Identification of Contact Failures in Multi-Layered Composites

Abstract

This paper deals with the solution of an inverse heat conduction problem, aiming at the identification of contact failures in composites formed by layers of different materials. The inverse problem is solved within the Bayesian framework, with a Markov chain Monte Carlo method. The effects of the prior models, for the unknown contact conductance at the interface of a plate with two layers, are examined. The solution of the inverse problem is performed with simulated temperature measurements.

Detection of contact failures with the Markov chain Monte Carlo method by using integral transformed measurements

“…The detection of internal failures in materials is a subject of extensive research due to its importance in several fields, for example, in structural health monitoring [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. With the recent advancement and practical applications (e.g., in the aeronautic, space and petroleum industries) of composites consisting of layers of different materials, nondestructive and noninvasive methods for the detection of adhesion failures between the composite layers have been developed [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Heat transfer techniques can be found among these methods, by using qualitative [1,2,7,13,14] as well quantitative analyses based on the solutions of inverse problems [3][4][5][6][7][8][9][10][11][12].…”

“…With the recent advancement and practical applications (e.g., in the aeronautic, space and petroleum industries) of composites consisting of layers of different materials, nondestructive and noninvasive methods for the detection of adhesion failures between the composite layers have been developed [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Heat transfer techniques can be found among these methods, by using qualitative [1,2,7,13,14] as well quantitative analyses based on the solutions of inverse problems [3][4][5][6][7][8][9][10][11][12].…”

“…In our previous works [3,4], the contact failures were detected through the estimation of the contact conductance between the layers of different materials from measurements of the transient temperature over the surface of the composite. The approach used in Refs.…”

“…The approach used in Refs. [3,4] was based on a Bayesian formulation of the inverse problem, with a total variation prior model for the unknowns and using the Markov chain Monte Carlo (MCMC) method for the inference of the Bayesian model. The computational complexity of MCMC with large dimensional problems is often prohibitive.…”

“…The computational complexity of MCMC with large dimensional problems is often prohibitive. Therefore, in this paper, we extend [3,4] to accommodate a data compression scheme. The temperatures measured with an infrared camera are spatially compressed through the integral transformation with eigenfunctions related to the actual physical problem.…”