• Journal of Korean Society for Quality Management
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• v.33 no.1
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• pp.51-63
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• 2005

This paper presents the investigation on the demand of domestic companies for reliability. For persons undertaking reliability tasks of 224 companies, the questionnaire study is made to investigate the importance and necessity of reliability, needs and priorities of reliability manuals, and the appropriate scheme to propagate them by internet and telephone. By analyzing the responses according to fields of industry, types of manufacturing, numbers of employees, and total sales, we obtained the useful informations for developing and propagating reliability manuals.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.27-36
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• 2001

This Paper proposes a new methodology for assessing the reliability of an accident management, which Is based on the reliability physics and the scheme to generate dynamic event tree. The methodology consists of 3 main steps: screening; uncertainty propagation; and probability estimation. Sensitivity analysis is used for screening the variables of significance. Latin Hypercube sampling technique and MAAP code are used for uncertainty propagation, and the dynamic event tree generation method is used for the estimation of non-success probability of implementing an accident management strategy. This approach is applied in assessing the non-success probability of implementing a cavity flooding strategy, which is to supply water into the reactor cavity using emergency fire systems during the sequence of station blackout at the reference plant.

• Journal of Ship and Ocean Technology
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• v.9 no.1
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• pp.64-71
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• 2005

In probabilistic design, the challenge is to estimate the uncertainty propagation, since outputs of subsystems at lower levels could constitute inputs of other systems or at higher levels of the multilevel systems. Three uncertainty propagation estimation techniques are compared in this paper in terms of numerical efficiency and accuracy: root sum square (linearization), distribution-based moment approximation, and Taguchi-based integration. When applied to reliability-based design optimization (RBDO) under uncertainty, it is investigated which type of applications each method is best suitable for. Two nonlinear analytical examples and one vehicle crashworthiness for side-impact simulation example are employed to investigate the unique features of the presented techniques for uncertainty propagation. This study aims at helping potential users to identify appropriate techniques for their applications in the multilevel design.

• Journal of KIISE:Information Networking
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• v.35 no.1
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• pp.1-10
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• 2008

Once the sensor node in wireless sensor networks is installed, it usually operates without human intervention for a long time. The remote code update scheme is required because it is difficult to recall the sensor node in many situations. Therefore, studies on the reliable and efficient transport protocol for code propagation in wireless sensor networks have been increasingly done. However, by considering only the stability aspect of transmission, most of previous works ignore the consideration on the fast code propagation. This results the energy inefficiency by consuming unnecessary energy due to the slow code propagation. In this paper, in order to overcome limitation of the previous code propagation protocols, we propose a new code propagation protocol called "FCPP(Fast Code Propagation Protocol)". The FCPP aims at improving the reliability at well as performance. For this purpose, the FCPP accomplishes the fast code propagation by using the RTT-based transmission rate control and NACK suppression scheme, which provides a better the network utilization and avoids a unnecessary transmission delay. Based on the ns-2 simulation result, we prove that the FCPP Improves significantly both reliability and performance.

• Journal of the Korean Ceramic Society
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• v.54 no.6
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• pp.492-498
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• 2017

A thermal barrier coating (TBC) with self-healing property for cracks was proposed to improve reliability during gas turbine operation, including structural design. Effect of healing agent on crack propagation behavior in TBCs with and without buffer layer was investigated through furnace cyclic test (FCT). Molybdenum disilicide ($MoSi_2$) was used as the healing agent; it was encapsulated using a mixture of tetraethyl orthosilicate and sodium methoxide. Buffer layers with composition ratios of 90 : 10 and 80 : 20 wt%, using yttria stabilized zirconia and $MoSi_2$, respectively, were prepared by air plasma spray process. After generating artificial cracks in TBC samples by using Vickers indentation, FCTs were conducted at $1100^{\circ}C$ for a dwell time of 40 min., followed by natural air cooling for 20 min. at room temperature. The cracks were healed in the buffer layer with the healing agent of $MoSi_2$, and it was found that the thermal reliability of TBC can be enhanced by introducing the buffer layer with healing agent in the top coat.

• International Journal of Reliability and Applications
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• v.10 no.1
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• pp.1-15
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• 2009

Even though the impact of manufacturing quality to reliability is not considered much as well as that of design area, a major cause of an early failure of the product is known as manufacturing problem. This research applies two different types of neural network algorithms, the Back propagation (BP) algorithm and Learning Vector Quantization (LVQ) algorithm, to identify and classify the nonrandom variation pattern on the control chart based on knowledge-based diagnosis of dimensional variation. The performance and efficiency of both algorithms are evaluated to choose the better pattern recognition system for auto body assembly process. To analyze hundred percent of the data obtained by Optical Coordinate Measurement Machine (OCMM), this research considers an application in which individual observations rather than subsample means are used. A case study for analysis of OCMM data in underbody assembly process is presented to demonstrate the proposed knowledge-based pattern recognition system.

• Journal of Power System Engineering
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• v.15 no.6
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• pp.73-80
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• 2011

The experimental investigation focuses on an influence of artificial aging time in longitudinal butt welded Al 6013-T4 aluminum alloy on the fatigue crack growth resistance. The preferred welding processes for this alloy are frequently tungsten inert gas welding (TIG) process due to its comparatively easier applicability and better weldability than other gas metal arc welding. Fatigue crack growth tests were carried out on compact tension specimens (CT) in longitudinal butt TIG welded after T82 heat treatment was varied in three artificial aging times of 6 hours, 18 hours and 24 hours. Of the three artificial aging times, 24 hours of artificial aging time are offering better resistance against the growing fatigue cracks. The superior fatigue crack growth resistance preferred spatial variation of materials within each specimen in the Paris equation based on reliability theory and fatigue crack growth rate by crack length are found to be the reasons for superior fatigue resistance of 24 hours of artificial aging time was compared to other joints. The highest of crack propagation resistance occurs in artificial aging times of 24 hours due to the increase in grain size (fine grained microstructures).

• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.228-240
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• 1991

Many experimental data of fatigue crack propagation show that the fatigue crack propagation process is stochastic. Therefore, the study on the crack propagation must be based on the probabilistic approach. In the present paper, fatigue crack propagation process is assumed to be a discrete Markov process and the method is developed, which can evaluate the reliability of the structural component by using Markov chain model(Unit step B-model) suggested by Bogdanoff. In this method, leak failure, plastic collapse and brittle fracture of the critical component are taken as failure modes, and the effects of initial crack distribution, periodic and non-periodic inspection on the probability of failure are considered. In this method, an equivalent load value for random loading such as wave load is used to facilitate the analysis. Finally some calculations are carried out in order to show the usefulness and the applicability of this method. And then some remarks on this method are mentioned.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.