• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.684-701
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• 2016

The Gaussian process model (GPM) is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitions while dealing with a large number of uncertainties.

• The KSFM Journal of Fluid Machinery
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• v.13 no.6
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• pp.42-50
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• 2010

The present analysis deals with a numerical procedure for optimizing the shape of elliptical dimples in a cooling channel. The three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis is employed in conjunction with the SST model for predictions of the turbulent flow and the heat transfer. Three non-dimensional geometric design variables, such as the ellipse dimple diameter ratio, ratio of the dimple depth to the average diameter, and ratio of the distance between dimples to the pitch are considered in the optimization. Twenty-one experimental points within design space are selected by Latin Hypercube Sampling. Each objective function values at these points are evaluated by RANS analysis and producing optimal point using surrogate model. The linear combination of heat transfer coefficient and friction loss related terms with a weighting factor is defined as the objective function. The results show that the optimized elliptical dimple shape improves considerably the heat transfer performance than the circular dimple shape.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.161-176
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• 2005

In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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• pp.113-120
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• 2013

This paper proposes a design optimization approach for core of solenoid actuators by combining optimization techniques with the finite element method (FEM). A solenoid is an important element part which hydraulically controls a transmission system, etc. The demanded feature of the solenoid is that it performs an electromagnetic force output being constant regardless of the stroke and being proportional to coil current. The plunger compresses a spring with a minimum force of 12 N over an 1.7 mm travel. The orthogonal array, analysis of variance (ANOVA) techniques and response surface optimization, are employed to determine the main effects and their optimal design variables. The methodology is demonstrated as a optimization tool for the core design of a solenoid actuator.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.3
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• pp.373-382
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• 2020

This study proposes a method of separating uranium (U) and minor actinides from rare earth (RE) elements in the LiCl-KCl salt system. Several RE metals were used to reduce UCl₃ and MgCl₂ from the eutectic LiCl-KCl salt systems. Five experiments were performed on drawdown U and plutonium (Pu) surrogate elements from RECl₃-enriched LiCl-KCl salt systems at 773 K. Via the introduction of RE metals into the salt system, it was observed that the UCl₃ concentration can be lowered below 100 ppm. In addition, UCl₃ was reduced into a powdery form that easily settled at the bottom and was successfully collected by a salt distillation operation. When the RE metals come into contact with a metallic structure, a galvanic interaction occurs dominantly, seemingly accelerating the U recovery reaction. These results elucidate the development of an effective and simple process that selectively removes actinides from electrorefining salt, thus contributing to the minimization of the influx of actinides into the nuclear fuel waste stream.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.8
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• pp.1218-1227
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• 1999

Consumer evaluate the jeans product by price brand and store because these cues be surrogate indicator that could infer the product quality. But we need to confirm if depending on these cues were rational and this is the goal of this study. method of the study was based on theoretical and empirical study. For empirical study experiments by the subjects among students of Ewha Womans University were done by using jeans as stimulus,. Data was analized by ANOVA factor analysis grouping analysis F-test Pearson's correlation duncan Test and etc 571 data was analyzed of the 600 data. The results of this study are as follows : Evaluation on jeans product were different even though they were exactly the same jeans. Therefore we could confirm the bias by price brand store when consumer evaluate jeans product. Cues like price brand store effected significantly the evaluation of jeans. Quality perception of jeans was most favorable when evaluation cues were combined with high price famous brand and high prestige store. Value perception was favorable when combined with famous brand and high prestige store but value perception on high price became lowe. Purchase intention correlate with value perception and it shows same format with value preception. The most important cue of all three was store the next was price and then brand. These three cues effect the evaluation of jeans product seperately and together.

• Human Ecology Research
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• v.55 no.6
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• pp.581-592
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• 2017

This study investigated the occupational experiences of social workers in child care facilities. The participants of the study were six social workers in child care facilities. This qualitative research used a Consensual Qualitative Research (CQR) method that and classified the main findings into five categories and twelve sub-themes. This study revealed that child care professionals define themselves as "caregivers" and "role models." Positive effects of institutional life on a child were forming peer relationships and being able to use diverse services while negative effects included acquiring a social stigma, having problems in developing attachment between a child and a surrogate caregiver, developing passive attitude and weak will power from communal living. Meanwhile, conflicts with children and poor working conditions led to burnout for caregivers. Our recommendations on the direction of change for the facilities are: categorizing admitted children, supporting restoration of family functions, reinforcing support for children's preparation for an independent life, and developing expertise. This paper provides a better understanding of child care facilities as well as encourages further social discourse on institutionalized children in order to promote policy making and implementation.

• The Journal of Information Systems
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• v.15 no.4
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• pp.171-188
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• 2006

Information technology and the Internet have had a dramatic effect on education method and individual life. Universities and companies we making large investments in e-Learning applications but are hard to pressed to evaluate the success of their e-Learning systems. e-Learning can be seen as not only one of Internet based information systems which can provide education services but also one of teaching-teaming methods which can implement self-directed teaming. This paper tests the updated model of information system success proposed by Delone and McLean using a field study of a e-Learning. The five dimensions - information quality, system quality, service quality, user satisfaction, net benefit - of the updated model are parsimonious framework for organizing the e-learning success metrics identified in the literature. Questionaires are collected from 107 students who are enrolling a e-learning class using online survey. The model is tested using SPSS and LISREL. The results show that information quality and service quality are significant predictors of user satisfaction with the e-Learning system but system quality is not. Also user satisfaction is found to be a strong predictor of the learning performance. This strong association between user satisfaction and teaming performance suggests that user satisfaction may serve as a valid surrogate for teaming performance. Empirical testing of the updated DeLone & McLean model should therefore be extended to cover a wider variety of systems.

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.209-218
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• 2021

For engineering, there are two major challenges in reliability analysis. First, to ensure the accuracy of simulation results, mechanical products are usually defined implicitly by complex numerical models that require time-consuming. Second, the mechanical products are fortunately designed with a large safety margin, which leads to a low failure probability. This paper proposes an efficient and high-precision adaptive active learning algorithm based on the Kriging surrogate model to deal with the problems with low failure probability and time-consuming numerical models. In order to solve the problem with multiple failure regions, the adaptive kernel-density estimation is introduced and improved. Meanwhile, a new criterion for selecting points based on the current Kriging model is proposed to improve the computational efficiency. The criterion for choosing the best sampling points considers not only the probability of misjudging the sign of the response value at a point by the Kriging model but also the distribution information at that point. In order to prevent the distance between the selected training points from too close, the correlation between training points is limited to avoid information redundancy and improve the computation efficiency of the algorithm. Finally, the efficiency and accuracy of the proposed method are verified compared with other algorithms through two academic examples and one engineering application.

• Geomechanics and Engineering
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• v.18 no.6
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• pp.595-603
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• 2019

A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.