• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.3
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• pp.291-302
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• 2005

Due to the importance of the parameter in structural response, the uncertain elastic modulus was located at the center of stochastic analysis, where the response variability caused by the uncertain system parameters is pursued. However when we analyze the so-called stochastic systems, as many parameters as possible must be included in the analysis if we want to obtain the response variability that can reach a true one, even in an approximate sense. In this paper, a formulation to determine the statistical behavior of in-plane structures due to multiple uncertain material parameters, i.e., elastic modulus and Poisson's ratio, is suggested. To this end, the polynomial expansion on the coefficients of constitutive matrix is employed. In constructing the modified auto-and cross-correlation functions, use is made of the general equation for n-th moment. For the computational purpose, the infinite series of stochastic sub-stiffness matrices is truncated preserving required accuracy. To demons4rate the validity of the proposed formulation, an exemplary example is analyzed and the results are compared with those obtained by means of classical Monte Carlo simulation, which is based on the local averaging scheme.

• Journal of the Korean Society for Advanced Composite Structures
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• v.1 no.2
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• pp.29-35
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• 2010

In addition to the Young's modulus, the Poisson's ratio is also at the center of attention in the field stochastic finite element analysis since the parameters play an important role in determining structural behavior. Accordingly, the sole effect of this parameter on the response variability is of importance from the perspective of estimation of uncertain response. To this end, a formulation to determine the response variability in laminate composite plates due to the spatial randomness of Poisson's ratio is suggested. The independent contributions of random Poisson's ratiocan be captured in terms of sub-matrices which include the effect of the random parameter in the same order, which can be attained by using the Taylor's series expansion about the mean of the parameter. In order to validate the adequacy of the proposed formulation, several example analyses are performed, and then the results are compared with Monte Carlo simulation (MCS). A good agreement between the suggested scheme and MCS is observed showing the adequacy of the scheme.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.589-595
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the evolutionary structural optimization (ESO). An actual design involves uncertain conditions such as material property, operational load, poisson's ratio and dimensional variation. The deterministic optimization (DO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBSO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability-based shape design optimization method is proposed by utilization the reliability index approach (RIA), performance measure approach (PMA), single-loop single-vector (SLSV), adaptive-loop (ADL) are adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBSO, a sensitivity number is defined as the change of strain energy in the displacement constraint. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.1
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• pp.81-87
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• 2008

This study is about the back analysis to optimize the uncertain parameters of geotechnical properties used in stability analysis of cut and cover tunnel. The Simplex algorithm, Powell algorithm, Rosenbrock algorithm, and Levenberg-Marquardt algorithm are applied for artificial problems of ground excavation. Furthermore, results are compared in the matter of the reliability of optimal solutions with a certain accuracy and the computation speed for evaluations of variables. As shown in results of numerical analysis, all of four algorithms are converged to exact solution satisfying the allowable criteria. And Levenberg-Marquardt's and Rosenbrock's algorithms are identified to be the more efficient methods in the evaluations of functions. After the back analysis for Poisson ratio and Young's modulus for cut and cover tunnel has been performed, design parameters have been correctly estimated and computation time has been improved while the number of measure points is increased.