• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1248-1257
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• 1999

MDDS는 디스크 시스템의 성능을 향상시키기 위해 하이퍼큐브의 각 노드에 디스크 블록들을 분산 저장하며, 인접한 노드에서 분산 저장하고 있는 디스크 블록을 중복 저장하고 있는 디스크 시스템이다. 본 논문에서는 디스크 서비스 시간을 분석하기 위한 선행 연구로서 소스 노드에서 생성된 디스크 서비스 요구 메시지가 디스크 서비스를 제공하는 목적 노드에 수신될 때까지의 시간인 전송 시간을 분석한다. 이러한 메시지의 전송 시간을 분석하기 위해 이 메시지가 링크를 통해 전송되지 못하고 대기할 확률인 전송 대기 확률을 분석한다. 이들 메시지의 전송 대기 확률을 분석하기 위해 메시지가 각 링크에서 전송되지 못하고 대기해야 하는 시간인 전송 대기 시간을 분석한다. 또 디스크 서비스 요구 메시지의 전송을 위해 링크가 사용되는 비를 분석하며, 메시지의 전송 대기 확률, 전송 대기 시간, 메시지 전송을 위해 링크가 사용될 비를 이용하여 디스크 서비스 요구 메시지의 전송 시간을 분석한다. Abstract Mirrored Declustering Disk System(MDDS) is the disk system to enhance the performance of disk system for hypercube. In MDDS, each node stores the disk blocks using the declustering technique. And the node also duplicates the disk blocks stored in neighboring nodes. In this paper, as the leading research for analyzing the disk service time, we analyze the transmission time of the disk service request message from the source node to the destination node. To analyze the transmission time of disk service request message, we analyze the probability of blocking the message related to the disk service request. For the analysis of the blocking probability, we analyze the blocking time at the link. We also analyze the rate at which the transmission link is used for transferring the disk service requests. And we analyze the transmission time of disk service request message by using the blocking probability, the blocking time, and the usage rate of link for transmitting the message.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.269-280
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• 2004

The Pyramid-Technique is based on mapping n-dimensional space data into one-dimensional data and expresses it as a B+-tree. By solving the problem of search time complexity the pyramid technique also prevents the effect of "phenomenon of dimensional curse" which is caused by treatment of hypercube range query in n-dimensional data space. The SPY-TEC applies the space division strategy in pyramid method and uses spherical range query suitable for similarity search so that Improves the search performance. However, nearest neighbor query is more efficient than range query because it is difficult to specify range in similarity search. Previously proposed index methods perform well only in the specific distribution of data. In this paper, we propose an efficient searching technique for nearest neighbor object using PdR-Tree suggested to improve the search performance for high dimensional data such as multimedia data. Test results, which uses simulation data with various distribution as well as real data, demonstrate that PdR-Tree surpasses both the Pyramid-Technique and SPY-TEC in views of search performance.rformance.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.7
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• pp.703-714
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• 2010

This paper describes the design optimization of a rotating rectangular channel with staggered arrays of pin-fins by Kriging metamodeling technique. Two non-dimensional variables, the ratio of the height to the diameter of the pin-fins and the ratio of the spacing between the pin-fins to the diameter of the pin-fins are chosen as the design variables. The objective function that is a linear combination of heat transfer and friction loss related terms with a weighting factor is selected for the optimization. To construct the Kriging model, objective function values at 20 training points generated by Latin hypercube sampling are evaluated by a three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis method with the SST turbulence model. The Kriging model predicts the objective function value that agrees well with the value calculated by the RANS analysis at the optimum point. The objective function is reduced by 11% by the optimization of the channel.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.8
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• pp.763-771
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• 2011

An optimization procedure for the design of a ventilation axial-flow fan is presented in this paper. Flow analyses of the preliminary fan are performed by solving three-dimensional Reynolds-averaged Navier-Stokes equations via a finite-volume solver with the shear-stress transport turbulence model as a turbulence closure. Three variables, the hub-to-tip ratio and the stagger angles at the mid and tip spans, are selected for the optimization. The Latin-hypercube sampling method as a design-of-experiments technique is used to generate twenty-five design points within the design space. and the weighted average surrogate models, WTA1, WTA2, and WTA3, are applied for find optimal designs. The results show that the efficiency is considerably enhanced.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.77-84
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• 2021

A sampling-based approach was devised as a nuclear seismic probabilistic risk assessment (SPRA) method to account for the partially correlated relationships between components. However, since this method is based on sampling, there is a limitation that a large number of samples must be extracted to estimate the results accurately. Thus, in this study, we suggest an effective approach to improve the existing sampling method. The main features of this approach are as follows. In place of the existing Monte Carlo sampling (MCS) approach, the Latin hypercube sampling (LHS) method that enables effective sampling in multiple dimensions is introduced to the SPRA method. In addition, the degree of segmentation of the seismic intensity is determined with respect to the final seismic risk result. By applying the suggested approach to an actual nuclear power plant as an example, the accuracy of the results were observed to be almost similar to those of the existing method, but the efficiency was increased by a factor of two in terms of the total number of samples extracted. In addition, it was confirmed that the LHS-based method improves the accuracy of the solution in a small sampling region.