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

Madsen, Steen Hjelm

  • Google
  • 3
  • 7
  • 96

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2021Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring50citations
  • 2019Understanding progressive failure mechanisms of a wind turbine blade trailing edge section through subcomponent tests and nonlinear FE analysis46citations
  • 2018Buckling and progressive failure of trailing edge subcomponent of wind turbine bladecitations

Places of action

Chart of shared publication
Chen, Xiao
3 / 13 shared
Berring, Peter
3 / 14 shared
Branner, Kim
3 / 26 shared
Mcgugan, Malcolm
1 / 21 shared
Yeniceli, Süleyman Cem
1 / 2 shared
Semenov, Sergei
3 / 4 shared
Belloni, Federico
1 / 6 shared
Chart of publication period
2021
2019
2018

Co-Authors (by relevance)

  • Chen, Xiao
  • Berring, Peter
  • Branner, Kim
  • Mcgugan, Malcolm
  • Yeniceli, Süleyman Cem
  • Semenov, Sergei
  • Belloni, Federico
OrganizationsLocationPeople

article

Understanding progressive failure mechanisms of a wind turbine blade trailing edge section through subcomponent tests and nonlinear FE analysis

  • Chen, Xiao
  • Madsen, Steen Hjelm
  • Berring, Peter
  • Branner, Kim
  • Semenov, Sergei
Abstract

This paper presents a comprehensive study on structural failure of a trailing edge section cut from a composite wind turbine blade. The focus is placed on understanding progressive failure behavior of the trailing edge section in subcomponent testing during its entire failure sequence. Digital Image Correlation (DIC) is used to capture buckling deformation and strain distributions of the specimen. Detailed post-test inspection is performed to identify failure modes and failure characteristics. A nonlinear Finite Element (FE) model that accounts for all observed failure modes is developed based on continuum damage mechanics and progressive failure analysis techniques. Multiple structural nonlinearities originate from buckling, and contact and material failures are included in the model to predict the failure process. The study shows that in addition to the buckling-driven failure phenomenon, the surface contact of sandwich panels contributes to the failure process of the trailing edge section. Foam materials start to fail before the ultimate load-carrying capacity of the specimen is reached, while both composite materials and adhesive materials fail in the post-peak regime. The matrix-dominant failure and delamination develop before the fiber-dominant failure in composite laminates. The proposed FE model captures the progressive failure process of the trailing edge section reasonably well.

Topics
  • impedance spectroscopy
  • surface
  • composite