• Journal of Korean Society for Quality Management
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• v.36 no.4
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• pp.77-86
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• 2008

Due to the rapid growth in automated testing and manufacturing systems, screening inspection becomes very attractive. In this paper, we investigate the effects of limited capacity on screening inspection using a surrogate variable. The model is developed under the assumption that the reprocessed and nonreprocessed items are produced by the same manufacturing process and therefore their quality characteristics are independently and identically distributed. Profit models are constructed which involve four price/cost components; selling price, cost incurred by imperfect quality, reprocessing and quality inspection costs. Methods of finding the optimal screening limits are presented, and a numerical example is given. Sensitivity analyses are also performed to study the effect of a process standard deviation on this model.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.187-194
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• 2010

Shape optimization of an upper plenum of PBMR type gas cooled nuclear reactor has been performed by using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) analysis and surrogate modeling technique. The objective function is defined as a linear combination of uniformity of flow distribution in the core and pressure drop in the upper plenum and the core. The ratio of thickness of slot to diameter of rising channels, ratio of height of upper plenum to diameter of rising channels, and ratio of eight of the slot at inlet to outlet, are used as design variables for optimization. Design points are selected through Latin-hypercube sampling. The optimal point is determined through surrogate-based optimization method which uses 3-D RANS analyses at design points. The results show that the optimum shape represent remarkably improved performance in flow uniformity and friction loss than the reference shape.

• Journal of computational fluids engineering
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• v.15 no.3
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• pp.16-23
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• 2010

Shape optimization of an upper plenum of a PBMR type gas cooled nuclear reactor has been performed by using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) analysis and surrogate modeling technique. The objective function is defined as a linear combination of uniformity of flow distribution in the core and pressure drop in the upper plenum and the core. The ratio of thickness of slot to diameter of rising channels, ratio of height of upper plenum to diameter of rising channels, and ratio of height of the slot at inlet to outlet, are used as design variables for optimization. Design points are selected through Latin-hypercube sampling. The optimal point is determined through surrogate-based optimization method which uses 3-D RANS analyses at design points. The results show that the optimum shape represent remarkably improved performance in flow uniformity and friction loss than the reference shape.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.200-205
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• 2000

An economic process monitoring procedure is presented using a surrogate variable for the case where performance variable is dichotomous. Every item is inspected with a surrogate variable and determined whether it should be accepted or rejected. When an item is rejected, the previous number of consecutively accepted items is compared with a predetermined number r to decide whether there is a shift in fraction nonconforming or not. The conditional distribution of the surrogate variable given the performance variable is assumed to be normal. A cost model is constructed which includes costs of inspection, misclassification, illegal signal, undetected out-of-control state, and correction. Methods of finding the optimum number r and screening limit are provided. Numerical studies on the effects of cost coefficients are also performed.

• International Journal of Fluid Machinery and Systems
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• v.9 no.4
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• pp.313-324
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• 2016

Surrogate model based shape optimization methodology to enhance performance of a centrifugal pump has been implemented in this work. Design variables, such as blade number and blade angles defining the pump impeller blade shape were selected and a three-level full factorial design approach was used for efficiency enhancement. A three-dimensional simulation using Reynolds-averaged Navier Stokes (RANS) equations for the performance analysis was carried out after designing the geometries of the impellers at the design points. Standard $k-{\varepsilon}$ turbulence model was used for steady incompressible flow simulations. The optimized impeller incurred lower losses by shifting the trailing edge towards the impeller pressure side. It is observed that the surrogates are problem dependent and most accurate surrogate does not deliver the best design always.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1543-1550
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• 2013

In this paper, we study Bayesian estimation for the finite population proportion in binary data under selection bias. We use a Bayesian nonignorable selection model to accommodate the selection mechanism. We compare four possible estimators of the finite population proportions based on data analysis as well as Monte Carlo simulation. It turns out that nonignorable selection model might be useful for weekly biased samples.

• Management Science and Financial Engineering
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• v.18 no.2
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• pp.13-17
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• 2012

Set covering has widely been accepted as a staple tool for feature selection in data mining. We present a generalized version of this classical combinatorial optimization model to make it better suited for the purpose and propose a surrogate relaxation-based procedure for its meta-heuristic solution. Mathematically and also numerically with experiments on 25 set covering instances, we demonstrate the utility of the proposed model and the proposed solution method.

• Earthquakes and Structures
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• v.20 no.1
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• pp.109-122
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• 2021

Significant progress in the oil and gas industry advances the application of pipeline into an intelligent era, which poses rigorous requirements on pipeline safety, reliability, and maintainability, especially when crossing seismic zones. In general, strike-slip faults are prone to induce large deformation leading to local buckling and global rupture eventually. To evaluate the performance and safety of pipelines in this situation, numerical simulations are proved to be a relatively accurate and reliable technique based on the built-in physical models and advanced grid technology. However, the computational cost is prohibitive, so one has to wait for a long time to attain a calculation result for complex large-scale pipelines. In this manuscript, an efficient and accurate surrogate model based on machine learning is proposed for strain demand prediction of buried X80 pipelines subjected to strike-slip faults. Specifically, the support vector regression model serves as a surrogate model to learn the high-dimensional nonlinear relationship which maps multiple input variables, including pipe geometries, internal pressures, and strike-slip displacements, to output variables (namely tensile strains and compressive strains). The effectiveness and efficiency of the proposed method are validated by numerical studies considering different effects caused by structural sizes, internal pressure, and strike-slip movements.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.304-309
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• 2017

This paper studies a nonpremixed turbulent flame in a model scramjet combustor using zonal hybrid RANS/LES method. The numerical domain is divided into two region, RANS and LES region. The interface between the two regions is treated with synthetic eddy method. A model scramjet combustor experimented at German aerospace center is selected for the comparative study. The fuel injection of cracked kerosene surrogate which is composed of ethylene and methane is considered. Turbulent combustion of cracked kerosene surrogate is achieved using flamelet approach.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.1-14
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• 2011

The surrogate safety assessment model which was developed based on the conflict theory by FHWA in the US is software to analyze traffic conflicts using the individual vehicle trajectory data from a microscopic traffic simulation model. This study aims at assessing the safety of different signal control strategies, including pre-time and actuated signal control, using the SSAM. To this end, this study effort has developed a microscopic traffic simulation model using VISSIM through a field study, and then produced the surrogate measures, including TTC, PET, DR, MaxS and DeltaS, and the numbers of conflicts, including rear-end, right angle and lane-changing conflicts. The assessment results indicated that the actuated signal control may produce more conflicts in terms of rear-end conflicts. The use of SSAM in the safety assessments for diverse traffic alternatives in a safe and fast way may contribute to the improvement of safety in the roadway transportation.