Experimental characterization of axial fuel mixing in fluidized beds by magnetic particle tracking

Köhler, Anna; Rasch, Alexander; Pallarès, David; Johnsson, Filip

doi:10.1016/j.powtec.2016.12.093

Cited by 52 publications

(37 citation statements)

References 27 publications

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“…Therefore, the application of these techniques is challenging. Magnetic particle tracking (MPT) [24][25][26][27][28][29][30] has emerged as a novel experimental technique that has proven to be less expensive and safer than XRT and PEPT. MPT relies on following a magnetic dipole of a single tracer particle which allows tracking of the particle position, together with its orientation.…”

Section: Introductionmentioning

confidence: 99%

Fluidization of spherical versus elongated particles: Experimental investigation using magnetic particle tracking

et al. 2019

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In biomass processing fluidized beds are used to process granular materials where particles typically possess elongated shapes. However, for simplicity, in computer simulations particles are often considered spherical, even though elongated particles experience more complex particle-particle interactions as well as different hydrodynamic forces. The exact effect of these more complex interactions in dense fluidized suspensions is still not well understood. In this study we use the magnetic particle tracking technique to compare the fluidization behavior of spherical particles to that of elongated particles. We found a considerable difference between fluidization behavior of spherical versus elongated particles in the time-averaged particle velocity field as well as in the time-averaged particle rotational velocity profile. Moreover, we studied the effect of fluid velocity and the particle's aspect ratio on the particle's preferred orientation in different parts of the bed, which provides new insight in the fluidization behavior of elongated particles.

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Section: Introductionmentioning

confidence: 99%

Fluidization of spherical versus elongated particles: Experimental investigation using magnetic particle tracking

et al. 2019

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“…There are several ways to observe mixing and segregation phenomena in fluidized beds like magnetic particle tracking [17], electromagnetic tracking [18], bed-frozen method [19][20][21]. In case of the bed-frozen method, firstly an arbitrary, stationary fluidized state should be achieved with the mixture of the examined active particles and the bed material.…”

Section: The Bed-frozen Methodsmentioning

confidence: 99%

Experimental Investigation on Mixing and Segregation Behavior of Oxygen Carrier and Biomass Particle in Fluidized Bed

Szücs

Szentannai

2019

Period. Polytech. Mech. Eng.

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In this work, lab-scale cold fluidization equipment is designed and constructed to investigate the mixing and segregating phenomena of binary fluidized beds. The focus of the investigation is carbon reduction with the fluidized bed technology-based Chemical Looping Combustion (CLC). Nowadays, aspiration to carbon reduction focuses on the solid fuels. Therefore, it is of great importance to integrate the benefits of CLC technology with the use of solid fuels. The measurements of fuel particles in the fluidized bed are extended from the homogeneous and spherical shape to the inhomogeneous, non-spherical shape. During the tests, an iron-based oxygen carrier (OC) for chemical looping combustors is examined with different particle sizes. In addition, the tests included the examination of three different fuel samples (crushed coal, agricultural pellet, and Solid Recovered Fuel (SRF)), which can be utilized in chemical looping combustion with In-situ gasification. The experiments are carried out using the bed-frozen method. With this method, the vertical concentration of active particles could be measured. The results show that the particle size of the oxygen carrier does fundamentally influence its vertical placement, and the non-spherical character of most alternative fuels must also be considered for optimal reactor design.

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“…A new magnetic particle tracking (MPT) technology has recently been developed to address the issues facing the non-optical methods [12][13][14][15][16][17][18][19][20]. The working principle of MPT is to locate a magnetic source according to its field, which is modeled as a dipole.…”

Section: Introductionmentioning

confidence: 99%

A semi-analytical solution and AI-based reconstruction algorithms for magnetic particle tracking

Kokate

et al. 2021

PLoS ONE

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Magnetic particle tracking is a recently developed technology that can measure the translation and rotation of a particle in an opaque environment like a turbidity flow and fluidized-bed flow. The trajectory reconstruction usually relies on numerical optimization or filtering, which involve artificial parameters or thresholds. Existing analytical reconstruction algorithms have certain limitations and usually depend on the gradient of the magnetic field, which is not easy to measure accurately in many applications. This paper discusses a new semi-analytical solution and the related reconstruction algorithm. The new method can be used for an arbitrary sensor arrangement. To reduce the measurement uncertainty in practical applications, deep neural network (DNN)-based models are developed to denoise the reconstructed trajectory. Compared to traditional approaches such as wavelet-based filtering, the DNN-based denoisers are more accurate in the position reconstruction. However, they often over-smooth the velocity signal, and a hybrid method that combines the wavelet and DNN model provides a more accurate velocity reconstruction. All the DNN-based and wavelet methods perform well in the orientation reconstruction.

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Experimental characterization of axial fuel mixing in fluidized beds by magnetic particle tracking

Cited by 52 publications

References 27 publications

Fluidization of spherical versus elongated particles: Experimental investigation using magnetic particle tracking

Fluidization of spherical versus elongated particles: Experimental investigation using magnetic particle tracking

Experimental Investigation on Mixing and Segregation Behavior of Oxygen Carrier and Biomass Particle in Fluidized Bed

A semi-analytical solution and AI-based reconstruction algorithms for magnetic particle tracking

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