Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Hectors, Kris

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Ghent University

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (8/8 displayed)

  • 2024Neural network based fatigue lifetime prediction of metals subjected to block loading5citations
  • 2024Neural network based fatigue lifetime prediction of metals subjected to block loading5citations
  • 2023Stress intensity factor calculation for short cracks initiating from a semi-ellipsoidal pitcitations
  • 2023Stress intensity factor calculation for short cracks initiating from a semi-ellipsoidal pitcitations
  • 2023Quantitative analysis of the correlation between geometric parameters of pits and stress concentration factors for a plate subject to uniaxial tensile stress9citations
  • 2023Quantitative analysis of the correlation between geometric parameters of pits and stress concentration factors for a plate subject to uniaxial tensile stress9citations
  • 2023A numerical study on tensile stress concentration in semi-ellipsoidal corrosion pits2citations
  • 2020Evaluation of fatigue crack propagation in steel ESET specimens subjected to variable load spectra3citations

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Ahmed, Bilal
2 / 7 shared
De Waele, Wim
4 / 78 shared
Bouckaert, Quinten
2 / 2 shared
Plets, Jelle
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Waele, Wim De
4 / 30 shared
Vancoillie, Robin
2 / 2 shared
Saeed, Hasan
2 / 8 shared
Mehri Sofiani, Farid
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Elahi, Seyed Ahmad
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Chaudhuri, Somsubhro
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Chaudhuri, S.
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Trogh, Sven
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De Tender, Steven
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Micone, Nahuel
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2020

Co-Authors (by relevance)

  • Ahmed, Bilal
  • De Waele, Wim
  • Bouckaert, Quinten
  • Plets, Jelle
  • Waele, Wim De
  • Vancoillie, Robin
  • Saeed, Hasan
  • Mehri Sofiani, Farid
  • Elahi, Seyed Ahmad
  • Chaudhuri, Somsubhro
  • Chaudhuri, S.
  • Trogh, Sven
  • De Tender, Steven
  • Micone, Nahuel
OrganizationsLocationPeople

article

Quantitative analysis of the correlation between geometric parameters of pits and stress concentration factors for a plate subject to uniaxial tensile stress

  • Elahi, Seyed Ahmad
  • Chaudhuri, S.
  • Hectors, Kris
  • Mehri Sofiani, Farid
  • Waele, Wim De
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.

Topics
  • impedance spectroscopy
  • surface
  • corrosion
  • crack
  • steel
  • fatigue
  • quantitative determination method