Multiphysics Modelling on the Effects of Composition and Microstructure during Tribocorrosion of Aluminum-based Metals and Structures

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Virginia Tech


Wear and corrosion are two major threats to material integrity in multiple real-life circumstances, including oil and gas pipelines, marine and offshore infrastructures and transportations and biomedical implants. Furthermore, the synergistic effects between the two, named tribocorrosion, could cause, most of the time, severer material degradation to jeopardize materials' long-term sustainability and structural integrity. A representative case is aluminum (Al) and its alloys, which exhibit good corrosion resistance in aqueous solution due to the protection provided by the passive layer. However, these naturally formed layers are thin and delicate, leaving the materials vulnerable to simultaneous mechanical and corrosion damage, which in turn, compromise their resistance to tribocorrosion. Past research in tribocorrosion mainly relies on costly and trial-and-error experimental methods to study the materials' deformation and degradation under simultaneous wear and corrosion. In an attempt to predict tribocorrosion behavior using numerical analysis, this work developed a set of finite-element-based multiphysics models, in combination with experimental methods for parameter input and validation, focusing on different factors influencing the tribocorrosion behavior of materials. The first study developed a model with the coupling between strain and corrosion potential and investigated the effect of bulk material properties on tribocorrosion. This model was validated by existing tribocorrosion experiments of two Al-Mn alloys, to analyze the synergistic effects of mechanical and corrosion properties on the material degradation mechanisms of tribocorrosion. During consecutive passes of the counter body, significant residual stress was found to develop near the edge of the wear track, leading to highly concentrated corrosion current than elsewhere. Such non-uniform surface corrosion and stress-corrosion coupling led to variations of tribocorrosion rate over time, even though testing conditions were kept constant. Tribocorrosion rate maps were generated to predict material loss as a function of different mechanical and electrochemical properties, indicating a hard, complaint metal with high anodic Tafel slope and low exchange current density is most resistant to tribocorrosion. Secondly, the influence of microstructural design on the tribocorrosion behavior of Al-based nanostructured metallic multilayers (NMMs) was investigated computationally. Specifically, this model accounts for elastic-plastic mechanical deformation during wear and galvanic corrosion between exposed inner layers after wear. The effects of individual layer thickness (from 10 to 100 nm) and layer orientation (horizontally and vertically aligned) on the tribocorrosion behavior of Al/Cu NMMs was studied. Both factors were found to affect the subsurface stress and plastic strain distribution and localized surface corrosion kinetics, hence affecting the overall tribocorrosion rate. This model and the obtained understanding could shed light on future design and optimization strategies of NMMs against tribocorrosion. Finally, a combined experimental and computational investigation of the crystallographic effect using Al (100), (110), and (111) single crystals as model systems, to understand the effects of crystallographic orientation on the tribocorrosion kinetics by combining tribocorrosion experiments, materials characterization, and multiphysics modeling. EBSD was exploited to characterize the crystal orientation and dislocation density of the worn samples. The tribocorrosion model was built based on the results of EBSD characterization with the coupling effect of crystal orientation and corrosion. The model successfully predicted the overall tribocorrosion current of single-crystal samples, indicating the important role played by crystal orientation and dislocation density in the acceleration of corrosion.



Tribocorrosion, Finite element modeling, Aluminum