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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1.080 Topics available

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977 Locations available

693.932 PEOPLE
693.932 People People

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University of Strathclyde

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (11/11 displayed)

  • 20243-Dimensional residual neural architecture search for ultrasonic defect detection5citations
  • 2023In-process non-destructive evaluation of metal additive manufactured components at build using ultrasound and eddy-current approaches11citations
  • 2023Mapping SEARCH capabilities to Spirit AeroSystems NDE and automation demand for compositescitations
  • 2022Mechanical stress measurement using phased array ultrasonic systemcitations
  • 2022Multi-sensor electromagnetic inspection feasibility for aerospace composites surface defectscitations
  • 2022Investigating ultrasound wave propagation through the coupling medium and non-flat surface of wire + arc additive manufactured components inspected by a PAUT roller-probecitations
  • 2022Automated multi-modal in-process non-destructive evaluation of wire + arc additive manufacturingcitations
  • 2022In-process non-destructive evaluation of wire + arc additive manufacture components using ultrasound high-temperature dry-coupled roller-probecitations
  • 2022Collaborative robotic Wire + Arc Additive Manufacture and sensor-enabled in-process ultrasonic Non-Destructive Evaluation16citations
  • 2020In-process calibration of a non-destructive testing system used for in-process inspection of multi-pass welding29citations
  • 2020Laser-assisted surface adaptive ultrasound (SAUL) inspection of samples with complex surface profiles using a phased array roller-probecitations

Places of action

Chart of shared publication
Tunukovic, Vedran
2 / 6 shared
Mackinnon, Christopher
1 / 3 shared
Ohare, Tom
1 / 5 shared
Mohseni, Ehsan
11 / 22 shared
Mcknight, Shaun
1 / 7 shared
Macleod, Charles N.
10 / 45 shared
Pierce, Stephen
10 / 51 shared
Halavage, Steven
4 / 6 shared
Loukas, Charalampos
5 / 13 shared
Ding, Jialuo
5 / 39 shared
Williams, Stewart
5 / 39 shared
Rizwan, Muhammad Khalid
3 / 4 shared
Misael, Pimentel Espirindio E. Silva
4 / 5 shared
Mckegney, Scott
4 / 6 shared
Lines, David
7 / 18 shared
Foster, Euan A.
1 / 2 shared
Zimermann, Rastislav
7 / 9 shared
Fitzpatrick, Stephen
4 / 14 shared
Vasilev, Momchil
6 / 17 shared
Dobie, Gordon
2 / 21 shared
Poole, A.
1 / 2 shared
Obrien-Oreilly, J.
2 / 3 shared
Pyle, Richard
1 / 2 shared
Munro, G.
2 / 3 shared
Ohare, T.
2 / 3 shared
Mcinnes, M.
2 / 2 shared
Hifi, A.
1 / 1 shared
Mcknight, S.
2 / 3 shared
Gomez, R.
1 / 3 shared
Shields, M.
1 / 1 shared
Hutchison, Alistair
1 / 1 shared
Mehnen, Jorn
1 / 4 shared
Lotfian, Saeid
1 / 22 shared
Gachagan, Anthony
5 / 76 shared
Javadi, Yashar
4 / 31 shared
Foster, E.
1 / 2 shared
Burnham, K.
1 / 1 shared
Gover, H.
1 / 1 shared
Paton, S.
1 / 1 shared
Grosser, M.
1 / 2 shared
Foster, Euan
2 / 8 shared
Macdonald, Charles
1 / 1 shared
Pierce, Stephen Gareth
1 / 3 shared
Stratoudaki, Theodosia
1 / 7 shared
Mineo, Carmelo
1 / 15 shared
Qiu, Zhen
2 / 14 shared
Sweeney, Nina E.
1 / 3 shared
Chart of publication period
2024
2023
2022
2020

Co-Authors (by relevance)

  • Tunukovic, Vedran
  • Mackinnon, Christopher
  • Ohare, Tom
  • Mohseni, Ehsan
  • Mcknight, Shaun
  • Macleod, Charles N.
  • Pierce, Stephen
  • Halavage, Steven
  • Loukas, Charalampos
  • Ding, Jialuo
  • Williams, Stewart
  • Rizwan, Muhammad Khalid
  • Misael, Pimentel Espirindio E. Silva
  • Mckegney, Scott
  • Lines, David
  • Foster, Euan A.
  • Zimermann, Rastislav
  • Fitzpatrick, Stephen
  • Vasilev, Momchil
  • Dobie, Gordon
  • Poole, A.
  • Obrien-Oreilly, J.
  • Pyle, Richard
  • Munro, G.
  • Ohare, T.
  • Mcinnes, M.
  • Hifi, A.
  • Mcknight, S.
  • Gomez, R.
  • Shields, M.
  • Hutchison, Alistair
  • Mehnen, Jorn
  • Lotfian, Saeid
  • Gachagan, Anthony
  • Javadi, Yashar
  • Foster, E.
  • Burnham, K.
  • Gover, H.
  • Paton, S.
  • Grosser, M.
  • Foster, Euan
  • Macdonald, Charles
  • Pierce, Stephen Gareth
  • Stratoudaki, Theodosia
  • Mineo, Carmelo
  • Qiu, Zhen
  • Sweeney, Nina E.
OrganizationsLocationPeople

article

Collaborative robotic Wire + Arc Additive Manufacture and sensor-enabled in-process ultrasonic Non-Destructive Evaluation

  • Halavage, Steven
  • Loukas, Charalampos
  • Mohseni, Ehsan
  • Ding, Jialuo
  • Williams, Stewart
  • Macleod, Charles N.
  • Misael, Pimentel Espirindio E. Silva
  • Mckegney, Scott
  • Lines, David
  • Wathavana Vithanage, Randika Kosala
  • Pierce, Stephen Gareth
  • Zimermann, Rastislav
  • Fitzpatrick, Stephen
  • Vasilev, Momchil
  • Javadi, Yashar
Abstract

<p>The demand for cost-efficient manufacturing of complex metal components has driven research for metal Additive Manufacturing (AM) such as Wire + Arc Additive Manufacturing (WAAM). WAAM enables automated, time-and material-efficient manufacturing of metal parts. To strengthen these benefits, the demand for robotically deployed in-process Non-Destructive Evaluation (NDE) has risen, aiming to replace current manually deployed inspection techniques after completion of the part. This work presents a synchronized multi-robot WAAM and NDE cell aiming to achieve (1) defect detection in-process, (2) enable possible in-process repair and (3) prevent costly scrappage or rework of completed defective builds. The deployment of the NDE during a deposition process is achieved through real-time position control of robots based on sensor input. A novel high-temperature capable, dry-coupled phased array ultrasound transducer (PAUT) roller-probe device is used for the NDE inspection. The dry-coupled sensor is tailored for coupling with an as-built high-temperature WAAM surface at an applied force and speed. The demonstration of the novel ultrasound in-process defect detection approach, presented in this paper, was performed on a titanium WAAM straight sample containing an intentionally embedded tungsten tube reflectors with an internal diameter of 1.0 mm. The ultrasound data were acquired after a pre-specified layer, in-process, employing the Full Matrix Capture (FMC) technique for subsequent post-processing using the adaptive Total Focusing Method (TFM) imaging algorithm assisted by a surface reconstruction algorithm based on the Synthetic Aperture Focusing Technique (SAFT). The presented results show a sufficient signal-to-noise ratio. Therefore, a potential for early defect detection is achieved, directly strengthening the benefits of the AM process by enabling a possible in-process repair.</p>

Topics
  • Deposition
  • impedance spectroscopy
  • surface
  • defect
  • ultrasonic
  • titanium
  • tungsten
  • wire
  • additive manufacturing