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Experimental investigation, stochastic modelling and reliability analysis of fatigue behavior of tapered composite laminates

Title:

Experimental investigation, stochastic modelling and reliability analysis of fatigue behavior of tapered composite laminates

Guo, Xuan Ning (2005) Experimental investigation, stochastic modelling and reliability analysis of fatigue behavior of tapered composite laminates. Masters thesis, Concordia University.

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Abstract

The present thesis contains the results of testing, stochastic process modeling and reliability analysis of symmetric tapered laminates with pre-set delaminations. Two laminate configurations, called lay-up A and lay-up B are considered. Lay-up A is a [0/±45/0/(±45) 3 /±45/0 7 ] s laminate that is reduced to a [0/±45/0/±45/0 7 ] s laminate and lay-up B is a [0 7 /±45/0/(±45) 3 /±45/0] s laminate that is reduced to a [0 7 /±45/0/±45/0] s laminate. Two locations of pre-set delaminations, at the center of the core layer and in between belt and core layers in the thin side of lay-up A tapered laminate, are considered. Two loading conditions, (a) cyclic tension-compression loading and (b) cyclic tension-compression loading with 85% over tension load, are applied for the fatigue tests in the present thesis. A stochastic approach to model the fatigue damage development based on the test data which has been developed and presented in an existing work is used in the present thesis. The Markov Chain is used to represent the fatigue damage accumulation in this approach, and the differences between the true probability distribution and the unconditional probability distribution (or predicted unconditional probability distribution) of the fatigue response parameter are determined by using different methodologies, that are, the Maximum Entropy Method (MEM) and, Gaussian (single and bivariate) probability distribution and joint probability density function. The test data on the fatigue response parameter are analyzed based on the reliability function, hazard rate and failure density function.

Divisions:Concordia University > Faculty of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Guo, Xuan Ning
Pagination:xx, 141 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical and Industrial Engineering
Date:2005
Thesis Supervisor(s):Ganesan, Rajamohan
ID Code:8592
Deposited By:Concordia University Libraries
Deposited On:18 Aug 2011 14:29
Last Modified:18 Aug 2011 14:29
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