• Geotechnical Engineering
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• v.4 no.3
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• pp.19-26
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• 1988

A stochastic numerical model for predictions of differential settlement of foundation Eoils is developed in this Paper. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the elastic modulus. This technique provides the best linear unbiased estimator of a parameter and its minimum variance from a limited number of measured data. The stochastic finite element method, employing the first-order second-moment analysis for computations of error Propagation, is used to obtain the means, ariances, and covariances of nodal displacements. Finally, a reliability model of differential settlement is proposed by using the results of the stochastic FEM analysis. It is found that maximum differential settlement occurs when the distance between two foundations is approximately same It with the scale of fluctuation in horizontal direction, and the probability that differential settlement exceeds the allot.able vague might be significant.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.789-799
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• 2007

In this paper, we propose a stochastic finite element formulation which takes into account the randonmess in the material and geometrical parameters. The formulation is proposed for plate structures, and is based on the weighted integral approach. Contrary to the case of elastic modulus, plate thickness contributes to the stiffness as a third-order function. Furthermore, Poisson's ratio is even more complex since this parameter appears in the constitutive relations in the fraction form. Accordingly, we employ Taylor's expansion to derive decomposed stochastic field functions in ascending order. In order to verify the proposed formulation, the results obtained using the proposed scheme are compared with those in the literature and those of Monte Carlo analysis as well.

• Computational Structural Engineering
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• v.7 no.1
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• pp.125-134
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• 1994

Response variability of reinforced concrete frame subjected to material property randomness has been evaluated with the aid of the finite element method. The spatial variation of Young's modulus is assumed to be a two-dimensional homogeneous stochastic process. Young's Modulus of concrete material has been investigated based on the uiaxial strength of concrete cylinder. Direct Monte Carlo simulation method is used to investigate the response of reinforced concrete frame due to the variation of Young's modulus with the Neumann expansion method and the pertubation method. The results by three analytic methods are compared with those by deterministic finite element analysis. These stochastic technique may be an efficient tool for evaluating the structural safety and reliability of reinforced concrete structures.

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.199-204
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• 2002

본 연구에서는 저압 증기 터빈블레이드의 안전성 확보를 위하여 작용응력 및 강도의 변동성을 고려한 확률론적 해석을 수행하였다. 정상상태에서 작용응력은 이론 및 유한요소해석에 의해서 얻을 수 있으며, 최대 von-Mises 응력은 215.4MPa이다. 회전굽힘 하중하에서의 피로한도는 응력비 R= -1에서 계단식 시험법을 이용하여 구하였으며, 이의 확률론적 특성에 가장 적합한 분포는 3 모수 와이블 분포이다. 그리고 신뢰성에 미치는 다양한 인자들의 영향은 영향계수(sensitivity factor)를 이용하여 정량적으로 평가하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.365-372
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• 2003

In this study, the program which determine the initial cable tension force by tile initial shape analysis for cable stayed bridge is developed. Also, DSFEMP(Dynamic Stochastic Finite Element Analysis Program) is developed to consider the variance of random variables at each step of dynamic response analysis, not use existing methods that apply to the theory of reliability at the final step of structural analysis. In addition, the output from the developed program was compared with the results from DMCSP(Direct Monte Carlo Simulation Program) to prove its validity.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.4
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• pp.219-225
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• 2000

This paper presents the shape optimization considering the uncertainty of design variable to find robust optimal solution that has insensitive performance to its change of design variable. Stochastic finite element method (SFEM) is used to treat input data as stochastic variables. It is method that the potential values are series form for the expectation and small variation. Using correlation function of their variables, the statistics of output obtained form the input data distributed. From this, design considering uncertainty of design variables.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.635-642
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• 2014

In this paper, an efficient technique is developed to predict failure probability of three failure modes(case rupture, fracture and bolt breakage) related to solid rocket motor case due to the inner pressure during the mission flight. The overall procedure consists of the steps: 1) design parameters affecting the case failure are identified and their uncertainties are modelled by probability distribution, 2) combustion analysis in the interior of the case is carried out to obtain maximum expected operating pressure(MEOP), 3) stress and other structural performances are evaluated by finite element analysis(FEA), and 4) failure probabilities are calculated for the above mentioned failure modes. Axi-symmetric assumption for FEA is employed for simplification while contact between bolted joint is accounted for. Efficient procedure is developed to evaluate failure probability which consists of finding first an Most Probable Failure Point(MPP) using First-Order Reliability Method(FORM), next making a response surface model around the MPP using Latin Hypercube Sampling(LHS), and finally calculating failure probability by employing Importance Sampling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.1001-1011
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• 2006

It is a general agreement that exact statistical solutions can be found by a Monte Carlo technique. Due to difficulties, however, in the numerical generation of random fields, which satisfy not only the probabilistic distribution but the spectral characteristics as well, it is recognized as relatively difficult to find an exact response variability of a structural response. In this study, recognizing that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for general structures. In this procedure, the probability density function is directly used. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density function, and has capability of considering correlations between multiple random variables.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.4
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• pp.432-446
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• 1996

A stochastic Hamilton variational principle(SHVP) is formulated for dynamic problems of linear continuum. The SHVP allows incorporation of probabilistic distributions into the finite element analysis. The formulation is simplified by transformation of correlated random variables to a set of uncorrelated random variables through a standard eigenproblem. A procedure based on the Fourier analysis and synthesis is presented for eliminating secularities from the perturbation approach. In addition to, a method to analyse stochastic design sensitivity for structural dynamics is present. A combination of the adjoint variable approach and the second order perturbation method is used in the finite element codes. An alternative form of the constraint functional that holds for all times is introduced to consider the time response of dynamic sensitivity. The algorithms developed can readily be adapted to existing deterministic finite element codes. The numerical results for stochastic analysis by proceeding approach of cantilever, 2D-frame and 3D-frame illustrates in this paper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4398-4404
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• 2015

Stainless steel sheets are widely used as the structural material for dynamic machine structures, These kinds structures used stainless steel sheets are commonly fabricated by using the gas welding, For fatigue design of gas welded joints such as various type joint. It is necessary to obtain design information on stress distribution at the weldment as well as fatigue strength of gas welded joints. Thus in this paper, ${\Delta}P-N_f$ curves were obtained by fatigue tests. and, ${\Delta}P-N_f$ curves were rearranged in the ${\Delta}{\sigma}-N_f$ relation with the hot spot stresses at the gas welded joints. Using these results, the accelerated life test(ALT) is conducted. From the experiment results, an life prediction model is derived and factors are estimated. So it is intended to obtain the useful information for the fatigue lifetime of welded joints and data analysis by statistic reliability method, to save time and cost, and to develop optimum accelerated life prediction plans.