pressures on vertical or sloping sea dikes are one of the most severe and dangerous loads that sea dike structures can suffer. Many studies have investigated the impact forces caused by breaking waves for maritime structures including sea dikes and most predictions of the breaker forces are based on empirical or semi-empirical formulae calibrated from laboratory experiments. However, the wave breaking mechanism is complex and more research efforts are still needed to improve the accuracy in predicting breaker forces. This study proposes a semi-empirical formula, which is based on impulse-momentum relation, to calculate the slamming pressure due to plunging wave breaking on a sloping sea dike. Compared with some measured slamming pressure data in two literature, the calculation results by the new formula show reasonable agreements. Also, by analysing probability distribution function of wave heights, the proposed formula can be converted into a probabilistic expression form for convenience only.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.05a
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• pp.393-398
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• 2002

This study shows the fatigue test results of experiment on the strengthened slabs, the probability analysis of the fatigue behavior is also presented. Static und fatigue tests were performed on bridge decks strengthened with fiber plastics(Carbon Fiber Sheet, Glass Fiber Sheet, Grid Type Carbon Fiber). In this study, to analyze the probabilistic distribution of the fatigue life, the Weibull distribution was adopted. The Weibull distribution coefficient is inferred from the S-N diagram and the number of repeated load. As the result analysis, as the stress level is higher, the fatigue limit of the strengthened bridge deck are similarly discovered but in the range of the fatigue limit, CG specimen that was strengthened with Grid Type Carbon was proved most effective of reinforcement.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.1-6
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• 2010

Ball bearings are one of main components that support the rotational shaft in high speed rotary machinery. So, it is very important to detect the incipient faults and fault growth of bearing since the damage and failure of bearing can cause a critical failures or accidents of machinery system. In the past, many researchers mainly performed to detect the bearing fault using traditional method such as wavelet, statistics, envelope etc in vibration signals. But study on the detection technique for bearing fault growth has a little been performed. In this paper, we verified the possibility for monitoring of fault growth and detection of fault size in bearing outer-race by using the envelope powerspectrum and probabilistic density function from measured vibration signals.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.109-141
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• 1998

Many processes in the industrial realm exhibit sstochastic and nonlinear behavior. Consequently, an intelligent system must be able to nonlinear production processes as well as probabilistic phenomena. In order for a knowledge based system to control a manufacturing processes as well as probabilistic phenomena. In order for a knowledge based system to control manufacturing process, an important capability is that of prediction : forecasting the future trajectory of a process as well as the consequences of the control action. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes, includinb chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a chaotic process in the presence of various patterns of noise.