Using tomograms to assess the local solid concentrations in a slurry reactor equipped with a Maxblend impeller

Mishra, Prakash Chandra; Ein‐Mozaffari, Farhad

doi:10.1016/j.powtec.2016.07.007

Cited by 46 publications

(63 citation statements)

References 54 publications

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“…Denoting ( Q ( i ),

) as the i th pair of the existing record, there is a tremendous amount of historical records whose set is denoted as QS . Consequently, we realize the relation F in Equation (3) by the basic principle “similar problems have similar solutions” in case-based reasoning model [ 19 , 20 ], and naturally it is a weighting average of all inputs. For any new indirect measurement Q ( i ), we can estimate its unknown value of SC value

by a simple weighting mean as

where d j is computed by the similarity from Q i to m historical records that are the closest to Q i , and thus their similarity is measured by the following weighting distance:

where w k is the weighting value of Q k , k = 1, 2, …, 13.…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…Denoting ( Q ( i ),

Section: The Proposed Methodsmentioning

confidence: 99%

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Solid Concentration Estimation by Kalman Filter

Tan

Yue

2020

Sensors

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One of the major tasks in process industry is solid concentration (SC) estimation in solid–liquid two-phase flow in any pipeline. The γ-ray sensor provides the most used and direct measurement to SC, but it may be inaccurate due to very local measurements and inaccurate density baseline. Alternatively, under various conditions there are a tremendous amount of indirect measurements from other sensors that can be used to adjust the accuracy of SC estimation. Consequently, there is complementarity between them, and integrating direct and indirect measurements is helpful to improve the accuracy of SC estimation. In this paper, after recovering the interrelation of these measurements, we proposed a new SC estimation method according to Kalman filter fusion. Focusing on dredging engineering fields, SCs of representative flow pattern were tested. The results show that our proposed methods outperform the fused two types of measurements in real solid–liquid two-phase flow conditions. Additionally, the proposed method has potential to be applied to other fields as well as dredging engineering.

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“…Denoting ( Q ( i ),

by a simple weighting mean as

where d j is computed by the similarity from Q i to m historical records that are the closest to Q i , and thus their similarity is measured by the following weighting distance:

where w k is the weighting value of Q k , k = 1, 2, …, 13.…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…Denoting ( Q ( i ),

Section: The Proposed Methodsmentioning

confidence: 99%

Solid Concentration Estimation by Kalman Filter

Tan

Yue

2020

Sensors

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show abstract

“…Many experimental methods have been used to investigate LSFBs, and the reader is referred to section 2.2 for an overview of such experimental techniques. Among the aforementioned techniques, ERT has been commonly used for liquid-solid (two-phase) systems due to its simplicity and its ability to provide visualizations of particle concentrations without disturbing the flow (Kazemzadeh, 2016;Pakzad et al, 2008;Hosseini et al, 2010;Mishra & Ein-Mozaffari, 2016;Mishra & Ein-Mozaffari, 2017). Hou et al (2001) conducted ERT experiments to study mixing characteristics in a magnetically stabilized LSFB.…”

Section: Application Of Cfd-dem In Lsfb Literaturementioning

confidence: 99%

“…One of the most common experimental measurement techniques employed for liquid-solid (twophase) systems is the Electrical Resistance Tomography (ERT). Its popularity is due to its nonintrusive nature, and its ability to provide visualizations of particle concentrations (Kazemzadeh, 2016;Pakzad et al, 2008;Hosseini et al, 2010;Mishra & Ein-Mozaffari, 2016;Mishra & Ein-Mozaffari, 2017). Furthermore, to analyze processes experimentally, statistical design of experiments is often employed.…”

Section: Introduction Objectivesmentioning

confidence: 99%

Hydrodynamic analysis of a liquid-solid fluidized bed via CFD-DEM simulations, stability analysis, and tomography

Zbib¹

2023

Preprint

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A coupled computational fluid dynamics (CFD) and discrete element method (DEM) model was developed to analyze the fluid-particle and particle-particle interactions in a 3D liquid-solid fluidized bed (LSFB). The CFD-DEM model was validated using the Electrical Resistance Tomography (ERT) experimental method. ERT was employed to measure the bed-averaged particle volume fraction (BPVF) of 0.002 m glass beads fluidized with water for various particle numbers and flow rates. It was found that simulations employing the combination of the Gidaspow drag model with pressure gradient and virtual mass forces provided the least percentage error between experiments and simulations. It was also found that contact parameters must be calibrated to account for the particles being wet. The difference between simulations and experiments was 4.74%. The CFD-DEM model was also employed alongside stability analysis to investigate the hydrodynamic behavior within the LSFB and the intermediate flow regime for all cases studied.

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“…By comparing their definition with those proposed by Williams et al [45] and Hosseini et al [20], they also confirmed that the radial distribution was more significant for fine particles. Mishra and Ein-Mozaffari [48] also compared various mixing index definitions. Specifically, those proposed by Williams et al [45], Hosseini et al [20], and Carletti et al [47].…”

Section: Ert Applications In Solid-liquid Mixingmentioning

confidence: 99%

A Novel Approach For Analyzing Mixing Quality In Solid-Liquid Stirred Tanks Via Coupled Computational Fluid Dynamics - Discrete Element Method And Electrical Resistance Tomography

Tran¹

2021

Preprint

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The mixing quality of a solid-liquid stirred tank operating in the turbulent regime was investigated, numerically and to an extent experimentally. Simulations were performed by coupling Computational Fluid Dynamics (CFD) and the Discrete Element Method (DEM). The results were evaluated against experimental data obtained using Electrical Resistance Tomography (ERT). This facilitated a novel and more rigorous assessment of CFD-DEM coupling – i.e. based on the spatial distribution of particle concentrations. Furthermore, a new mixing index definition was developed to quantify suspension quality to work in tandem with existing dispersion mixing indexes. This provides a more complete interpretation of mixing quality. In this work, it was found that the model underestimated suspension and dispersion due to model limitations associated with mesh size and fluid-particle interaction models. Furthermore, the predicted mixing quality was sensitive to changes in the drag model, including other fluid-particle interaction forces in simulations, and variations in certain particle properties

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Using tomograms to assess the local solid concentrations in a slurry reactor equipped with a Maxblend impeller

Cited by 46 publications

References 54 publications

Solid Concentration Estimation by Kalman Filter

Solid Concentration Estimation by Kalman Filter

Hydrodynamic analysis of a liquid-solid fluidized bed via CFD-DEM simulations, stability analysis, and tomography

A Novel Approach For Analyzing Mixing Quality In Solid-Liquid Stirred Tanks Via Coupled Computational Fluid Dynamics - Discrete Element Method And Electrical Resistance Tomography

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