• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.3
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• pp.397-410
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• 2023

This study examined the efficacy of various chlorinating agents in partitioning light water reactor spent fuel, with the aim of optimizing the chlorination process. Through thermodynamic equilibrium calculations, we assessed the outcomes of employing MgCl₂, NH₄Cl, and Cl₂ as chlorinating agents. A comparison was drawn between using a single agent and a sequential approach involving all three agents (MgCl₂, NH₄Cl, and Cl₂). Following heat treatment, the utilization of MgCl₂ as the sole chlorinating agent resulted in a moderate separation. Specifically, this method yielded a solid separation with 96.9% mass retention, 31.7% radioactivity, and 44.2% decay heat, relative to the initial spent fuel. In contrast, the sequential application of the chlorinating agents following heat treatment led to a final solid separation characterized by 93.1% mass retention, 5.1% radioactivity, and 15.4% decay heat, relative to the original spent fuel. The findings underscore the potential effectiveness of a sequential chlorination strategy for partitioning spent fuel. This approach holds promise as a standalone technique or as a complementary process alongside other partitioning processes such as pyroprocessing. Overall, our findings contribute to the advancement of spent fuel management strategies.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.103-115
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• 2022

The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.892-902
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• 2009

An efficient sequential optimization approach for metamodel was presented by Choi et al. This paper describes a new approach of the multilevel optimization method studied in Refs. [2] and [20,21]. The basic idea is concerned with multilevel iterative methods which combine a descent scheme with a hierarchy of auxiliary problems in lower dimensional subspaces. After fitting a metamodel based on an initial space filling design, this model is sequentially refined by the expected improvement criterion. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to understand and use. As a check on effectiveness, the proposed method is applied to an engineering example.

• Korean Management Science Review
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• v.23 no.3
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• pp.13-25
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• 2006

To reduce the signaling tost of paging in mobile communication, sequential paging schemes are proposed by partitioning a location area into several paging areas such that each area is paged sequentially. Necessary conditions for the optimal partition of cells with delay bound are examined by considering the mobiles location probability at each cell. The Optimal Cell Partitioning (OCP) is proposed based on the necessary conditions and the fathoming rule which trims off the unnecessary solution space and expedite the search process. Two Heuristics, BSG and BNC are also presented to further increase the computational efficiency in real-world paging scheme for the next generation mobile systems. The effectiveness of the 1)reposed paging schemes is illustrated with computational results. The Heuristic BSG that performs the search in the most promising solution group outperforms the best existing procedure with the 6-69% gain in paging cost in problems with 100 cells.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.2
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• pp.10-21
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• 1998

In this paper, we analyze the problems of conventional and previous mehtod on delay test method in IEEE 1149.1. To solve them, we propose two kinds of delay test architectures. One is called ARCH-C, is for combinatonal circuit, and the other is ARCH-S, for clocked sequential circuit. ARCH-C is able to detect delay defect of 0.5 $T_{tck}$ or 1 $T_{tck}$ size. And ARCH-C have a fixed and small amount of hardware overhead, on the contrary preious method has a hardware overhead on the dependent of CUT. This paper discusses weveral problems of Delay test on IEEE 1149.1 for clocked sequential circuit. We suggest the method called ARCH-S, is based on a clock counting technique to generate continuous clocked input of CUT. the simulation results ascertain the accurate operation and effectiveness of the proposed architectures.res.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.1041-1049
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• 2003

In this paper, a new local two-point approximation method which is based on the exponential intervening variable is proposed. This new algorithm, called the Two-Point Convex Approximation(TPCA), use the function and design sensitivity information from the current and previous design points of the sequential approximate optimization to generate a sequence of convex, separable subproblems. This paper describes the derivation of the parameters associated with the approximation and the numerical solution procedure. In order to show the numerical performance of the proposed method, a sequential approximate optimizer is developed and applied to solve several typical design problems. These optimization results are compared with those of other optimizers. Numerical results obtained from the test examples demonstrate the effectiveness of the proposed method.

• Journal of the Ergonomics Society of Korea
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• v.21 no.1
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• pp.1-14
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• 2002

The main purpose of this paper is to present selection criteria for ROK Airforce pilot training candidates in order to save costs involved in sequential pilot training. We use classification models such Decision Tree, Logistic Regression and Neural Network based on aptitude test results of 288 ROK Air Force applicants in 1994-1996. Different models are compared in terms of classification accuracy, ROC and Lift-value. Neural network is evaluated as the best model for each sequential flight test result while Logistic regression model outperforms the rest of them for discriminating the last flight test result. Therefore we suggest a pilot selection criterion based on this logistic regression. Overall. we find that the factors such as Attention Sharing, Speed Tracking, Machine Comprehension and Instrument Reading Ability having significant effects on the flight results. We expect that the use of our criteria can increase the effectiveness of flight resources.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.636-638
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• 2003

This paper presents a new approach which is able to determine the reasonable incentive levels of direct load control using sequential Monte Carlo simulation techniques. The economic analysis needs to determine the reasonable incentive level. However, the conventional methods have been based on the scenario methods because they had not considered all cases of the direct load control situations. To overcome there problems, this paper proposes a new technique using sequential Monte Carlo simulation. The Monte Carlo method is a simple and flexible tool to consider large scale systems and complex models for the components of the system. To show its effectiveness, numerical studies were performed to indicate the possible applications of the proposed technique.

• Journal of the military operations research society of Korea
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• v.3 no.1
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• pp.137-150
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• 1977

The effectiveness of an actual combat tank system is analyzed. A measure of effectiveness which includes performance and reliability called pseudo-reliability is introduced. A model is introduced to optimize the design of the system in which the system pseudo-reliability is maximized subject to cost constraint. This model is a nonlinear programming problem and is solved by the sequential unconstrained minimization technique (SUMT). A numerical exampl with actual data from the test evaluation of five combat tanks is used to illustrate the model.

• Journal of Mechanical Science and Technology
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• v.16 no.2
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• pp.203-210
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• 2002

For effective response surface modeling during sequential approximate optimization (SAO), the normalized and the augmented D-optimality criteria are presented. The normalized D-optimality criterion uses the normalized Fisher information matrix by its diagonal terms in order to obtain a balance among the linear-order and higher-order terms. Then, it is augmented to directly include other experimental designs or the pre-sampled designs. This augmentation enables the trust region managed sequential approximate optimization to directly use the pre-sampled designs in the overlapped trust regions in constructing the new response surface models. In order to show the effectiveness of the normalized and the augmented D-optimality criteria, following two comparisons are performed. First, the information surface of the normalized D-optimal design is compared with those of the original D-optimal design. Second, a trust-region managed sequential approximate optimizer having three D-optimal designs is developed and three design problems are solved. These comparisons show that the normalized D-optimal design gives more rotatable designs than the original D-optimal design, and the augmented D-optimal design can reduce the number of analyses by 30% - 40% than the original D-optimal design.