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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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2016Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition. FBGs, OBR and strain gauges comparison116citations

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Güemes, Alfredo
1 / 1 shared
Sierra, Julian
1 / 11 shared
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2016

Co-Authors (by relevance)

  • Güemes, Alfredo
  • Sierra, Julian
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article

Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition. FBGs, OBR and strain gauges comparison

  • Torres-Arredondo, Miguel Angel
  • Güemes, Alfredo
  • Sierra, Julian
Abstract

<p>A 13.5 m wind turbine blade prototype was designed and made of glass fiber and vinylester resin doped with carbon nanofibers. The blade was manufactured using Light RTM (Resin Transfer Molding) as a monocoque structure with a PVC foam core.Within the presented work, a methodology for instrumenting the blade with Fiber Optic Sensors (FOS) embedded into the structure during the manufacturing process was developed. Two different FOS technologies for strain sensing were embedded into the blade: Fiber Bragg Gratings (FBGs) and a plain fiber optic for distributed sensing using an Optical Backscatter Reflectometer (OBR). Besides the FOS, traditional electrical extensometers were bonded to the surface of the blade.By using Hierarchical nonlinear principal component analysis (h-NLPCA) it was possible to perform a pattern recognition technique based on the strain field inferred from the measurements acquired by different sensors. Defects and nonlinearities could be detected during the certification testing of the blades, avoiding the premature failure of the structure.Several static tests were conducted, including a test campaign with known artificial damages induced into the structure and the sensitivity of the technique was evaluated. The results showed that every damages could be detected by using different sensing techniques.</p>

Topics
  • surface
  • Carbon
  • glass
  • glass
  • defect
  • resin