Slurry electrolysis(SE),as a hydrometallurgical process,has the characteristic of a multitank series connection,which leads to various stirring conditions and a complex solid suspension state.The computational fluid d...Slurry electrolysis(SE),as a hydrometallurgical process,has the characteristic of a multitank series connection,which leads to various stirring conditions and a complex solid suspension state.The computational fluid dynamics(CFD),which requires high computing resources,and a combination with machine learning was proposed to construct a rapid prediction model for the liquid flow and solid concentration fields in a SE tank.Through scientific selection of calculation samples via orthogonal experiments,a comprehensive dataset covering a wide range of conditions was established while effectively reducing the number of simulations and providing reasonable weights for each factor.Then,a prediction model of the SE tank was constructed using the K-nearest neighbor algorithm.The results show that with the increase in levels of orthogonal experiments,the prediction accuracy of the model improved remarkably.The model established with four factors and nine levels can accurately predict the flow and concentration fields,and the regression coefficients of average velocity and solid concentration were 0.926 and 0.937,respectively.Compared with traditional CFD,the response time of field information prediction in this model was reduced from 75 h to 20 s,which solves the problem of serious lag in CFD applied alone to actual production and meets real-time production control requirements.展开更多
The flexible superhydrophobic thermoplastic polyurethane(TPU)porous material was prepared by heat-induced phase separation method with two cooling steps.The influence of the preparation process on the microstructure o...The flexible superhydrophobic thermoplastic polyurethane(TPU)porous material was prepared by heat-induced phase separation method with two cooling steps.The influence of the preparation process on the microstructure of the material was discussed in depth.The microstructure,hydrophobicity and specific surface area of porous TPU materials were analyzed in detail.The surface wettability,separation selectivity,saturated adsorption capacity and adsorption rate,mechanical properties,environmental adaptability and cyclic properties of porous TPU materials were studied.The results show that the TPU-8%porous monolithic material prepared by heat-induced phase separation method shows good performance when the polymer concentration is 8%,the phase separation temperature is 0℃,the phase separation time is 30min,and the mixing solvent ratio is 9:1.展开更多
基金financially supported by the National Natural Science Foundation of China(No.51974018the Open Foundation of the State Key Laboratory of Process Automation in Mining and Metallurgy(No.BGRIMM-KZSKL-2022-9).
文摘Slurry electrolysis(SE),as a hydrometallurgical process,has the characteristic of a multitank series connection,which leads to various stirring conditions and a complex solid suspension state.The computational fluid dynamics(CFD),which requires high computing resources,and a combination with machine learning was proposed to construct a rapid prediction model for the liquid flow and solid concentration fields in a SE tank.Through scientific selection of calculation samples via orthogonal experiments,a comprehensive dataset covering a wide range of conditions was established while effectively reducing the number of simulations and providing reasonable weights for each factor.Then,a prediction model of the SE tank was constructed using the K-nearest neighbor algorithm.The results show that with the increase in levels of orthogonal experiments,the prediction accuracy of the model improved remarkably.The model established with four factors and nine levels can accurately predict the flow and concentration fields,and the regression coefficients of average velocity and solid concentration were 0.926 and 0.937,respectively.Compared with traditional CFD,the response time of field information prediction in this model was reduced from 75 h to 20 s,which solves the problem of serious lag in CFD applied alone to actual production and meets real-time production control requirements.
基金We acknowledge the fnancial support from the Research Project of Keyi College of Zhejiang Sci-Tech University(KY2021001)the National Natural Science Foundation of Zhejiang Province China(LY15B030002).
文摘The flexible superhydrophobic thermoplastic polyurethane(TPU)porous material was prepared by heat-induced phase separation method with two cooling steps.The influence of the preparation process on the microstructure of the material was discussed in depth.The microstructure,hydrophobicity and specific surface area of porous TPU materials were analyzed in detail.The surface wettability,separation selectivity,saturated adsorption capacity and adsorption rate,mechanical properties,environmental adaptability and cyclic properties of porous TPU materials were studied.The results show that the TPU-8%porous monolithic material prepared by heat-induced phase separation method shows good performance when the polymer concentration is 8%,the phase separation temperature is 0℃,the phase separation time is 30min,and the mixing solvent ratio is 9:1.
