• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.331-338
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• 2013

A new reliability calculation method is proposed based on design sensitivity analysis by the finite element method for nonlinear performance constraints in the optimal design of electromagnetic devices. In the proposed method, the reliability of a given design is calculated by using the Monte Carlo simulation (MCS) method after approximating a constraint function to a linear one in the confidence interval with the help of its sensitivity information. The validity and numerical efficiency of the proposed sensitivity-assisted MCS method are investigated by comparing its numerical results with those obtained by using the conventional MCS method and the first-order reliability method for analytic functions and the TEAM Workshop Problem 22.

• Computers and Concrete
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• v.13 no.5
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• pp.659-677
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• 2014

A Bayesian response surface updating procedure is applied in order to update the parameters of the covariance function of a random field for concrete properties based on a limited number of available measurements. Formulas as well as a numerical algorithm are presented in order to update the parameters of response surfaces using Markov Chain Monte Carlo simulations. The parameters of the covariance function are often based on some kind of expert judgment due the lack of sufficient measurement data. However, a Bayesian updating technique enables to estimate the parameters of the covariance function more rigorously and with less ambiguity. Prior information can be incorporated in the form of vague or informative priors. The proposed estimation procedure is evaluated through numerical simulations and compared to the commonly used least square method.

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.463-482
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• 1994

In Bayesian analysis of randomized response models, the likelihood function does not combine tractably with typical priors for the parameters of interest, causing computational difficulties in posterior analysis of the parameters of interest. In this article, the difficulties are solved by introducing appropriate latent variables to the model and using the Gibbs sampling algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.654-657
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• 1988

In the existing GFCS (Gun Fire Control Systems) there is sometimes the problem of the miss distance which is between a target and the projectiles from gun and cannot be neglected. This errors are difficult to reduce either in the gun design phase or by precalibration exercise. In this paper the CLSA (Closed Loop Spotting Algorithm) which is applied to improve the performance of the GFCS is porposed and analysed. The results simulated by Monte Carlo technics show us better performance than the existing GFCS.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.33-41
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• 1999

The original tolerances, which are assigned by designers on the basis of handbooks and experience, cannot always be expected to be optimal or feasible, because they may yield an unacceptable manufacturing costs. So the systematic tolerance design considering manufacturing costs should be done. Therefore, this research analyzes the tolerance within the tolerance design using Monte-Carlo simulation method and sensitivity analysis and using genetic algorithm by tolerance allocation method. The genetic algorithm was developed for allocation of the optimal tolerance under the manufacturing limitation cost.

• Earthquakes and Structures
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• v.7 no.2
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• pp.119-139
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• 2014

A new method is proposed for random vibration anaylsis of hysteretic systems subjected to non-stationary random excitations. With the Bouc-Wen model, motion equations of hysteretic systems are first transformed into quasi-linear equations by applying the concept of equivalent excitations and decoupling of the real and hysteretic displacements, and the derived equation system can be solved by either the precise time integration or the Newmark-${\beta}$ integration method. Combining the numerical solution of the auxiliary differential equation for hysteretic displacements, an explicit iteration algorithm is then developed for the dynamic response analysis of hysteretic systems. Because the computational cost for a large number of deterministic analyses of hysteretic systems can be significantly reduced, Monte-Carlo simulation using the explicit iteration algorithm is now viable, and statistical characteristics of the non-stationary random responses of a hysteretic system can be obtained. Numerical examples are presented to show the accuracy and efficiency of the present approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.852-857
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• 2013

In this paper we propose a design algorithm for nonbinary LDPC (low-density parity-check) codes with low error-floors. The proposed algorithm determines the nonbinary values of the nonzero entries in the parity-check matrix in order to maximize the binary minimum distance of the designed nonbinary LDPC codes. We verify the performance of the designed nonbinary LDPC codes in the error-floor region by Monte Carlo simulation and importance sampling over BPSK (binary phase-shift keying) modulation.

• Advances in robotics research
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• v.2 no.2
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• pp.161-182
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• 2018

This paper proposes a novel receding horizon control (RHC) algorithm for formation control of a swarm of unmanned surface vehicles (USVs) using particle swarm optimization (PSO). The proposed control algorithm provides the coordinated path tracking of multi-agent USVs while preventing collisions and considering external disturbances such as ocean currents. A three degrees-of-freedom kinematic model of the USV is used for the RHC with guaranteed stability and convergence by incorporating a sequential Monte Carlo (SMC)-based particle initialization. An ocean current model-based estimator is designed to compensate for the effect of ocean currents on the USVs. This method is compared with the PSO-based RHC algorithms to demonstrate the performance of the formation control and the collision avoidance in the presence of ocean currents through numerical simulations.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.119-126
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• 2005

Load bearing structural members in a wide variety of applications accumulate damage over their service life. From a standpoint of both safety and performance, it is desirable to monitor the occurrence, location, and extent of such damage. Structures require complicated element models with a number of degrees of freedom in structural analysis. During experiment much effort and cost is needed for measuring structural parameters. The sparseness and errors of measured data have to be considered during the parameter estimation Of Structures. In this paper we introduces damage identification algorithm by a system identification(S.I) using static and dynamic response. To study the behaviour of the estimators in noisy environment Using Monte Carlo simulation and a data measured perturbation scheme is adopted to investigate the influence of measurement errors on identification results. The assessment result by static and dynamic response were compared, and the efficiency and applicabilities of the proposed algorithm are demonstrated through simulated static and dynamic responses of a truss bridge. The assessment results by each method were compared and we could observe that the 5.1 method is superior to the other conventional methods.

• Structural Engineering and Mechanics
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• v.47 no.2
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• pp.167-183
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• 2013

Methods for estimating structural reliability using probability ideas are well established. When the residual ultimate strength of a buried pipeline is exceeded the limit, breakage becomes imminent and the overall reliability of the pipe distribution network is reduced. This paper is concerned with estimating structural failure of underground flexible pipes due to corrosion induced excessive deflection, buckling, wall thrust and bending stress subject to externally applied loading. With changes of pipe wall thickness due to corrosion, the moment of inertia and the cross-sectional area of pipe wall are directly changed with time. Consequently, the chance of survival or the reliability of the pipe material is decreased over time. One numerical example has been presented for a buried steel pipe to predict the probability of failure using Hasofer-Lind and Rackwitz-Fiessler algorithm and Monte Carlo simulation. Then the parametric study and sensitivity analysis have been conducted on the reliability of pipeline with different influencing factors, e.g. pipe thickness, diameter, backfill height etc.