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Estimating effective volumes in industrial forced-air flotation cells
Minerals Engineering ( IF 4.8 ) Pub Date : 2024-04-03 , DOI: 10.1016/j.mineng.2024.108678
Luis Vinnett , Juan Yianatos , Francisco Díaz , Ahmad Hassanzadeh

Mean residence time (MRT) in industrial flotation cells is one of the key parameters for kinetic modelling and identification of effective volumes. However, not all plants have access to robust tracer techniques to reliably measure this parameter with reasonable accuracy. For this reason, flotation practitioners estimate the mean residence time from the volumetric pulp flowrate and the effective cell volume. The latter requires assumptions on the air and froth volumes inside the machines, which has led to inaccuracies in MRT estimations. To overcome this challenge, the present communication correlated the measured () and calculated MRTs from the rougher circuits of four copper flotation plants (twenty-eight surveys). The rougher stages of these plants consisted of forced-air mechanical cells of 100, 160 and 200 m. The correlation between the measured and calculated MRTs showed that the following equation can be used as an approach to predict the MRT in industrial forced-air flotation cells: with 0.872 representing the relative effective volume (95 % confidence interval of 0.839–0.905), the total cell volume, and the volumetric feed flowrate of pulp. This interval for the relative effective volume is proposed as a reference range to consolidate current assumptions for cell sizing, or to revisit these assumptions in case of significant deviations regarding the observed interval.

中文翻译:

估算工业强制通风浮选机的有效体积

工业浮选机中的平均停留时间 (MRT) 是动力学建模和有效体积识别的关键参数之一。然而,并非所有工厂都能使用强大的示踪技术来以合理的精度可靠地测量该参数。因此,浮选从业者根据矿浆体积流量和有效细胞体积来估计平均停留时间。后者需要对机器内部的空气和泡沫量进行假设,这导致 MRT 估算不准确。为了克服这一挑战,目前的通讯将四个铜浮选厂的粗糙回路中测量的 () 和计算的 MRT 相关联(二十八次调查)。这些工厂的粗加工阶段由 100、160 和 200 m 的强制通风机械单元组成。测量的 MRT 与计算的 MRT 之间的相关性表明,以下方程可用作预测工业强制通风浮选池中 MRT 的方法:用 0.872 表示相对有效体积(95% 置信区间为 0.839–0.905),总细胞体积和纸浆的体积进料流量。建议将相对有效体积的这个区间作为参考范围,以巩固当前对电池尺寸的假设,或者在观察到的区间存在显着偏差的情况下重新审视这些假设。
更新日期:2024-04-03
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