Experimental study and 3D cellular automata simulation of corrosion pits on Q345 steel surface under salt-spray environment

Cui, Chuanjie; Ma, Rujin; Chen, Airong; Pan, Zichao; Tian, Hao

doi:10.1016/j.corsci.2019.03.011

Cited by 48 publications

(20 citation statements)

References 28 publications

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“…CAbased approaches provide one way to link between these two scales and cover far longer corrosion times. 187 CA works at an intermediate mesoscopic scale by coarse-graining the large-scale effects of random, microscopic corrosion events that are difficult to collectively simulate at the molecular scale. 188,189 The multi-phase system is represented by a fixed lattice of discrete cells with finite states, with each cell expressing only one state at a given time.…”

Section: Cellular Automatonmentioning

confidence: 99%

Pitting Corrosion in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion Additive Manufacturing: A Review and Perspective

Voisin

Shi

Zhu

et al. 2022

JOM

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Abstract316L stainless steel (316L SS) is a flagship material for structural applications in corrosive environments, having been extensively studied for decades for its favorable balance between mechanical and corrosion properties. More recently, 316L SS has also proven to have excellent printability when parts are produced with additive manufacturing techniques, notably laser powder bed fusion (LPBF). Because of the harsh thermo-mechanical cycles experienced during rapid solidification and cooling, LPBF processing tends to generate unique microstructures. Strong heterogeneities can be found inside grains, including trapped elements, nano-inclusions, and a high density of dislocations that form the so-called cellular structure. Interestingly, LPBF 316L SS not only exhibits better mechanical properties than its conventionally processed counterpart, but it also usually offers much higher resistance to pitting in chloride solutions. Unfortunately, the complexity of the LPBF microstructures, in addition to process-induced defects, such as porosity and surface roughness, have slowed progress toward linking specific microstructural features to corrosion susceptibility and complicated the development of calibrated simulations of pitting phenomena. The first part of this article is dedicated to an in-depth review of the microstructures found in LPBF 316L SS and their potential effects on the corrosion properties, with an emphasis on pitting resistance. The second part offers a perspective of some relevant modeling techniques available to simulate the corrosion of LPBF 316L SS, including current challenges that should be overcome.

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Section: Cellular Automatonmentioning

confidence: 99%

Pitting Corrosion in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion Additive Manufacturing: A Review and Perspective

Voisin

Shi

Zhu

et al. 2022

JOM

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“…Finite element analysis (FEA) can be utilised to predict the stress field in engineering structures subject to loads, which can be used for CF analyses. FEA has been applied in fatigue studies at various scales including: ♣ Stress assisted corrosion for pitting evolution studies using cellular automation finite element model (Córdoba-Torres et al 2001;Saucedo-Mora and Marrow 2014;Fatoba et al 2018;Cui et al 2019). The model provided useful information on real-time diagnostics of CF i.e.…”

Section: Finite Element Analysis Of Corrosion Fatigue In High Strengt...mentioning

confidence: 99%

A review of challenges and framework development for corrosion fatigue life assessment of monopile-supported horizontal-axis offshore wind turbines

Okenyi

Bodaghi

Mansfield

et al. 2022

Ships and Offshore Structures

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Digital tools such as machine learning and the digital twins are emerging in asset management of offshore wind structures to address their structural integrity and cost challenges due to manual inspections and remote sites of offshore wind farms. The corrosive offshore environments and salt-water effects further increase the risk of fatigue failures in offshore wind turbines. This paper presents a review of corrosion fatigue research in horizontal-axis offshore wind turbines (HAOWT) support structures, including the current trends in using digital tools that address the current state of asset integrity monitoring. Based on the conducted review, it has been found that digital twins incorporating finite element analysis, material characterisation and modelling, machine learning using artificial neural networks, data analytics, and internet of things (IoT) using smart sensor technologies, can be enablers for tackling the challenges in corrosion fatigue (CF) assessment of offshore wind turbines in shallow and deep waters.

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“…More recently, a new class of models has emerged that solves the governing equations defined over a two-phase, electrolyte-solid domain, and predict the evolution of the corrosion front caused by anodic dissolution more efficiently This approach eliminates the need to explicitly track the corrosion front, simplifies numerical complexity, and improves a model's applicability to more complex situations. One such class of models is Cellular Automata (CA) [27,28]. However, given their discrete nature and the heuristic rules for "cell" transformation they implement, they are difficult to calibrate and less applicable for quantitative predictions [5].…”

Section: Introductionmentioning

confidence: 99%

A Peridynamic Model for Crevice Corrosion Damage

Jafarzadeh¹,

Zhao²,

Shakouri³

et al. 2021

Preprint

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A new peridynamic (PD) model for crevice corrosion damage is introduced and cross-validated with experimental results reported in the literature. The model defines a simple metal ion concentration-dependent corrosion rate along the metal-electrolyte interface. Crevice problems have ratios of gap-to-length of 1/100 or lower. To increase the computational efficiency when having a domain with an extreme aspect ratio, the PD formulation with spherical horizons is modified to accommodate arbitrary-shape horizons. The model is validated against experimental results on immersed bolted washers. The PD simulations predict the observed corrosion kinetics, and the deepest corrosion trenches form at a critical distance from the mouth of the crevice. The location of the most severe corrosion attack does not have to be specified as an input. Instead, it results directly from solving the problem with PD. The evolution of crevice corrosion damage is autonomous in PD, and only the geometry, initial, and boundary conditions control the evolution of the corrosion process.

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Experimental study and 3D cellular automata simulation of corrosion pits on Q345 steel surface under salt-spray environment

Cited by 48 publications

References 28 publications

Pitting Corrosion in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion Additive Manufacturing: A Review and Perspective

Pitting Corrosion in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion Additive Manufacturing: A Review and Perspective

A review of challenges and framework development for corrosion fatigue life assessment of monopile-supported horizontal-axis offshore wind turbines

A Peridynamic Model for Crevice Corrosion Damage

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