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Research Papers: Conduction

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

[+] Author and Article Information
L. A. Abreu, R. M. Cotta

Department of Mechanical Engineering,
Politecnica/COPPE,
Federal University of Rio de Janeiro – UFRJ,
Cid. Universitária, Cx. 68503,
Rio de Janeiro, RJ 21941-972, Brazil

H. R. B. Orlande

Department of Mechanical Engineering,
Politecnica/COPPE,
Federal University of Rio de Janeiro – UFRJ,
Cid. Universitária, Cx. 68503,
Rio de Janeiro, RJ 21941-972, Brazil
e-mail: helcio@mecanica.coppe.ufrj.br

J. Kaipio

Department of Mathematics,
University of Auckland,
Private Bag 92019,
Auckland Mail Centre,
Auckland 1142, New Zealand

V. Kolehmainen

Department of Applied Physics,
University of Eastern Finland,
P.O. Box 1627,
Kuopio 70211, Finland

J. N. N. Quaresma

School of Chemical Engineering,
Universidade Federal do Pará,
UFPA, Campus Universitário do Guamá,
Rua Augusto Corrêa, 01,
Belém, PA 66075–110, Brazil

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received July 28, 2013; final manuscript received March 23, 2014; published online July 29, 2014. Assoc. Editor: Ali Khounsary.

J. Heat Transfer 136(10), 101302 (Jul 29, 2014) (9 pages) Paper No: HT-13-1376; doi: 10.1115/1.4027364 History: Received July 28, 2013; Revised March 23, 2014

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.

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References

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Figures

Grahic Jump Location
Fig. 2

(a) Exact temperature distribution at Z = 1 and τ = 0.065—two square failures of size 0.01 m and (b) simulated measurements at Z = 1 and τ = 0.065—two square failures of size 0.01 m

Grahic Jump Location
Fig. 1

(a) Overview of the physical problem and (b) multilayered plate

Grahic Jump Location
Fig. 6

(a) True target contact conductance—two square failures of size 0.005 m and (b) estimated posterior means for the contact conductance—two square failures of size 0.005 m

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Fig. 3

(a) True target contact conductance—two square failures of size 0.01 m and (b) estimated posterior means for the contact conductance—two square failures of size 0.01 m

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Fig. 4

(a) States of the Markov chains—two square failures of size 0.01 m and (b) evolution of the posterior distribution—two square failures of size 0.01 m

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Fig. 5

(a) Exact temperature distribution at Z = 1 and τ = 0.065—two square failures of size 0.005 m and (b) Simulated measurements at Z = 1 and τ = 0.065—two square failures of size 0.005 m

Grahic Jump Location
Fig. 7

(a) Exact temperature distribution at Z = 1 and τ = 0.065—rectangular contact failure, (b) simulated measurements at Z = 1 and τ = 0.065 for a standard deviation of 0.05 °C—rectangular contact failure, and (c) simulated measurements at Z = 1 and τ = 0.065 for a standard deviation of 0.2 °C—rectangular contact failure

Grahic Jump Location
Fig. 8

(a) True target contact conductance—rectangular contact failure, (b) estimated posterior means for the contact conductance obtained with measurements of a standard deviation 0.05 °C—rectangular contact failure, and (c) estimated posterior means for the contact conductance obtained with measurements of a standard deviation 0.2 °C—rectangular contact failure

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