| Slurry electrolysis is a hydrometallurgical process that offers benefits such as a shorter process,reduced energy consumption,and environmental protection.It is particularly advantageous for extracting metals from polymetallic complex ores and has been implemented in industrial applications.However,challenges such as ore sinking and membrane deformation arise in the actual production process.Additionally,the multi-tank series configuration results in variable working conditions within tanks and complex control of process parameters.The existing mixing experience formula and particle suspension characteristics are insufficient for slurry electrolysis production.To address these issues,this study focused on antimony concentrate slurry electrolysis,and employed cold-state physical experiments and numerical simulation technology to investigate the distribution patterns of flow field,particle concentration field,and membrane stress-strain field in the slurry electrolysis tank for the first time.The study also utilized machine learning methods to develop a rapid prediction model for the field information of solid-liquid flow process.This study provides the guidance for the optimization and further development of the slurry electrolysis process.The main contents and conclusions include:(1)A laboratory-scale slurry electrolysis tank with a 1:6 similarity ratio was constructed using the similarity principle.High-speed camera and probe measurement technology were used to analyze particle concentration distribution characteristics within the tank.Accurate measurements of particle concentration throughout the tank were obtained through point design and probe height control.Experimental results indicated that stable flow at the solid-liquid interface,no significant eddy currents in the tank center,and a particle concentration distribution characterized by a uniform middle and high edge.When the rotation speed N=200 rpm,particles were uniformly suspended,and a clear liquid layer disappeared.When N=240 rpm,particle suspension uniformity increased with higher solid volume fractions,suggesting that particle-particle interactions within the tank cannot be ignored.(2)Computational fluid dynamics(CFD)model of solid-liquid suspension in slurry electrolysis was established,incorporating the kinetic theory of granular flow(KTGF)within the Eulerian-Eulerian framework.Numerical simulations and experimental results were compared across multiple dimensions,including point,line,surface,and volume.The results showed that the relative error of particle concentration did not exceed 4.7%,and the CFD calculated value closely matched the experimental data.Based on the distribution patterns of the flow field and particle concentration field in the slurry electrolysis tank,the stirring tank was divided into five regions.The solid concentration was higher in the weak circulation region near the tank wall and at the bottom of the impeller shaft.Using the tracer method to study mixing time,it was found that the mixing time in both the strong circulation and weak circulation regions were close to 20 seconds.The fluid flow between the anodic baffles(94 seconds)was identified as the limiting factor for mixing time.The flow throughout the entire tank was centrosymmetric,and the particle distribution in the middle region of the tank(y=0.1-0.8H)was uniform and orderly.(3)Using an industrial-scale slurry electrolysis tank as the research subject,the impacts of key physical and process parameters on solid phase concentration,liquid phase flow rate,particle suspension uniformity(σ),and power consumption were examined.The findings revealed that as stirring kinetic energy increased,turbulence intensity progressively shifted from the lower regions of the electrode plates towards the impeller shaft and between the electrode plates.Based on the observed changes in field information,a criterion for evaluating solid-liquid suspension characteristics in the slurry electrolysis tank was proposed.Whenσ≥0.9,particles are uniformly suspended;when 0.9<σ<0.8,a clear liquid layer forms between adjacent membrane bags;and when σ≤0.8,stirring is inadequate,with the weakest stirring effect occurring at the impeller shaft center.By considering suspension homogeneity and power consumption,optimal working conditions of particle size d=50μm and liquid level H=1800 mm were determined.And the quantitative expressions were established between the rotational speed,ore specific gravity,with the indexes.Furthermore,the effect from the impeller diameter should not be overlooked in the upper part of the tank(y≥0.8H),as the power required for achieving uniform suspension was minimized when the impeller diameter D=T/3,was 6.28 kW.Suspending particles at the lower wall connection of the slurry electrolysis tank required high energy consumption,and particle distribution results for multiple particle sizes indicated that larger particles were more likely to accumulate at the chamfers,with particle numbers increasing closer to the bottom of tank.(4)Numerical simulation of the membrane deformation mechanism in the slurry electrolytic stirring tank was conducted using a combination of one-way and two-way fluid-structure interaction.The analysis demonstrated that the pressure difference on either side of the membrane bag was the primary cause of deformation,with the maximum deformation occurring at a vertical height ofy=1.2 m,measuring 891.66 mm.Higher stirring speeds resulted in smaller optimal liquid level differences needed for membrane deformation.When the cathode region pressure was low,the membrane bag was compressed and deformed inward;when the pressure increases,it bulged outward.Controlling the electrolyte density in the cathode region at 1392-1413 kg/m~3 is more suitable.Additionally,the relationship between the maximum deformation and the solid volume fraction(X)in the anode region was established,showing that at X=1 5%,the membrane deformation reaches its minimum value of 226.7 mm.After adding external frame constraints,the maximum membrane deformation decreased to 0.664 mm.The two-way fluid-solid interaction revealed that when the membrane bulged outward,the particle suspension height increased.(5)Combining CFD calculations and machine learning,a rapid prediction model for flow field and concentration field in slurry electrolysis stirring tank was developed.Calculation points were scientifically chosen through orthogonal testing,effectively reducing simulation conditions and establishing a comprehensive data training.Meanwhile a reasonable weight for the prediction model was provided by the orthogonal test.In conjunction with the K-nearest neighbor algorithm,the corresponding prediction model was built.The results indicated that as the number of levels in the orthogonal test increased,the prediction accuracy improved significantly.The model established with four factors and nine levels can accurately predict flow field and concentration field information in the stirred tank.Compared to traditional numerical simulation,the prediction model reduced field information response time from 75 hours to 20 seconds,meeting real-time control requirements for production and addressing the severe lag issue when applying numerical simulations to actual production. |
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