• Proceedings of the Korean Geotechical Society Conference
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• 1988.06c
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• pp.3-67
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• 1988

Model studies on the response of homgeneous earth embankment dams subjected to strike-slip fault movement have been penomed via centrifuge and finite element analysis. The centrifuge model tests have shown that crack development in earth embankment experiences two major patters: shear failure deep inside the embankment and tension failure near the surface. The shear rupture zone develops from the base level and propagates upward continuously in the transverse direction but allows no open leakage chnnel. The open tensile cracks develop near the surface of the embankment, but they disappear deep in the embankment. The functional relationship has been developed based on the results of the centrifuge model tests incorporating tile variables of amount of fault movement, embankment geometry, and crack propagation extent in earth des. This set of information can be used as a guide line to evaluate a "transient" safety of the duaged embankment subjected to strike-slip fault movement. The finite element analysis has supplemented the additional expluations on crack development behavior identified from the results of the centrifuge model tests. The bounding surface time-independent plasticity soil model was employed in the numerical analysis. Due to the assumption of continuum in the current version of the 3-D FEM code, the prediction of the soil structure response beyond the failure condition was not quantitatively accurate. However, the fundamental mechanism of crack development was qualitatively evaluated based on the stress analysis for the deformed soil elements of the damaged earth embankment. The tensile failure zone is identified when the minor principal stress of the deformed soil elements less than zero. The shear failure zone is identified when the stress state of the deformed soil elements is at the point where the critical state line intersects the bounding surface.g surface.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.9
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• pp.413-422
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• 2002

In a power plant, disturbance detection and diagnosis are massive and complex problems. Once a disturbance occurs, it can be either persistent, self cleared, cleared by the automatic controllers or propagated into another disturbance until it subsides in a new equilibrium or a stable state. In addition to the Physical complexity of the power plant structure itself, these dynamic behaviors of the disturbances further complicate the fault monitoring and diagnosis tasks. A data structure called a disturbance interrelation analysis graph(DIAG) is proposed in this paper, trying to capture, organize and better utilize the vast and interrelated knowledge required for power plant disturbance detection and diagnosis. The DIAG is a multi-layer directed AND/OR graph composed of 4 layers. Each layer includes vertices that represent components, disturbances, conditions and sensors respectively With the implementation of the DIAG, disturbances and their relationships can be conveniently represented and traced with modularized operations. All the cascaded disturbances following an initial triggering disturbance can be diagnosed in the context of that initial disturbance instead of diagnosing each of them as an individual disturbance. DIAG is applied to a typical cooling water system of a thermal power plant and its effectiveness is also demonstrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9A
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• pp.868-877
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• 2006

Sensor network applications need synchronized time to the highest degree such as object tracking, consistent state updates, duplicate detection, and temporal order delivery. In addition, reliability issues and fault tolerance in sophisticated sensor networks have become a critical area of research today. In this paper, we proposed a fault tolerant clock management scheme in sensor networks considering two cases of fault model such as network faults and clock faults. The proposed scheme restricts the propagation of synchronization error when there are clock faults of nodes such as rapid fluctuation, severe changes in drift rate, and so on. In addition, it handles topology changes. Simulation results show that the proposed method has about $1.5{\sim}2.0$ times better performance than TPSN in the presence of faults.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.04a
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• pp.245-249
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• 2007

In this study a model-based diagnostic method using the Neural Network was proposed for PW206C turbo shaft engine and performance model was developed by SIMULINK. Fault and test database to build the NN was obtained at various off-design operating range such as flight altitude, flight Mach number and gas generator rotational speed variation. According to the fault detection analysis results, it was confirmed that the proposed fault detection method could find well the fault of compressor, compressor turbine and power turbine at on-design point as well as off-design point conditions.

• Journal of the Korean Society of Propulsion Engineers
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• v.11 no.3
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• pp.29-34
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• 2007

In this study a model-based diagnostic method using the Neural Network was proposed for PW206C turbo shaft engine and performance model was developed by SIMULINK. Fault and test database to build the NN was obtained at various off-design operating range such as flight altitude, flight Mach number and gas generator rotational speed variation. According to the fault detection analysis results, it was confirmed that the proposed fault detection method could find well the fault of compressor, compressor turbine and power turbine at on-design point as well as off-design point conditions.

• 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.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.119-130
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• 2023

Among the various elements of probabilistic safety assessment (PSA), human failure events (HFEs) and their dependencies are major contributors to the quantification of risk of a nuclear power plant. Currently, the dependency among HFEs is reflected using a post-processing method in PSA, wherein several drawbacks, such as limited propagation of minimal cutsets through the fault tree and improper truncation of minimal cutsets exist. In this paper, we propose a method to model the HFE dependency directly in a fault tree using the if-then-else logic. The proposed method proved to be equivalent to the conventional post-processing method while addressing the drawbacks of the latter. We also developed a software tool to facilitate the implementation of the proposed method considering the need for modeling the dependency between multiple HFEs. We applied the proposed method to a specific case to demonstrate the drawbacks of the conventional post-processing method and the advantages of the proposed method. When applied appropriately under specific conditions, the direct fault-tree modeling of HFE dependency enhances the accuracy of the risk quantification and facilitates the analysis of minimal cutsets.

• Journal of KSNVE
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• v.8 no.5
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• pp.929-935
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• 1998

Safety diagnosis of electric train driving system is performed using vibration signals of running electric train. Safety diagnosis is tried on the viewpoints of the appreciation of superannuation and the fault diagnosis of motor, reduction gear and bogie. The appreciation of superannuation is checked by the vibration levels of driving parts and the fault diagnosis is done by analyzing the frequencies of the vibration signals which are measured directly from a running electric train. The results shows that the vibration levels of each parts increase as the train gets older and each parts have their own frequency patterns of the vibration. Vibration propagation path is also investigated using calculated the coherence value between bogie and driving system. As the results, it is known that vibration signal can be utilized successfully for the safety diagnosis of the driving part of electric train.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.1-9
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• 1994

This paper analyzes the faults and their mechanism of CMOS ICs using IDDQ testing technique and evalutes the reliability of the chips that fail this test. It is implemented by the three testing phases, initial test, burn-in and life test. Each testing phase includes the parametric test, functional test, IDDQ test and propagation delay test. It is shown that the short faults such as gate-oxide short, bridging can be only detected by IDDQ testing technique and the number of test patterns for this test technique is very few. After first burn-in, the IDDQ of some test chips is decreased, which is increased in conventional studies and in subsequent burn-in, the IDDQ of all test chips is stabilized. It is verified that the resistive short faults exist in the test chips and it is deteriorated with time and causes the logic fault. Also, the new testing technique which can easily detect the rsistive short fault is proposed.