Pitting corrosion identification approach based on inverse finite element method for marine structure applications

Ghasemzadeh, Maryam; Mokhtari, Mojtaba; Bilgin, Mahmut Hudayi; Kefal, Adnan

doi:10.1016/j.oceaneng.2023.113953

Cited by 8 publications

(1 citation statement)

References 32 publications

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“…Most structural systems currently in operation are exposed to some degree of corrosion deterioration; this is especially true for marine structures, which is the primary field of the authors. Despite recent interest in deploying SHM systems for CITL monitoring [17,[41][42][43], the naturally slow evolution of the phenomenon has constrained investigations to a numerical setting. In response to this, a novel testing procedure has been employed to achieve substantial CITL in a laboratory setting in a significantly accelerated timeframe, that is presented here for the first time.…”

Section: Accelerated Corrosion Under Three-point Bending Experimentsmentioning

confidence: 99%

On the Detection of Thickness Loss in Ship Hull Structures Through Strain Sensing

Silionis¹,

Anyfantis²

2022

Lecture Notes in Civil Engineering

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Fatigue crack growth is one of the most common types of deterioration in metal structures with significant implications on their reliability. Recent advances in Structural Health Monitoring (SHM) have motivated the use of structural response data to predict future crack growth under uncertainty, in order to enable a transition towards predictive maintenance. Accurately representing different sources of uncertainty in stochastic crack growth (SCG) processes is a non-trivial task. The present work builds on previous research on physics-based SCG modeling under both material and loadrelated uncertainty. The aim here is to construct computationally efficient, probabilistic surrogate models for SCG processes that successfully encode these different sources of uncertainty. An approach inspired by latent variable modeling is employed that utilizes Gaussian Process (GP) regression models to enable the surrogates to be used to generate prior distributions for different Bayesian SHM tasks as the application of interest. Implementation is carried out in a numerical setting and model performance is assessed for two fundamental crack SHM problems; namely crack length monitoring (damage quantification) and crack growth monitoring (damage prognosis).

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Section: Accelerated Corrosion Under Three-point Bending Experimentsmentioning

confidence: 99%

On the Detection of Thickness Loss in Ship Hull Structures Through Strain Sensing

Silionis¹,

Anyfantis²

2022

Lecture Notes in Civil Engineering

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Corrosion pit-induced stress concentration in 7005 aluminium alloy: Mechanical degradation and pit parameter analysis

Li,

Wang,

Kou

et al. 2024

Engineering Fracture Mechanics

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Optimal sensor placement for corrosion induced thickness loss monitoring in ship structures

Silionis,

Anyfantis

2024

Marine Structures

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Pitting corrosion identification approach based on inverse finite element method for marine structure applications

Cited by 8 publications

References 32 publications

On the Detection of Thickness Loss in Ship Hull Structures Through Strain Sensing

On the Detection of Thickness Loss in Ship Hull Structures Through Strain Sensing

Corrosion pit-induced stress concentration in 7005 aluminium alloy: Mechanical degradation and pit parameter analysis

Optimal sensor placement for corrosion induced thickness loss monitoring in ship structures

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