Modelling the screening process: A probabilistic approach

Subasinghe, G.K.N.S.; Schaap, Ward B.; Kelly, E.G.

doi:10.1016/0032-5910(89)80093-2

Cited by 32 publications

(25 citation statements)

References 3 publications

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“…Many attempts in the past to describe the performance of screening processes kinetically have ended up adopting either probabilistic or empirical approaches . However, a recent study seems to have found another intuitive method that enables dynamic quantification of not only the oversized and undersized particles simultaneously, but also estimates the intermediate amounts between the initial feed and the overflow product at any given time …”

Section: Theoretical Models Developmentmentioning

confidence: 99%

Dynamic population balance and flow models for granular solids in a linear vibrating screen

Rotich

Tuunila

Elkamel³

et al. 2016

AIChE Journal

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Vibrating screens are a widely applied form of particle separations. In spite of this significance, their understanding is still an obstacle. Three approaches were used to characterize the flow of granular material in a linear vibrating screen. The statistical model, mass action, and kinetic model based on conservation of momentum were derived. Experiments were then conducted on a multi-sized prototype screen and glass beads of sizes 0.75, 1, 2, 3 mm. Deck inclinations were varied over 7.5,12.5, and 17.58, and frequencies over 7, 15, and 20 Hz. A total of 72 feed batches and a constant power of 50 W was used. The experimental data was then used to validate the models. The three models provided accurate flow prediction over the screens. Additionally, the kinetic model also provided a basis for optimal design of the screening unit operation, by allowing manipulation of seven design variables to obtain a 95-100% efficient vibrating screen.

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Section: Theoretical Models Developmentmentioning

confidence: 99%

Dynamic population balance and flow models for granular solids in a linear vibrating screen

Rotich

Tuunila

Elkamel³

et al. 2016

AIChE Journal

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“…In this paper, non-spherical particles which match sand's sphericity and a banana vibrating screen with a curved sieving surface were established by using DEM modeling. In order to study the relationship between vibration parameters and screening performance, Brereton and Dymott based on particle penetrating probability theory of Gaudin established the mathematical model of two-layer thickness screening stage [14,15]. Chen established a comprehensive screening model about vibration and structure parameters [16].…”

Section: Introductionmentioning

confidence: 99%

Performance optimization of banana vibrating screens based on PSO-SVR under DEM simulations

Li¹,

Li²,

Ge³

et al. 2019

J. vibroeng.

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This paper carried out the numerical simulation about the movement of non-spherical particles on banana vibrating screen using direct element method (DEM) considering the complexity of particle collision and avoiding obtaining motion information with difficulty. Experimental prototype of banana vibrating screen under variable parameters was manufactured to verify the feasibility of simulations. Because the complex non-linear mathematical model is the basis of optimization. Based on the simulation data this paper applied the least squares support vector machines (LS-SVM) to establish relationships between vibrating parameters of banana screen and screening performance. LS-SVM based on statistical theory can effectively solve the mapping problem of small sample. At same time, in order to improving the quality of modeling, the kernel parameters of SVM were optimized by particle swarm optimization (PSO). Considering multi-extremum, large-scale, and non-differentiable of this computational model, the artificial fish-swarm algorithm (AFSA) with strong robustness and global convergence was applied to vibration parameters optimization. Finally, the optimal vibration parameters were: vibration amplitude 2.4 mm, vibration frequency 21 Hz, vibration direction angle 40 degrees.

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“…Neben den probabilistischen Modellen [9,10] wie dem Modell von Dong [8] existieren für den stationären Siebprozess auch kinetische Ansätze [11 -13]. Die Anzahl der Versuche N, die jedes Partikel für einen Durchtritt hat, wird durch die Amplitude A, die Frequenz f, den Partikeldurchmesser x, die Gravitationskraft g, die Siebdecklänge L*, den Siebneigungswinkel q und die anpassbaren Parameter k, a, b und g beeinflusst.…”

Section: Introductionunclassified

Separation Curves of Screening and Air Classifying Processes at Low Material Loadings

Spötter

Elskamp

Hennig

et al. 2017

Chemie Ingenieur Technik

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Zur Abtrennung unterschiedlich großer Partikeln sind in der Feststoffverfahrenstechnik trockene Klassierprozesse zur Herstellung enger Fraktionen von großer Bedeutung. Um das Trennverhalten von Strömungs-und Siebklassierprozessen genauer vorhersagen zu können, wurden experimentelle Resultate mit DEM-Simulationen verglichen. Bei der Siebklassierung wurde der Einfluss der Partikelform auf den Trennprozess betrachtet, während das Partikelverhalten zwischen den Schaufeln eines Abweiseradsichters mit DEM simuliert wurde. Die Kombination aus DEM und Experiment ermöglicht es, Modellvorhersagen durch Ermittlung prozessspezifischer Parameter zu verbessern und Klassiermodelle abzuleiten, die in dynamischen Feststofffließschemasimulationen verwendet werden.For the separation of particles with different sizes, dry classification processes are of great importance for the production of narrow fractions in the solid processing technology. To be able to more accurately predict the separation behavior of flow and sieve classifying processes, experimental results were compared with DEM simulations. In screening the influence of the particle shape on the separation process was considered while the particle behavior between the paddles of a deflector wheel classifier was simulated with DEM. The combination of DEM simulation and experiment makes it possible to improve model predictions by identifying process-specific parameters and to develop classification models, which are applicable in dynamic flowsheet simulations of solids processes.

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Modelling the screening process: A probabilistic approach

Cited by 32 publications

References 3 publications

Dynamic population balance and flow models for granular solids in a linear vibrating screen

Dynamic population balance and flow models for granular solids in a linear vibrating screen

Performance optimization of banana vibrating screens based on PSO-SVR under DEM simulations

Separation Curves of Screening and Air Classifying Processes at Low Material Loadings

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