• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.82-91
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• 1998

This paper presents a neural networks based approach for the problem of sensor failure detection and accommodation for ship without physical redundancy in the sensors. The designed model consists of two neural networks. The first neural network is responsible for the failure detection and the second neural network is responsible for the failure identification and accommodation. On the yaw rate sensor of ship, simulation results indicates that the proposed method can be useful as failure detector and sensor estimator.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.2096-2101
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• 1999

This paper presents the effect of shape of external corrosion in pipeline on failure prediction by using numerical simulation. The numerical study for the pipeline failure analysis is based on the FEM(Finite Element Method) with an elastic-plastic and large-deformation analysis. The predicted failure stress assessed for the simulated corrosion defects having different corroded shapes along the pipeline axis are compared with those by methods specified in ANSl/ASME B31G code and a modified B31G code.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.13 no.1
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• pp.40-47
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• 2017

In this paper, we investigate the feasibility of a strategy of failure detection and identification. The point of proposed strategy includes a pattern extraction approach for failure identification using Auto-Associative Kernel Regression (AAKR). We consider a simulation data concerning 605 signals of a Generic Pressurized Water Reactor(GPWR). In the application, the reconstructions are provided by a set of AAKR models, whose input signals have been selected by Correlation Analysis(CA) for the identification of the groups. The failure pattern is extracted by analyzing the residuals of observations and reconstructions. We present the possibility of extraction of patterns for six failure.

• Journal of the Korean Society of Safety
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• v.25 no.6
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• pp.1-8
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• 2010

P-PIE program is developed for evaluating failure probability of pipes in nuclear power plants based on the existing PRAISE program. In the program, crack growth due to fatigue loading and stress corrosion can be considered and the probability of fracture or leakage of pipes can be calculated. Crack growth simulation is performed based on stress intensity factor and a damage parameter and failure of a pipe is determined based on J integral or net section yielding. Using the developed program the failure probabilities of tubes in a domestic nuclear power is obtained and discussed.

• International Journal of Reliability and Applications
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• v.13 no.2
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• pp.91-104
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• 2012

Sarhan and Kundu (2009) introduced a new distribution named as the generalized linear failure rate distribution. This distribution generalizes several well known distributions. The probability density function of the generalized linear failure rate distribution can be right skewed or unimodal and its hazard function can be increasing, decreasing or bathtub shaped. This distribution can be used quite effectively to analyze lifetime data in place of linear failure rate, generalized exponential and generalized Rayleigh distributions. In this paper, we apply the simulated annealing algorithm to obtain the maximum likelihood point estimates of the parameters of the generalized linear failure rate distribution. Simulated annealing algorithm can not only find the global optimum; it is also less likely to fail because it is a very robust algorithm. The estimators obtained using simulated annealing algorithm have been compared with the corresponding traditional maximum likelihood estimators for their risks.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1052-1059
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• 2018

This paper deals with commutation failure of the line-commutated converter high voltage direct current (LCC HVDC) system caused by a three phase fault in the ac power system. An analytic calculation method is proposed to estimate the maximum permissible voltage drop at the LCC HVDC station on various operating point and to assess the area of vulnerability for commutation failure (AOV-CF) in the power system based on the residual phase voltage equation. The concept is extended to multi-infeed HVDC power system as the area of severity for simultaneous commutation failure (AOS-CF). In addition, this paper presents the implementation of a shunt compensator applying to the proposed method. An analysis and simulation have been performed with the IEEE 57 bus sample power system and the Jeju island power system in Korea.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.409-416
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• 2005

Design analysis for underground spaces requires evaluating stability related to tunnel collapses. A failure mode is one of the critical factors in the conventional methods of stability analysis. Therefore identification of failure modes is essential in securing safe construction in the phase of design analysis, instrumentation planning and implementation of reinforcing measures. In this study failure modes at the tunnel heading in granular soils are investigated using physical model tests and numerical simulation for various tunnel depths and ground surface inclinations. Test results indicated that the effect of depth and inclination of ground surface on a failure mode are significant. It is identified that, with an incase in depth, failure modes become localized in a region close to the tunnel. It is also known that an increase in the inclination of ground surface results in inclined and wide failure modes.

• Convergence Security Journal
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• v.8 no.2
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• pp.35-40
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• 2008

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. The used software failure time data for forecasting failure time is random number of Weibull distribution(shaper parameter 1, scale parameter 0.5), Using this data, we are proposed to ARIMA(AR(1)) and simulation method for forecasting failure time. The practical ARIMA method is presented.

• Journal of the Korean GEO-environmental Society
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• v.17 no.5
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• pp.5-16
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• 2016

A rainfall induced slope failure is a common natural hazard in mountainous areas worldwide. Sudden and rapid failures which have a high possibility of occurrence in a steep slope are always the most dangerous due to their suddenness and high velocities. Based on a series of experiments this study aimed to determine a critical angle which could be considered as an approximate threshold for a sudden failure. The experiments were performed using 0.42 mm mean grain size sand in a 200 cm long, 60 cm wide and 50 cm deep rectangular flume. A numerical model was created by integrating a 2D seepage flow model and a 2D slope stability analysis model to predict the failure surface and the time of occurrence. The results showed that, the failure mode for the entire material will be sudden for slopes greater than $67^{\circ}$; in contrast the failure mode becomes retrogressive. There is no clear link between the degree of saturation and the mode of failure. The simulation results in considering matric suction showed good matching with the results obtained from experiment. A subsequent discarding of the matric suction effect in calculating safety factors will result in a deeper predicted failure surface and an incorrect predicted time of occurrence.

• Smart Structures and Systems
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• v.33 no.3
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• pp.177-188
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• 2024

The fatigue-induced sequential failure of a structure having structural redundancy requires system-level analysis to account for stress redistribution. System reliability-based design optimization (SRBDO) for preventing fatigue-initiated structural failure is numerically costly owing to the inclusion of probabilistic constraints. This study incorporates the Branch-and-Bound method employing system reliability Bounds (termed the B³ method), a failure-path structural system reliability analysis approach, with a metaheuristic optimization algorithm, namely grey wolf optimization (GWO), to obtain the optimal design of structures under fatigue-induced system failure. To further improve the efficiency of this new optimization framework, an additional bounding rule is proposed in the context of SRBDO against fatigue using the B³ method. To demonstrate the proposed method, it is applied to complex problems, a multilayer Daniels system and a three-dimensional tripod jacket structure. The system failure probability of the optimal design is confirmed to be below the target threshold and verified using Monte Carlo simulation. At earlier stages of the optimization, a smaller number of limit-state function evaluation is required, which increases the efficiency. In addition, the proposed method can allocate limited materials throughout the structure optimally so that the optimally-designed structure has a relatively large number of failure paths with similar failure probability.