• 한국의류학회지
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• 제32권2호
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• pp.179-189
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• 2008

The purposes of this study were to segment surrogate internet shopping mall consumers by fashion leadership and to find the differences among the segmented groups in regard to surrogate internet shopping perceived risks, selection criteria, dissatisfactions with surrogate shopping malls, and other purchase behavior. The subjects of this study were female consumers who were users of surrogate internet shopping malls. The data were collected during October, 2005. The respondents returned the questionnaires and 283 questionnaires were finally used in the data analysis. The statistical analyses used for the study were factor analysis, ANOVA, Duncan test, and $X^2$-test. The results showed that consumers were segmented by four groups: fashion dual leaders, fashion leaders, fashion followers, and fashion laggards. These segmented groups were significantly different in regard to surrogate internet shopping mall perceived risks, selection criteria, dissatisfactions with surrogate shopping malls, and other purchase behavior. Generally, fashion dual leaders had less perceived risks, considered diverse selection criteria important, and were less dissatisfied with surrogate shopping malls. Also, the fashion dual leaders had a higher purchase frequency and paid a higher price on surrogate internet shopping malls.

• 산업경영시스템학회지
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• 제9권13호
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• pp.45-50
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• 1986

본 연구에서 고찰한 surrogate relaxation은 Lagrangian relaxation 방법과는 달리 제약식들을 선형조합으로 묶어 문제를 푼다. 수리계획 분계가 convexity를 만족하지 못하는 경우에는 Lagrangian의 경우와 마찬가지로 surrogate gap이 발생한다. Lagrangian 쌍대이론을 토대로 surrogate optimality condition을 알아보고 수리계획법의 특별 형태인 정수선형계획법에 적용해 보았다. 일반적으로 surrogate gap은 Lagrangian gap 보다 작기 때문에 좀더 근사하게 원 문제의 최적 목적 함수값에 접근할 수 있다. 따라서 branch and bound 알고리즘을 개발할 때 중요한 정보를 제공하는 것이다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2009년도 추계학술대회
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• pp.3-10
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• 2009

When the measurement method for a performance variable is destructive or expensive, it is profitable to replace the performance variable with a highly correlated surrogate variable. In this paper we propose screening procedures using a surrogate variable with specified producer's and consumer's risks. Blending the basic concepts of acceptance sampling plans and screening procedures, the proposed model can be used effectively by quality professionals. Two models are considered: the normal model with dichotomous performance and continuous surrogate variables, and the bivariate normal model with continuous performance and surrogate variables. It is assumed the surrogate variable given the performance variable is normally distributed in the normal model, and performance and surrogate variables are jointly normally distributed in the bivariate normal model. For the two models, Producer's and consumer's risks are derived, and methods of finding the optimal screening procedures are presented. Numerical examples are also given.

• 품질경영학회지
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• 제37권4호
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• pp.23-30
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• 2009

When the measurement method for a performance variable is destructive or expensive, it is profitable to replace the performance variable with a highly correlated surrogate variable. In this paper we propose screening procedures using a surrogate variable with specified producer's and consumer's risks. Blending the basic concepts of acceptance sampling plans and screening procedures, the proposed model can be used effectively by quality professionals. Two models are considered: the normal model with dichotomous performance and continuous surrogate variables, and the bivariate normal model with continuous performance and surrogate variables. It is assumed the surrogate variable given the performance variable is normally distributed in the normal model, and performance and surrogate variables are jointly normally distributed in the bivariate normal model. For the two models, producer's and consumer's risks are derived, and methods of finding the optimal screening procedures are presented. Numerical examples are also given.

• 한국항공우주학회지
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• 제38권8호
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• pp.823-833
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• 2010

액체 로켓 및 항공용 엔진 연료로서 사용되는 케로신의 열역학적 상태량을 연구하기 위해 surrogate 모델이 조사되었다. 초임계 조건에서 실제 기체 상태 방정식(SRK 상태 방정식, PR 상태 방정식)과 NIST SUPERTRAPP(ECS 원리)을 이용하였을 경우의 밀도 분포가 기존의 실험 결과와 비교되었다. 또한 surrogate 모델의 종류에 따른 열역학적 상태량의 오차 범위에 대한 고찰이 수행되었다. 탄화 수소 계열 연료에 대해서는 PR 상태 방정식과 ECS 원리가 높은 정확도를 나타내지만 압력, 온도와 같은 작동 환경에 따라 적절한 surrogate 모델을 선별하여 선택해야 함을 확인하였다.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.

• Advances in Computational Design
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• 제1권3호
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• pp.235-251
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• 2016

We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.

• Nuclear Engineering and Technology
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• 제51권2호
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• pp.495-500
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• 2019

When a new fuel is developed, various mechanical properties are absolutely necessary for a safety analysis of the fuel for the licensing and prediction of its mechanical behavior during operation and accident conditions. In this paper, a mechanically equivalent surrogate plate of U-Mo dispersion fuel is presented using tungsten, substitute material of U-Mo particle. A surrogate plate, composed of tungsten/aluminum dispersion meat and aluminum alloy cladding, is manufactured with the same fabrication process with that of fuel plate except that a tungsten powder is used instead of U-Mo powder. A modal test showed that the surrogate plate and fuel plate have similar dynamic characteristics, and a tensile test demonstrated the similarity of the material property up to the yield strength range. The conducted tests proved that the surrogate tungsten plate has equivalent mechanical behaviors with that of a fuel plate, which leads to the acceptable use of a surrogate fuel assembly using tungsten/aluminum dispersion meat in various mechanical tests. The surrogate fuel assembly can be utilized for various out-of-pile characteristic tests, which are necessary for the licensing achievement of a research reactor that uses U-Mo dispersion fuel as a driver.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.99-99
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• 2023

기후변화는 물 관리의 가장 큰 리스크 요인이므로 물 관리 계획을 수립하는 과정에서 기후변화의 영향을 고려하는 것이 필수적이다. 기후변화에 대한 수자원 예측 관련 연구가 이루어지고 있으나, 대부분의 연구에는 수문학적 모델링이나 시뮬레이션이 동반되는데, 이 과정에는 시간과 비용이 많이 들어가며, 지역이나 연구목적에 따른 정밀한 매개변수의 보정은 전문지식이 필요하기 때문에 현업에서 연구결과를 의사결정에 활용하기에는 한계가 있다고 볼 수 있다. 이에 따라 수문학적 모델링의 입력 및 출력 결과를 딥러닝의 학습자료로 하여 수문모델을 사용하지 않아도 효율적으로 결과를 도출할 수 있는 딥러닝 기반 Surrogate 모형에 대한 연구가 이루어지고 있으나 수자원 분야에 접목된 사례는 부재한 실정이다. 따라서 이 연구를 통해 국내 유역을 대상으로 Surrogate 모형을 구축한 뒤, 그 성능을 평가하고자 한다. 이를 위한 Surrogate 모형 구축 과정은 다음과 같다. 충주댐 유역을 대상으로 과거 20년간의 강우 및 기온 자료를 수집한 뒤, 이 자료를 바탕으로 기후변화의 영향을 고려한 3,162개의 시나리오를 생성한다. 그 후 장기유출모형 IHACRES에 생성된 시나리오를 입력자료로 하여 유입량 결과를 도출하고, 이 결과를 Python코드 기반의 딥러닝 학습자료로 하여 최적 예측 결과를 도출해내는 Surrogate 모형을 생성한 뒤 기존 장기유출모형과의 성능을 비교하고자 한다. 이와 같은 Surrogate 모형은 추가적인 데이터와 매개변수의 보정 과정이 없어도 장기유출모형과 같은 결과를 짧은 시간내에 상당히 정확하게 모사할 수 있어 시간과 비용을 줄일 수 있으며, 비전문가도 쉽게 사용할 수 있다는 장점을 가진다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2010년도 제35회 추계학술대회논문집
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• pp.19-23
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• 2010

초임계 환경에서 작동하는 액체 로켓 엔진의 케로신 스월 인젝터에서 케로신 물성치에 따른 인젝터 내외에서의 분사 특성을 연구하였다. 케로신의 물성치를 계산하기 위해 surrogate 모델이 적용되었다. 난류 수치 모델은 large eddy simulation을 기반으로 하였으며 SRK 상태 방정식, Chung의 기법을 포함하고 있다. 초임계 환경의 수치 해석 결과는 천이 임계 조건의 결과와 비교되었으며 스월 인젝터 내부의 액막과 중심부 사이의 밀도 및 점성 계수 분포의 차이가 관찰되었다.