• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4560-4570
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• 2022

Dynamic fault tree (DFT) and its related research methods have received extensive attention in safety analysis and reliability engineering. DFT can perform reliability modelling for systems with sequential correlation, resource sharing, and cold and hot spare parts. A technical modelling method of DFT is proposed for modelling ship collision accidents and loss-of-coolant accidents (LOCAs). Qualitative and quantitative analyses of DFT were carried out using the cutting sequence (CS)/extended cutting sequence (ECS) method. The results show nine types of dynamic fault failure modes in ship collision accidents, describing the fault propagation process of a dynamic system and reflect the dynamic changes of the entire accident system. The probability of a ship collision accident is 2.378 × 10^-9 by using CS. This failure mode cannot be expressed by a combination of basic events within the same event frame after an LOCA occurs in a marine nuclear reactor because the system contains warm spare parts. Therefore, the probability of losing reactor control was calculated as 8.125 × 10^-6 using the ECS. Compared with CS, ECS is more efficient considering expression and processing capabilities, and has a significant advantage considering cost.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.69-77
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• 2009

Stream service environment demands real-time query processing for voluminous data which are ceaselessly delivered from tremendous sources. Typical R-tree based query processing technologies cannot efficiently handle such situations, which require repetitive and inefficient exploration from the tree root on every data event. However, many stream data including sensor readings show high locality, which we exploit to reduce the search space of queries to explore. In this paper, we propose a query processing scheme exploiting the locality of stream data. From the simulation, we conclude that the proposed scheme performs much better than the traditional ones in terms of scalability and exploration efficiency.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.134-134
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• 2022

Streamflow forecasting plays a crucial role in water resource control, especially in highly urbanized areas that are very vulnerable to flooding during heavy rainfall event. In addition to providing the accurate prediction, the evaluation of effects and importance of the input predictors can contribute to water manager. Recently, machine learning techniques have applied their advantages for modeling complex and nonlinear hydrological processes. However, the techniques have not considered properly the importance and uncertainty of the predictor variables. To address these concerns, we applied the GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting and analyzing input predictors. The Jungrang urban basin was selected as a case study and a database was established based on 39 heavy rainfall events during 2003 and 2020 from the rain gauges and monitoring stations. For the goal of this study, we used a combination of inputs that included the areal rainfall of the subbasins at current time step and previous time steps and water level and streamflow of the stations at time step for multistep-ahead streamflow predictions. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. In addition, the GA-BART model could reasonably determine the relative importance of the input variables. The assessment might help water resource managers improve the accuracy of forecasts and early flood warnings in the basin.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.3
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• pp.75-80
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• 2002

In these days of severe struggle for existence, the world has changed a great deal to global and digital oriented period. The enterprises try to introduce new management and production system to adapt such a change. But, if the only new technologies are applied to an enterprise without definite analysis about manufacturing, failure fellows as a logical consequence. Hence, enterprise must analyze manufacturing system definitely and needs new methodologies to mitigate risk. This study suggests that the new approach, which is systems approach for process improvement, is organized to systems analysis, systems diagnosis, and systems verification. Systems analysis analyzes manufacturing systems with object-oriented methodology-UML(Unified Modeling language) from a point of product, process, and resource view. Systems diagnosis identifies the constraints to optimize the system through scientific management or TOC(Theory of constraints). Systems verification shows the solution with virtual manufacturing technique applied to the core problem which emerged from systems diagnosis. This research shows the artifacts to improve the productivity with the above methodology applied to forming shop. UML provides the definite tool for analysis and re-usability to adapt itself to environment easily. The logical tree of TOC represents logical tool to optimize the forming shop. Discrete event simulator-QUEST suggests the tool for making a decision to verify the optimized forming shop.

• Korean Journal of Ecology and Environment
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• v.35 no.1 s.97
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• pp.52-61
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• 2002

This research was conducted to evaluate the effect of forest management practices on pH and electrical conductivity to get fundamental information on water purification capacity after forest operation. Rainfall, throughfall and stemflow　were　sampled at the study sites which consist of Abies holophylla and Pinus koraiensis　in Gwangreung Experimental Forest for S months from May to November 1999. Mean pH of the throughfall of the beginning of the event was higher in management (thinning and pruning) sites of Abies holophylla and Pinus koraiensis stands than nonmanagement site of Abies holophylla and Pinus koraiensis stands. In addition, pH of the throughfall of the total amount of the event showed similar trends which are higher pH in the management sites compared with the non- management sites. This result indicates that managements such as thinning and pruning improve tree butler capacity of rainfall pH. According to the linear regression results, pH of the throughfall of the total amount of the event in non-management sites = 0.735${\times}$pH of the throughfall of the beginning of the event in non-management sites+1.849 ($R^2\;=\;0.82$) and pH of the throughfall of the total amount of the event in management sites= 0.863${\times}$pH of the throughfall of the beginning of the event in management sites +1.0242 ($R^2\;=\;0.87$). In case of stemflow pH, pH of the sternflow of the total amount of　the event in non-management sites = 0.53${\times}$pH of the stemflow of the beginning of　the event in non- management sites+2.7709 ($R^2\;=\;0.64$) and pH of the stemflow of the total amount of the event in management sites = 0.5854${\times}$pH of the stemflow of the beginning of the event in management sites+2.7045 ($R^2\;=\;0.65$). Electrical conductivity (EC) of the throughfall of the beginning and total amount of the event was highest in non- management site in Abies holophylla, followed by management sites in fsies Abies holophylla, non-management site in Pinus koraiensis, and management sites in Pinus koraiensis stands, respectively. According to the linear regression results, EC of the throughfall of the total amount of the event in non-managementsites = 0.4045${\times}$EC of the throughfall of the beginning of the event in non-management sites+26.766 ($R^2\;=\;0.69$) and EC of the throughfall of the total amount of the event in management sites = 0.6002${\times}$EC of the throughfall of the beginning of the event in management sites+8.0184 ($R^2\;=\;0.54$). In case of stemflow EC, EC of thestemflow of the total amount of the event in non-management sites = 0.6298${\times}$EC of the stemflow of the beginning of the event in non-management sites+11.582 ($R^2\;=\;0.72$) and pH of the stemflow of the total amount of the event in management sites =0.602${\times}$pH of the stemflow of the beginning of the event in management sites+20.783($R^2\;=\;0.49$).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.637-644
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• 2004

This paper proposes an expert system with the knowledge learning capability which can enhance the safety and effectiveness of substation operation in the automated substation as well as existing substation by inferring multiple events such as main transformer fault, busbar fault and main transformer work schedule under multiple inference mode and multiple objective mode and by considering totally the switch status and the main transformer operating constraints. Especially inference mode includes the local minimum tree search method and pattern recognition method to enhance the performance of real-time bus reconfiguration strategy. The inference engine of the expert system consists of intuitive inferencing part and logical inferencing part. The intuitive inferencing part offers the control strategy corresponding to the event which is most similar to the real event by searching based on a minimum distance classification method of pattern recognition methods. On the other hand, logical inferencing part makes real-time control strategy using real-time mode(best-first search method) when the intuitive inferencing is failed. Also, it builds up a knowledge base or appends a new knowledge to the knowledge base using pattern learning function. The expert system has main transformer fault, main transformer maintenance work and bus fault processing function. It is implemented as computer language, Visual C++ which has a dynamic programming function for implementing of inference engine and a MFC function for implementing of MMI. Finally, it's accuracy and effectiveness is proved by several event simulation works for a typical substation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1295-1304
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• 2010

This paper proposes a fault-tolerant data aggregation which provides energy efficient and reliable data collection in wireless sensor networks. The traditional aggregation scheme does not provide the countermeasure to packet loss or the countermeasure scheme requires a large amount of energy. The proposed scheme applies caching and re-transmission based on the track topology to the adaptive timeout scheduling. The proposed scheme uses a single-path routing based on the traditional tree topology at normal, which reduces the dissipated energy in sensor nodes without any countermeasure against packet loss. The proposed scheme, however, retransmits the lost packet using track topology under event occurrences in order to fulfill more accurate data aggregation. Extensive simulation work under various workloads has revealed that the proposed scheme decrease by 8% in terms of the dissipated energy and enhances data accuracy 41% when the potential of event occurrence exists as compared with TAG data aggregation. And the proposed scheme decrease by 53% in terms of the dissipated energy and shows a similar performance in data accuracy when the potential of event occurrence exists as compared with PERLA data aggregation.

• Nuclear Engineering and Technology
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• v.21 no.1
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• pp.1-11
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• 1989

Numerous losses of decay heat removal capability have occurred at U during stutodwn while its significance to safety is needless to say. A study is carried out as an attempt to assess what could be done to lower the frequency of these events and to mitigate their consequences in the unlikely event that one occurs. The shutdown risk model is developed and analyzed using Event/Fault Tree for the typical pressurized water reactor. The human cognitive reliability (HCR) model, two-stage bayesian approach and staircase function model are used to estimate human reliability, initiating event frequency and offsite power non-recovery probability given loss of offsite power, respectively. The results of this study indicate that the risk of a Pm at shutdown is not much lower than the risk when the plant is operating. By examining the dominant accident sequences obtained, several design deficiencies are identified and it is found that some proposed changes lead to significant reduction in core damage frequency due to loss of cooling events.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.11-22
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• 2009

For a wireless ad-hoc network, event routing algorithm of the publish/subscribe system is especially important for the performance of the system because of the dynamic characteristic and constraint network of its own. In this paper, we propose a new hybrid event routing algorithm. TopSim for efficient publish/subscribe system on the wireless ad-hoc network by extending the ShopParent algorithm by considering not only network overheads to choose a Parent of the publish/subscribe tree, but also topic similarity which is closeness of subscriptions. Our evaluation shows our proposed TopSim performs better for the case where a new joining node subscribed to the multiple topics and there is a node among Parent candidate nodes who subscribe to the ones in the list of multiple topics (related topics).

• Journal of the Korean Institute of Gas
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• v.9 no.4 s.29
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• pp.57-61
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• 2005

The objective of paper is to carry out a comparative Quantitative Risk Assessment (QRA) of two KOGAS tank designs using a fault tree methodology, a standard 'Full Containment' tank and a 'Membrane' tank. For the membrane tank, both the initial KOGAS design and 4 modified KOGAS designs have been assessed, giving six separate cases. In this paper, the frequencies of releases are quantified using a fault tree approach. For clarity in the analysis, and to ensure consistency, all cases have been quantified using the same fault tree. Logic within the fault tree is used to select each of the cases. Full quantification of risks is often difficult, owing to a lack of relevant failure data, but the aim of this study has been to be as quantitative as possible, with full transparency of failure information. The most significant general cause of external LNG leaks is predicted to be a seismic event, which has been quantified nominally. 4modified KOGAS desiens to Prevent damage of bottom membrane panels that was shown in preparatory estimation could quantitively confirm safety improvement. According to result, the predicted frequencies of an external LNG leak for the full containment and modified membrane tanks are very similar, failures due to dropped pumps are predicted to be significantly greater for the membrane tank with thickened plate than for the full containment tank.