• Smart Structures and Systems
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• v.14 no.2
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• pp.145-158
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• 2014

The objective of this study is to improve the survivability and reliability of the FBG sensor network in the structural health monitoring (SHM) system. Therefore, a model reconstruction soft computing recognition algorithm based on support vector regression (SVR) is proposed to achieve the high reliability of the FBG sensor network, and the grid search algorithm is used to optimize the parameters of SVR model. Furthermore, in order to demonstrate the effectiveness of the proposed model reconstruction algorithm, a SHM system based on an eight-point fiber Bragg grating (FBG) sensor network is designed to monitor the foreign-object low velocity impact of a CFRP composite plate. Simultaneously, some sensors data are neglected to simulate different kinds of FBG sensor network failure modes, the predicting results are compared with non-reconstruction for the same failure mode. The comparative results indicate that the performance of the model reconstruction recognition algorithm based on SVR has more excellence than that of non-reconstruction, and the model reconstruction algorithm almost keeps the consistent predicting accuracy when no sensor, one sensor and two sensors are invalid in the FBG sensor network, thus the reliability is improved when there are FBG sensors are invalid in the structural health monitoring system.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1130-1135
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• 2003

The need to increase the reliability of a structural system has been significantly brought in the procedure of real designs to consider, for instance, the material properties or geometric dimensions that reveal a random or incompletely known nature. Reliability based design optimization of a real system now becomes an emerging technique to achieve reliability, robustness and safety of these problems. Finite element analysis program and the reliability analysis program are necessary to evaluate the responses and the probabilities of failure of the system, respectively. Moreover, integration of these programs is required during the procedure of reliability based design optimization. It is well known that reliability based design optimization can often have so many local minima that it cannot converge to the specified probability of failure. To overcome this problem, barrier function method in reliability based design optimization is suggested. To illustrate the proposed formulation, reliability based design optimization of a bracket is performed. AMV and FORM are employed for reliability analysis and their optimization results are compared based on the accuracy and efficiency.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.1
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• pp.69-76
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• 2017

In this study, design of a small hybrid rocket is carried out using Failure Mode and Effects Analysis (FMEA) and Criticality Analysis(CA), which is a method for qualitative and semi-quantitative reliability analysis. In order to carry out FMEA, the structure of the hybrid rocket is divided into 31 parts and 72 potential failure modes. As a result of the FMEA, the relationship between potential failure modes, causes and effects, and their severity are evaluated qualitatively. Criticality analysis is followed for the failure modes, in which the criticality number is estimated using the failure rate information available from the handbook. Moreover, the failure modes with higher criticality and severity are chosen for improvement, and a series of design or material changes are made for the improvement of the hybrid rocket reliability.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.3
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• pp.157-163
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• 2022

An automatic mooring system for a ship consists of a vacuum suction pad and a mechanical part, enabling quick and safe mooring of a ship. In the development of a mooring system, the design of a vacuum suction pad is a key to secure enough mooring forces and achieve stable operation of a mooring system. In the vacuum suction pad, properly designing its rubber seal determines the performance of the suction pad. Therefore, it is necessary to appropriately design the rubber seal for maintaining a high-vacuum condition inside the pad as well as achieving its mechanical robustness for long-time use. Finite element analysis for the design of the rubber seal requires the use of an appropriate strain energy function model to accurately simulate mechanical behavior of the rubber seal material. In this study, we conducted simple uniaxial tensile testing of Chloroprene Rubber (CR) to explore the strain energy function model best-fitted to its experimentally measured engineering strain-stress curves depending on various temperature environments. This study elucidates the temperature-dependent mechanical behaviors of CR and will be foundational to design rubber seal for an automatic mooring system under various temperature conditions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.870-877
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• 2009

This study provides how the Dimension Reduction (DR) method as an efficient technique for reliability analysis can acquire its increased efficiency when it is applied to highly nonlinear problems. In the highly nonlinear engineering systems, 4N+1 (N: number of random variables) sampling is generally recognized to be appropriate. However, there exists uncertainty concerning the standard for judgment of non-linearity of the system as well as possibility of diverse degrees of non-linearity according to each of the random variables. In this regard, this study judged the linearity individually on each random variable after 2N+1 sampling. If high non-linearity appeared, 2 additional sampling was administered on each random variable to apply the DR method. The applications of the proposed sampling to the examples produced the constant results with increased efficiency.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.55-69
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• 2009

A quasi ideal importance sampling simulation method combined in the conditional expectation is proposed for the structural reliability estimation. The quasi ideal importance sampling joint probability density function (p.d.f.) is so composed on the basis of the ideal importance sampling concept as to be proportional to the conditional failure probability multiplied by the p.d.f. of the sampling variables. The respective marginal p.d.f.s of the ideal importance sampling joint p.d.f. are determined numerically by the simulations and partly by the piecewise integrations. The quasi ideal importance sampling simulations combined in the conditional expectation are executed to estimate the failure probabilities of structures with multiple failure surfaces and it is shown that the proposed method gives accurate estimations efficiently.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.25-28
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• 2001

Recently, STI(Shallow Trench Isolation) process has attracted attention for high density of semiconductor device as a essential isolation technology. Without applying the conventional complex reverse moat process, CMP(Chemical Mechanical Polishing) has established the Process simplification. However, STI-CMP process have various defects such as nitride residue, torn oxide defect, damage of silicon active region, etc. To solve this problem, in this paper, we discussed to determine the control limit of process, which can entirely remove oxide on nitride from the moat area of high density as reducing the damage of moat area and minimizing dishing effect in the large field area. We, also, evaluated the reliability and reproducibility of STI-CMP process through the optimal process conditions.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2257-2264
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• 1994

A method to evaluate the position performance for a stochastically defined planar robot manipulator is presented. Performance is defined as the operational reliability based upon the positional errors of the manipulator tip. An analytical method is developed and applied to a two-link robot manipulator through forward kinematics. This study includes uncertainties in the link length, pin center location and radial clearance. By virtue of the effective link length model, only the nominal manipulator model and statistical information on the uncertainties are required. The results from the analytical method is compared to those from the Monte Carlo simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.113-120
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• 2007

Design optimization of layered plates bonding process is conducted by considering uncertainties in a manufacturing process, in order to reduce the crack failure arising due to the residual stress at the surface of the adherent which is caused by different thermal expansion coefficients. Robust optimization is peformed to minimize the mean as well as its variance of the residual stress, while constraining the distortion as well as the instantaneous maximum stress under the allowable reliability limits. In this optimization, the dimension reduction (DR) method is employed to quantify the reliability such as mean and variance of the layered plate bonding. It is expected that the DR method benefits the optimization from the perspectives of efficiency, accuracy, and simplicity. The obtained robust optimal solution is verified by the Monte Carlo simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.12 s.255
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• pp.1534-1542
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• 2006

In this paper, the concept of accelerated life test, which is a popular research field nowadays, is applied to the shot peened material. To predict the efficient and exact room temperature fatigue characteristics from the high temperature fatigue data, the adequate accelerated model is investigated. Ono type rotary bending fatigue tester and high temperature chamber were used for the experiment. Room temperature fatigue lives were predicted by applying accelerated models and doing reliability evaluation. Room temperature fatigue tests were accomplished to check the effectiveness of predicted data and the adequate accelerated life test models were presented by considering errors. Experimental result using Arrhenius model, fatigue limit obtain almost 5.45% of error, inverse power law has about 1.36% of error, so we found that inverse power law is applied well to temperature-life relative of shot peened material.