Abstract:We report experimental observations of the dynamic behavior
of single, magnetically tagged 3–4 mm particles varying in
density from 0.55 g/cm3 to 1.2 g/cm3 as they
migrate freely in a bubbling air-fluidized bed of 177–250 μm
glass beads of 2.5 g/cm3 density over a range of air flows.
The densities of the tracer particles (made by imbedding small magnets
in wooden particles) were chosen to span a range typical for many
biomass materials and exhibited both segregated and well-mixed behavior.
Using high-speed mea… Show more
“…Using MPT, a tracer particle that fluid-dynamically resembles a fuel particle can be tracked in a 3-dimensional bed, yielding highly resolved information about the particle trajectory and rotation [52], and exhibiting better performance and wider scope than X-ray tomography at a much lower cost. Despite the fact that various research groups have applied MPT to particle tracking in fluidised beds in recent years [46,[49][50][51][52][53][54], the literature on this topic is still scarce and is limited to pseudo-2-dimensional beds or narrow reactors and lacking any application of fluid-dynamical scaling laws, except in the initial work by the authors [52], which proved the feasibility of using MPT in beds operated with particles that fulfilled fluid dynamic scaling.…”
“…Using MPT, a tracer particle that fluid-dynamically resembles a fuel particle can be tracked in a 3-dimensional bed, yielding highly resolved information about the particle trajectory and rotation [52], and exhibiting better performance and wider scope than X-ray tomography at a much lower cost. Despite the fact that various research groups have applied MPT to particle tracking in fluidised beds in recent years [46,[49][50][51][52][53][54], the literature on this topic is still scarce and is limited to pseudo-2-dimensional beds or narrow reactors and lacking any application of fluid-dynamical scaling laws, except in the initial work by the authors [52], which proved the feasibility of using MPT in beds operated with particles that fulfilled fluid dynamic scaling.…”
“…They were able to follow a rather large magnetic marker at 62.5 Hz. Halow et al studied segregation effects in fluidized beds using just four Hall effect sensors. Finally, Neuwirth et al have used MPT to enable comparison of measured particle motion in a rotor granulator with simulated results obtained from discrete element model.…”
Noninvasive monitoring of multiphase flow is rapidly gaining increased interest. More specifically noninvasive particle tracking techniques have received a lot of attention in recent years to study dense granular flow. However, these techniques are usually quite expensive and require strict safety measures. An improved magnetic particle tracking (MPT) technique for dense granular flow will be presented in this article. The improvements of the analysis technique for MPT will be demonstrated and rigorously tested with a three-dimensional system and two-dimensional sensor system. The strengths and limitations of the MPT technique will also be reported. Finally, the results of the MPT are compared with data obtained from a combined particle image velocimetry and digital image analysis technique. V C 2014 American Institute of Chemical Engineers AIChE J, 60: [3133][3134][3135][3136][3137][3138][3139][3140][3141][3142] 2014
“…Although using these novel experimental techniques (e.g., RPT and PEPT) has provided some valuable insights into the particle motions in a fluidized bed, the high expense and the concomitant safety concerns of such techniques still highly hinder their wider applications in a large number of repetitive experiments. Based on this, Mohs et al 10 for the first time utilized the so-called magnetic particle tracking (MPT) technology, which is non-intrusive and relatively cheap, to track single solid particles in a prismatic spouted bed, and later this technology was successfully employed in a spouted fluidized bed 11 and a bubbling fluidized bed, 12 demonstrating its great potential in particle tracking. Buist et al 13 improved the accuracy of MPT by sequential quadratic programming and wavelet filtering.…”
In
this paper, dispersion behaviors of continuous-feeding fuel
particles in a 3D fluidized bed were studied in detail using CFD–DEM
simulations with a substantial difference in particle properties between
the fuel and bed material, as well as the dynamic fuel-feeding process
being reasonably considered. By quantitively evaluating the dispersion
characteristics of fuel particles, the effects of key factors including
the fluidization velocity, initial bed height, and the particle properties
of fuel and bed materials on the dispersion behaviors of fuel particles
were comprehensively examined with the motion and distribution of
fuel particles being discussed in detail. The results indicated that
crucially dominated by the bubble behaviors, the axial dispersion
coefficient of fuel particles is 1–2 orders-of-magnitude larger
than that in the radial direction in the fluidized bed. Increasing
the fluidization velocity obviously promotes the dispersion and thus
the uniformity distribution of the fuel particles. More intense axial
dispersion of fuel particles appears with the higher initial bed height,
under which conditions the axial distribution uniformity of fuel particles
is efficiently improved. On the other hand, using the finer bed material
enhances the fuel dispersion at the same fluidization velocity but
instead weakens the dispersion at a similar fluidization number. Furthermore,
the low-density fuel particles have a larger dispersion coefficient,
which can be mainly explained by their preferential distribution behavior
in the dense bed surface region.
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