• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.2
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.9 no.13
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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.

• Proceedings of the Korean Society for Quality Management Conference
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• 2009.10a
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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.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.8
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• pp.823-833
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• 2010

For the study of thermophysical properties of kerosene for the liquid rocket and aviation fuels, the surrogate models are investigated. The density distributions based on the real gas equations of state(Soave modification of Redlich-Kwong and Peng-Robinson equation of state) and NIST SUPERTRAPP(extended corresponding state principle) are compared with the previous experimental results at supercritical conditions. The error range of thermophysical properties analyzed for the surrogate models as well. Peng-Robinson equation of state and extended corresponding state principle are especially accurate for the hydrocarbon fuels but the appropriate surrogate models need to be chosen to the operation conditions such as pressure and temperature.

• Nuclear Engineering and Technology
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• v.49 no.6
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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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• v.1 no.3
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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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• v.51 no.2
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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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.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.19-23
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• 2010

Injection characteristics of a kerosene swirl injector of liquid rocket engine operating at supercritical environment have been investigated. Kerosene surrogate models are proposed to model the kerosene properties. Turbulent numerical model is based on large eddy simulation and contains Soave modification of Redlich-Kwong equation of state and Chung's model. Numerical analysis results at supercritical environment are compared with the one at transcritical condition. Differences of density and viscosity are analyzed at both liquid film and core gas in the swirl injector.