• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 봄 학술발표회 논문집
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• pp.157-164
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• 1998

An elasto-plastic stochastic finite element method is developed to evaluate the probability of failure of the underground structure. The Mohr-Coulomb failure criteria is adopted for yield condition. The material properties such as the elastic modulus and the cohesion are assumed to be statistically independent random variables which are modeled as spatial stochastic fields. The displacements around the excavated area and the probability of the failure are examined by varying the coefficient of variance for each variables. It is found that the developed procedure can provide the proper probabilistic information about the failure of the underground structure

• Smart Structures and Systems
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• 제10권2호
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• pp.89-110
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• 2012

This study was intended to efficiently perform the probabilistic optimal safety assessment of steel cable-stayed bridges (SCS bridges) using stochastic finite element analysis (SFEA) and expected life-cycle cost (LCC) concept. To that end, advanced probabilistic finite element algorithm (APFEA) which enables to execute the static and dynamic SFEA considering aleatory uncertainties contained in random variable was developed. APFEA is the useful analytical means enabling to conduct the reliability assessment (RA) in a systematic way by considering the result of SFEA based on linearity and nonlinearity of before or after introducing initial tensile force. The appropriateness of APFEA was verified in such a way of comparing the result of SFEA and that of Monte Carlo Simulation (MCS). The probabilistic method was set taking into account of analytical parameters. The dynamic response characteristic by probabilistic method was evaluated using ASFEA, and RA was carried out using analysis results, thereby quantitatively calculating the probabilistic safety. The optimal design was determined based on the expected LCC according to the results of SFEA and RA of alternative designs. Moreover, given the potential epistemic uncertainty contained in safety index, failure probability and minimum LCC, the sensitivity analysis was conducted and as a result, a critical distribution phase was illustrated using a cumulative-percentile.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2005년도 추계학술대회 논문집
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• pp.476-479
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• 2005

In this study, the process parameters in powder compaction are optimized for getting high relative densities. To find optimized parameters, the analytic models of powder compaction are firstly prepared by 2-dimensional rod arrays with random green densities using a quasi-random multi-particle array. Then, using finite element method, the changes in relative densities are analyzed by varying the size of the particle, the amplitude of cyclic compaction, and the coefficient of friction, which influence the relative density in cyclic compactions. After the analytic function of relative density associated process parameters are formulated by aid of the response surface method, the optimal conditions in powder compaction process are found by the grid search method.

• 대한조선학회논문집
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• 제28권2호
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• pp.241-250
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• 1991

구조설계에 사용되는 대부분의 변수들은 다소간의 불확실성을 내포하고 있으며, 구조물의 안전성을 향상시키기 위해서는 이러한 불확실성에 대한 체계적인 연구를 통하여 구조설계시 이를 고려하는 것이 바람직하다. 본 논문에서는 선체와 같이 복잡한 구조물의 신뢰성해석을 효율적으로 수행할 수 있는 방법을 개발하기 위하여, 구조해석의 마지막 단계에서 신뢰성이론을 적용하던 종전의 방법과는 달리, 구조해석의 각 단계마다 확률변수들이 분산특성을 고려할 수 있는 확률 유한요소법을 도입하여, 기존의 신뢰성 이론중 가장 많이 사용되고 있는 2차 모우먼트방법(second moment method)에의 응용에 적합하도록 정식화하고, 이를 바탕으로 유조선 web frame의 신뢰성해석을 수행하여 확률변수들의 분산특성에 따른 web frame의 안전성을 검토하였다. 확률 유한요소법에 의한 신뢰성해석 기법은 유한요소법 알고리즘을 응용한 것이므로, 기존의 각종 유한 요소 package에 본 논문의 신뢰성해석 알고리즘을 도입하는 경우, 기존의 유한요소법에서 사용되는 입력데이타에 확률변수들의 분산특성(C.O.V)등의 통계 데이타만을 추가로 입력하면 구조응답의 평균치뿐만 아니라, 구조물의 신뢰성에 대한 다양한 정보들도 얻을 수 있다.

• 대한조선학회논문집
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• 제57권2호
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• pp.80-87
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• 2020

As the Arctic sea ice decreases due to various reasons such as global warming, the demand for ships and offshore structures operating in the Arctic region is steadily increasing. In the case of sea ice, the anisotropy is caused by the uncertainty inside the material. For most of the research, nevertheless, estimating the ice load has been treated deterministically. With regard to this, in this paper, a four-point bending strength analysis of an ice specimen was attempted using a stochastic finite element method. First, spatial distribution of the material properties used in the yield criterion was assumed to be a multivariate Gaussian random field. After that, a direct method, which is a sort of stochastic finite element method, and a sensitivity method using the sensitivity of response for random variables were proposed for calculating the probabilistic distribution of ice specimen strength. A parametric study was conducted with different mean vectors and correlation lengths for each material property used in the above procedure. The calculation time was about ten seconds for the direct method and about three minutes for the sensitivity methods. As the cohesion and correlation length increased, the mean value of the critical load and the standard deviation increased. On the contrary, they decreased as the friction angle increased. Also, in all cases, the direct and sensitivity methods yielded very similar results.

• Structural Engineering and Mechanics
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• 제14권5호
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• pp.505-520
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• 2002

Based on the modal coordinates of the structure, a finite-element and CQC (complete quadratic combination) method for analyzing the coupled buffeting response of long-span bridges is presented. The formulation of nodal equivalent aerodynamic buffeting forces is derived based on a reasonable assumption. The power spectral density and variance of nodal displacements and elemental internal forces of the bridge structure are computed using the finite-element method and the random vibration theory. The method presented is very efficient and can consider the arbitrary spectrum and spatial coherence of natural winds and the multimode and intermode effects on the buffeting responses of bridge structures. A coupled buffeting analysis of the Jiangyin Yangtse River Suspension Bridge with 1385 in main span is performed as an example. The results analyzed show that the multimode and intermode effects on the buffeting response of the bridge deck are quite remarkable.

• Structural Engineering and Mechanics
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• 제21권5호
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• pp.507-518
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• 2005

In the shear-lag analysis of structures deterministic procedure is insufficient to provide complete information. Probabilistic analysis is a holistic approach for analyzing shear-lag effects considering uncertainties in structural parameters. This paper proposes an efficient and accurate algorithm to analyze shear-lag effects of structures with parameter uncertainties. The proposed algorithm integrated the advantages of the response surface method (RSM), finite element method (FEM) and Monte Carlo simulation (MCS). Uncertainties in the structural parameters can be taken into account in this algorithm. The algorithm is verified using independently generated finite element data. The proposed algorithm is then used to analyze the shear-lag effects of a simply supported beam with parameter uncertainties. The results show that the proposed algorithm based on the central composite design is the most promising one in view of its accuracy and efficiency. Finally, a parametric study was conducted to investigate the effect of each of the random variables on the statistical moment of structural stress response.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제19권4호
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• pp.387-407
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• 2015

This paper analyzes the $h{\times}p$ version of the finite element method for optimal control problems constrained by elliptic partial differential equations with random inputs. The main result is that the $h{\times}p$ error bound for the control problems subject to stochastic partial differential equations leads to an exponential rate of convergence with respect to p as for the corresponding direct problems. Numerical examples are used to confirm the theoretical results.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1999년도 가을 학술발표회 논문집
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• pp.351-358
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• 1999

The structural responses of underground structures are examined in probability by using the elasto-plastic stochastic finite element method in which the spatial distributions of material properties are assumed to be stochastic fields. In addition, the adaptive importance sampling method using the response surface technique is used to improve simulation efficiency. The method is found to provide appropriate information although the nonlinear Limit State involves a large number of basic random variables and the failure probability is small. The probability of plastic local failures around an excavated area is effectively evaluated and the reliability for the limit displacement of the ground is investigated. It is demonstrated that the adaptive importance sampling method can be very efficiently used to evaluate the reliability of a large scale stochastic finite element model, such as the underground structures located in the multi-layered ground.

• Structural Engineering and Mechanics
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• 제11권4호
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• pp.373-392
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• 2001

The main idea behind the paper is to present two alternative methods of homogenization of the heat conduction problem in composite materials, where the heat conductivity coefficients are assumed to be random variables. These two methods are the Monte-Carlo simulation (MCS) technique and the second order perturbation second probabilistic moment method, with its computational implementation known as the Stochastic Finite Element Method (SFEM). From the mathematical point of view, the deterministic homogenization method, being extended to probabilistic spaces, is based on the effective modules approach. Numerical results obtained in the paper allow to compare MCS against the SFEM and, on the other hand, to verify the sensitivity of effective heat conductivity probabilistic moments to the reinforcement ratio. These computational studies are provided in the range of up to fourth order probabilistic moments of effective conductivity coefficient and compared with probabilistic characteristics of the Voigt-Reuss bounds.