Corrosion informatics: an integrated approach to modelling corrosion

Abstract

Materials informatics is based on the integration of tools for generating, classifying, analysing and disseminating knowledge in the domain of materials science and engineering, a subset of which includes corrosion science. The purpose of integration is to decrease costs and time associated with research and development. In the context of corrosion, it is proposed that informatics can produce superior decision making tools, decrease risks of failure and improve asset management. An integrated approach is necessary for corrosion because of the multiphysics nature of its contributing mechanisms that include processes at the megascale, materials deformation, electrochemical reactions and fluid dynamics. A hierarchy is introduced that combines models from these subdisciplines with models at more fundamental scientific levels (thermodynamics, microstructural, quantum mechanical and density functional theory/atomistics) and methods for treating uncertainty (Bayesian inference, Monte Carlo and reliability methods). To demonstrate the multiphysics approaches currently available for corrosion prediction, applications are drawn from the recent literature and categorised by topic: general corrosion, localised corrosion and passivity, environmentally assisted cracking, and coatings and inhibitors. Opportunities for integration in each of these subthemes are suggested. Some remarks concerning the integration of probabilistic with deterministic models are made because of the importance of attaching uncertainties to the predictions made by corrosion models, and applying a time-invariant scientific approach to the interpretation of a time-dependent historical record. Finally, a strategy for implementing the integrated approach to corrosion modelling is presented, under the name ‘corrosion informatics’.

Keywords:

• Corrosion modelling
• Materials genome
• Informatics
• Multiscale modeling
• Multiphysics
• Review

Acknowledgements

Support for this project is acknowledged from the Strategic Research and Innovation group within DNV GL. The author thanks Narasi Sridhar (DNV GL) for insightful discussions and a careful reading of the manuscript.