• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2395-2406
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• 2023

To study the influence of parameter uncertainty in small pressurized water reactor (SPWR) once-through steam generator (OTSG), the nonlinear mathematical model of the SPWR is firstly established. Including the reactor core model, the OTSG model and the pressurizer model. Secondly, a control strategy that both the reactor core coolant average temperature and the secondary-side outlet pressure of the OTSG are constant is adopted. Then, the uncertainty quantification method is established based on Latin hypercube sampling and statistical method. On this basis, the quantitative platform for parameter uncertainty of the OTSG is developed. Finally, taking the uncertainty in primary-side flowrate of the OTSG as an example, the platform application work is carried out under the variable load in SPWR and step disturbance of secondary-side flowrate of the OTSG. The results show that the maximum uncertainty in the critical output parameters is acceptable for SPWR.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2221-2234
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• 1997

Distributed mutual exclusion algorithms have employed two approaches to achieve mutual exclusion and can be divided into two broad classes:token-based and permission-based. Token-based algorithms share a unique token among the nodes and a node is allowed to access its common resources if it possesses the token. Permission-based algorithms require one or more successive rounds of message exchanges among the nodes to obtain the permission to access the common resources. A hypercube architecture has earned wide acceptance in multiprocessor systems in the past few years because of its simple, yet rich topology. Accordingly, we study distributed permission-based mutual exclusion algorithms for hypercubes, and design a distributed permission-based mutual exclusion algorithm based on a new information structure adapted to the hypercubes. The new information structure is a request set of T-pattern from a logical mesh that is embedded into a hypercube. If a node wants to access the common resources, it sends request message to all nodes in the request set by Lan's multicast algorithm. Once the node receives a grant message from all nodes in the request set, it accesses the common resource. We evaluate our algorithm with respect to minimum round-trip delay, blocking delay, and the number of messages per access to the common resource.

• Journal of Korea Water Resources Association
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• v.38 no.4 s.153
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• pp.281-292
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• 2005

The water balance analysis for the long-term water resources plan is a simple calculation that compares water demands with possible water supplies. For a watershed being considered the reports on the performance of the water balance analysis, however, have shown inconsistent results and thus have not earned credibility due to the uncertainty of the data acquired and models used. In this research, uncertainties in the water scarcity estimate were assessed through probability representation based on the Monte Carlo simulation using Latin Hypercube Sampling (LHS). The natural flow, municipal demand, industrial demand, agricultural demand, and return flow rate were selected as representative input variables for the water balance analysis, and their distributions were set based on the linear regression and the entropy theory. The statistical properties of the output variable samples were analyzed in comparison with a deterministic estimate of the water scarcity of an existing study. Application of LHS to three sub-basins of the Geum river basin showed the deterministic estimate could be overestimated or underestimated. The sensitivity analysis as well as the uncertainty analysis found that the return flow rate of the agricultural water is the most uncertain but is rarely sensitive to the output of the water balance analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1065-1071
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• 2012

Wind energy is becoming one of the most preferable alternatives to conventional sources of electric power that rely on fossil fuels. For stable electric power generation, constant rotating speed control of a wind turbine is performed through pitch control and stall control of the turbine blades. Recently, variable pitch control has been implemented in modern wind turbines to harvest more energy at variable wind speeds that are even lower than the rated one. Although wind turbine pitch controllers are currently optimized using a step response via the Ziegler-Nichols auto-tuning process, this approach does not satisfy the requirements of variable pitch control. In this study, the variable pitch controller was optimized by a genetic algorithm using a neural network model that was constructed by the Latin Hypercube sampling method to improve the Ziegler-Nichols auto-tuning process. The optimized solution shows that the root mean square error, rise time, and settle time are respectively improved by more than 7.64%, 15.8%, and 15.3% compared with the corresponding initial solutions obtained by the Ziegler-Nichols auto-tuning process.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.878-880
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• 2003

대부분의 진단 알고리즘은 PMC 모델을 바탕으로 결함의 개수가 t개를 초과하지 않는다는 t-진단가능 시스템의 특성을 이용한다. 하지만, 병렬처리 시스템의 규모가 커짐에 따라 시스템 내에서 발생되는 결함의 빈도가 높아지게 된다. 즉, 진단 알고리즘에서 가정하는 결함의 개수 t는 병렬처리 시스템 안에 있는 노드의 수에 비해 상당히 작은 개수이며, 결함의 개수가 t를 초과할 경우는 거의 고려하지 않았다. 본 논문에서는 결함의 개수가 t개를 초과하는 경우에 대하여 진단의 정확여부를 판단할 수 없는 충분히 작은 개수의 노드가 존재한다는 것을 허락함으로서, 진단 가능한 결함의 최대 수를 증가시키는 알고리즘을 제안한다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.23-29
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• 1992

In this paper, a method of representing the pattern classifier as a collection of hypercubic regions is proposed. This representation has following advantages over the conventional ones : 1) a simple form of human knowledge can be used in designing the classifier, 2) the form of the classifier is suit for the rule-based system, and 3) this can reduce the classification time. A method of synthesis of the classifier under this representation is also proposed and the experimental result shows that the proposed method is faster than the well-known nearest neighbor classifier.

• Journal of the Chungcheong Mathematical Society
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• v.6 no.1
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• pp.139-155
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• 1993

A new sequential algorithm and computational results for large-scale linear programs with a special structure were presented in the previous paper [9]. In this paper, a parallel version of the algorithm was developed for a hypercube multiprocessor architecture NCUBE2. Computational results using 128 processors are presented for a randomly generated large-scale sparse or dense problems with the number of variables up to 256 and constraints up to 5 million.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.462-465
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• 2006

This paper is aimed at proposing the sampling method to reduce variance of statistical parameters in uncertainty analysis of concrete structures. The proposed method is a modification of Latin Hypercube sampling method. This uses specially modified tables of random permutations of rank number. Also, the Spearman coefficient is used to make modified tables. Numerical analysis is carried out to predict the uncertainty of axial shortening in prestressed concrete bridge. The numerical results show that the method is efficient for uncertainty analysis of complex structural system such as prestressed concrete bridges.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05b
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• pp.659-664
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• 1998

The importance of input wariables of real-time accident consequence assessment model has been analyzed. Partial correlation coefficients of input variables related to the plume and the ingestion exposure have been estimated using latino hypercube sampling technique. It is known that wind speed and growth dilution rate are the most important variable in plume and ingestion exposure, respectively.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.577-582
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• 2007

A continuum structure function (CSF) is a non-decreasing mapping from the unit hypercube to the unit interval. A B-type CSF, defined in the text, is a CSF whose behaviour is modeled by its underlying binary structures. As the measure of importance of a system component for a B-type CSF, the structural and reliability importance of a component at a system level ${\alpha}$(0 < ${\alpha}$ < 1) are defined and their properties are deduced.