Browsing by Author "Rao, BN"

Now showing 1 - 3 of 3

item: Conference-Full-text
Crack identification using improved 2D cracked finite element in conjunction with micro genetic algorithm
(2013-11-25) Kalanad, A; Rao, BN
In this paper a crack diagnosis method based on an improved twodimensional (2D) finite element (FE) with an embedded edge crack, and micro genetic algorithm (GA) is proposed. The crack is not physically modeled within the element, but instead, its influence on the local flexibility of the structure is accounted for by the reduction of the element stiffness as a function of the crack length. The components of the stiffness matrix for the cracked element are determined from the Castigliano’s first principle. The element was implemented in the commercial FE code ABAQUS as a user element (UEL) subroutine. The identification of the crack location and depth is formulated as an optimization problem, and GA is used to find the optimal location and depth by minimizing the cost function based on the difference of measured and calculated natural frequencies. The proposed crack detection procedure using the improved 2D FE with an embedded edge crack, and GA is validated using the available experimental and FE modal analysis data reported in the existing literature. The predicted crack locations and crack sizes demonstrate that this approach is capable of detecting small crack location and depth with small errors.
item: Conference-Full-text
Inverse reliability analysis using high dimensional model representation
(2013-11-26) Balu, AS; Rao, BN
Reliability analysis is one of the major concerns at the design stage since the occurrence of failures in engineering systems may lead to catastrophic consequences. Therefore, the expectation of higher reliability and lower environmental impact has become imperative. Hence the inverse reliability problem arises when one is seeking to determine the unknown design parameters such that prescribed reliability indices are attained. The inverse reliability problems with implicit response functions require the evaluation of the derivatives of the response functions with respect to the random variables. When these functions are implicit functions of the random variables, derivatives of these response functions are not readily available. Moreover in many engineering systems, due to unavailability of sufficient statistical information, some uncertain variables cannot be modelled as random variables. In this paper High Dimensional Model Representation (HDMR) based inverse reliability analysis method is presented for the determination of the design parameters in the presence of mixed uncertain variables. The method involves HDMR approximation of the limit state function, transformation technique to obtain the contribution of the fuzzy variables to the convolution integral, and fast Fourier transform techniques to evaluate the convolution integral for solving the inverse reliability problem. The accuracy and efficiency of the proposed method is demonstrated through two numerical examples.
item: Conference-Full-text
Multicut-HDMR based reliability bounds estimation under mixed uncertainties
(2013-11-26) Rao, BN; Balu, AS
Reliability analysis taking into account the uncertainties involved in a structural system plays an important role in the analysis and design of structures. Due to the complexity of structural systems, the information about the functioning of various structural components has different sources and the failure of systems is usually governed by multiple failure criteria, all of which are to be taken into consideration for reliability estimation. In this paper High Dimensional Model Representation (HDMR) based uncertain analysis method is presented for estimating the bounds on the reliability of structural systems involving multiple design points in the presence of mixed uncertain variables. The method involves HDMR approximation of the limit state function, weight function to identify multiple design points, transformation technique to obtain the contribution of the fuzzy variables to the convolution integral, and fast Fourier transform techniques to evaluate the convolution integral for estimation of the membership function of reliability. The proposed effort in evaluating the failure probability involves calculating conditional responses at a selected input determined by sample points. Three numerical examples have been presented, and comparisons have been made with direct MCS method to evaluate the accuracy and the computational efficiency of the present method.