• 한국자기학회지
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• 제23권2호
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• pp.62-67
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• 2013

본 논문에서는 전자기 관련 제품의 효율적인 신뢰도 기반 최적설계를 위해 확률구속조건을 평가하는 기법으로 해의 안정성과 효율성이 우수한 목표 성능치법을 제시 하였다. 목표 성능치법을 적용한 신뢰도 기반 최적설계의 효율성 검증을 위하여 스피커 모델과 초전도 자기에너지 저장장치 모델에 대한 최적설계를 수행하였고, 이를 기존 신뢰도 지수법을 적용한 최적설계 결과와 비교하였다. 또한 몬테카를로 수치모사기법을 이용하여 도출된 최적해의 신뢰도를 재 계산 후 비교함으로써 제안된 기법의 신뢰도 평가 결과의 정밀도를 검증하였다.

• 전산구조공학
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• 제4권2호
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• pp.119-129
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• 1991

본 논문은 교량구조의 체계신뢰도를 추정하기 위한 효율적인 중요도 표본추출기법의 개발을 목적으로 한다. 기존의 체계신뢰성 해석을 위한 방법은 1차 모멘트법, 2차 모멘트법, AFOSM 근사해법, 그리고 시뮬레이션 방법등이 있다. 중요도 표본추출기법은 아주 적은 경비와 노력으로 정확한 해를 구하는 시뮬레이션 방법이다. 적용 예를 통하여 중요도 표본추출기법은 교량구조의 체계신뢰성해석에 아주 효과적인 방법임을 알 수 있었다.

• Wind and Structures
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• 제27권5호
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• pp.283-291
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• 2018

This study presents the reliability assessment of a 100.5 m tall reinforced concrete chimney at a glass factory under wind loading by using vibration-based identified modal values. Ambient vibration measurements were recorded and modal values such as frequencies, shapes and damping ratios were identified by using Enhanced Frequency Domain Decomposition (EFDD) method. Afterwards, Finite Element Model (FEM) of the chimney was verified based on identified modal parameters. Reliability assessment of the chimney under wind loading was performed by obtaining the exceedance probability of demand to capacity distribution. Demand distribution of the chimney was developed under repetitive seeds of multivariate stochastic wind fields generated along the height of chimney. Capacity distribution of the chimney was developed by Monte Carlo simulation. Finally, it was found that reliability of the chimney is lower than code suggested limit values.

• Structural Engineering and Mechanics
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• 제84권3호
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.

• 전기학회논문지
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• 제60권7호
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• pp.1314-1323
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• 2011

The maintenance of generating units is implicitly related with power system reliability and has a tremendous bearing on the operation of the power system. A technique using a fuzzy search method which is based on fuzzy multi-criteria function has been proposed for GMS (generator maintenance scheduling) in order to consider multi-objective function. In this study, a new technique using combined fuzzy set theory and genetic algorithm(GA) is proposed for generator maintenance scheduling. The genetic algorithm(GA) is expected to make up for that fuzzy search method might search the local solution. The effectiveness of the proposed approach is demonstrated by the simulation results on a practical size test systems.

• 콘크리트학회논문집
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• 제22권4호
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• pp.595-603
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• 2010

염소이온 침투를 받는 해양환경 콘크리트의 확률기반 내구수명 예측을 위해 몬테카를로 시뮬레이션 방법이 많이 사용된다. 그러나 몬테카를로 시뮬레이션 방법은 해석에 매우 긴 시간이 소요되며 해석결과도 매번 다른 결과를 준다. 이에 비해 신뢰성해석에 자주 사용되는 모멘트법은 계산에 소요되는 시간의 거의 없고, 동일문제에 대해서는 항상 동일한 결과를 주는 장점이 있다. 이에 이 연구에서는 신뢰성이론의 모멘트법을 염소이온 침투에 대한 부식개시확률 산정에 적용하였다. 이를 위해 먼저 일계이차 모멘트법과 이계이차 모멘트법에 의한 파괴확률 산정 프로그램을 개발하였다. 개발된 해석 프로그램들을 사용한 예제해석을 통하여 일계이차 모멘트법에 비하여 이계이차 모멘트법이 더 정확한 부식개시확률 산정결과를 줌을 확인하였다. 또 부식개시확률에 미치는 각 확률변수의 영향을 평가하는 민감도 해석을 수행하였으며, 가장 큰 영향인자는 피복두께로 나타났다. 특히 피복두께의 변동계수 변화에 의한 영향이 평균값 변화에 의한 영향 보다 더욱 현저함을 확인하였다.

• Advances in aircraft and spacecraft science
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• 제9권3호
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• pp.263-278
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• 2022

The time-varying structural reliability of an aeroelastic launch vehicle subjected to stochastic parameters is investigated. The launch vehicle structure is under the combined action of several stochastic loads that include aerodynamics, thrust as well as internal combustion pressure. The launch vehicle's main body structural flexibility is modeled via the normal mode shapes of a free-free Euler beam, where the aerodynamic loadings on the vehicle are due to force on each incremental section of the vehicle. The rigid and elastic coupled nonlinear equations of motion are derived following the Lagrangian approach that results in a complete aeroelastic simulation for the prediction of the instantaneous launch vehicle rigid-body motion as well as the body elastic deformations. Reliability analysis has been performed based on two distinct limit state functions, defined as the maximum launch vehicle tip elastic deformation and also the maximum allowable stress occurring along the launch vehicle total length. In this fashion, the time-dependent reliability problem can be converted into an equivalent time-invariant reliability problem. Subsequently, the first-order reliability method, as well as the Monte Carlo simulation schemes, are employed to determine and verify the aeroelastic launch vehicle dynamic failure probability for a given flight time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 정기총회 및 창립40주년기념 학술대회 학회본부
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• pp.193-196
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• 1987

We reported that hot electron phenomena in submicron nMOSFET by Monte Carlo method. In order to predict the influence of the hot electron effects on the device reliability, either simple analytical model or a complete two dimensional numerical simulation has been adopted. Results of numerical simulation, based on the static mobility model, may be inaccurate when gate length of MOSFET is scaled down to less than 1um. Most of device simulation packages utilize the static nobility model. Monte Carlo method based on stochastic analysis of carrier movement may be a powerful tool to characterize hot electrons. In this work, energy and velocity distribution of carriers were obtained to predict the relative degree of short channel effects for different device parameters. Our analysis shows a few interesting results when $V_{ds}$ is 5 volt, average electron energy does not increase with gate bias as evidenced by substrate current.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.877-888
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• 2021

The water entry behaviors of projectiles with different cone-headed angles were studied numerically, experimentally and theoretically, mainly focusing on the hydrodynamic impact in the initial stage. Based on MMALE algorithm, it was proposed a formula of impact deceleration, which relied on the initial entry velocity and cone-headed angle. Meanwhile, in order to verify the validity of the simulation model, experiments using accelerometer and high-speed camera were carried out, and their results were in a good agreement with simulation results. Also, theoretical calculation results of cavity diameter were compared with experiments and simulation results. It was observed that the simulation method had a good reliability, which would make forecast on impact deceleration in an engineering project.

• Geomechanics and Engineering
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• 제30권2호
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• pp.187-199
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• 2022

Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.