Tomographic X-ray particle tracking velocimetry

Abstract

We investigate the feasibility of in-laboratory tomographic X-ray particle tracking velocimetry (TXPTV) and consider creeping flows with nearly density matched flow tracers. Specifically, in these proof-of-concept experiments we examined a Poiseuille flow, flow through porous media and a multiphase flow with a Taylor bubble. For a full 360$$^\circ$$ ∘ computed tomography (CT) scan we show that the specially selected 60 micron tracer particles could be imaged in less than 3 seconds with a signal-to-noise ratio between the tracers and the fluid of 2.5, sufficient to achieve proper volumetric segmentation at each time step. In the pipe flow, continuous Lagrangian particle trajectories were obtained, after which all the standard techniques used for PTV or PIV (taken at visible wave lengths) could also be employed for TXPTV data. And, with TXPTV we can examine flows inaccessible with visible wave lengths due to opaque media or numerous refractive interfaces. In the case of opaque porous media we were able to observe material accumulation and pore clogging, and for flow with Taylor bubble we can trace the particles and hence obtain velocities in the liquid film between the wall and bubble, with thickness of liquid film itself also simultaneously obtained from the volumetric reconstruction after segmentation. While improvements in scan speed are anticipated due to continuing improvements in CT system components, we show that for the flows examined even the presently available CT systems could yield quantitative flow data with the primary limitation being the quality of available flow tracers. Graphic abstract

X-ray tomographic micro-particle velocimetry in porous media

“…Contrary to established micro-velocimetry approaches, our method used cone-beam CT data, which may suffer from specific artifacts that could impact the detection and localization of tracer particles: the geometrical deformations at the top and bottom of the volume ("cone beam artifacts"), limited spatial resolution for fast image acquisition, and motion artifacts (Cnudde and Boone, 2013;Mäkiharju et al, 2022). Since the impact of these artifacts was unclear and difficult to quantify in the experimental data, we created and analyzed a digital twin of the porous glass experiment.…”

“…Very recently, Mäkiharju et al (2022) provided a proof-of-concept that flow tracer parti-4 This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.…”

X-ray Tomographic Micro-Particle Velocimetry in Porous Media

“…Contrary to established micro-velocimetry approaches, our method used cone-beam µCT data, which may suffer from specific artifacts that could impact the detection and localization of tracer particles: the geometrical deformations at the top and bottom of the volume ("cone beam artifacts"), limited spatial resolution for fast image acquisition, and motion artifacts (Cnudde and Boone, 2013;Mäkiharju et al, 2022). Since the impact of these artifacts was unclear and difficult to quantify in the experimental data, we created and analyzed a digital twin of the porous glass experiment.…”

“…Very recently, Mäkiharju et al (2022) provided a proof-of-concept that flow tracer particles (60 µm large silver-coated hollow glass spheres) in a cylindrical tube could be visualized with laboratory-based µCT at frame rates on the order of seconds. Here, we present the first successful µCT-based particle velocimetry measurements of creeping single-phase flow in porous media, namely a sandpack and a sintered glass filter.…”

Four-dimensional X-ray micro-tomography imaging of dynamic processes in geosciences

“…In multi-phase fluid flow, especially, tracking the interface may be difficult because of the large number of interfaces and the large amount of deformation they experience. In that case, tomographic X-ray particle tracking velocimetry [Dubsky et al, 2012, Mäkiharju et al, 2021 techniques may be preferred to measure the fluid velocity and characterize flow more efficiently than XMT.…”