Liquid distribution and holdup in the random packed column

Velo, Alexandre França; Carvalho, D.V.S.; Hamada, M.M.

doi:10.1016/j.flowmeasinst.2017.11.002

Cited by 4 publications

(5 citation statements)

References 18 publications

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“…Clear and blurred images were convolued to carry out the deblur process. By doing this, a system of ill-posed linear equations was evolved, as represented in equation (1). Finally, equation (2) represents the matrix of equation (1).…”

Section: Methodsmentioning

confidence: 99%

“…Industrial tomography offers a prospect to measure and visualize the physically constrained industry operations [1]. Industrial tomography is divided into two categories: (i) hard field and (ii) soft field.…”

Section: Introductionmentioning

confidence: 99%

“…Problems like these are cropped up in astronomy, imaging for the medical field, and geophysics. In general, discretization of an ill-posed continuous model produces equation (1). For example, discretization means that matrix U could be illconditioned [12], or its data could be distorted, which could lead to inaccuracies in the approximate solution.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Iterative Algorithms for Deblurring of Images in Case of Electrical Capacitance Tomography

Jaffri

Almogren

Ahmad

et al. 2021

Mathematical Problems in Engineering

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Electrical capacitance tomography (ECT) has been used to measure flow by applying gas-solid flow in coal gasification, pharmaceutical, and other industries. ECT is also used for creating images of physically confined objects. The data collected by the acquisition system to produce images undergo blurring because of ambient conditions and the electronic circuitry used. This research includes the principle of ECT techniques for deblurring images that were created during measurement. The data recorded by the said acquisition system ascends a large number of linear equations. This system of equations is sparse and ill-conditioned and hence is ill-posed in nature. A variety of reconstruction algorithms with many pros and cons are available to deal with ill-posed problems. Large-scale systems of linear equations resulting during image deblurring problems are solved using iterative regularization algorithms. The conjugate gradient algorithm for least-squares problems (CGLS), least-squares QR factorization (LSQR), and the modified residual norm steepest descent (MRNSD) algorithm are the famous variations of iterative algorithms. These algorithms exhibit a semiconvergence behavior; that is, the computed solution quality first improves and then reduces as the error norm decreases and later increases with each iteration. In this work, soft thresholding has been used for image deblurring problems to tackle the semiconvergence issues. Numerical test problems were executed to indicate the efficacy of the suggested algorithms with criteria for optimal stopping iterations. Results show marginal improvement compared to the traditional iterative algorithms (CGLS, LSQR, and MRNSD) for resolving semiconvergence behavior and image restoration.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Iterative Algorithms for Deblurring of Images in Case of Electrical Capacitance Tomography

Jaffri

Almogren

Ahmad

et al. 2021

Mathematical Problems in Engineering

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“…This system had been previously described by Mesquita et al [12,13]. [14] A multiphase phantom was used to evaluate the performance of the multisource third generation tomography device [12]. The phantom consists of a polymethylmethacrylate (PMMA ((ρ ≈ 1.19 g/cm 3 )) solid cylinder containing three holes: one filled with steel (ρ ≈ 7.874 g/cm3), another with aluminum (ρ ≈ 2.698 g/cm3) and a third one empty (filled with air) and surrounded with glass, as illustrated in Fig.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Iterative Algorithms for Tomography Image Reconstruction

et al. 2019

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The greatest impact of the tomography technology currently occurs in medicine. The success is due to the fact that human body presents standardized dimensions with well-established composition. These conditions are not found in industrial objects. In industry, there is a great deal of interest in using the tomography in order to know the inner part of (i) manufactured industrial objects or (ii) the machines and their means of production. In these cases, the purpose of the tomography is: (a) to control the quality of the final product and (b) to optimize the production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. This scan system is a non-destructive, efficient and fast method for providing sectional images of industrial objects and it is able to show the dynamic processes and the dispersion of the materials structures within these objects. In this context, it is important that the reconstructed image may present a great spatial resolution with a satisfactory temporal resolution. Thus, the algorithm to reconstruct the images has to meet these requirements. This work consists in the analysis of three different iterative algorithm methods, namely the Maximum Likelihood Estimation Method (MLEM), the Maximum Likelihood Transmitted Method (MLTR) and the Simultaneous Iterative Reconstruction Method (SIRT. The analyses involved the measurement of the contrast to noise ratio (CNR), the root mean square error (RMSE) and the Modulation Transfer Function (MTF),in order to know which algorithm fits the conditions to optimize the system better. The algorithms and the image quality analyses were performed by Matlab® 2013b.

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“…For instance, Fagan et al (2014) evaluated the potential connections between liquid retention and dipper parameters of a bioleaching system using magnetic resonance imaging (MRI); based on MRI, the solute transfer and the liquid spreading with irrigation time were quantified [25]. Besides, the third-generation gamma transmission tomography system [26] and the UV fluorescence [27] were also utilized to reveal liquid spreading in an inter-particle scale [28]. However, even though these mentioned findings broke the study-scale bottleneck, these novel characterized methods are partially limited by their shortcomings such as high cost, transience, etc.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Effect of Stepwise Irrigation on Liquid Holdup and Hysteresis Behavior of Unsaturated Ore Heap

2021

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Liquid is a crucial medium to contain soluble oxygen, valuable metal ions, and bacteria in unsaturated heap leaching. Liquid retention behavior is the first critical issue to be considered to efficiently extract low-grade minerals or wastes. In this study, the residual liquid holdup of an unsaturated packed bed was quantitatively discussed by liquid holdup (θ), residual liquid holdup (θresidual), relative liquid holdup (θ’), and relative porosity (n*) using the designed measuring device. The detailed liquid holdup and the hysteresis behavior under stepwise irrigation are indicated and discussed herein. The results show that relative porosity of the packed bed was negatively related to particle size, and intra-particle porosity was more developed in the −4.0 + 2.0 mm packed bed. The higher liquid retention of the unsaturated packed bed could be obtained by using stepwise irrigation (incrementally improved from 0.001 to 0.1 mm/s) instead of uniform irrigation (0.1 mm/s). It could be explained in that some of the immobile liquid could not flow out of the unsaturated packed bed, and this historical irrigation could have accelerated formation of flow paths. The θ was sensitive to superficial flow rate (or irrigation rate) in that it obviously increased if a higher superficial flow rate (u) was introduced, however, the θresidual was commonly affected by n* and θ’. Moreover, the liquid hysteresis easily performed under stepwise irrigation condition, where θ and θresidual were larger at u of the decreasing flow rate stage (DFRS) instead of u of the increasing flow rate stage (IFRS). These findings effectively quantify the liquid retention and the hysteresis behavior of ore heap, and the stepwise irrigation provides potential possibility to adjust liquid retention conditions.

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Liquid distribution and holdup in the random packed column

Cited by 4 publications

References 18 publications

Iterative Algorithms for Deblurring of Images in Case of Electrical Capacitance Tomography

Iterative Algorithms for Deblurring of Images in Case of Electrical Capacitance Tomography

Evaluation of Iterative Algorithms for Tomography Image Reconstruction

Understanding the Effect of Stepwise Irrigation on Liquid Holdup and Hysteresis Behavior of Unsaturated Ore Heap

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