• Journal of the KSME
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• v.54 no.2
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• pp.35-40
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• 2014

이 글에서는 나노재료의 멀티스케일 해석에 있어서 재료 구성/조성의 불확실성과 해석 모델의 불확실성을 고려하는 통계적 접근의 중요성과 그 방법에 대해 소개하고자 한다.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.81-81
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• 2011

현재 국내에서 사용하고 있는 교량구조물의 성능평가방법으로는 크게 공용하중에 대한 내하율을 구하기 위하여 허용응력개념이나 강도설계 개념을 적용한 내하력 평가 기법이 사용되고 있다. 그러나 위의 방법들은 일반적으로 공용연수의 경과에 따른 재료 및 구조적 성능의 손실과 여러 가지 하중 및 환경적 요인들의 불확실성으로 인하여 발생하는 손상 및 열화를 반영하기 어렵다. 그리고 제원 및 재료물성치의 불확실성에 대한 기존 설계 자료의 DB 부족으로 기존의 평가방법에서는 이러한 시간의 경과에 따른 성능저하를 정확히 산정할 수 없어 이론상의 값과 실제 구조물과의 차이로 인한 불확실성이 존재 한다. 이에 본 연구에서는 공용년수 경과에 따른 시설물의 재료 구조적인 성능 및 거동분석 수행, 신뢰성 해석 수행을 바탕으로 교량 안전성 평가의 합리성 및 현실성을 제고하며, 구조 신뢰성 해석을 수행함으로써 실제 구조물의 강도 한계상태에 대한 파괴확률을 산정하고 그에 대응하는 위험도를 평가함으로써 안전성 검토를 수행하였다. 본 실험을 통해 1. 재료 강도, 부재 제원, 긴장력, 작용하중 등에 있어 설계 시 가정과 실제 사용 환경 사이의 변동성이 존재한다는 것을 알 수 있었으며, 2. 연구 수행 결과 일반 정밀진단 및 해석에서는 얻을 수 없는 다양하고 중요한 결과를 산출할 수 있었으며 이러한 연구 결과를 바탕으로 개선된 성능평가 기법이 제안 될 수 있음을 알 수 있었다.

• Journal of the Korean Society of Safety
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• v.23 no.5
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• pp.125-130
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• 2008

To optimize the selected reinforcing method for application to PSC Beam bridges, the reliability analysis was performed with consideration for the increase and decrease of the member section based on the standard design section, and the minimum life-cycle cost(LCC) was calculated from this analysis with consideration for the aleatory uncertainty. Moreover, the mean, 50%, 75%, and 90% distributions of the analysis results were re-evaluated quantitatively by considering the effect of the epistemic uncertainty. The reliability results gained from the application of the reinforcing method, as well as the optimal design method based on the minimum LCC, will provide more reasonable design criteria for the PSC Beam bridges.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.523-526
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• 2011

This is concerned with the structural reliability analysis(RA) considering uncertainties in material properties. This method is performed by the stochastic process using Kriging with calculating the distribution of probability and equation of limit state for saving calculated and analyzed time. The proposed methodology is applied to the rocket motor case and compared with monte-calro simulation in efficiency and accuracy of this process.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.377-377
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• 2020

이상기후변화에 따른 홍수피해는 매년 빈번히 발생하고 있고, 이러한 피해에 대비하여 예측 및 대응방안을 신속히 확보할 수 있는 재난예측 및 대응시스템은 필수로 요구되는 실정이다. 강우의 의한 홍수발생과 하천수위 급상승에 의한 제방의 월류 및 파제 메커니즘은 상당히 복잡하고 유동적이며 다양한 불확실성을 포함한다. 본 연구에서는 극치 강수량의 매개변수들의 불확실성을 고려하기 위해 수행된 비정상성 빈도해석 기반의 수문시나리오를 바탕으로 산정된 MCS(Monte Carlo Simulation)기반 확률홍수위를 산정하였고, 이를 활용하여 2차원 제내지 침수해석의 경계조건으로 활용하여 홍수위 변동에 의한 하천 제방 붕괴 변동폭의 범위를 설정하고, 그에 따른 제방붕괴 유출량의 변동 범위를 산정하였다. 또한 확률론적 파제 유입량에 의한 제내지의 침수심과 침수범위를 MCS기반의 2차원 제내지 침수해석을 통해 정량화하여 확률침수심도를 작성하였다. 이러한 홍수발생의 전반적인 메커니즘을 고려하여 매개변수들의 불확실도를 정량적으로 평가함으로써 기존의 결정론적 해석기법보다 신뢰성 있는 침수심 예측결과를 확보하였다.

• Journal of the Korean Geotechnical Society
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• v.24 no.8
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• pp.111-123
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• 2008

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of soil properties is presented to study the response of spatially random soil. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two-dimensional non-Gaussian random fields are generated based on a Karhunen-$Lo{\grave{e}}ve$ expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to study the effects of uncertainty due to the spatial heterogeneity on the settlement and bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to the geotechnical problem and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.26-32
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• 2016

Usually, there are many uncertainties regarding the error of an assumed load, material properties, member size, and structure analysis in a structure, and it may have a direct influence on the qualities of optimal design of structures. Probabilistic analysis has developed rapidly into a desirable process and structural reliability analysis is an increasingly important tool that assists engineers to consider uncertainties during the design, construction and life of a structure to calculate its probability of failure. This study deals with the applications of two optimization techniques to solve the reliability-based optimization problem of structures. The reliability-based optimization problem was formulated as a minimization of the structural volume subject to the constraints on the values of componential reliability index determined by the AFOSM approach. This presented method may be a useful tool for the reliability-based design optimization of structures.

• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.195-206
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• 1991

This paper is concerned with comparison of the first-order reliability methods applied to the assessment of structural safety. For convenience the reliability methods are divided into two categories : the One can explicitly consider the effects of uncertainties in material and geometric variables on those of load effects, say stresses and displacement in the structural analysis procedure and the other one does not. The first method is commonly termed as the stochastic finite element method(SFEM) or probabilistic finite element method(PFEM) and the second method is termed heroin as the ordinary reliability method to distinct it from the stochastic finite element method in which the structural analysis is carried out just once and the load effects are directly input into the reliability analysis procedure. This is based on the reasonable assumption that the level of uncertainties of load effects is the same as those of load itself. In this paper the above two different reliability method have been applied to the safety assessment of plane frame structures and compared thier results from the view point of their efficiency and usefulness. As lear as results of the present structure models are concerned, it can be said that the ordinary reliability method can give reasonable results when the uncertainties of material and geometric variables are comparatively small, say when less than about 15% and the stochastic finite element method is desired to be applied to the structure in which the COV's are comparatively great, say when greater than about 15%.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.2
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• pp.131-137
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• 2018

This paper analyzes the probability of failure for the equivalence ratio error. The control error of the equivalence ratio is affected by the aleatory and epistemic uncertainties. In general, reliability analysis techniques are easily incorporated to handle the aleatory uncertainty. However, the epistemic uncertainty requires a new approach, as it does not provide an uncertainty distribution. The Bayesian inference incorporates the reliability analysis results to handle both uncertainties. The result gives a distribution of failure probability, whose equivalence ratio does not meet the requirement. This technique can be useful in the analysis of most engineering systems, where the aleatory and epistemic uncertainties exist simultaneously.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.791-798
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• 2011

All mechanical-system parameters have uncertainty, and this uncertainty directly affects system performances and results in a decrease in the manufacturing outputs. In particular, since the size of a MEMS system is extremely small, the manufacturing tolerances of a MEMS system are relatively large when compared to the tolerances of a macro-scale system. High manufacturing tolerances result from an increase in the uncertainty of the system parameters, thereby affecting the performances and manufacturing yields. In this paper, the performance uncertainty of a MEMS accelerometer due to system parameter uncertainty is analyzed by using several uncertainty analysis methods. Finally, the performance distributions and manufacturing yields of the MEMS accelerometer are predicted.