| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Mehri Sofiani, Farid
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (21/21 displayed)
- 2024A hybrid probabilistic-deterministic framework for prediction of characteristic size of corrosion pits in low-carbon steel following long-term seawater exposurecitations
- 2023Stress intensity factor calculation for short cracks initiating from a semi-ellipsoidal pit
- 2023Stress intensity factor calculation for short cracks initiating from a semi-ellipsoidal pit
- 2023Thermometric investigation of fatigue crack initiation from corrosion pits in structural steel used in offshore wind turbines
- 2023Quantitative analysis of the correlation between geometric parameters of pits and stress concentration factors for a plate subject to uniaxial tensile stresscitations
- 2023Quantitative analysis of the correlation between geometric parameters of pits and stress concentration factors for a plate subject to uniaxial tensile stresscitations
- 2023Investigation of the effect of pitting corrosion on the fatigue strength degradation of structural steel using a short crack modelcitations
- 2023Investigation of the effect of pitting corrosion on the fatigue strength degradation of structural steel using a short crack modelcitations
- 2023Smart S-N curve for fatigue lifetime predictions of offshore wind turbine support structures affected by corrosion
- 2023Smart S-N curve for fatigue lifetime predictions of offshore wind turbine support structures affected by corrosion
- 2023Evaluation of the corrosion pit growth rate in structural steel S355 by phase-field modelling
- 2023Evaluation of the corrosion pit growth rate in structural steel S355 by phase-field modelling
- 2023A numerical study on tensile stress concentration in semi-ellipsoidal corrosion pitscitations
- 2022Numerical study on the effect of pitting corrosion on the fatigue strength degradation of offshore wind turbine substructures using a short crack model
- 2022Numerical study on the effect of pitting corrosion on the fatigue strength degradation of offshore wind turbine substructures using a short crack model
- 2022A numerical investigation on the pitting corrosion in offshore wind turbine substructures
- 2022A numerical investigation on the pitting corrosion in offshore wind turbine substructures
- 2022Fracture Toughness Determination on an SCB Specimen by Meshless Methodscitations
- 2022Fracture Toughness Determination on an SCB Specimen by Meshless Methodscitations
- 2022Fatigue strength degradation of structural steel in sea environment due to pitting corrosion
- 2022Pitting corrosion and its transition to crack in offshore wind turbine supporting structures
Places of action
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article
Quantitative analysis of the correlation between geometric parameters of pits and stress concentration factors for a plate subject to uniaxial tensile stress
Abstract
The offshore environment is inherently corrosive. Consequently, pits may nucleate on exposed steel surfaces. Corrosion pits can be a source of crack initiation when the structure is subject to fatigue loading. The criticality of a corrosion pit with respect to the structural integrity depends on its shape and size and can be quantified using a stress concentration factor ( ). In this work, a parametric 3D finite element model is developed to perform stress analysis of a pitted plate subjected to uniaxial tensile stress. The model is used for an extensive parameter study in whichis determined for various pit configurations. It is demonstrated that each one of the geometric parameters holds a substantial influence on the location of the Most Critical Region (MCR). It is shown thatincreases as the pit gets narrower. Pits with an elliptical mouth yield highervalues when the angle between the load direction and the pit mouth major axis increases. Moreover,increases with the increase in the localized thickness loss which is more pronounced for relatively wider pits. Finally, a regression model is presented for estimatingbased on the geometric parameters of a pit.