Feed Flow Rate Research Articles

A Novel Configuration of Hybrid Reverse Osmosis, Humidification–Dehumidification, and Solar Photovoltaic Systems: Modeling and Exergy Analysis

The pressing demand for clean water worldwide has increased attention to developing innovative desalination processes. In this work, the second law of thermodynamics is used to examine and assess two coupled desalination systems: a separation-based reverse osmosis (RO) system and a thermal desalination-based humidification–dehumidification (HDH) system. The HDH unit configuration used here is based on the working principle of the heat pump, where the process is open-air, open-water, and air-heated. The RO system is equipped with a pressure exchanger (PX) and has been examined under various operating circumstances, such as different feed water pressures, salinities, and flow rates. To improve the system’s sustainability, a solar photovoltaic system (PV) was integrated. An exergy model was used to precisely evaluate the system components and the hybrid systems by employing a proper exergy efficiency definition. The evaluation of the second law of thermodynamics for the RO–HDH–PX and RO–HDH–PX–PV systems indicated maximum efficiencies of 23% and 23.25%, respectively. A cost analysis was also performed on the hybrid RO–HDH–PX–PV desalination system using two approaches: the first included a battery storage system, whereas, in the second, the battery was not considered. When a battery storage system is included, the cost per cubic meter varies from USD 3.22 to USD 5.10. In contrast, it varies from USD 3.96 to USD 7.12 without a battery storage system.

The dynamic behaviour of ORC-based power units fed by exhaust gases of internal combustion engines in mobile applications

Exhaust gases Waste Heat Recovery (WHR) in Internal Combustion Engines (ICEs) performed through ORC-based Power Units (ORC-bPU) ensures a reduction of fuel consumption and consequently CO2 emissions. Nevertheless, high fluctuations of hot source push the ORC-bPU to work frequently in severe off-design conditions. Hence, a deep knowledge of the unit dynamic behaviour is fundamental to develop control and operating strategies allowing to achieve a successful recovery. Dynamic response assessment of ORC-bPUs has been treated in literature but making mainly reference to theoretical approaches or to variations of input variables without considering the matching to the engine and the necessary constraints which are present in a real mobile application. Moreover, Moving Boundary (MB) models are generally used as theoretical tools to support the dynamic analysis focusing the attention on Heat Recovery Vapor Generator (HRVG) which rules the plant dynamic response. In MB models, boundary conditions at the HRVG exit are mainly fixed by the expander and by the remaining circuit. To date, the attention was focused on the presence as expander of dynamic machines (turbine), deserving an evident lower attention to volumetric expanders nonetheless their higher suitability for low-medium scale ORC applications (few kWs). To fill these knowledge gaps, a novel approach is pursued in the present paper. The dynamic response of an ORC-bPU was experimentally observed for a step change of torque and revolution speed of an ICE directly connected to the recovery unit. The variation of engine operating conditions produced an unsteady variation of the temperature and flow rate of the exhaust gas feeding the unit. The dynamics of the engine and the connecting pipes is considered as well as all the typical constraints of a real situation. Results show HRVG and exhaust pipe ruling the dynamic behaviour of the unit, leading to long time constant and raising time of gas temperature of 150 s and 300 s respectively. These results show that the unit almost always works in transient conditions being engine torque and speed variations very fast. Nevertheless, thanks to the self-regulation capacity and the robustness of the scroll expander, the unit reacts in a satisfactory way. A further novelty of the present study concerns the integration of the widely used Moving Boundary (MB) approach with Permeability theory which considers the presence of a volumetric expander and all the ither downstream components, finding a match not available in literature between the HRVG and a volumetric expander and pump. The results of the new Permeability-Moving Boundary model (P-MB) was compared with those of a more comprehensive mathematical model. The comparisons show a comparable accuracy and a significantly lower computational time achieved with P-MB. Hence, P-MB could be implemented on board to set up control strategies enhancing the recovery tuned by a model-based approach.

Competitive multi-component bio-syngas separation for hydrogen production: breakthrough dynamics, thermal effects, and adsorbent stability analysis under practical operating conditions

The present work experimentally investigates the ability of zeolite 13X to purify H2 from a multi-component bio-syngas feed [composition (mol%): H2/CH4/CO/CO2 – 51.7/3.4/13.2/31.7] in a bench scale, glass wool insulated column simulating a near-industrial adiabatic environment. The column breakthrough dynamics and thermodynamic interactions are studied as a function of total pressure and feed flow rate. The adsorbent showed excellent separation characteristics with the highest affinity for CO2 followed by CO and CH4, and completely restricts their propagation for pure H2 production. The non-isothermal operation results in forming two distinct temperature fronts and manifests itself by broadening the mass transfer zone, decreasing loadings, and causing an early breakthrough of various adsorbates. The competitive adsorption is confirmed through the presence of roll-ups with a slowly moving CO2 concentration front displacing pre-adsorbed CH4 and CO over the duration of the experiment. Further, dynamic adsorption and desorption (sweep gas: He and CO2) experiments are respectively employed to measure competitive equilibrium loadings of heavy (CO2) and light components (CH4, CO). Additionally, the variation in breakthrough time, adsorbate propagation rate, column peak temperature, breakthrough and effective loading, and competitive selectivities are analyzed and discussed. Finally, a novel methodology to design H2 purification systems is proposed and put to practical use by developing and long duration (∼1500 cycles) testing a pilot scale (feed flow rate: 100 Nm3/h) vacuum pressure swing adsorption system. The cyclic separation unit while generating fuel-cell grade H2, displayed complete operational repeatability, with minimal deviation (<6 %) in adsorbent textural properties and crystalline structure.

Sorption-enhanced glycerol steam reforming over lithium cuprate-based bifunctional material for the production of high-purity hydrogen

We investigated the production of high-purity H2 through sorption-enhanced glycerol steam reforming (SEGSR) using lab-made bifunctional materials consisting of nickel, Al2O3, and Li2CuO2. Different bifunctional materials were prepared with 10 wt % Ni loading but varying wt % of Al2O3 and Li2CuO2, and their catalytic activity was evaluated in a continuous fixed-bed down-flow reactor. HM-50, which had an equal wt % of Al2O3 and Li2CuO2, showed the highest performance. The conversion of glycerol and the purity of H2 were examined with respect to temperature, feed flow rate, and steam-to-carbon molar ratio (S/C). At the optimum reaction conditions (temperature = 700 °C, feed flow rate = 0.5 ml/min, and S/C = 6), glycerol conversion and H2 purity were 100 % and 94 mol %, respectively. The adsorption capacity of HM-50 was found to be 3.9 mmol CO2 per gram. With a breakthrough time of 15 min, the substance was stable for 13 adsorption-desorption cycles. The material was regenerated by substituting the feed with a N2 and steam mixture heated to 700 °C for 30 min. A most likely reaction mechanism suggested that glycerol was catalytically converted to acetaldehyde, which was then quickly decomposed to CO and CH4. We are the first research team to investigate the use of Li2CuO2 in any steam reforming process.

Proportional-Integral Control and ARX-based Model Predictive Control for Extractive Dividing Wall Column

Extractive dividing wall column (EDWC) is a typical process intensification technology and possesses significant energy-saving prospects, while the poor dynamic controllability hinders its industrialization goal. In this work, taking the benzene and cyclohexene azeotrope separation as an example, a proportional-integral (PI) control structure based on four-point temperature control loops is proposed for EDWC by considering temperature difference as the discriminant criterion. Subsequently, to improve the control performance of EDWC, two model predictive control (MPC) structures based on auto-regressive with external input (ARX) model obtained from closed-loop identification and linear time-invariant state-space (LTI-SS) model, respectively, are studied for EDWC. The performance of three control structures is tested by ±20 % feed flow rate and composition disturbances, and further quantitatively evaluated by integral absolute error (IAE). The dynamic responses demonstrate that the ARX-based MPC structure achieves the best control performance in the presence of feed flow rate and composition disturbances, which can be attributed to the capability of the identified ARX model to track the dynamic features of EDWC accurately.

Treatment of Stainless Steel Rinse Waters Using Non-Dispersive Extraction and Strip Dispersion Membrane Technology.

The extraction of Fe(III), Cr(III), and Ni(II) from stainless steel rinse water using non-dispersive extraction and strip dispersion membrane technology was carried out in a microporous hydrophobic hollow-fibre module contactor. The fibres were of polypropylene, whereas the organic extractant DP8R (bis(2-ethylhexyl) phosphoric acid) diluted in ExxsolD100 was used as the carrier phase. The rinse water containing the three elements was passed through the tube side, and the pseudo-emulsion formed by the organic phase of DP8R in Exxol D100 and an acidic strip solution were passed through the shell side in a counter-current operation; thus, a unique hollow fibre module was used for extraction and stripping. In non-dispersive extraction and strip dispersion technology, the stripping solution was dispersed into the organic membrane solution in a vessel with an adequate mixing device (impeller) designed to form strip dispersion. This pseudo-emulsion was circulated from the vessel to the membrane module to provide a constant supply of the organic phase to the membrane pores. Different hydrodynamic and chemical variables, such as variation in feed and pseudo-emulsion flow rates, strip phase composition, feed phase pH, and extractant concentration in the organic phase, were investigated. Mass transfer coefficients were estimated from the experimental data. It was possible to separate and concentrate the metals present in the rinse water using the non-dispersive extraction and strip dispersion technique.

Flow and mass transfer for the adsorption separation of para-xylene in a packed bed by particle-resolved CFD simulations

As the leading polyester product chain, para-xylene (PX) is the most important xylene isomer. In industry, high purity paraxylene is mainly produced by adsorption separation technology. In this study, the PX adsorption process has been investigated by a 3D particle-resolved CFD model. For spherical particle packed beds, the channeling effect, flow stagnation and backflow regions are the main factors leading to non-ideal flow. According to the residence time distribution (RTD) and adsorbent efficiency, the more uniform the flow in the packed bed, the higher the adsorption separation efficiency. Therefore, low feed flow rate and large bed-to-particle diameter ratio (N) are beneficial to the adsorption process. In addition, the effect of particle geometries (trilobe, five-lobe, Raschig ring, four-spoke ring, and six-hole cylindrical) on the flow and adsorption characteristics of the packed bed has been investigated in terms of pressure drop, adsorbed amount and adsorbent efficiency. Internal void particles perpendicular to the flow direction are unfavorable for the adsorption process. The four-spoke ring adsorbent with more surface areas has the largest bed adsorbed amount and exhibits the best adsorption performance. The trilobe adsorbent has the largest adsorbed amount per unit bed pressure drop and is the optimally shaped adsorbent for industrial PX adsorption separation.

Influence of internal design on the performance of pilot vacuum-assisted air-gap membrane distillation modules for brine concentration with solar energy

Membrane distillation (MD) in batch operation is proposed for brine concentration with solar energy in zero liquid discharge (ZLD) desalination processes, but there are some research gaps yet. Energy efficiency is key for implementing the technology with solar energy and there is not enough experience and experimental results of operation of MD pilot modules at high salinity feeds. This research focuses on the experimental evaluation and comparison of two multi-envelope spiral wound commercial membrane distillation modules operating in vacuum-assisted air gap MD at the solar MD pilot facilities of Plataforma Solar de Almería in Spain. These modules have similar membrane area (24 and 25.9 m2) and residence time (large, to maximize thermal efficiency), but different internal design: 6 envelopes 5 m long and 12 envelopes 2.7 m long, respectively. This difference affects mostly the feed circulation velocity for equal feed flow rate. Performance parameters such as permeate production and specific thermal energy consumption (STEC) are compared and experimental models performed and validated for different feed salinities. Permeate quality and specific electrical energy (SEEC) consumption are also evaluated. The results show that the best module for batch operation is the one with a larger number of channels but of shorter length.

Permeation Flux Prediction of Vacuum Membrane Distillation Using Hybrid Machine Learning Techniques.

Vacuum membrane distillation (VMD) has attracted increasing interest for various applications besides seawater desalination. Experimental testing of membrane technologies such as VMD on a pilot or large scale can be laborious and costly. Machine learning techniques can be a valuable tool for predicting membrane performance on such scales. In this work, a novel hybrid model was developed based on incorporating a spotted hyena optimizer (SHO) with support vector machine (SVR) to predict the flux pressure in VMD. The SVR-SHO hybrid model was validated with experimental data and benchmarked against other machine learning tools such as artificial neural networks (ANNs), classical SVR, and multiple linear regression (MLR). The results show that the SVR-SHO predicted flux pressure with high accuracy with a correlation coefficient (R) of 0.94. However, other models showed a lower prediction accuracy than SVR-SHO with R-values ranging from 0.801 to 0.902. Global sensitivity analysis was applied to interpret the obtained result, revealing that feed temperature was the most influential operating parameter on flux, with a relative importance score of 52.71 compared to 17.69, 17.16, and 14.44 for feed flowrate, vacuum pressure intensity, and feed concentration, respectively.

Simulation of spiral-wound pressure retarded osmosis for harvesting osmotic power: Module-level modeling and implications of feed pre-treatment

A process-scale model for pressure retarded osmosis (PRO) using a 1-dimensional representation of the spiral-wound membrane is presented. Comparing a length-averaged modeling approach with a true counter-current approach reveals that the former holds only for relatively short membrane lengths while it over-predicts the net power output for longer membranes. For a membrane line with eight spiral-wound elements in series, the length-average model over-predicted the PRO performance by 20 %. The model was further used to assess the impact of feed pre-treatment on process performance and optimal process design. Feed pre-treatment was found to be a dominant factor affecting the optimal inlet feed flow rate and the power output. Our model suggests that for a moderate to high feed pre-treatment requirement the inlet feed flow rate is close to minimum feed flow rate of the membrane module. In the absence of feed pre-treatment a power density of 143 and 284 W m−2 for CTA and TFC membranes, respectively, was found. When feed pre-treatment with 100 Wh m−3 was employed these numbers dropped to 48 and 94 W m−2.

Experimental investigation on the hybrid system of mechanical vapor recompression and hollow fiber vacuum membrane distillation applied for wastewater treatment

In order to achieve zero discharge and resource utilization of industrial high salt wastewater, a hybrid system of mechanical vapor recompression (MVR) and hollow fiber vacuum membrane distillation (HFVMD) was constructed, and several experiments of air tightness, single working condition and multiple working conditions were carried out with ammonium chloride solution as feed, then thermal economic performance were evaluated via a single factor analysis method. The obtained results showed that the system had excellent airtightness to ensure normal evaporation experiment, and high separation efficiency of 99.9% and lower evaporation energy consumption to achieve high efficient separation by combining the advantages of the hydrophobic membrane evaporation and latent heat recovery in view of MVR and HFVMD technologies. Furthermore, increasing feed temperature and feed flow rate increased evaporation rate and decreased evaporation energy consumption, while increasing feed concentration decreased evaporation rate and increased evaporation energy consumption. Finally, the single factor analysis indicated that total investment cost, annual operation cost and annual evaporation capacity were the main factors while environmental cost and equipment service life were the secondary factors which affected the specific evaporation cost. The above research provides theoretical and experimental bases for the development of the proposed system in the future.

Optimisation of direct contact membrane distillation to enhance brackish water desalination and study polyvinylidene fluoride (PVDF) membrane performance

This study explores the optimisation of operational parameters in direct contact membrane distillation (DCMD) for brackish water desalination using polyvinylidene fluoride (PVDF) membranes. Central composite design (CCD) identified optimal conditions, and quadratic regression models demonstrated a strong correlation (R2 values: 0.98 for salt rejection, 0.99 for permeate flux) between operational factors and membrane performance. Artificial neural network (ANN) models surpassed Response Surface Methodology (RSM) in predictability for permeate flux and salt rejection. Multi-objective Genetic Algorithm (MOGA) optimisation yielded a pareto optimal solution, revealing two sets of conditions: one maximising permeate flux (21.40 L/m2 h) with 44.75 LPH feed flowrate and the other achieving 100 % salt rejection with 52.48 LPH feed flowrate. Optimising DCMD for flexible water desalination, this study positions it as a promising, sustainable technique, providing practical large-scale implementation guidance. Addressing limitations is key to widespread adoption as a cost-effective freshwater production method.

Membrane clarification of pomegranate and carrot juices using scraped surface membrane unit, a comparative study

The membrane processes are used for clarification of fruit juices, but fouling is a limiting phenomenon. The blade rotation in scraped surface membrane unit can increase flow turbulence and thus reduce fouling phenomenon. This unit was used to clarify the carrot juice (which has a cloudy texture) and pomegranate juice (which has a non-cloudy texture) to compare the effect of juice texture on the efficiency of process. The process was performed at three transmembrane pressures (1, 1.5 and 2 bar), three feed flow rates (5, 10 and 15 ml/s) and three blade rotation speeds (0, 147.5 and 222.5 RPM) and changes in permeate flux and volume concentration factor (VCF) and fouling mechanism were studied. The results showed that the rotation of the blade, especially at 222.5 RPM, increased the permeate flux and VCF during clarification of both juices. Also, reduction of feed flow rate increases the effectiveness of blade rotation during membrane clarification of juices. Comparison between two juices showed that the increase in permeate flux and VCF after blade rotation for pomegranate juice was higher than the increase value for carrot juice, especially in the early stages of the process. But, decreasing the transmembrane pressure makes the effect of blade rotation on carrot juice that has a cloudy texture more than pomegranate juice that has a non-cloudy texture, especially when the blade rotation speed is low. The cake formation is the main fouling mechanism in the most tests and SEM images confirm that blade rotation has a significant effect on reduction of cake layer thickness.

Process development for pilot-scale spray drying of ultrasmall iron (oxyhydr)oxide nanoparticles

In manufacturing iron (oxyhydr)oxide nanoparticles, drying is often necessary to increase stability or to enable granulation and tableting. Lyophilization is a simple drying method, although it is characterized by high energy consumption and high cost. This study aims to demonstrate that spray drying is a suitable alternative for preparing iron (oxyhydr)oxide nanoparticles. A Design of Experiment approach was used varying the inlet air temperature, feed flow rate, and feed concentration. Especially a low feed flow rate was beneficial for low residual moisture (< 7%) and high yield (> 80%). The process was subsequently transferred to pilot scale at a feed flow rate of 2.3 kg/h. The nanomaterial had comparable properties and efficacy to the freeze-dried product. However, about 15% lower yield and 35% lower energy consumption were found for spray drying the nanoparticles. This study shows that spray drying is a suitable alternative to freeze drying for iron (oxyhydr)oxide nanoparticles.

Numerical study of flame inclination instability in a packed bed with extra lean methane/air intake by an adaptive multi-scale model

The common numerical method to simulate the evolution of flame instability during filtration combustion mainly includes volume average method and pore scale simulation. However, they are not satisfying in computation accuracy and cost respectively. In this paper, a self-developed adaptive multi-scale model is built to study the inclination instability of the flame front in a packed bed with honeycomb ceramics. The perturbations on the distribution of the intake parameters and physical properties of fillings in the packed bed lead to the flame inclination. The influences of the amplitude and range of the perturbations on the flame inclination development are investigated. The development mechanism of flame inclination is analyzed by method of flow competition (MFC) theory. The results show that the increase of the flame inclination angle will enhance the transversal heat transfer. Subsequently, the radiation and conduction fluxes restrain the increase of the flame inclination. Under the same level of perturbation amplitude, the result shows that the influence sequences of the four factors for the flame inclination are as follows: fillings porosity, feed flow rate, fillings heat capacity, and feed concentration. In addition, larger amplitude of perturbation leads to higher maximum flame inclination angle. However, the perturbation range has little influence on the development of flame inclination angle. Finally, the flame inclination is restrained successfully through adding new perturbation of intake parameters or elimination of initial perturbation. The above.studies are quite meaningful to the stable operation and wide application of porous media combustion technology in the utilization of low calorific value gas energy.

Industrial Textile Wastewater Treatment by Crossflow NF Membrane Filtration

Ineffective dyeing procedures frequently lead to the release of approximately 10–50% of the dye applied, which does not adhere to the fabric and is consequently discharged into the environment along with the effluent. This situation is undesirable both for potential recycling within the textile manufacturing process and because of its adverse environmental pollution effects. This study thoroughly examines nanofiltration (NF) membrane characteristics and their performance in textile wastewater treatment. Pristine NF membrane surfaces were revealing a web-like structure with well-defined pores predominantly in the membrane active region. This assessment confirms the membrane initial cleanliness, free from any external contaminants, which is vital for effective membrane-based filtration. Additionally, the study investigates how different feed flow rates affect water flux during NF membrane filtration. The results demonstrate a clear relationship, where the increasing flow rates boost water flux. This can be attributed to heightened cross-flow velocity and shear force on the membrane surface due to the increased water flux, minimizing external concentration polarization and reducing membrane fouling. The impact of feed flow rate on membrane separation efficiency is also examined, showing consistent efficiency at feed flow rates between 2 LPM and 5 LPM (approximately 80.8% to 82.22%). However, efficiency drops as the feed flow rate increases from 5 LPM to 6 LPM, likely due to increased pressure drop across the membrane, affecting separation efficiency.

Plantwide Simulation and Operation of a Methanol to Propylene (MTP) Process

BackgroundMethanol to propylene (MTP) process is considered as one of the most important methods for propylene production. The MTP process consists of four sections: conversion of reactants to products, cooling, compression and products separation. In this process, is utilized from multi-stage fixed bed reactors. Due to high exothermicity of the MTP reactors, and existence of recycle loops, a plant-wide control structure is required to be designed for stable, safe and maximum production of propylene. MethodModeling and simulation of the heterogeneous fixed bed MTP reactors with interphase and intra-particle mass and heat transfer were carried out in Aspen Custom Modeler. Steady-state simulations of the MTP process were carried out in Aspen Plus. A simple control strategy was proposed to achieve maximum propylene production with temperature control of the MTP multi-stage reactors by splitting the cold oxygenate feed and the recycled hydrocarbons among the reactor beds. The performance of the proposed control strategy was tested against several disturbances including change in flowrate and composition of feed, using dynamic simulations by Aspen Plus Dynamics. Significant findingDynamic simulation results revealed that simultaneous control of the split range for the 5th and 6th reactor beds and cascade temperature of other reactor beds, could be a suitable temperature control strategy for the reaction section of the MTP process.

Continuous Treatment of Refractory Wastewater from Research and Teaching Laboratories via Supercritical Water Oxidation–Experimental Results and Modeling

Teaching and research laboratories generate wastes of various compositions and volumes, ranging from diluted aqueous solutions to concentrated ones, which, due to milder self-regulation waste-management policies, are carelessly discarded, with little attention given to the consequences for the environment and human health. In this sense, the current study proposes the application of the supercritical water oxidation (SCWO) process for the treatment of complex refractory wastewater generated in research and teaching laboratories of universities. The SCWO, which uses water in conditions above its critical point (T &gt; 647.1 K, p &gt; 22.1 MPa), is regarded as an environmentally neutral process, uniquely adequate for the degradation of highly toxic and bio-refractory organic compounds. Initially, the wastewater samples were characterized via headspace gas chromatography coupled with mass spectrometry. Then, using a continuous tubular reactor, the selected operational parameters were optimized by a Taguchi L9 experimental design, aiming to maximize the total organic carbon reduction. Under optimized conditions—that is, temperature of 823.15 K, feed flow rate of 10 mL min−1, oxidizing ratio of 1.5 (50% excess over the oxygen stoichiometric ratio), and sample concentration of 30%—TOC, COD, and BOD reductions of 99.9%. 91.5% and 99.2% were achieved, respectively. During the treatment process, only CO2, methane, and hydrogen were identified in the gaseous phase. Furthermore, the developed methodology was applied for the treatment of wastewater samples generated in another research laboratory and a TOC reduction of 99.5% was achieved, reinforcing the process’s robustness. A thermodynamic analysis of SCWO treatment of laboratory wastewater under isothermal conditions was performed, using the Gibbs energy minimization methodology with the aid of the GAMS® 23.9.5. (General Algebraic Modeling System) software and the CONOPT 4 solver. Therefore, the results showed that SCWO could be efficiently applied for the treatment of wastewater generated by different teaching and research laboratories without the production of harmful gases and the addition of hazardous chemicals.

Stress-based approach for predicting and improving large-scale HIG mill performance

As a fine and ultrafine grinding technology, the High Intensity Grinding (HIG) Mill is relatively new and there is opportunity to improve its performance by adjusting operational conditions. A laboratory HIG5 mill is commonly used for HIG mill sizing and scale up, however the clear correlation between the operational variables of laboratory mill to their production level is somewhat lacking. This paper presents a stress-based approach for predicting and improving large-scale HIG mill performance. A total of 27 experimental tests were performed with a HIG5 mill over a range of operational variable set points, including media density, media filling level, feed solid content, mill speed and flow rate. The influence of the variables on product size, mill operating power and specific grinding energy was characterized via multivariable linear regression modelling. Based on theoretical stress analysis and empirical calibration with available survey data, the model derived from laboratory testing was calibrated to predict the operation of the commercial HIG1600 mill. An approach was proposed for determining the effect of operational variables using a HIG5 that can be directly applied to reduce energy consumption at a given mill feed rate and product size target for the production scale mill. Results demonstrated that the stress-based approach integrated with laboratory testing can be used for predicting and improving large-scale HIG mill performance.

Application of radiotracers as tools to determine feed flowrate imbalances and particle size segregation in industrial flotation circuits

This publication presents the application of radiotracers in the characterization of industrial flotation circuits. Two examples are showcased: the detection of feed flow rate imbalances and the characterization of particle size segregation in automatic mineral-cutting machines. The feed pulp distribution was determined from the mean residence times. Particle size segregation was measured by sampling the cutting machines (≅ 25 grams samples) using coarse, intermediate, and fine-sized radiotracer particles. Radiotracers were injected into the feed streams and measured at various points of the circuit using nuclear instruments, allowing for non-invasive and real time detection. Results show that in the rougher flotation stage, the feed flow is distributed almost evenly in lines 2 and 3 (approximately 38% of the flow goes to each line) and to a lesser extent towards line 4 (approximately 24%). In lines 1 and 2 of the scavenger stage, a higher percentage of the flow goes towards line 1 (approximately 59%) and a lower percentage towards line 2 (41%). Line 6 of the rougher flotation is the fastest of the circuit (shortest residence time). In addition, the inlet mineral-cutting machine of the rougher stage segregates particles with a bias for fine sizes (11.4 % more fine-sized particles than coarse ones). This work is an example of how radiotracer technology can be applied to improve metal production and processes. Radiotracers provide reliable information to be used in combination with other metallurgical data to properly assess flotation circuits.