Flotation of coarse particles by hydrodynamic cavitation generated in the presence of conventional reagents

Modeling of energy consumption factors for an industrial cement vertical roller mill by SHAP-XGBoost: a "conscious lab" approach

Cement production is one of the most energy-intensive manufacturing industries, and the milling circuit of cement plants consumes around 4% of a year's global electrical energy production. It is well understood that modeling and digitalizing industrial-scale processes would help control production circuits better, improve efficiency, enhance personal training systems, and decrease plants' energy consumption. This tactical approach could be integrated using conscious lab (CL) as an innovative concept in the internet age. Surprisingly, no CL has been reported for the milling circuit of a cement plant. A robust CL interconnect datasets originated from monitoring operational variables in the plants and translating them to human basis information using explainable artificial intelligence (EAI) models. By initiating a CL for an industrial cement vertical roller mill (VRM), this study conducted a novel strategy to explore relationships between VRM monitored operational variables and their representative energy consumption factors (output temperature and motor power). Using SHapley Additive exPlanations (SHAP) as one of the most recent EAI models accurately helped fill the lack of information about correlations within VRM variables. SHAP analyses highlighted that working pressure and input gas rate with positive relationships are the key factors influencing energy consumption. eXtreme Gradient Boosting (XGBoost) as a powerful predictive tool could accurately model energy representative factors by R-square ever 0.80 in the testing phase. Comparison assessments indicated that SHAP-XGBoost could provide higher accuracy for VRM-CL structure than conventional modeling tools (Pearson correlation, Random Forest, and Support vector regression.

Recent Developments in Generation, Detection and Application of Nanobubbles in Flotation

This paper reviews recent developments in the fundamental understating of ultrafine (nano) bubbles (NBs) and presents technological advances and reagent types used for their generation in flotation. The generation of NBs using various approaches including ultrasonication, solvent exchange, temperature change, hydrodynamic cavitation, and electrolysis was assessed. Most importantly, restrictions and opportunities with respect to the detection of NBs were comprehensively reviewed, focusing on various characterization techniques such as the laser particle size analyzer (LPSA), nanoparticle tracking (NTA), dynamic light scattering (DLS), zeta-phase light scattering (ZPALS), and zeta sizer. As a key feature, types and possible mechanisms of surfactants applied to stabilize NBs were also explored. Furthermore, flotation-assisted nano-bubbles was reported as an efficient method for recovering minerals, with a special focus on flotation kinetics. It was found that most researchers reported the existence and formation of NBs by different techniques, but there is not enough information on an accurate measurement of their size distribution and their commonly used reagents. It was also recognized that a suitable method for generating NBs, at a high rate and with a low cost, remains a technical challenge in flotation. The application of hydrodynamic cavitation based on a venturi tube and using the LPSA and NTA in laboratory scales were identified as the most predominant approaches for the generation and detection of NBs, respectively. In this regard, neither pilot- nor industrial-scale case studies were found in the literature; they were only highlighted as future works. Although the NB-stabilizing effects of electrolytes have been well-explored, the mechanisms related to surfactants remain the issue of further investigation. The effectiveness of the NB-assisted flotation processes has been mostly addressed for single minerals, and only a few works have been reported for bulk materials. Finally, we believe that the current review paves the way for an appropriate selection of generating and detecting ultrafine bubbles and shines the light on a profound understanding of its effectiveness.

Global trends and characteristics of nano- and micro-bubbles research in environmental engineering over the past two decades: A scientometric analysis

The present study has two primary goals, the first goal is to investigate a bibliometric analysis and assess the trends to evaluate the global scientific production of microbubbles and nanobubbles from 2000 to 2020. The aim is to elucidate the cornucopia of benefits the two technologies (micro and nanobubbles) can offer in environmental sciences and environmental amelioration such as wastewater treatment, seed germination, separation processes, etc. The second goal is to explicate the reason behind every chart and trend through environmental engineering perspectives, which can confer value to each analysis. The data was acquired from the Web of Science and was delineated by VOS viewer software and GraphPad Prism. Considering 1034 publications in the area of micro-and nanobubbles, this study was conducted on four major aspects, including publication growth trend, countries contribution assessment, categories, journals and productivity, and keywords co-occurrence network analysis. This article revealed a notable growth in microbubbles and nanobubbles-related publications and a general growth trend in published articles in a 20-year period. China had the most significant collaboration with other countries, followed by the USA and Japan. The most dominant categories for microbubbles were environmental sciences and environmental engineering comprising 22.5% of the total publications, while multidisciplinary subjects such as nanotechnology and nanosciences (8%) were among the dominant categories for nanobubbles. Keyword's analysis results showed that microbubbles had reached the apex since their discovery. Consequently, they are being used mostly in water/wastewater treatment or environmental improvement. On the other hand, nanobubbles are still in their infancy, and their pervasive use is yet to be fully materialized. Most of the publications are still striving to understand the nature of nanobubbles and their stability; however, a critical analysis showed that during the past two years, the trend of using nanobubbles as a cost-effective and environmentally friendly approach has already begun.

Ventilation Prediction for an Industrial Cement Raw Ball Mill by BNN-A "Conscious Lab" Approach

In cement mills, ventilation is a critical key for maintaining temperature and material transportation. However, relationships between operational variables and ventilation factors for an industrial cement ball mill were not addressed until today. This investigation is going to fill this gap based on a newly developed concept named “conscious laboratory (CL)”. For constructing the CL, a boosted neural network (BNN), as a recently developed comprehensive artificial intelligence model, was applied through over 35 different variables, with more than 2000 records monitored for an industrial cement ball mill. BNN could assess multivariable nonlinear relationships among this vast dataset, and indicated mill outlet pressure and the ampere of the separator fan had the highest rank for the ventilation prediction. BNN could accurately model ventilation factors based on the operational variables with a root mean square error (RMSE) of 0.6. BNN showed a lower error than other traditional machine learning models (RMSE: random forest 0.71, support vector regression: 0.76). Since improving the milling efficiency has an essential role in machine development and energy utilization, these results can open a new window to the optimal designing of comminution units for the material technologies.

Nanobubble-Assisted Flotation of Apatite Tailings: Insights on Beneficiation Options

Processing of materials that originated from tailings of industrial plants (with a wide range of particle size distribution, "PSD") without grinding has several advantages since mines are faced with a lot of pressure to minimize their environmental impacts. This article indicates that the introduction of submicron bubbles (known as nanobubbles, "NBs") to conventional flotation could improve the separation efficiency of valuable minerals from their associated gangue phases. It was demonstrated that metallurgical responses (recovery, grade, selectivity, and kinetics) of NB flotation could improve compared to those of conventional tests. Various hydrodynamic cavitation setups for NB generation may lead to different metallurgical responses. In general, the addition of surfactants (frothers and collectors) for NB generation could increase both mass and water recoveries, which would be key factors on selectivity. Selectivity is also markedly dependent on the PSD of feed, and the selectivity of NB flotation is improved significantly by decreasing the feed size. In general, generation of NBs in the presence of a frother leads to higher flotation metallurgical responses than in the presence of a collector.

Process Variable Importance Analysis by Use of Random Forests in a Shapley Regression Framework

Linear regression is often used as a diagnostic tool to understand the relative contributions of operational variables to some key performance indicator or response variable. However, owing to the nature of plant operations, predictor variables tend to be correlated, often highly so, and this can lead to significant complications in assessing the importance of these variables. Shapley regression is seen as the only axiomatic approach to deal with this problem but has almost exclusively been used with linear models to date. In this paper, the approach is extended to random forests, and the results are compared with some of the empirical variable importance measures widely used with these models, i.e., permutation and Gini variable importance measures. Four case studies are considered, of which two are based on simulated data and two on real world data from the mineral process industries. These case studies suggest that the random forest Shapley variable importance measure may be a more reliable indicator of the influence of predictor variables than the other measures that were considered. Moreover, the results obtained with the Gini variable importance measure was as reliable or better than that obtained with the permutation measure of the random forest.

Effects of Conventional Flotation Frothers on the Population of Mesophilic Microorganisms in Different Cultures

Bioleaching is an environment-friendly and low-investment process for the extraction of metals from flotation concentrate. Surfactants such as collectors and frothers are widely used in the flotation process. These chemical reagents may have inhibitory effects on the activity of microorganisms through a bioleaching process; however, there is no report indicating influences of reagents on the activity of microorganisms in the mixed culture which is mostly used in the industry. In this investigation, influences of typical flotation frothers (methyl isobutyl carbinol and pine oil) in different concentrations (0.01, 0.10, and 1.00 g/L) were examined on activates of bacteria in the mesophilic mixed culture (Acidithiobacillus ferrooxidans, Leptospirillum ferrooxidans, and Acidithiobacillus thiooxidans). For comparison purposes, experiments were repeated by pure cultures of Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans in the same conditions. Results indicated that increasing the dosage of frothers has a negative correlation with bacteria activities while the mixed culture showed a lower sensitivity to the toxicity of these frothers in comparison with examined pure cultures. Outcomes showed the toxicity of Pine oil is lower than methyl isobutyl carbinol (MIBC). These results can be used for designing flotation separation procedures and to produce cleaner products for bio extraction of metals.