- Meher A Prasad

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# Meher A Prasad

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Meher A Prasad

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Meher A Prasad

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- PublicationHigh-dimensional model representation for structural reliability analysis: Authors' reply to comments by S. Rahman and H. Xu(01-10-2011)
;Chowdhury, Rajib; Show more - PublicationHigh dimensional model representation based higher order limit state function for reliability analysis(01-02-2008)
;Chowdhury, Rajib; Show more A new response surface method for predicting the failure probability of structural or mechanical systems subjected to random loads and material properties is presented in this paper. The method involves high dimensional model representation (HDMR) technique in conjunction with moving least squares to approximate the original implicit performance function with an explicit performance function. HDMR is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is a very efficient formulation of the system response, if higher-order variable correlations are weak, allowing the physical model to be captured by the first few lower-order terms. Once the response surface form is defined, the failure probability can be obtained by statistical simulation. Results of seven numerical examples involving mathematical functions and structural mechanics problems indicate that the proposed method provides accurate and computationally efficient estimates of the probability of failure.Show more - PublicationHigh-dimensional model representation for structural reliability analysis(20-05-2009)
;Chowdhury, Rajib; Show more This paper presents a new computational tool for predicting failure probability of structural/mechanical systems subject to random loads, material properties, and geometry. The method involves high-dimensional model representation (HDMR) that facilitates lower-dimensional approximation of the original high-dimensional implicit limit state/ performance function, response surface generation of HDMR component functions, and Monte Carlo simulation. HDMR is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is a very efficient formulation of the system response, if higher-order variable correlations are weak, allowing the physical model to be captured by the first few lower-order terms. Once the approximate form of the original implicit limit state/performance function is defined, the failure probability can be obtained by statistical simulation. Results of nine numerical examples involving mathematical functions and structural mechanics problems indicate that the proposed method provides accurate and computationally efficient estimates of the probability of failure. Copyright © 2008 John Wiley & Sons, Ltd.Show more - PublicationHybrid high dimensional model representation for failure probability estimation(01-08-2010)
;Chowdhury, Rajib; Show more This work presents a new probabilistic method based on Hybrid High Dimensional Model Representation (HHDMR) for predicting the failure probability of randomly parametered structural/mechanical system. High Dimensional Model Representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is a very efficient formulation of the system response, if higher order variable cooperative effects are weak and if the response function is dominantly of additive nature, allowing the physical model to be captured by the first few lower order terms. But, if multiplicative nature of the response function is dominant then Factorized HDMR (FHDMR) must be used, to get a desired accuracy with least number of numerical calculations. But in most cases the nature of the limit state/performance function has neither additive nor multiplicative nature. Rather it has an intermediate nature. This paper presents a new HHDMR based approximation of an implicit limit state/performance function has neither additive nor multiplicative nature but rather an intermediate nature. The proposed approximation of an implicit limit state/performance function includes both HDMR and FHDMR expansions through a hybridity parameter. Results of six numerical examples involving elementary mathematical functions and structural/solid-mechanics problems indicate that the failure probability obtained using HHDMR approximation of an implicit limit state/performance function provides significant accuracy when compared with the conventional Monte Carlo method, while requiring fewer original model simulations.Show more