A new empirical model to calculate bubble size in froth flotation columns

Ostadrahimi, Mahdi; Farrokhpay, Saeed; Gharibi, Khodakaram; Dehghani, Ali

doi:10.1016/j.colsurfa.2020.124672

Cited by 10 publications

(4 citation statements)

References 32 publications

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“…On the other hand, errors were identified in nomenclature and the use of measurement units, maybe due to writing in the publications analyzed, which created confusion and ambiguity. Finally, it is assumed that the model proposed by Yianatos et al (1988); Banisi and Finch (1994); and Ostadrahimi et al, (2020), can be used in a multi-species system, including bubbles in a swarm in a flotation column.…”

Section: Drift Flux Models Comparisonmentioning

confidence: 99%

Enhancing bubble bize prediction in flotation processes: a drift flux model accounting for frother type

Leiva,

Acuña,

Luukkanen

et al. 2024

Physicochem. Probl. Miner. Process.

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This communication presents a methodology, based on a modified drift flux model, to determine bubble size distribution in column flotation. The modified drift flux model incorporates a surfactant-type parameter. This parameter considers the impact of surfactant on bubble hydrodynamics. The methodology aims to improve the accuracy of bubble size distribution prediction, which presents deviation depending on surfactant type (i.e. polyglycolic based or alcoholic base). Many authors have proposed different mathematical improvements to reduce de experimental data deviations in the presence of different surfactants. However, from 1988 to 2022, the determination coefficient, or the quality of the adjustments, from the proposed mathematical models is, at the most, 92% (relative error). The proposed methodology improves the quality of the adjustments to 98.6, adding a single parameter for groups of surfactants. This methodology incorporates a single parameter in the terminal velocity calculation that can compensate for the impact of surfactant type in bubble hydrodynamic (bubble skin friction or drag coefficient, bubble wake, bubble shape, bubble rigidity). This parameter is a function of the gas holdup calculated from gas velocity measured and the bubble size distribution calculated (deviated) from gas holdup and gas velocity measured. The methodology is validated with reported experimental results and proposed modifications from various authors. The confidence interval (2 σ) is reduced from 0.11mm to 0.05mm in the case of (Yianatos, Banisi, Ostadrahimi). In the case of the recently reported experimental results from Maldonado and Gomez, the confidence interval is reduced from 0.31 mm to 0.09 mm. These results improve bubble size estimation based on drift flux in column flotation, contributing to a better understanding of surfactant impact on bubble swarm hydrodynamics.

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Section: Drift Flux Models Comparisonmentioning

confidence: 99%

Enhancing bubble bize prediction in flotation processes: a drift flux model accounting for frother type

Leiva,

Acuña,

Luukkanen

et al. 2024

Physicochem. Probl. Miner. Process.

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“…Monodisperse particles and bubbles were used. The physical simulation parameters are based on representative flotation conditions [19][20][21][22][23] and are given in Table 1. The corresponding non-dimensional numbers are given in Table 2.…”

Section: Configurationmentioning

confidence: 99%

Collision dynamics of particles and bubbles in gravity‐driven flotation: A DNS investigation

Tiedemann,

Fröhlich

2023

Proc Appl Math and Mech

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This paper presents a numerical method to study the collision process of mineral particles and air bubbles in flotation cells. A bubble‐resolved and particle‐modelled direct numerical simulation was performed to study the particle–bubble collision frequency for representative flotation conditions. The location of the particle collisions on the bubble surface and the particle concentration around a bubble are investigated.

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“…O controle da distribuição do tamanho de bolhasé amplamente difundido na prática industrial como também na literatura como uma das características visuais mais importantes a serem consideradas. Esta característica influencia diretamente na capacidade do processo de flotação de coletar os minerais de interesse (Ostadrahimi et al, 2020). O tamanho médio da bolha não depende apenas das características da máquina de flotação, mas também do minério a ser flotado, da vazão de ar e da taxa de dosagem dos reagentes químicos.…”

Section: Motivação E Justificativaunclassified

“…Umas das variáveis mais importantes a serem observadaś e o tamanho médio das bolhas presentes na espuma de flotação. Este parâmetroé importante devido ao efeito na coleta e transporte das partículas minerais, ou seja, interfere diretamente no objetivo do processo de flotação (Ostadrahimi et al, 2020).…”

Section: Introductionunclassified

Estimativa do Tamanho de Bolhas em Espuma de Flotação Utilizando Visão Computacional

Silva

Souza

Pessin

et al. 2020

Anais Do Congresso Brasileiro De Automática 2020

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Dentre as etapas de processamento de minérios, a flotação se destaca como um dos mais importantes, principalmente quando se trata de separação de minerais. O rendimento deste processo está muito ligado as variáveis de processo como a vazão de ar e o controle de abertura das válvulas de descarga. Estas variáveis, muitas vezes, são determinadas através do aspecto visual da espuma deste processo, onde os operadores se baseiam em suas experiências para a tomada de decisão e escolha destes parâmetros. As principais características observadas são: tamanho das bolhas, textura e velocidade de deslocamento. Como esta análise, muitas vezes, fica a cargo do operador do processo ela acaba se tornando subjetiva, variando de operador para operador. Além desta análise subjetiva, o controle deste processo é uma tarefa complexa. Desta forma, a automação deste processo se torna ainda mais importante. Utilizando as técnicas de visão computacional é possível obter as principais características da espuma importantes ao processo. A proposta deste trabalho é utilizar técnicas de visão computacional para estimar o tamanho médio e o número de bolhas presentes na espuma de flotação como ferramenta de apoio na tomada de decisão dos operadores deste tipo de processo.

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A new empirical model to calculate bubble size in froth flotation columns

Cited by 10 publications

References 32 publications

Enhancing bubble bize prediction in flotation processes: a drift flux model accounting for frother type

Enhancing bubble bize prediction in flotation processes: a drift flux model accounting for frother type

Collision dynamics of particles and bubbles in gravity‐driven flotation: A DNS investigation

Estimativa do Tamanho de Bolhas em Espuma de Flotação Utilizando Visão Computacional

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