Pub Date : 2024-11-22DOI: 10.1016/j.partic.2024.11.002
Yuanye Zhou , Hongqiang Wang , Borun Wu , LiGe Wang , Xizhong Chen
The discrete element method (DEM) model calculates interaction forces between each pair of particles. However, it becomes computational expensive especially when the number of particles is large. In this study, a novel artificial neural network (ANN) model is proposed to replace the model of interaction forces between multiple particles in DEM including contact force and electrostatic force. The ANN model combines the residual network (ResNet) with the physics informed neural network (PINN). The physical loss term is derived from the Newton's third law about internal forces in multi-particle system. The performance of the ANN model is evaluated based on the DEM simulation data of 100, 200, and 300-particle system in a wall-bounded 2D swirling flow. It is found that the computing time is reduced nearly an order of magnitude (7–10 times) compared with the DEM model. In addition, the accuracy of the ANN model achieves the with only particles are not well predicted.
{"title":"Physics informed neural network model for multi-particle interaction forces","authors":"Yuanye Zhou , Hongqiang Wang , Borun Wu , LiGe Wang , Xizhong Chen","doi":"10.1016/j.partic.2024.11.002","DOIUrl":"10.1016/j.partic.2024.11.002","url":null,"abstract":"<div><div>The discrete element method (DEM) model calculates interaction forces between each pair of particles. However, it becomes computational expensive especially when the number of particles is large. In this study, a novel artificial neural network (ANN) model is proposed to replace the model of interaction forces between multiple particles in DEM including contact force and electrostatic force. The ANN model combines the residual network (ResNet) with the physics informed neural network (PINN). The physical loss term is derived from the Newton's third law about internal forces in multi-particle system. The performance of the ANN model is evaluated based on the DEM simulation data of 100, 200, and 300-particle system in a wall-bounded 2D swirling flow. It is found that the computing time is reduced nearly an order of magnitude (7–10 times) compared with the DEM model. In addition, the accuracy of the ANN model achieves the <span><math><mrow><msup><mi>R</mi><mn>2</mn></msup><mo>></mo><mn>0.93</mn></mrow></math></span> with only <span><math><mrow><mo>≤</mo><mn>2</mn><mo>%</mo></mrow></math></span> particles are not well predicted.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 126-138"},"PeriodicalIF":4.1,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-15DOI: 10.1016/j.partic.2024.10.019
Kun Jiang, Hui Jin
By employing the Eulerian-Eulerian Two Fluid Model, the effect of different particle size, supercritical CO2 (scCO2) velocity at slit jet (Ujet) and initial bed height on the macroscopic characteristics (i.e., fountain morphology, profiles of particle velocity, momentum transfer characteristics among particles, transient temperature evolutions of particles, interphase heat transfer coefficient and wall to bed heat transfer characteristics) in the pseudo 2D rectangular spouted bed using scCO2 as fluidizing agent is numerically studied in detail herein. Considering there are currently no relevant visualized experiments reported using scCO2 as a fluidized agent due to the extreme operating pressure of CO2 (25 MPa in this paper) under supercritical conditions, present numerical model was validated with experimental data by using air as the fluidizing agent, confirming simulated instantaneous volume fraction distribution of air and transient temperature evolutions of particles basically consistent with the experiments. Numerical results reveal some of the internal relations among hydrodynamics characteristics in bed, momentum transfer characteristics among particles and relevant heat transfer behaviours. Results show larger Ujet and smaller particle size will accelerate the particles' translational motion in spout, spout core and fountain core zone. Larger particle concentration will promote inter-particle collisions while suppress the kinetic motion of particles in above zones. Decrease the particle size will enhance interphase convective heat transfer coefficient, while increasing Ujet results insignificant impacts. Finally, we also observe the transition zone between annular and periphery zone has a certain enhancing effect on the wall to bed heat transfer coefficient.
{"title":"Numerical simulation on characteristics of hydrodynamics, interphase and wall to bed heat transfer in a pseudo 2D spouted bed using supercritical CO2 as fluidizing agent","authors":"Kun Jiang, Hui Jin","doi":"10.1016/j.partic.2024.10.019","DOIUrl":"10.1016/j.partic.2024.10.019","url":null,"abstract":"<div><div>By employing the Eulerian-Eulerian Two Fluid Model, the effect of different particle size, supercritical CO<sub>2</sub> (scCO<sub>2</sub>) velocity at slit jet (<em>U</em><sub>jet</sub>) and initial bed height on the macroscopic characteristics (i.e., fountain morphology, profiles of particle velocity, momentum transfer characteristics among particles, transient temperature evolutions of particles, interphase heat transfer coefficient and wall to bed heat transfer characteristics) in the pseudo 2D rectangular spouted bed using scCO<sub>2</sub> as fluidizing agent is numerically studied in detail herein. Considering there are currently no relevant visualized experiments reported using scCO<sub>2</sub> as a fluidized agent due to the extreme operating pressure of CO<sub>2</sub> (25 MPa in this paper) under supercritical conditions, present numerical model was validated with experimental data by using air as the fluidizing agent, confirming simulated instantaneous volume fraction distribution of air and transient temperature evolutions of particles basically consistent with the experiments. Numerical results reveal some of the internal relations among hydrodynamics characteristics in bed, momentum transfer characteristics among particles and relevant heat transfer behaviours. Results show larger <em>U</em><sub>jet</sub> and smaller particle size will accelerate the particles' translational motion in spout, spout core and fountain core zone. Larger particle concentration will promote inter-particle collisions while suppress the kinetic motion of particles in above zones. Decrease the particle size will enhance interphase convective heat transfer coefficient, while increasing <em>U</em><sub>jet</sub> results insignificant impacts. Finally, we also observe the transition zone between annular and periphery zone has a certain enhancing effect on the wall to bed heat transfer coefficient.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 106-125"},"PeriodicalIF":4.1,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-10DOI: 10.1016/j.partic.2024.10.017
Ming Bao, Wanrong Wu, Guangtian Tian, Binghui Qiu
Accurately simulating the crushing process of ore particles in a semi-autogenous grinding mill (SAG mill) is quite challenging. This study utilizes the discrete element method (DEM) to construct a breakage model for ore particles. Calibration of the discrete element basic parameters and Tavares breakage model parameters is conducted based on angle of repose (AoR) tests and single-particle impact tests. 3D scanning is employed to capture the morphology of the ore for particle modeling. On this basis, a discrete element breakage model for ore particles is built for single-particle impact simulations and validated through testing to determine the calibrated model parameters. The results indicate that the AoR angles and stacking shapes from the simulation and tests are highly similar, with a relative error of about 0.19%. The similarity in crushing outcomes and quantitative values between single-particle impact simulations and tests preliminary validates the reliability of the calibration method and the applicability of the Tavares breakage model, successfully determining a group of model parameters suitable for simulating ore particle crushing processes. This study lays the groundwork for utilizing DEM to simulate the visualization of ore particle crushing.
精确模拟矿石颗粒在半自磨机（SAG 磨机）中的破碎过程具有相当大的挑战性。本研究利用离散元素法（DEM）构建了矿石颗粒的破碎模型。离散元基本参数和塔瓦雷斯破碎模型参数的校准是基于静止角（AoR）试验和单颗粒冲击试验进行的。采用三维扫描捕捉矿石的形态，以建立颗粒模型。在此基础上，建立了用于单颗粒冲击模拟的矿石颗粒离散元素破碎模型，并通过测试进行验证，以确定校准模型参数。结果表明，模拟和试验得出的 AoR 角和堆积形状高度相似，相对误差约为 0.19%。单颗粒冲击模拟和试验在破碎结果和定量值上的相似性初步验证了校准方法的可靠性和塔瓦雷斯破碎模型的适用性，成功确定了一组适合模拟矿石颗粒破碎过程的模型参数。这项研究为利用 DEM 模拟矿石颗粒破碎的可视化奠定了基础。
{"title":"Research on discrete element parameter calibration of ore particles based on Tavares breakage model in a SAG mill","authors":"Ming Bao, Wanrong Wu, Guangtian Tian, Binghui Qiu","doi":"10.1016/j.partic.2024.10.017","DOIUrl":"10.1016/j.partic.2024.10.017","url":null,"abstract":"<div><div>Accurately simulating the crushing process of ore particles in a semi-autogenous grinding mill (SAG mill) is quite challenging. This study utilizes the discrete element method (DEM) to construct a breakage model for ore particles. Calibration of the discrete element basic parameters and Tavares breakage model parameters is conducted based on angle of repose (<em>AoR</em>) tests and single-particle impact tests. 3D scanning is employed to capture the morphology of the ore for particle modeling. On this basis, a discrete element breakage model for ore particles is built for single-particle impact simulations and validated through testing to determine the calibrated model parameters. The results indicate that the <em>AoR</em> angles and stacking shapes from the simulation and tests are highly similar, with a relative error of about 0.19%. The similarity in crushing outcomes and quantitative values between single-particle impact simulations and tests preliminary validates the reliability of the calibration method and the applicability of the Tavares breakage model, successfully determining a group of model parameters suitable for simulating ore particle crushing processes. This study lays the groundwork for utilizing DEM to simulate the visualization of ore particle crushing.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 44-56"},"PeriodicalIF":4.1,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-09DOI: 10.1016/j.partic.2024.10.018
Qilei Xu , Bin Lian , Yan Long , Baoming Shan , Xuezhong Wang , Fangkun Zhang
Optimal control of batch crystallization systems is still a focus and hot topic in the field of industrial crystallization, which seriously affects the consistency of batch product quality. In this paper, a new method with a new objective function and improved optimization algorithm was proposed for optimization of crystal size distribution (CSD) in case of fine crystals occurrence. The new objective function was developed with better margin metric and weighting technique to minimize fine crystal mass, meanwhile, a newly constructed sinusoidal weight function was introduced to improve the particle swarm optimization (PSO) algorithm. A precise control of CSD with suppressed numerical discrepancy caused by fine crystals removal was developed by combining seed recipe and temperature-swing. In addition, the effects of temperature curve segments on CSD during process optimization were systematically investigated to achieve optimal results. Two typical batch cooling crystallization systems were used to verify the effectiveness of the proposed method in controlling product CSD while minimizing fine crystal mass. Results demonstrated that the desired product CSD can be achieved with minor errors while the fine crystals could be shrunk to be negligible, i.e., the fine crystal mass and number can be reduced by over 90%. This work has an important guiding significance for the removal of fine crystals in industrial crystallization processes, especially when only operational optimization rather than equipment updating is considered.
{"title":"Optimization of batch cooling crystallization systems considering crystal growth, nucleation and dissolution. Part I: Simulation","authors":"Qilei Xu , Bin Lian , Yan Long , Baoming Shan , Xuezhong Wang , Fangkun Zhang","doi":"10.1016/j.partic.2024.10.018","DOIUrl":"10.1016/j.partic.2024.10.018","url":null,"abstract":"<div><div>Optimal control of batch crystallization systems is still a focus and hot topic in the field of industrial crystallization, which seriously affects the consistency of batch product quality. In this paper, a new method with a new objective function and improved optimization algorithm was proposed for optimization of crystal size distribution (CSD) in case of fine crystals occurrence. The new objective function was developed with better margin metric and weighting technique to minimize fine crystal mass, meanwhile, a newly constructed sinusoidal weight function was introduced to improve the particle swarm optimization (PSO) algorithm. A precise control of CSD with suppressed numerical discrepancy caused by fine crystals removal was developed by combining seed recipe and temperature-swing. In addition, the effects of temperature curve segments on CSD during process optimization were systematically investigated to achieve optimal results. Two typical batch cooling crystallization systems were used to verify the effectiveness of the proposed method in controlling product CSD while minimizing fine crystal mass. Results demonstrated that the desired product CSD can be achieved with minor errors while the fine crystals could be shrunk to be negligible, i.e., the fine crystal mass and number can be reduced by over 90%. This work has an important guiding significance for the removal of fine crystals in industrial crystallization processes, especially when only operational optimization rather than equipment updating is considered.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 84-96"},"PeriodicalIF":4.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To accelerate the recycling of black soil, it is necessary to develop a new type of soil remediation equipment to improve its working efficiency. The one-way test was used to determine the mean level value of the steepest climb test, and the combined equilibrium method was used to determine the upper and lower interval levels of the response surface test for parameter optimisation. Based on the results of the response surface indices, machine learning was performed and the optimal model was determined. The results show that the predictive ability and stability of the decision tree model for the two indicators are better than that of random forest and support vector machine. The optimal parameter combinations determined using the decision tree model are: speed 73 rpm, homogenisation pitch 183 mm, homogenisation time 1 s, descent speed 0.06 m/s. The error between the optimal value of the machine learning prediction model and the actual simulation is 1.1% and 5.72%, respectively. The results of the study show that the effect of optimizing the parameters through machine learning achieves a satisfactory prediction accuracy.
{"title":"Optimisation of parameters of a dual-axis soil remediation device based on response surface methodology and machine learning algorithm","authors":"Zhipeng Wang, Tong Zhu, Youzhao Wang, Feng Ma, Chaoyue Zhao, Xu Li, Yanping Zhang","doi":"10.1016/j.partic.2024.10.013","DOIUrl":"10.1016/j.partic.2024.10.013","url":null,"abstract":"<div><div>To accelerate the recycling of black soil, it is necessary to develop a new type of soil remediation equipment to improve its working efficiency. The one-way test was used to determine the mean level value of the steepest climb test, and the combined equilibrium method was used to determine the upper and lower interval levels of the response surface test for parameter optimisation. Based on the results of the response surface indices, machine learning was performed and the optimal model was determined. The results show that the predictive ability and stability of the decision tree model for the two indicators are better than that of random forest and support vector machine. The optimal parameter combinations determined using the decision tree model are: speed 73 rpm, homogenisation pitch 183 mm, homogenisation time 1 s, descent speed 0.06 m/s. The error between the optimal value of the machine learning prediction model and the actual simulation is 1.1% and 5.72%, respectively. The results of the study show that the effect of optimizing the parameters through machine learning achieves a satisfactory prediction accuracy.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 26-43"},"PeriodicalIF":4.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.partic.2024.10.015
Jichen Zhong , Junxing Zheng , Lin Gao , Qixin Wu , Zhenchang Guan , Shuangping Li , Dong Wang
In this study, advanced image processing technology is used to analyze the three-dimensional sand composite image, and the topography features of sand particles are successfully extracted and saved as high-quality image files. These image files were then trained using the latent diffusion model (LDM) to generate a large number of sand particles with real morphology, which were then applied to numerical studies. The effects of particle morphology on the macroscopic mechanical behavior and microscopic energy evolution of sand under complex stress paths were studied in detail, combined with the circular and elliptical particles widely used in current tests. The results show that with the increase of the irregularity of the sample shape, the cycle period and radius of the closed circle formed by the partial strain curve gradually decrease, and the center of the circle gradually shifts. In addition, the volume strain and liquefaction strength of sand samples increase with the increase of particle shape irregularity. It is particularly noteworthy that obvious vortex structures exist in the positions near the center where deformation is severe in the samples of circular and elliptical particles. However, such structures are difficult to be directly observed in sample with irregular particles. This phenomenon reveals the influence of particle morphology on the complexity of the mechanical behavior of sand, providing us with new insights into the understanding of the response mechanism of sand soil under complex stress conditions.
{"title":"Study on micromechanical behavior and energy evolution of granular material generated by latent diffusion model under rotation of principal stresses","authors":"Jichen Zhong , Junxing Zheng , Lin Gao , Qixin Wu , Zhenchang Guan , Shuangping Li , Dong Wang","doi":"10.1016/j.partic.2024.10.015","DOIUrl":"10.1016/j.partic.2024.10.015","url":null,"abstract":"<div><div>In this study, advanced image processing technology is used to analyze the three-dimensional sand composite image, and the topography features of sand particles are successfully extracted and saved as high-quality image files. These image files were then trained using the latent diffusion model (LDM) to generate a large number of sand particles with real morphology, which were then applied to numerical studies. The effects of particle morphology on the macroscopic mechanical behavior and microscopic energy evolution of sand under complex stress paths were studied in detail, combined with the circular and elliptical particles widely used in current tests. The results show that with the increase of the irregularity of the sample shape, the cycle period and radius of the closed circle formed by the partial strain curve gradually decrease, and the center of the circle gradually shifts. In addition, the volume strain and liquefaction strength of sand samples increase with the increase of particle shape irregularity. It is particularly noteworthy that obvious vortex structures exist in the positions near the center where deformation is severe in the samples of circular and elliptical particles. However, such structures are difficult to be directly observed in sample with irregular particles. This phenomenon reveals the influence of particle morphology on the complexity of the mechanical behavior of sand, providing us with new insights into the understanding of the response mechanism of sand soil under complex stress conditions.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 71-83"},"PeriodicalIF":4.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.partic.2024.10.014
Yanan Miao , Haoran Li , Mingzhu Zhu , Chaojie Zhao , Tengwen Zhang , Hussein Mohammed Ahmed Kaid
To investigate the mesoscopic influence of surfactants on seepage law during water injection in coal seam, this paper innovatively establishes a fluid transport lattice Boltzmann (LBM) model by incorporating the seepage resistance generated from the porous media and external forces, which embodies the impact of wettability degree resulted from cocamidopropyl betaine (CAB), sodium dodecyl sulfate (SDS), and coconutt diethanol amide (CDEA) reagents at a 0.1% concentration. The main conclusions derived from this investigation are as follows: Firstly, as the lattice number in the X direction increases, the average seepage velocities in coal samples treated by deionized water, 0.1% CAB, 0.1% SDS, and 0.1% CDEA reagents (Nos. 1, 2, 3, and 4) exhibit three distinct stages: rapid decline, slow decline, and steady decline; in comparison to raw coal sample, modified coal samples demonstrate decreases of 20.84%, 33.91%, and 61.70%, respectively. Secondly, the critical values of displacement pressure difference exist during the phenomenon that modified reagents spread out in the entire flow channel, which are 3.5, 3.5, and 5.2 MPa, respectively, for coal samples Nos. 2, 3, and 4; this signifies that surpassing these critical values help prevent issues such as blank belts within the wetting range and insufficient dust control. Finally, at a displacement pressure difference of 0.01 (lattice unit), the average velocity ratios for samples (Nos. 2, 3, and 4) are 0.78, 0.56, and 0.37 (lattice unit), respectively; notably, the water flow velocities in modified coal samples are lower compared to that in raw coal sample, indicating that the addition of surfactants impede the seepage process of water injection in coal seam. Moreover, when the displacement pressure difference reaches 0.03 (lattice unit), the velocity ratio of CDEA-modified coal sample exceeds 100%; this means that when the displacement pressure difference surpasses 15.6 MPa, the water injection effect of CDEA-modified coal sample begins to be improved. These research findings offer a theoretical basis for enhancing water injection technology in coal mines.
{"title":"Mesoscale modeling on the influence of surfactants on seepage law during water injection in coal","authors":"Yanan Miao , Haoran Li , Mingzhu Zhu , Chaojie Zhao , Tengwen Zhang , Hussein Mohammed Ahmed Kaid","doi":"10.1016/j.partic.2024.10.014","DOIUrl":"10.1016/j.partic.2024.10.014","url":null,"abstract":"<div><div>To investigate the mesoscopic influence of surfactants on seepage law during water injection in coal seam, this paper innovatively establishes a fluid transport lattice Boltzmann (LBM) model by incorporating the seepage resistance generated from the porous media and external forces, which embodies the impact of wettability degree resulted from cocamidopropyl betaine (CAB), sodium dodecyl sulfate (SDS), and coconutt diethanol amide (CDEA) reagents at a 0.1% concentration. The main conclusions derived from this investigation are as follows: Firstly, as the lattice number in the X direction increases, the average seepage velocities in coal samples treated by deionized water, 0.1% CAB, 0.1% SDS, and 0.1% CDEA reagents (Nos. 1, 2, 3, and 4) exhibit three distinct stages: rapid decline, slow decline, and steady decline; in comparison to raw coal sample, modified coal samples demonstrate decreases of 20.84%, 33.91%, and 61.70%, respectively. Secondly, the critical values of displacement pressure difference exist during the phenomenon that modified reagents spread out in the entire flow channel, which are 3.5, 3.5, and 5.2 MPa, respectively, for coal samples Nos. 2, 3, and 4; this signifies that surpassing these critical values help prevent issues such as blank belts within the wetting range and insufficient dust control. Finally, at a displacement pressure difference of 0.01 (lattice unit), the average velocity ratios for samples (Nos. 2, 3, and 4) are 0.78, 0.56, and 0.37 (lattice unit), respectively; notably, the water flow velocities in modified coal samples are lower compared to that in raw coal sample, indicating that the addition of surfactants impede the seepage process of water injection in coal seam. Moreover, when the displacement pressure difference reaches 0.03 (lattice unit), the velocity ratio of CDEA-modified coal sample exceeds 100%; this means that when the displacement pressure difference surpasses 15.6 MPa, the water injection effect of CDEA-modified coal sample begins to be improved. These research findings offer a theoretical basis for enhancing water injection technology in coal mines.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 1-13"},"PeriodicalIF":4.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.partic.2024.10.016
Yifan Wang, Tianyi Zhang, Lei Chen, Wenquan Tao
In precise fuel circuit systems, the filtration of particulate impurities seriously affects the efficiency and service life of various components. For filtration process intensification of high-pressure fuel laser perforated filters, the two-phase flow characteristics in filters is studied. The size, position and number of filtration holes are taken as optimization variables, and take the filtration efficiency and flow pressure drop as optimization objectives. Computational fluid dynamics (CFD) is used to simulate the two-phase motion of continuous phase and discrete particles in a periodic unit. Artificial neural networks (ANN) are utilized for objectives prediction, and the NSGA-II genetic algorithm is employed for multi-objective optimization, resulting in the Pareto front solution set. Furtherly, the reasonable solution is selected by introducing TOPSIS to ensure that two optimization indexes are relatively smaller and balanced. The optimized filter element scheme allows the filter to have a pressure drop of less than 3.2 MPa under high pressure and a filtration efficiency of over 80% for spherical particle impurities with a diameter of 5 μm or more.
{"title":"Multi-objective optimization of laser perforated fuel filter parameters based on artificial neural network and genetic algorithm","authors":"Yifan Wang, Tianyi Zhang, Lei Chen, Wenquan Tao","doi":"10.1016/j.partic.2024.10.016","DOIUrl":"10.1016/j.partic.2024.10.016","url":null,"abstract":"<div><div>In precise fuel circuit systems, the filtration of particulate impurities seriously affects the efficiency and service life of various components. For filtration process intensification of high-pressure fuel laser perforated filters, the two-phase flow characteristics in filters is studied. The size, position and number of filtration holes are taken as optimization variables, and take the filtration efficiency and flow pressure drop as optimization objectives. Computational fluid dynamics (CFD) is used to simulate the two-phase motion of continuous phase and discrete particles in a periodic unit. Artificial neural networks (ANN) are utilized for objectives prediction, and the NSGA-II genetic algorithm is employed for multi-objective optimization, resulting in the Pareto front solution set. Furtherly, the reasonable solution is selected by introducing TOPSIS to ensure that two optimization indexes are relatively smaller and balanced. The optimized filter element scheme allows the filter to have a pressure drop of less than 3.2 MPa under high pressure and a filtration efficiency of over 80% for spherical particle impurities with a diameter of 5 μm or more.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 57-70"},"PeriodicalIF":4.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1016/j.partic.2024.10.011
Chunya Sun , Zhifang Xu , Yanqiu Xiao , Guangzhen Cui , Zhengdong Xiao , Wanbin Cui , Pengpeng Wang , Lianhui Jia
Pipeline hydraulic transportation is extensively utilized across diverse sectors, with enhancing the performance of pipeline hydrodynamic transport and minimizing erosion wear on the pipeline walls being essential for ensuring the stability of pipeline operations. This paper introduces a methodology for the hydraulic transport of a twisted four-lobed pipe, employing a numerical and erosion model developed through the CFD-DEM (computational fluid dynamics and discrete element method) coupling approach. An experimental circulating flow platform is constructed for validation purposes. The performance of the pipe is assessed by analyzing key indices including fluid velocity, pressure drop, particle trajectory, and erosion wear. The results indicate that twisted four-lobed pipe enhances fluid flow rates, facilitating particle discharge and mitigating accumulation, with reduced wear compared to the twin twist triangle spiral pipe. The analysis of structural parameters’ impact on hydraulic conveyance is also presented. These findings offer theoretical insights for optimizing pipeline performance in hydraulic conveyance while minimizing wear.
{"title":"Study of hydraulic transport characteristics and erosion wear of twisted four-lobed pipe based on CFD-DEM","authors":"Chunya Sun , Zhifang Xu , Yanqiu Xiao , Guangzhen Cui , Zhengdong Xiao , Wanbin Cui , Pengpeng Wang , Lianhui Jia","doi":"10.1016/j.partic.2024.10.011","DOIUrl":"10.1016/j.partic.2024.10.011","url":null,"abstract":"<div><div>Pipeline hydraulic transportation is extensively utilized across diverse sectors, with enhancing the performance of pipeline hydrodynamic transport and minimizing erosion wear on the pipeline walls being essential for ensuring the stability of pipeline operations. This paper introduces a methodology for the hydraulic transport of a twisted four-lobed pipe, employing a numerical and erosion model developed through the CFD-DEM (computational fluid dynamics and discrete element method) coupling approach. An experimental circulating flow platform is constructed for validation purposes. The performance of the pipe is assessed by analyzing key indices including fluid velocity, pressure drop, particle trajectory, and erosion wear. The results indicate that twisted four-lobed pipe enhances fluid flow rates, facilitating particle discharge and mitigating accumulation, with reduced wear compared to the twin twist triangle spiral pipe. The analysis of structural parameters’ impact on hydraulic conveyance is also presented. These findings offer theoretical insights for optimizing pipeline performance in hydraulic conveyance while minimizing wear.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"95 ","pages":"Pages 356-369"},"PeriodicalIF":4.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1016/j.partic.2024.10.012
Zhiqi Xie , Shengwen Zhu , Xingsheng Wang , Shuang Wei , Ruirui Zhang , Ruixia Liu
Vanadium phosphorus oxide (VPO) catalysts play a crucial role in the selective oxidation of n-butane to maleic anhydride (MA), and their catalytic performance is highly dependent on the synthesis conditions of the precursor. This study focuses on a facile and rapid microwave irradiation method for the synthesis of VPO precursors. The effects of microwave exposure time and power on morphology, crystalline structure, and catalytic effect of VPO are investigated. The relationship between the structure and performance of the catalysts is explored by SEM, TEM, BET, FT-IR, XRD, Raman, and XPS characterization. The results demonstrate that microwave power is the key factor influencing the size, thickness, surface area, and active surfaces of vanadium pyrophosphate after activation. Additionally, the P/V ratio and Lat-O/Sur-O ratio on the catalyst surface vary with different synthesis conditions, which significantly affect the catalytic performance. In conclusion, the microwave-synthesized VPO catalyst exhibits remarkable enhancements in n-butane conversion (87.2%) and maleic anhydride (MA) selectivity (70.2%), which shows high efficiency and energy-saving, providing a new research direction for the future preparation of VPO catalysts.
{"title":"Microwave synthesis of vanadium phosphorus oxide catalysts for n-butane selective oxidation","authors":"Zhiqi Xie , Shengwen Zhu , Xingsheng Wang , Shuang Wei , Ruirui Zhang , Ruixia Liu","doi":"10.1016/j.partic.2024.10.012","DOIUrl":"10.1016/j.partic.2024.10.012","url":null,"abstract":"<div><div>Vanadium phosphorus oxide (VPO) catalysts play a crucial role in the selective oxidation of <em>n</em>-butane to maleic anhydride (MA), and their catalytic performance is highly dependent on the synthesis conditions of the precursor. This study focuses on a facile and rapid microwave irradiation method for the synthesis of VPO precursors. The effects of microwave exposure time and power on morphology, crystalline structure, and catalytic effect of VPO are investigated. The relationship between the structure and performance of the catalysts is explored by SEM, TEM, BET, FT-IR, XRD, Raman, and XPS characterization. The results demonstrate that microwave power is the key factor influencing the size, thickness, surface area, and active surfaces of vanadium pyrophosphate after activation. Additionally, the P/V ratio and Lat-O/Sur-O ratio on the catalyst surface vary with different synthesis conditions, which significantly affect the catalytic performance. In conclusion, the microwave-synthesized VPO catalyst exhibits remarkable enhancements in <em>n</em>-butane conversion (87.2%) and maleic anhydride (MA) selectivity (70.2%), which shows high efficiency and energy-saving, providing a new research direction for the future preparation of VPO catalysts.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"96 ","pages":"Pages 97-105"},"PeriodicalIF":4.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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