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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Ward, Mark
University of Birmingham
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (25/25 displayed)
- 2021Metallurgical modelling of Ti-6Al-4V for welding applicationscitations
- 2020Microstructural modelling of thermally-driven β grain growth, lamellae & martensite in Ti-6Al-4Vcitations
- 2019Microstructural modelling of the α+β phase in Ti-6Al-4V:citations
- 2019Modelling of the heat-affected and thermomechanically affected zones in a Ti-6Al-4V inertia friction weldcitations
- 2017Study of as-cast structure formation in Titanium alloy
- 2017Keyhole formation and thermal fluid flow-induced porosity during laser fusion welding in titanium alloyscitations
- 2016Porosity formation in laser welded Ti-6Al-4V Alloy: modelling and validation
- 2016Linking a CFD and FE analysis for Welding Simulations in Ti-6Al-4V
- 2016Calculating the energy required to undergo the conditioning phase of a titanium alloy inertia friction weldcitations
- 2016An integrated modelling approach for predicting process maps of residual stress and distortion in a laser weldcitations
- 2016Defect formation and its mitigation in selective laser melting of high γ′ Ni-base superalloyscitations
- 2016Technology scale-up in metal additive manufacture
- 2015Linear friction welding of Ti6Al4V: experiments and modellingcitations
- 2015Validation of a Model of Linear Friction Welding of Ti6Al4V by Considering Welds of Different Sizescitations
- 2015On the role of melt flow into the surface structure and porosity development during selective laser meltingcitations
- 2015Influence of processing conditions on strut structure and compressive properties of cellular lattice structures fabricated by selective laser meltingcitations
- 2013Determination of the magnitude of interfacial air-gap and heat transfer during ingot casting into permanent metal moulds by numerical and experimental techniquescitations
- 2013A multiscale 3D model of the Vacuum Arc remelting processcitations
- 2012A multi-scale 3D model of the vacuum arc remelting processcitations
- 2011Linear friction welding of Ti-6Al-4V: Modelling and validationcitations
- 2010Microstructure and corrosion of Pd-modified Ti alloys produced by powder metallurgycitations
- 2009An analysis of the use of magnetic source tomography to measure the spatial distribution of electric current during vacuum arc remeltingcitations
- 2008Effect of Variation in Process Parameters on the Formation of Freckle in INCONEL 718 by Vacuum Arc Remeltingcitations
- 2004The effect of VAR process parameters on white spot formation in INCONEL 718citations
- 2004A simple transient numerical model for heat transfer and shape evolution during the production of rings by centrifugal spray depositioncitations
Places of action
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article
An analysis of the use of magnetic source tomography to measure the spatial distribution of electric current during vacuum arc remelting
Abstract
Magnetic source tomography is explored to analyse the distribution of electric current during vacuum arc remelting (VAR). The goal is to use sensors outside the process to deduce the behaviour within. VAR systems having non-axisymmetric distributions of arc current were modelled using a commercial finite element electromagnetic code (Opera 3d), and a database was created from the resulting patterns of magnetic flux predicted to occur outside the crucible. A reconstruction algorithm was developed using constrained nonlinear optimization to estimate the arc current distribution within the process from the magnetic field data outside. The capabilities of this algorithm were studied, and it was found that given sufficiently low noise in the measurement data it was possible to accurately deduce important features of the spatial distribution of the arc current.