• Nuclear Engineering and Technology
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• v.38 no.6
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• pp.483-488
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• 2006

Highly radioactive waste is placed in metal canisters embedded in dense clay termed buffer. The radioactive decay is associated with heat production, which causes degradation of the buffer and thereby time-dependent loss of its waste-isolating potential. The buffer is prepared by compacting air-dry smectite clay powder and is initially not fully water saturated. The evolution of the buffer starts with slow wetting by uptake of water from the surrounding rock followed by a long period of exposure to heat, pressure from the rock and chemical reactants. It can be described by conceptual and theoretical models describing processes related to temperature (T), hydraulic (H), mechanical (M) and chemical performance (C). For temperatures below 90 C more than 75 % of the smectite will be preserved for 100 000 years but cementation may reduce the excellent performance of the buffer to a yet not known extention.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.12
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• pp.685-697
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• 2001

Cache memories are small fast memories used to temporarily hold the contents of main memory that are likely to be referenced by processors so as to reduce instruction and data access time. In this paper, we represent analytical models of instruction fetch process for four types of instruction cache structures that can be used for superscalar processors. In the models, we define various kinds of architectural parameters and take cache miss and branch misprediction into consideration. To prove the correctness of the proposed models, we performed extensive simulations and compared the results with the analytical models. Simulation results showed that the proposed model can estimate the instruction fetch rate accurately within 10% error in most cases. Both analytical model and simulation show that the increase of cache misses reduces the instruction fetch rate more severely than that of branch misprediction does. However, the analytical model can explain the causes of performance degradation which cannot be uncovered by the simulation method only. The model is also able to provide exact relationship between cache miss and branch misprediction for instruction fetch analysis.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.596-604
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• 2016

In this study, we used a stochastic approach for guaranteeing the reliability and robustness of the performance with regard to the design of polymer components, while taking into consideration the degradation properties and operating conditions in automobiles. Creep and tensile tests were performed for obtaining degradation properties. The Prony series, which described the viscoelastic models, were calculated to use the creep data by the Maxwell fluid model. We obtained the stress data from the frequency response analysis of the polymer components while considering the degradation properties. Limit state functions are generated by using these data. Reliability assessments are conducted under the variation of the degradation properties and area of frequency at peak response. For this study, the input parameters are assumed to be a normal distribution, and the reliability under the yield stress criteria is evaluated by using the Monte Carlo Simulation. As a result, the reliabilities, according to the three types of polymer materials in automotive components, are compared to each other and suggested the applicable possibility of polymeric materials in automobiles.

• Steel and Composite Structures
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• v.46 no.3
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• pp.385-401
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• 2023

Steel is becoming increasingly popular due to its high strength, excellent ductility, great assembly performance, and recyclability. In reality, steel structures serving for a long time in atmospheric, industrial, and marine environments inevitably suffer from corrosion, which significantly decreases the durability and the service life with the exposure time. For the mechanical properties of corroded steel, experimental studies are mainly conducted. The existing numerical analyses only evaluate the mechanical properties based on corroded morphology at the isolated time-in-point, ignoring that this morphology varies continuously with corrosion time. To solve this problem, the relationships between pit depth expectation, standard deviation, and corrosion time are initially constructed based on a large amount of wet-dry cyclic accelerated test data. Successively, based on that, an in-situ pitting evolution method for evaluating the residual tensile strength of corroded steel is proposed. To verify the method, 20 repeated simulations of mass loss rates and mechanical properties are adopted against the test results. Then, numerical analyses are conducted on 135 models of corrosion pits with different aspect ratios and uneven corrosion degree on two corroded surfaces. Results show that the power function with exponents of 1.483 and 1.091 can well describe the increase in pit depth expectation and standard deviation with corrosion time, respectively. The effect of the commonly used pit aspect ratios of 0.10-0.25 on yield strength and ultimate strength is negligible. Besides, pit number ratio α equating to 0.6 is the critical value for the strength degradation. When α is less than 0.6, the pit number increases with α, accelerating the degradation of strength. Otherwise, the strength degradation is weakened. In addition, a power function model is adopted to characterize the degradation of yield strength and ultimate strength with corrosion time, which is revised by initial steel plate thickness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.355-363
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• 2005

This paper is discussed about the technology of the performance enhancement in the wireless communication between indoor and outdoor environments. In the outdoor wireless communication, the signal has mainly a severe degradation by the fading effect of channel, but that problem may be overcome by using ordinary multiple antenna technology and array signal processing algorithm. Hence, since the channel has the characteristics of both fading and angle spread in the wireless communication between indoor and outdoor, the ordinary technology cannot solve the signal degradation due to the angle spread. In order to solve the problem, in this paper, the characteristic of the wireless channel between indoor and outdoor is first analyzed and considered the channel models fit to that case. We propose the new multiple antenna algorithm by use of mean steering vector concept, and obtained the results of the performance enhancement. With the results of the performance analyses through of the numerical study and computer simulation, we show that the proposed algorithm has more enhanced signal to noise ratio than the previous algorithm.

• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.24-31
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• 1994

In this paper, we study continuous speech recognition of Korean language using acoustic models of word juncture coarticulation. To alleviate the performance degradation due to coarticulation problems, we use context-dependent units that model inter-word transitions in addition to intra-word transitions. In all cases the initial phone of each word has to be specified for each possible final phone of the previous word similarly for the final phone of each word. To improve the robustness of the HMM parameters, the covariance matrix is smoothed. We also use position-dependent units to improve the discriminative power between units. Simulation results show that when the improved models of word juncture coarticulation are used. the recognition performance is considerably improved compared to the baseline system using only intra-word units.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1181-1188
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• 2021

When abnormal events occur in a nuclear power plant, operators must conduct appropriate abnormal operating procedures. It is burdensome though for operators to choose the appropriate procedure considering the numerous main plant parameters and hundreds of alarms that should be judged in a short time. Recently, various research has applied deep-learning algorithms to support this problem by classifying each abnormal condition with high accuracy. Most of these models are trained with simulator data because of a lack of plant data for abnormal states, and as such, developed models may not have tolerance for plant data in actual situations. In this study, two approaches are investigated for a deep-learning model trained with simulator data to overcome the performance degradation caused by noise in actual plant data. First, a preprocessing method using several filters was employed to smooth the test data noise, and second, a data augmentation method was applied to increase the acceptability of the untrained data. Results of this study confirm that the combination of these two approaches can enable high model performance even in the presence of noisy data as in real plants.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.217-230
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• 2014

The purpose of this study is to develop the Generalized Depreciation Function (GDF) and Winfrey Depreciation Function (WDF) by reviewing methods for the depreciation accountings. The Depreciation Accounting Models (DAM), including straight-line model, declining-balance model, sum-of-the-year-digit model and sinking fund model presented in this paper, are reclassified into the charging pattern of increasing type, decreasing type and constant type. This paper also discusses the development of the GDFs based on convex type, concave type and constant type according to the demand pattern of product, frequency of plant usage, deterioration of time, relative inadequacy, Capital Expenditure (CAPEX) and Operating Expenditure (OPEX) of the Total Productive Maintenance (TPM). The WDFs presented in this paper depict a sudden degradation of plant performance by measuring the change of TPM activity at the midpoint of useful life of asset. The WDFs are classified into left-modal type, symmetrical type and right-modal type by varying the value of skewness and kurtosis. Moreover, three increasing patterns, such as convex, concave and linear types, are used in this paper to present the distinct identification of WFDs by using Instantaneous Depreciation Rate (IDR) in terms of Performance Depreciation Function (PDF) and Depreciation Density Function (DDF). In order to have better understanding of depreciation models, the numerical examples are used for evaluating the Net Operating Less Adjusted Tax (NOPLAT) and Economic Value Added (EVA). It is concluded that the depreciation models showing a large dispersion of EVA require the adjustment of NOPLAT and Invested Capital (IC) based on the objective cash basis and net operating activity for reducing the variation of EVA.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1458-1467
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• 1999

Existing index structures such as extendable hashing and B+-tree do not support partial string searches perfectly. The inverted file method and the signature file method that are used in the web retrieval engine also have problems that they do not provide partial string searches and suffer from serious retrieval performance degradation respectively. In this paper, we propose an efficient index method that supports partial string searches and achieves good retrieval performance. The proposed index method is based on the Inverted file structure. It constructs the index file with patterns that result from dividing terms by two syllables to support partial string searches. We analyze the characteristics of our proposed method through simulation experiments using wide range of parameter values. We analyze the derive analytic performance evaluation models of the existing inverted file method, signature file method and the proposed index method in terms of retrieval time and storage overhead. We show through performance comparison based on analytic models that the proposed method significantly improves retrieval performance over the existing method.

• Steel and Composite Structures
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• v.23 no.3
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• pp.303-315
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• 2017

This paper describes the finite element model for predicting the fundamental performance of embedded steel column base connections under monotonic and cyclic loading. Geometric and material nonlinearities were included in the proposed finite element model. Bauschinger and pinching effects were considered in the simulation of embedded column base connections under cyclic loading. The degradation of steel yield strength and accumulation of plastic damage can be well simulated. The accuracy of the finite element model is examined by comparing the predicted results with independent experimental dataset. It is demonstrated that the finite element model accurately predicts the behaviour and failure models of the embedded steel column base connections. The finite element model is extended to carry out evaluations and parametric studies. The investigated parameters include column embedded length, concrete strength, axial load and base plate thickness. Moreover, analytical models for predicting the initial stiffness and bending moment strength of the embedded column base connection were developed. The comparison between results from analytical models and those from experiments and finite element analysis proved the developed analytical model was accurate and conservative for design purposes.