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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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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693.932 PEOPLE
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Zhang, Jie

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University of Bristol

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2022Sizing limitations of ultrasonic array images for non-sharp defects and their impact on structural integrity assessments3citations
  • 2020Data fusion of multi-view ultrasonic imaging for characterisation of large defects31citations
  • 2020Effect of crack-like defects on the fracture behaviour of Wire + Arc additively manufactured nickel-base Alloy 71876citations
  • 2012Monte Carlo inversion of ultrasonic array data to map anisotropic weld properties30citations
  • 2012Autofocus imagingcitations
  • 2010Ultrasonic condition monitoring using thin-film piezoelectric sensors11citations
  • 2006Monitoring of lubricant film failure in a ball bearing using ultrasound63citations

Places of action

Chart of shared publication
Bhat, Shivaprasad Shridhara
1 / 1 shared
Larrosa, Nicolas O.
1 / 21 shared
Bevan, Rhodri L. T.
1 / 1 shared
Budyn, Nicolas
1 / 1 shared
Kitazawa, So
1 / 1 shared
Croxford, Anthony J.
1 / 9 shared
Wilcox, Pd
3 / 20 shared
Coules, Harry E.
1 / 17 shared
Ding, Jialuo
1 / 39 shared
Williams, Stewart W.
1 / 33 shared
Jones, Cp
1 / 11 shared
Seow, Cui Er
1 / 2 shared
Wu, Guiyi
1 / 1 shared
Drinkwater, Bw
4 / 25 shared
Hunter, Alan J.
1 / 2 shared
Hunter, A.
1 / 5 shared
Hutson, D.
1 / 4 shared
Elgoyhen, J.
1 / 1 shared
Hood, Jp
1 / 1 shared
Kirk, Kj
1 / 1 shared
Dwyer-Joyce, Rs
2 / 3 shared
Chart of publication period
2022
2020
2012
2010
2006

Co-Authors (by relevance)

  • Bhat, Shivaprasad Shridhara
  • Larrosa, Nicolas O.
  • Bevan, Rhodri L. T.
  • Budyn, Nicolas
  • Kitazawa, So
  • Croxford, Anthony J.
  • Wilcox, Pd
  • Coules, Harry E.
  • Ding, Jialuo
  • Williams, Stewart W.
  • Jones, Cp
  • Seow, Cui Er
  • Wu, Guiyi
  • Drinkwater, Bw
  • Hunter, Alan J.
  • Hunter, A.
  • Hutson, D.
  • Elgoyhen, J.
  • Hood, Jp
  • Kirk, Kj
  • Dwyer-Joyce, Rs
OrganizationsLocationPeople

document

Autofocus imaging

  • Hunter, A.
  • Drinkwater, Bw
  • Wilcox, Pd
  • Zhang, Jie
Abstract

<p>The quality of an ultrasonic array image, especially for anisotropic material, depends on accurate information about acoustic properties. Inaccuracy of acoustic properties causes image degradation, e.g., blurring, errors in locating of reflectors and introduction of artifacts. In this paper, for an anisotropic austenitic steel weld, an autofocus imaging technique is presented. The array data from a series of beacons is captured and then used to statistically extract anisotropic weld properties by using a Monte-Carlo inversion approach. The beacon and imaging systems are realized using two separated arrays; one acts as a series of beacons and the other images these beacons. Key to the Monte-Carlo inversion scheme is a fast forward model of wave propagation in the anisotropic weld and this is based on the Dijkstra algorithm. Using this autofocus approach a measured weld map was extracted from an austenitic weld and used to reduce location errors, initially greater than 6mm, to less than 1mm. © 2012 American Institute of Physics.</p>

Topics
  • impedance spectroscopy
  • laser emission spectroscopy
  • anisotropic
  • steel
  • ultrasonic