Materials Map

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

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

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.

×

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.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Gripp, Iara

  • Google
  • 1
  • 4
  • 1

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2023Fatigue Life Prediction of S235 Details Based on Dislocation Density1citations

Places of action

Chart of shared publication
Pedrosa, Bruno
1 / 2 shared
Correia, José
1 / 7 shared
Fernandes, Lisete
1 / 5 shared
Rebelo, Carlos
1 / 8 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Pedrosa, Bruno
  • Correia, José
  • Fernandes, Lisete
  • Rebelo, Carlos
OrganizationsLocationPeople

article

Fatigue Life Prediction of S235 Details Based on Dislocation Density

  • Pedrosa, Bruno
  • Correia, José
  • Gripp, Iara
  • Fernandes, Lisete
  • Rebelo, Carlos
Abstract

<jats:title>Abstract</jats:title><jats:p>Global approaches have been the main procedure to design structural details and components under fatigue loading. This procedure is easy to apply but it disregards not only the effect of the material type but also the influence of the geometry in complex components. On the other hand, local approaches rely on the specific local damage parameters that can be assessed for each type of material and detail geometry. The parameters derived from low cycle fatigue (LCF) tests are the most common damage parameters used to predict the fatigue life and establish reliable fatigue design approaches. Recently, Huffman proposed a fatigue damage model based on strain energy density and on the dislocation density of the material. In this regard, S235 was selected to perform a metallographic and mechanical assessment aiming to define the dislocation density of the material and to describe the fatigue behavior using the Huffman damage model. Additionally, fatigue tests on structural details (plate with hole) were conducted and results were compared with fatigue life predictions based on Huffman local approach. It was found that Huffman model based on dislocation density is a reliable approach to predict the fatigue life of structural steel details.</jats:p>

Topics
  • density
  • impedance spectroscopy
  • energy density
  • fatigue
  • dislocation
  • structural steel