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Predictive and prognostic modelling and simulation of coating failures due to corrosion and mechanical failures.

Khan, Z. A., Latif, J., Nazir, H., Saeed, A. and Stokes, K., 2018. Predictive and prognostic modelling and simulation of coating failures due to corrosion and mechanical failures. International Journal of Computational Methods and Experimental Measurements, 6 (3), 487-498.

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Official URL: https://www.witpress.com/journals/cmem

DOI: 10.2495/CMEM-V6-N3-487-498

Abstract

This research presents analytical and mathematical modelling of coating failures within industrial components, structures, mobile assets and systems due to corrosive degradation and mechanical fracture. These failures lead to serval surface problems, therefore contact mechanics and electrochemistry approaches incorporating induced residual stresses have been adopted to develop a comprehensive solution for the prediction prognostic of such failures. Experimental study of film cracking and its propagation into substrates, interfacial transient behaviours and film-substrate system has been conducted. A parallel study of corrosive degradation to include cathodic delamination, cathodic blistering and tribo-corrosion of films has been conducted. Experimental and analytical studies of induced residual stresses within the coating and their effects on failure mechanisms and propagation have been completed. A detailed investigation of elastic mismatch at the interfacial contact and interfacial crack tip field has been performed and a complex stress intensity factor is presented. Mathematical derivation of oscillatory singularity, mode mix and interfacial fracture criterion to include adhesion are presented. This paper presents novel mathematical modelling incorporating interfacial crack propagating, diffusion of corrosive species and cathodic blistering for prediction and prognoses of coating failures.

Item Type:Article
ISSN:2046-0554
Uncontrolled Keywords:Coating failure; Compressive residual stress; Diffusion induced stress
Group:Faculty of Science & Technology
ID Code:27239
Deposited By: Symplectic RT2
Deposited On:21 Feb 2017 15:56
Last Modified:14 Mar 2022 14:02

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