• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1712-1720
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• 2017

In South Korea, minimum reserve rate, which is to satisfy reliability standard, has been determined by simulation result using WASP. But, it is still controversial whether the level of minimum reserve rate is adequate. Thus, in this study, various analyses of minimum reserve rate are being conducted. WASP uses the probabilistic simulation technique to evaluate whether reliability standard is satisfied. In this process, forced outage rate and maintenance periods of each generator play important roles. Especially, the long-term plan can be varied depending on how maintenance periods deal with. In order to model maintenance periods in the probabilistic simulation technique, WASP uses derating method. However, broad analyses have to be conducted because there are various ways including derating method to model maintenance periods which result in different results. Therefore, in this paper, 3 different maintenance outage rate modeling methods are applied to arbitrarily modeled system based on the basic plan for long-term electricity supply and demand of South Korea. Results show impact of each modeling method on minimum reserve rate.

• Journal of KIISE
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• v.42 no.7
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• pp.868-877
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• 2015

The barcode area extraction from images has been extensively studied, and existing methods exploit frequency characteristics or depend on the Hough transform (HT). However, the slantedness of the images and noise affects the performance of these approaches. Moreover, it is difficult to deal with the case where an image contains multiple barcodes. We therefore propose a barcode detection algorithm that is robust under such unfavorable conditions. The pre-processing step implements a probabilistic Hough transform to determine the areas that contain barcodes with a high probability, regardless of the slantedness, noise, and the number of instances. Then, a frequency component analysis extracts the barcodes. We successfully implemented the proposed system and performed a series of barcode extraction tests.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.138-145
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• 2019

With the application of digital technology to safety-critical infrastructures, cyber-attacks have emerged as one of the new dangerous threats. In safety-critical infrastructures such as a nuclear power plant (NPP), a cyber-attack could have serious consequences by initiating dangerous events or rendering important safety systems unavailable. Since a cyber-attack is conducted intentionally, numerous possible cases should be considered for developing a cyber security system, such as the attack paths, methods, and potential target systems. Therefore, prior to developing a risk-informed cyber security strategy, the importance of cyber-attacks and significant critical digital assets (CDAs) should be analyzed. In this work, an importance analysis method for cyber-attacks on an NPP was proposed using the probabilistic safety assessment (PSA) method. To develop an importance analysis framework for cyber-attacks, possible cyber-attacks were identified with failure modes, and a PSA model for cyber-attacks was developed. For case studies, the quantitative evaluations of cyber-attack scenarios were performed using the proposed method. By using quantitative importance of cyber-attacks and identifying significant CDAs that must be defended against cyber-attacks, it is possible to develop an efficient and reliable defense strategy against cyber-attacks on NPPs.

• Earthquakes and Structures
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• v.16 no.5
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• pp.523-532
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• 2019

Different types of gas reservoir such as Liquid Natural Gas (LNG) are among the strategic infrastructures, and have great importance for any government or their private owners. To keep the tank and its contents safe during earthquakes especially if the contents are of hazardous or flammable materials; using seismic protection systems such as base isolator can be considered as an effective solution. However, the major deficiency of this system can be the large deformation in the isolation level which may lead to the failure of bearing system. In this paper, as a solution, the efficacy of an optimally designed combined vibration control system, the combined laminated rubber isolator and rotational friction damper, is investigated to evaluate the enhancement of an existing metal tank response under both far- and near-field earthquakes. Responses like impulsive and convective accelerations, base shear, and sloshing height are studied herein. The probabilistic framework is used to consider the uncertainties in the structural modeling, as well as record-to-record variability. Due to the high calculation cost of probabilistic methods, a simplified structural model is used. By using the Mont-Carlo simulation approach, it is revealed that this combined isolation system is a highly reliable system which provides considerable enhancement in the performance of reservoir, not only leads to the reduction of probability of catastrophic failure of the tank but also decrease the reservoir damage during the earthquake. Moreover, the relative displacement of the isolation level is controlled very well by this combined system.

• Structural Engineering and Mechanics
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• v.81 no.4
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• pp.429-441
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• 2022

A probabilistic assessment of the seismic-excited buildings with a multiple-tuned-mass-damper (MTMD) system is carried out in the presence of uncertainties of the structural model, MTMD system, and the stochastic model of the seismic excitations. A free search optimization procedure of the individual mass, stiffness and, damping parameters of the MTMD system based on the snap-drift cuckoo search (SDCS) optimization algorithm is proposed for the optimal design of the MTMD system. Considering a 10-story structure in three cases equipped with single tuned mass damper (STMS), 5-TMD and 10-TMD, sensitivity analyses are carried out using Sobol' indices based on the Monte Carlo simulation (MCS) method. Considering different seismic performance levels, the reliability analyses are done using MCS and kriging-based MCS methods. The results show the maximum structural responses are more affected by changes in the PGA and the stiffness coefficients of the structural floors and TMDs. The results indicate the kriging-based MCS method can estimate the accurate amount of failure probability by spending less time than the MCS. The results also show the MTMD gives a significant reduction in the structural failure probability. The effect of the MTMD on the reduction of the failure probability is remarkable in the performance levels of life safety and collapse prevention. The maximum drift of floors may be reduced for the nominal structural system by increasing the TMDs, however, the complexity of the MTMD model and increasing its corresponding uncertainty sources can be caused a slight increase in the failure probability of the structure.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1420-1427
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• 2023

Seismic risk has received increased attention since the 2011 Fukushima accident in Japan. The seismic risk of a nuclear power plant is evaluated via seismic probabilistic safety assessment (PSA), for which several methods are available. Recently, the discrete approach has become widely used. This approximates the seismic risk by discretizing the ground motion level interval into a small number of subintervals with the expectation of providing a conservative result. The present study examines the effect of the number of subintervals upon the results of seismic risk quantification. It is demonstrated that a small number of subintervals may lead to either an underestimation or overestimation of the seismic risk depending on the ground motion level. The present paper also provides a method for finding the boundaries between overestimation and underestimation regions, and illustrates the effect of the number of subintervals upon the seismic risk evaluation with an example. By providing a method for determining the effect of a small number of subintervals upon the results of seismic risk quantification, the present study will assist seismic PSA analysts to determine the appropriate number of subintervals and to better understand seismic risk quantification.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2
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• pp.75-79
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• 2008

In this paper, we propose a novel speech enhancement technique using global soft decision (GSD) based on the probabilistic outputs of support vector machine (SVM). Generally, speech enhancement algorithms applied soft decision gain modification and noise power estimation have bettor performance than those employing hard decision. Especially, global speech absence probability (GSAP), which is known as an effective measure of the speech absence in each frame, has been adopted to SD-based speech enhancement methods. For this reason, we introduce a new GSAP estimated from the probabilistic output of SVM using sigmoid function. The performance of the proposed algorithm is evaluated by the PESQ and MOS test under various noise environments and yields better results compared with the conventional GSD scheme.

• Journal for History of Mathematics
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• v.35 no.2
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• pp.43-56
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• 2022

The 21st century world has experienced all-around changes from the 4th industrial revolution. In this developmental changes, artificial intelligence is at the heart, with data science adopting certain scientific methods and tools on data. It is necessary to investigate on the logic lying underneath the methods and tools. We look at the origins of logic, deduction and induction, and scientific methods, together with mathematical induction, probabilistic method and data science, and their meaning.

• Journal of the Korean Geotechnical Society
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• v.30 no.10
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• pp.5-18
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• 2014

Many regions around the world are vulnerable to rainfall-induced slope failures. A variety of methods have been proposed for revealing the mechanism of slope failure initiation. Current analysis methods, however, do not consider the effects of non-homogeneous soil profiles and variable hydraulic responses on rainfall-induced slope failures. In this study, probabilistic stability analyses were conducted for weathered residual soil slopes with different soil thickness overlying impermeable bedrock to study the rainfall-induced failure mechanisms depending on the soil thickness. A series of seepage and stability analyses of an infinite slope based on one-dimensional random fields were performed to consider the effects of uncertainty due to the spatial heterogeneity of hydraulic conductivity on the failure of unsaturated slopes due to rainfall infiltration. The results showed that a probabilistic framework can be used to efficiently consider various failure patterns caused by spatial variability of hydraulic conductivity in rainfall infiltration assessment for a infinite slope.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.61-69
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• 2010

The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.