Identification of Contact Failures in Multilayered Composites With the Markov Chain Monte Carlo Method

Abstract

This paper deals with the solution of an inverse heat conduction problem, aiming at the identification of the interface thermal contact conductance, which can be directly associated to the quality of the adhesion between layers of multilayered composite materials. The inverse problem is solved within the Bayesian framework, with a Markov chain Monte Carlo method. A total variation prior is used for the spatially distributed contact conductance. The feasibility of the approach is evaluated with simulated temperature measurements for cases with contact failures of different sizes.

Hybrid Approach in Microscale Transport Phenomena: Application to Biodiesel Synthesis in Micro-reactors

“…In parallel to the advancement of inverse problem analysis tools, experimental techniques have experienced significant progresses along recent years, such as in the case of infrared thermography for non-intrusive temperature measurements [53][54][55][56][57][58][59]. Microscopic lenses can also be employed to refine further the spatial information, and pixels of the order of 20 microns are fairly common in the present commercial IRT systems.…”

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.…”