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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University of Bristol

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (9/9 displayed)

  • 2021Developing a high-fidelity knowledge base for improvements in the nondestructive testing of advanced composite material products3citations
  • 2020Data fusion of multi-view ultrasonic imaging for characterisation of large defects31citations
  • 2020The influence of tensile stress on inductively coupled piezoceramic sensors embedded in fibre-reinforced plastics2citations
  • 2016Health monitoring of composite structures throughout the life cyclecitations
  • 2016Monitoring cure and detecting damage in composites with embedded sensors38citations
  • 2015Design, application and validation of embedded ultrasonic sensors within composite materials1citations
  • 2015Design of an embedded sensor, for improved structural performance21citations
  • 2013Investigation of Inductively Coupled Ultrasonic Transducer System for NDE21citations
  • 2013Investigation of Capacitively Coupled Ultrasonic Transducer System for Nondestructive Evaluationcitations

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Gandhi, Nikita
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Rose, Rob
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Ward, Carwyn
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Bevan, Rhodri L. T.
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Budyn, Nicolas
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Kitazawa, So
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Wilcox, Pd
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Zhang, Jie
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Bond, Ip
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Chilles, James S.
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Chilles, James
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Koutsomitopoulou, Anastasia F.
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Chilles, Jamie
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Zhong, Cheng Huan
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Co-Authors (by relevance)

  • Gandhi, Nikita
  • Rose, Rob
  • Ward, Carwyn
  • Bevan, Rhodri L. T.
  • Budyn, Nicolas
  • Kitazawa, So
  • Wilcox, Pd
  • Zhang, Jie
  • Bond, Ip
  • Chilles, James S.
  • Chilles, James
  • Koutsomitopoulou, Anastasia F.
  • Chilles, Jamie
  • Wilcox, Paul D.
  • Zhong, Cheng Huan
OrganizationsLocationPeople

article

Data fusion of multi-view ultrasonic imaging for characterisation of large defects

  • Bevan, Rhodri L. T.
  • Budyn, Nicolas
  • Kitazawa, So
  • Croxford, Anthony J.
  • Wilcox, Pd
  • Zhang, Jie
Abstract

The multi-view total focusing method (TFM) enables a region of interest within a specimen to be imaged using different ray paths and wave mode combinations. For defects larger than the ultrasonic wavelength, different portions of the same defect may manifest in a number of views. For a crack, the tip diffraction response may be evident in certain views and the specular reflection in others. Accurate characterisation of large defects requires the information in multiple views to be combined. In this work, three data fusion methodologies are presented: a simple sum over all views, a sum weighted according to the inverse of the noise in each view and a matched filter approach. Four large defects are examined, one stress corrosion crack (SCC), two weld cracks and a pair of slagline defects in a weld. The matched filter (matched to a small circular void) provided significant improvement over the best individual view. The data fusion process incorporates artefact removal, where non-defect artefact signals within each image view are identified and masked, using a single defect-free dataset for training. The matched filter was able to accurately visualise the full 3D extent of the four defects, allowing characterisation via the decibel drop method. When compared to x-ray CT and micrograph data in the case of the SCC, the matched filter fusion provided excellent agreement. Its performance was also superior to any individual view while providing a single fused image that is easier for an operator to interpret than a set of multi-view images.

Topics
  • impedance spectroscopy
  • crack
  • ultrasonic
  • void
  • stress corrosion