B Radhika¹, S S P,a¹, C S Manohar^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.27, No.1&2, pp. 79-110, 2008, DOI:10.3970/cmes.2008.027.079

Abstract Reliability of nonlinear vibrating systems under stochastic excitations is investigated using a two-stage Monte Carlo simulation strategy. For systems with white noise excitation, the governing equations of motion are interpreted as a set of Ito stochastic differential equations. It is assumed that the probability distribution of the maximum in the steady state response belongs to the basin of attraction of one of the classical asymptotic extreme value distributions. The first stage of the solution strategy consists of selection of the form of the extreme value distribution based on hypothesis tests, and the next stage involves the estimation of parameters of… More >

M. Manjuprasad¹, C. S. Manohar²

CMES-Computer Modeling in Engineering & Sciences, Vol.19, No.1, pp. 23-54, 2007, DOI:10.3970/cmes.2007.019.023

Abstract A technique for adaptive random field refinement for stochastic finite element reliability analysis of structures is presented in this paper. Refinement indicator based on global importance measures are proposed and used for carrying out adaptive random field mesh refinements. Reliability index based error indicator is proposed and used for assessing the percentage error in the estimation of notional failure probability. Adaptive mesh refinement is carried out using hierarchical graded mesh obtained through bisection of elements. Spatially varying stochastic system parameters (such as Young's modulus and mass density) and load parameters are modeled in general as non-Gaussian random fields with prescribed… More >

Yao Hsu¹, Chih-Yen Su², Wen-Fang Wu^3,4

CMC-Computers, Materials & Continua, Vol.36, No.2, pp. 155-176, 2013, DOI:10.3970/cmc.2013.036.155

Abstract To study the fatigue reliability of a flip-chip chip scale package (FCCSP) subject to thermal cyclic loading, a Monte Carlo simulation-based parametric study is carried out in the present study. A refined procedure as compared with the recently released Probabilistic Design System (PDS) of ANSYS is proposed and employed in particular. The thermal-cyclic fatigue life of the package is discussed in detail since it is related directly to the reliability of the package. In consideration of the analytical procedure as well as real manufacturing processes, a few geometric dimensions and material properties of the package are assumed random. The empirical… 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 of random interval structural responses… More >

A.J. Shaw¹ and P.D. Gosling^1,2

CMC-Computers, Materials & Continua, Vol.18, No.3, pp. 237-270, 2010, DOI:10.3970/cmc.2010.018.237

Abstract This article has no abstract. More >

C. Jiang¹, Y.C. Bai¹, X. Han^1,2, H.M. Ning¹

CMC-Computers, Materials & Continua, Vol.18, No.1, pp. 21-42, 2010, DOI:10.3970/cmc.2010.018.021

Abstract In this paper, an efficient interval optimization method based on a reliability-based possibility degree of interval (RPDI) is suggested for the design of uncertain structures. A general nonlinear interval optimization problem is studied in which the objective function and constraints are both nonlinear and uncertain. Through an interval order relation and a reliability-based possibility degree of interval, the uncertain optimization problem is transformed into a deterministic one. A sequence of approximate optimization problems are constructed based on the linear approximation technique. Each approximate optimization problem can be changed to a traditional linear programming problem, which can be easily solved by… More >