Rongxing Duan¹, Yanni Lin¹, Longfei Hu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.1, pp. 17-34, 2017, DOI:10.3970/cmes.2017.113.015

Abstract Fault tolerant technology has greatly improved the reliability of modern systems on one hand and makes their failure mechanisms more complex on the other. The characteristics of dynamics of failure, diversity of distribution and epistemic uncertainty always exist in these systems, which increase the challenges in the reliability assessment of these systems significantly. This paper presents a novel reliability analysis framework for complex systems within which the failure rates of components are expressed in interval numbers. Specifically, it uses a dynamic fault tree (DFT) to model the dynamic fault behaviors and copes with the epistemic More >

Damian Sokolowski¹, Marcin Kamiński², Michal Strakowski¹

CMES-Computer Modeling in Engineering & Sciences, Vol.99, No.3, pp. 209-231, 2014, DOI:10.3970/cmes.2014.099.209

Abstract The main issue in this paper is to present stochastic analysis of the steel plate girder with the corrugated web subjected to Gaussian random fluctuations in its web thickness. Such an analysis is carried out using the Stochastic Finite Element Method based on the generalized stochastic perturbation technique and discretization of structure with the quadrilateral 4-noded shell finite elements. It is numerically implemented using the FEM system ABAQUS and the symbolic algebra system MAPLE, where all the probabilistic procedures are programmed. We compare the perturbation-based results with these obtained from traditional Monte-Carlo simulation and, separately, More >

Xiyong Huang¹, M. H. Aliabadi², Z. Sharif Khodaei³

CMES-Computer Modeling in Engineering & Sciences, Vol.102, No.4, pp. 291-330, 2014, DOI:10.3970/cmes.2014.102.291

Abstract In this paper, a stochastic dual boundary element formulation is presented for probabilistic analysis of fatigue crack growth. The method involves a direct differentiation approach for calculating boundary and fracture response derivatives with respect to random parameters. Total derivatives method is used to obtain the derivatives of fatigue parameters with respect to random parameters. First- Order Reliability Method (FORM) is applied to evaluate the most probable point (MPP). Opening mode fatigue crack growth problems are used as benchmarks to demonstrate the performance of the proposed method. More >

W. Zhao^1,2, J.K. Liu³, X.Y. Li², Q.W. Yang⁴, Y.Y. Chen⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.93, No.6, pp. 469-488, 2013, DOI:10.3970/cmes.2013.093.469

Abstract In order to obtain reliable structural design, it is of extreme importance to evaluate the failure probability, safety levels of structure (reliability analysis) and the effect of a change in a variable parameter on structural safety (sensitivity analysis) when uncertainties are considered. With a computationally cheaper approximation of the limit state function, various response surface methods (RSMs) have emerged as a convenient tool to solve this especially for complex problems. However, the traditional RSMs may produce large errors in some conditions especially for those highly non-linear limit state functions. Instead of the traditional least squares… More >

M. Q. Chau^1,2, X. Han¹, Y. C. Bai¹, C. Jiang¹

CMC-Computers, Materials & Continua, Vol.27, No.2, pp. 128-142, 2012, DOI:10.32604/cmc.2012.027.128

Abstract The first-order reliability method (FORM) is one of the most widely used structural reliability analysis techniques due to its simplicity and efficiency. However, direct using FORM seems disability to work well for complex problems, especially related to high-dimensional variables and computation intensive numerical models. To expand the applicability of the FORM for more practical engineering problems, a response surface (RS) approach based FORM is proposed for structural reliability analysis. The radial basis function (RBF) is employed to approximate the implicit limit-state functions combined with Latin Hypercube Sampling (LHS) strategy. To guarantee the numerical stability, the More >

M.M. Kamiński¹, J. Szafran¹

CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.2, pp. 143-168, 2012, DOI:10.32604/cmes.2012.083.143

Abstract The main issue in this article is computational probabilistic analysis and reliability assessment of the steel telecommunication towers subjected to material and environmental uncertainty. Such a discussion is important since very wide, frequent and relatively modern application of these structures, which are subjected to various sources of uncertainty and having at this moment no rich and time-dependent failure evidence. Numerical analysis is based on the generalized stochastic perturbation technique implemented as the Stochastic Finite Elements using the Response Function Method applied with the use of computer algebra system. A simultaneous usage of the engineering FEM… More >

S.R. Santos¹, L.C. Matioli², A.T. Beck³

CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.1, pp. 23-56, 2012, DOI:10.3970/cmes.2012.083.023

Abstract Solution of structural reliability problems by the First Order method require optimization algorithms to find the smallest distance between a limit state function and the origin of standard Gaussian space. The Hassofer-Lind-Rackwitz-Fiessler (HLRF) algorithm, developed specifically for this purpose, has been shown to be efficient but not robust, as it fails to converge for a significant number of problems. On the other hand, recent developments in general (augmented Lagrangian) optimization techniques have not been tested in aplication to structural reliability problems. In the present article, three new optimization algorithms for structural reliability analysis are presented.… More >

Yuan-Qi Li, Li-Ping Wang, Zu-Yan Shen

The International Conference on Computational & Experimental Engineering and Sciences, Vol.16, No.1, pp. 13-14, 2011, DOI:10.3970/icces.2011.016.013

Abstract In structural design, sometimes analysis methods in available specifications cannot be used directly for new materials or new structural configurations. A common way is to test and check the behavior in question of the prototype units including complete or parts of structures, individual members or connections for design assessment. How to directly obtain the design capacity with an expected reliability level according to the related codes from test results is a critical issue. Currently, there isn't any explicit specification for the above issues in Chinese codes, and few references are available. In this paper, referring More >

C. Wang¹, W. Gao¹, C.W. Yang¹, C.M. Song¹

CMC-Computers, Materials & Continua, Vol.25, No.1, pp. 19-46, 2011, DOI:10.3970/cmc.2011.025.019

Abstract The random interval response and probabilistic interval reliability of structures with a mixture of random and interval properties are studied in this paper. Structural stiffness matrix is a random interval matrix if some structural parameters and loads are modeled as random variables and the others are considered as interval variables. The perturbation-based stochastic finite element method and random interval moment method are employed to develop the expressions for the mean value and standard deviation of random interval structural displacement and stress responses. The lower bound and upper bound of the mean value and standard deviation More >

Wei Gao¹, Chongmin Song¹, Francis Tin-Loi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.46, No.2, pp. 151-190, 2009, DOI:10.3970/cmes.2009.046.151

Abstract Static response and reliability of structures with a mixture of random and interval parameters under uncertain loads are investigated in this paper. Structural stiffness matrix is a random interval matrix when some structural parameters are modeled as random variables and others are considered as intervals. The structural displacement and stress responses are also random interval variables. From the static finite element governing equations, the random interval structural responses are obtained using the random interval perturbation method based on the first- and second-order perturbations. The expressions for mean value and standard deviation of random interval structural More >