• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.405-414
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• 2012

In this paper, we propose a reliability estimation method for DI&C systems. At the system level, a fault tree model is suggested and Boolean algebra is used to obtain the minimal cut sets. At the component level, an exponential distribution is used to model hardware failures, and Bayesian estimation is suggested to estimate the failure rate. Additionally, a binomial distribution is used to model software failures, and a recently developed software reliability estimation method is suggested to estimate the software failure rate. The overall system reliability is then estimated based on minimal cut sets, hardware failure rates and software failure rates.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.279-290
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• 2005

The purpose of this study is to attempt a Analysis of a pointed-end Equipment Arm Safety-Accident for Fault Tree Analysis. Three major techniques were used first problem is Z-Model by which accident Analysis & prevention of a pointed-end Industry can be made, Fault Tree Analysis(FTA) bywhich quantification of a pointed-end Equipment accident Analysis can be made it 5 years in past and the third, manual-written by which minimal cut set to accident can be Identified. A example has been made of issue point a pointed-end Equipment that the Arm in loader happen to Injuries. According to the Analysis lack of safety knowledge, unsafety-behavior seem to be the primal cause of accident. Comparision of the accident cause to actual report demonstratesthat the FTA a efficient tool for Industrial Accident prevention.

• Nuclear Engineering and Technology
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• v.24 no.1
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• pp.14-29
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• 1992

COMCAF, a computer code for the common-cause failure analysis, is developed to treat the common-cause failures in nuclear power plants. In the treatment of common-cause failures, the minimal cut sets of the system are obtained first without changing the fault-tree structure. The occurrence probabilities of the minimal cut sets are then calculated accounting for the common-cause failures among components in the same minimal cut set or in different minimal cut sets. The basic parameter model is used to model the common-cause failures between similar or identical components. For dissimilar components, the assumption of symmetry used in the basic parameter model is applied to the basic events affecting two or more components. The top event probability is evaluated using the inclusion-exclusion method. In addition to the common-cause failures of components in the same minimal cut sets, failures of components in the different minimal cut sets are also easily accounted for by this method. This study applied this common-cause failure analysis to the PWR auxiliary feedwater system. The results in the top event probability for the system are compared with those of no common-cause failures.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.105-111
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• 1995

The inverse dynamic equations for 5 link robot including a closed chain have been derived. The closed chain is virtually cut open, and the kinematics and dynamics of the virtual open chain robot are analyzed. The constraints are applied to the virtually cut joints by the Jacobian matrix which represents the configuration of the closed chain. The topology of tree structrued open chain robot is described by a FATHER array. The FATHER array of a link indicates the link tha tis connected in the direction of base link. Based on the inverse dynamic equations, the torque sensitivity models of the 5 link robot have been developed. The sensitivity models characterize the sensitivity of the driving torque with respect to the link parameters. All the procedures are illustrated through the 2 link robot.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.405-414
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• 2011

Korean grammar checkers typically detect context-dependent errors by employing heuristic rules that are manually formulated by a language expert. These rules are appended each time a new error pattern is detected. However, such grammar checkers are not consistent. In order to resolve this shortcoming, we propose new method for generalizing error decision rules to detect the above errors. For this purpose, we use an existing thesaurus KorLex, which is the Korean version of Princeton WordNet. KorLex has hierarchical word senses for nouns, but does not contain any information about the relationships between cases in a sentence. Through the Tree Cut Model and the MDL(minimum description length) model based on information theory, we extract noun classes from KorLex and generalize error decision rules from these noun classes. In order to verify the accuracy of the new method in an experiment, we extracted nouns used as an object of the four predicates usually confused from a large corpus, and subsequently extracted noun classes from these nouns. We found that the number of error decision rules generalized from these noun classes has decreased to about 64.8%. In conclusion, the precision of our grammar checker exceeds that of conventional ones by 6.2%.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.138-141
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• 1979

The purpose of this paper is to develop an efficient model for the analysis of a John's Chopper Circuit. In the John's Chopper Circuit analysis, the open branches are removed from the associated graph to formulate the modified incidence matrix. An algorithm for the generation of a modified proper tree and fundamental cut set matrix from a network graph is developed, which utilizes much less computer storage space and computation time compared to the classical methods.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.66-73
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• 2021

This report documents the results of an at-power internal events Level 1 Probabilistic Safety Assessment (PSA) for a Korea research reactor (KRR). The aim of the study is to determine the accident sequences, construct an internal level 1 PSA model, and estimate the core damage frequency (CDF). The accident quantification is performed using the AIMS-PSA software version 1.2c along with a fault tree reliability evaluation expert (FTREX) quantification engine. The KRR PSA model is quantified using a cut-off value of 1.0E-15/yr to eliminate the non-effective minimal cut sets (MCSs). The final result indicates a point estimate of 4.55E-06/yr for the overall CDF attributable to internal initiating events in the core damage state for the KRR. Loss of Electric Power (LOEP) is the predominant contributor to the total CDF via a single initiating event (3.68E-6/yr), providing 80.9% of the CDF. The second largest contributor is the beam tube loss of coolant accident (LOCA), which accounts for 9.9% (4.49E-07/yr) of the CDF.

• Journal of Korea Foresty Energy
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• v.21 no.1
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• pp.25-31
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• 2002

This study was carried out to estimate aboveground biomass and net primary production in an average 37-year-old Quercus acutissima stand of Pohang area. Ten sample trees were cut in the forest and soil samples were collected in August, 2001. Estimation for aboveground biomass and net primary production was made by the equation model Wt=$aD^b$ where Wt is ovendry weight in kg and D is DBH in cm. Total aboveground biomass was 115.47ton/ha in the study forest. The proportion of each tree component to total aboveground biomass was high in order of bolewood(63.9%), branches(19.8%), bolebark(16.2%) and leaves(1.2%) in the study forest. Aboveground total net primary production was estimated at 7.89ton/ha in the study area. The proportion of each tree component to total net primary production was high in order of bolewood, bolebark, branch, and leaves.

• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.87-95
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• 2011

The urgent VAI(Vital Area Identification) method development is required since 'The Act of Physical Protection and Radiological Emergency' that is established in 2003 requires an evaluation of physical threats in nuclear facilities and an establishment of physical protection in Korea. The KAERI(Korea Atomic Energy Research Institute) has developed the VAI methodology and VAI software called as VIPEX(Vital area Identification Package EXpert) for identifying the vital areas. This study is to demonstrate the applicability of KAERI's VAI methodology to a hypothetical facility, and to identify the importance of information of cable and piping runs when identifying the vital areas. It is necessarily needed to consider cable and piping runs to determine the accurate and realistic TEPS(Top Event Prevention Set). If the information of cable and piping runs of a nuclear power plant is not considered when determining the TEPSs, it is absolutely impossible to acquire the complete TEPSs, and the results could be distorted by missing it. The VIPEX and FTREX(Fault Tree Reliability Evaluation eXpert) properly calculate MCSs and TEPSs using the fault tree model, and provide the most cost-effective method to save the VAI and physical protection costs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.