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Coarsening of grain-refined semi-solid Al-Ge32 alloy: X-ray microtomography and in situ radiography
(2007)
A x-ray radioscopy technique for measuring in situ chemical diffusion coefficients in metallic melts
is presented. The long-capillary diffusion measurement method is combined with imaging
techniques using microfocus tubes and flat panel detectors in order to visualize and quantitatively
analyze diffusive mixing of two melts of different chemical composition. The interdiffusion
coefficient as function of temperature and time is obtained by applying Ficks diffusion laws.
Tracking the time dependence of the mean square penetration depth of the mixing process allows to
detect changes in the mass transport caused by convective flow. The possibility to sort out
convective mass transport contributions from analysis enhances significantly the accuracy compared
to the conventional long-capillary diffusion measurement method with postmortem analysis. The
performance of this novel diffusion measurement method with x-ray radiography technique is
demonstrated by a diffusion experiment in an Al-Ni melt.
The three-dimensional water distribution and water transport paths in the gas diffusion layer (GDL) and the adjacent micro-porous layer (MPL) of a polymer electrolyte membrane fuel cell (PEMFC) were analyzed during cell operation. The technique of quasi in-situ X-ray tomography was used for a 3D visualization of the water distribution and the structure of the GDL at different operating conditions. Based on findings from in-situ radiographic measurements water transport paths were detected and subsequently examined by tomography. The combination of these 2D and 3D techniques allows for a fully three-dimensionally resolved visualization of transport paths through the GDL.
An algorithm has been developed to remove reliably dotted interferences impairing the perceptibility of objects within a radiographic image. This particularly is a major challenge encountered with neutron radiographs collected at the NECTAR facility, Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II): the resulting images are dominated by features resembling a snow flurry. These artefacts are caused by scattered neutrons, gamma radiation, cosmic radiation, etc. all hitting the detector CCD directly in spite of a sophisticated shielding. This makes such images rather useless for further direct evaluations.
One approach to resolve this problem of these random effects would be to collect a vast number of single images, to combine them appropriately and to process them with common image filtering procedures. However, it has been shown that, e.g. median filtering, depending on the kernel size in the plane and/or the number of single shots to be combined, is either insufficient or tends to blur sharp lined structures. This inevitably makes a visually controlled processing image by image unavoidable. Particularly in tomographic studies, it would be by far too tedious to treat each single projection by this way. Alternatively, it would be not only more comfortable but also in many cases the only reasonable approach to filter a stack of images in a batch procedure to get rid of the disturbing interferences.
The algorithm presented here meets all these requirements. It reliably frees the images from the snowy pattern described above without the loss of fine structures and without a general blurring of the image. It consists of an iterative, within a batch procedure parameter free filtering algorithm aiming to eliminate the often complex interfering artefacts while leaving the original information untouched as far as possible.
Determining scatter ratios at high energies (> ~ 1MeV) presents challenges not immediately obvious from measurements at conventional X-ray energies. This includes reduced attenuation even in heavy elements as well as a stronger forward bias of scattering. In order to check the reliability of different measurement setups with regard to material thicknesses, distances, and collimation, attenuation and scattering were separately simulated using a Monte Carlo model. The simulation results help in understanding the sources of radiation scattered into the detection area, thereby aiding in eliminating undesired contributions.