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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Naji, M.
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University of Strathclyde

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (22/22 displayed)

  • 20243-Dimensional residual neural architecture search for ultrasonic defect detection5citations
  • 2023Application of eddy currents for inspection of carbon fibre compositescitations
  • 2023Application of machine learning techniques for defect detection, localisation, and sizing in ultrasonic testing of carbon fibre reinforced polymers citations
  • 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
  • 2023Using neural architecture search to discover a convolutional neural network to detect defects From volumetric ultrasonic testing data of compositescitations
  • 2023Phased array inspection of narrow-gap weld LOSWF defects for in-process weld inspectioncitations
  • 2022Transfer learning for classification of experimental ultrasonic non-destructive testing images from synthetic datacitations
  • 2022Autonomous and targeted eddy current inspection from UT feature guided wave screening of resistance seam weldscitations
  • 2022Mechanical stress measurement using phased array ultrasonic systemcitations
  • 2022Automated bounding box annotation for NDT ultrasound defect detectioncitations
  • 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
  • 2022Dual-tandem phased array inspection for imaging near-vertical defects in narrow gap weldscitations
  • 2022Targeted eddy current inspection based on ultrasonic feature guided wave screening of resistance seam weldscitations
  • 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
  • 2022Automated real time eddy current array inspection of nuclear assets16citations
  • 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
  • 2019Ultrasonic phased array inspection of a Wire + Arc Additive Manufactured (WAAM) sample with intentionally embedded defects74citations

Places of action

Chart of shared publication
Tunukovic, Vedran
6 / 6 shared
Mackinnon, Christopher
3 / 3 shared
Wathavana Vithanage, Randika Kosala
11 / 11 shared
Ohare, Tom
5 / 5 shared
Mcknight, Shaun
7 / 7 shared
Macleod, Charles N.
21 / 45 shared
Pierce, Stephen
19 / 51 shared
Munro, Gavin
1 / 1 shared
Burnham, Kenneth Charles
1 / 1 shared
Foster, Euan
5 / 8 shared
Dobie, Gordon
4 / 21 shared
Obrien-Oreilly, J.
3 / 3 shared
Pyle, Richard
2 / 2 shared
Munro, G.
3 / 3 shared
Ohare, T.
3 / 3 shared
Mcknight, S.
3 / 3 shared
Halavage, Steven
4 / 6 shared
Loukas, Charalampos
8 / 13 shared
Ding, Jialuo
6 / 39 shared
Williams, Stewart
6 / 39 shared
Rizwan, Muhammad Khalid
3 / 4 shared
Misael, Pimentel Espirindio E. Silva
4 / 5 shared
Mckegney, Scott
4 / 6 shared
Lines, David
12 / 18 shared
Foster, Euan A.
1 / 2 shared
Zimermann, Rastislav
7 / 9 shared
Fitzpatrick, Stephen
4 / 14 shared
Vasilev, Momchil
10 / 17 shared
Poole, A.
1 / 2 shared
Mcinnes, M.
2 / 2 shared
Hifi, A.
1 / 1 shared
Gomez, R.
1 / 3 shared
Shields, M.
1 / 1 shared
Nicolson, Ewan
3 / 5 shared
Tant, Katherine Margaret Mary
1 / 5 shared
Mcinnes, Martin
3 / 3 shared
Gachagan, Anthony
9 / 76 shared
Bernard, Robert
3 / 5 shared
Bolton, Gary
3 / 5 shared
Hutchison, Alistair
1 / 1 shared
Mehnen, Jorn
1 / 4 shared
Lotfian, Saeid
1 / 22 shared
Javadi, Yashar
5 / 31 shared
Lawley, Alistair
1 / 1 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
Macdonald, Charles
1 / 1 shared
Pierce, Stephen Gareth
1 / 3 shared
Foster, Euan Alexander
1 / 1 shared
Stratoudaki, Theodosia
1 / 7 shared
Mineo, Carmelo
2 / 15 shared
Qiu, Zhen
2 / 14 shared
Sweeney, Nina E.
1 / 3 shared
Su, Riliang
1 / 3 shared
Chart of publication period
2024
2023
2022
2020
2019

Co-Authors (by relevance)

  • Tunukovic, Vedran
  • Mackinnon, Christopher
  • Wathavana Vithanage, Randika Kosala
  • Ohare, Tom
  • Mcknight, Shaun
  • Macleod, Charles N.
  • Pierce, Stephen
  • Munro, Gavin
  • Burnham, Kenneth Charles
  • Foster, Euan
  • Dobie, Gordon
  • Obrien-Oreilly, J.
  • Pyle, Richard
  • Munro, G.
  • Ohare, T.
  • Mcknight, S.
  • 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
  • Poole, A.
  • Mcinnes, M.
  • Hifi, A.
  • Gomez, R.
  • Shields, M.
  • Nicolson, Ewan
  • Tant, Katherine Margaret Mary
  • Mcinnes, Martin
  • Gachagan, Anthony
  • Bernard, Robert
  • Bolton, Gary
  • Hutchison, Alistair
  • Mehnen, Jorn
  • Lotfian, Saeid
  • Javadi, Yashar
  • Lawley, Alistair
  • Foster, E.
  • Burnham, K.
  • Gover, H.
  • Paton, S.
  • Grosser, M.
  • Macdonald, Charles
  • Pierce, Stephen Gareth
  • Foster, Euan Alexander
  • Stratoudaki, Theodosia
  • Mineo, Carmelo
  • Qiu, Zhen
  • Sweeney, Nina E.
  • Su, Riliang
OrganizationsLocationPeople

document

Dual-tandem phased array inspection for imaging near-vertical defects in narrow gap welds

  • Lines, David
  • Mohseni, Ehsan
  • Nicolson, Ewan
  • Macleod, Charles N.
  • Pierce, Stephen
Abstract

When considering narrow-gap welding processes, common in the nuclear industry, wherein the weld angle is in the range of 2° – 10°, lack-of-fusion defects can appear at near-vertical angles. Traditional single-probe phased array weld inspection, operated in pulse-echo mode, have shown a relatively low sensitivity to vertical and near-vertical planar defects. This is largely due to the dependency of pulse-echo inspection on defect orientation for a favourable reflection angle. Using a single-probe setup may not provide suitable assurances for detection of such defects as the majority of sound energy is reflected away from the transducer by the defect. Multi-mode self-tandem inspection has been used to improve sensitivity to defects of this type, but this method still relies on reflection orientation from the defect. Furthermore, in the case of narrow gap welding, material thicknesses are often large in the hundreds of mm’s and a growing number of required skips can greatly increase ray paths, and in turn attenuation effects.<br/>To overcome the aforementioned traditional phased array inspection challenges,introducing a second opposite facing phased array probe on the far side of the weld to perform simultaneous through-transmission and pulse-echo inspection was investigated. The addition of through-transmission acquisition allows for enhanced detection capability enabled by the combined indications obtained from defect reflections and diffraction effects. For near-vertical defects, this will allow responses from tip-diffraction to be included, in addition to body reflections obtained from pulse-echo. Moreover, Full Matric Capture (FMC) acquisition was deployed to obtain four distinct sub-datasets - one for each of the two pulse-echo and two through-transmission acquisitions performed.<br/>In addition, the added adaptability of the inspection system due to the inclusion of a second probe, including mode choice, probe separation and wedge considerations was investigated through numerical simulations and experiments. One such wedge consideration is the balance between beamforming and transmissibility for shear and longitudinal modes. Longitudinal waves exhibit greater diffraction effects, and are therefore the desirable mode choice for through-transmission. Conversely, shear wave modes provide better resolution and amplitude, so are desirable for pulse-echo. It is therefore advantageous to maximise the transmission of each of these modes without completely limiting the other. Analysis of different wedge angles was conducted and a conclusion drawn from the results of an optimal wedge angle for aluminium of ~20°. This is closer to a standard longitudinal wedge angle to avoid the first critical angle, which is typically surpassed by standard shear wedge angles of ~35°.<br/>It has been shown using ray-tracing simulations that using a combined pulse-echo and through-transmission setup can produce high SNR TFM images of vertical and near-vertical defects. Care must be taken in choosing the correct modes for each FMC sub-dataset, so as to maximise defect detection sensitivity. Data fusion techniques can also be applied for multi-mode and multi-view imaging, further increasing available image parameters. Initial multi-view data fusion tests have shown tip diffraction TFM imaging with a SNR up to 36dB.<br/>

Topics
  • impedance spectroscopy
  • inclusion
  • experiment
  • simulation
  • aluminium