Article(id=1322164716156342490, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322164546295410919, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1731686400000, receivedDateStr=2024-11-16, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793158232964, onlineDateStr=2026-10-28, pubDate=1764000000000, pubDateStr=2025-11-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793158232964, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793158232964, creator=13701087609, updateTime=1793158232964, updator=13701087609, issue=Issue{id=1322164546295410919, tenantId=1146029695717560320, journalId=1225396423026438145, year='2025', volume='45', issue='11', pageStart='1', pageEnd='284', issueExtLink='null', onlineDate='null', pubDate='1764000000000', pubDateStr='2025-11-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793158192465, creator='13701087609', updateTime=1793158905697, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322167537857573862, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322164546295410919, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322167537861768167, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322164546295410919, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=277, endPage=284, ext={EN=ArticleExt(id=1322164716332503259, articleId=1322164716156342490, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=Simulation Study on the Influence of Ore Moisture Content on the Crushing Effect of High-Pressure Roller Grinding, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=

The optimization of the crushing effect of high-pressure roller grinding is of crucial importance in relation to the enhancement of ore processing efficiency, the reduction of energy consumption, and the elevation of product quality. In order to investigate the influence of ore moisture content on the crushing effect of high-pressure rollers, with the magnetite ore from eastern Hebei selected as the research specimen, the interaction between high-pressure rollers and particles under different feed moisture content conditions was simulated by the combination with SolidWorks modeling and EDEM simulation. The simulation results indicate that, as the particle surface energy increases from 0 to 25 J/m2, the crushing effect in the high-pressure roller initially strengthens and then weakens, when the particle surface energy reaches 20 J/m2, the crushing effect is the best. Open-circuit test results under different feed moisture conditions show that as the feed moisture content rises from 0.11% to 6%, the crushing performance of the high-pressure roller first improves and then deteriorates, aligning with the simulation trends. When the feed moisture content is within the 1.5% to 4.5% range, the product particle size after crushing is finer, and the crushing effect is more favorable.

, authors=Sanyang LIU1, Chenglong ZHANG2, Libing ZHAO1, Youbang LAI2, Zhaoyong WU3, Di ZHANG1, Mingmei LI1, authorsList=Sanyang LIU, Chenglong ZHANG, Libing ZHAO, Youbang LAI, Zhaoyong WU, Di ZHANG, Mingmei LI, authorCompany=null, correspAuthors=Libing ZHAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322164718710673650, articleId=1322164716156342490, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=矿石含水率对高压辊磨机粉碎效果影响的仿真模拟研究, columnId=1226462297560892399, journalTitle=矿业研究与开发, columnName=选矿与资源综合利用, runingTitle=null, highlight=null, articleAbstract=

优化高压辊磨机的粉碎效果对于提高矿石加工效率、降低能耗和提高产品质量具有重要意义。为探究矿石含水率对高压辊粉碎效果的影响,以冀东地区磁铁矿石为研究对象,采用颗粒表面能表征物料的含水率,结合SolidWorks建模和EDEM仿真,对不同入料含水率条件下高压辊与颗粒间的相互作用开展模拟研究。仿真结果表明,当颗粒表面能从0增加到25 J/m2时,颗粒在高压辊中的粉碎效果呈先增强后减弱的趋势,颗料表面能达到20 J/m2时粉碎效果最优。不同入料含水率条件下的高压辊开路试验结果表明,入料含水率由0.11%增大到6%时,高压辊粉碎效果不断优化后变差,与仿真结果规律一致;入料含水率在1.5%~4.5%范围时,高压辊磨机粉碎后的产品粒度更细,粉碎效果较好。

, authors=刘三阳1, 张成龙2, 赵礼兵1, 来有邦2, 吴照永3, 张迪1, 栗明媚1, authorsList=刘三阳, 张成龙, 赵礼兵, 来有邦, 吴照永, 张迪, 栗明媚, authorCompany=null, correspAuthors=赵礼兵, authorNote=

刘三阳(1999—),男,山东临沂人,硕士研究生,研究方向为矿产综合利用。E-mail:

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赵礼兵(1978—),男,河北廊坊人,教授,硕士生导师,主要从事矿产综合利用、选矿自动化方面的研究工作。E-mail:
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刘三阳(1999—),男,山东临沂人,硕士研究生,研究方向为矿产综合利用。E-mail:

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Minerals, 2021, 11 (8): 801., articleTitle=Investigation of lateral confinement, roller aspect ratio and wear condition on HPGR performance using DEM-MBD-PRM simulations, refAbstract=null), Reference(id=1322164728596648293, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, doi=null, pmid=null, pmcid=null, year=2022, volume=177, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[18], rfOrder=31, authorNames=RODRIGUEZ V A, BARRIOS G K P, BUENO G, journalName=Minerals Engineering, refType=null, unstructuredReference=RODRIGUEZ V A, BARRIOS G K P, BUENO G, et al. Coupled DEM-MBD-PRM simulations of high-pressure grinding rolls. part 1: calibration and validation in pilot-scale [J]. Minerals Engineering, 2022, 177: 107389., articleTitle=Coupled DEM-MBD-PRM simulations of high-pressure grinding rolls. part 1: calibration and validation in pilot-scale, refAbstract=null), Reference(id=1322164728688922982, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, doi=null, pmid=null, pmcid=null, year=2022, volume=178, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[19], rfOrder=32, authorNames=RODRIGUEZ V A, BARRIOS G K P, TAVARES L M, journalName=Minerals Engineering, refType=null, unstructuredReference=RODRIGUEZ V A, BARRIOS G K P, TAVARES L M. Coupled DEM-MBD-PRM simulations of high-pressure grinding rolls. part 2: investigation of roll skewing [J]. Minerals Engineering, 2022, 178: 107428., articleTitle=Coupled DEM-MBD-PRM simulations of high-pressure grinding rolls. part 2: investigation of roll skewing, refAbstract=null)], funds=[Fund(id=1322164724146491717, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, awardId=HG2022137, language=CN, fundingSource=河钢集团有限公司重点科技项目(HG2022137), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322164718966526195, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, xref=1., ext=[AuthorCompanyExt(id=1322164718974914804, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, companyId=1322164718966526195, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.School of Mining Engineering, North China University of Science and Technology, Tangshan, Hebei 063210, China), 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articleId=1322164716156342490, language=EN, label=Table 1, caption=

Material characteristic parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
材料泊松比密度/(kg/m3)杨氏模量/Pa
铁矿石0.253 6392×109
钢0.307 8007×1010
), ArticleFig(id=1322164723206967610, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=CN, label=表1, caption=

材料特性参数

, figureFileSmall=null, figureFileBig=null, tableContent=
材料泊松比密度/(kg/m3)杨氏模量/Pa
铁矿石0.253 6392×109
钢0.307 8007×1010
), ArticleFig(id=1322164723282465083, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=EN, label=Table 2, caption=

Material contact parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
材料恢复系数静摩擦因数滚动摩擦因数
矿石与矿石0.200.550.51
介质与钢0.150.490.47
), ArticleFig(id=1322164723362156860, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=CN, label=表2, caption=

材料接触参数

, figureFileSmall=null, figureFileBig=null, tableContent=
材料恢复系数静摩擦因数滚动摩擦因数
矿石与矿石0.200.550.51
介质与钢0.150.490.47
), ArticleFig(id=1322164723441848637, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=EN, label=Table 3, caption=

Sieve analysis results of particle size composition of test raw materials

, figureFileSmall=null, figureFileBig=null, tableContent=
粒级/mm试验原料
产率/%累积含量/%
+1521.69100.00
-15~+1034.4778.31
-10~+87.6243.84
-8~+611.5036.21
-6~+36.8324.71
-3~+22.3917.88
-2~+14.6415.49
-1~+0.52.7510.86
-0.5~+0.21.908.10
-0.2~+0.150.536.21
-0.15~+0.0742.015.67
-0.0743.663.66
合计100.00—
), ArticleFig(id=1322164723521540414, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=CN, label=表3, caption=

试验原料粒度组成筛析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
粒级/mm试验原料
产率/%累积含量/%
+1521.69100.00
-15~+1034.4778.31
-10~+87.6243.84
-8~+611.5036.21
-6~+36.8324.71
-3~+22.3917.88
-2~+14.6415.49
-1~+0.52.7510.86
-0.5~+0.21.908.10
-0.2~+0.150.536.21
-0.15~+0.0742.015.67
-0.0743.663.66
合计100.00—
), ArticleFig(id=1322164723601232191, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=EN, label=Table 4, caption=

Particle size distribution of rolled products under different feed moisture contents

, figureFileSmall=null, figureFileBig=null, tableContent=
粒级/mm0.11%含水率1.5%含水率3%含水率4.5%含水率6%含水率
产率/%负累积/%产率/%负累积/%产率/%负累积/%产率/%负累积/%产率/%负累积/%
+615.30100.0015.39100.0011.43100.0012.33100.0016.38100.00
-6~+57.3284.704.9784.614.8288.575.0987.674.0983.62
-5~+320.6577.3819.4879.6419.4383.7518.4482.5822.2279.53
-3~+25.9956.735.5960.166.0664.325.6264.146.4657.31
-2~+114.9250.7415.6254.5717.9458.2615.4558.5215.7350.85
-1~+0.56.8835.827.9938.958.9840.328.3143.077.2135.12
-0.5~+0.225.3528.946.0730.966.4531.346.7334.765.1727.91
-0.22~+0.159.8023.597.7124.898.4324.8911.7828.038.2122.74
-0.15~+0.0741.6813.793.3017.182.8616.462.1516.252.1014.53
-0.07412.1012.1013.8813.8813.6013.6014.1014.1012.4312.43
合计100.00—100.00—100.00—100.00—100.00—
), ArticleFig(id=1322164723697701184, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=CN, label=表4, caption=

不同入料含水率下的辊压产品的粒度分布

, figureFileSmall=null, figureFileBig=null, tableContent=
粒级/mm0.11%含水率1.5%含水率3%含水率4.5%含水率6%含水率
产率/%负累积/%产率/%负累积/%产率/%负累积/%产率/%负累积/%产率/%负累积/%
+615.30100.0015.39100.0011.43100.0012.33100.0016.38100.00
-6~+57.3284.704.9784.614.8288.575.0987.674.0983.62
-5~+320.6577.3819.4879.6419.4383.7518.4482.5822.2279.53
-3~+25.9956.735.5960.166.0664.325.6264.146.4657.31
-2~+114.9250.7415.6254.5717.9458.2615.4558.5215.7350.85
-1~+0.56.8835.827.9938.958.9840.328.3143.077.2135.12
-0.5~+0.225.3528.946.0730.966.4531.346.7334.765.1727.91
-0.22~+0.159.8023.597.7124.898.4324.8911.7828.038.2122.74
-0.15~+0.0741.6813.793.3017.182.8616.462.1516.252.1014.53
-0.07412.1012.1013.8813.8813.6013.6014.1014.1012.4312.43
合计100.00—100.00—100.00—100.00—100.00—
), ArticleFig(id=1322164723785781569, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=EN, label=Table 5, caption=

Regression results of R-R equation for rolled products under different moisture contents

, figureFileSmall=null, figureFileBig=null, tableContent=
含水率/%mb决定性系数R2
0.110.583 60.526 80.969 7
1.500.556 60.579 80.979 3
3.000.600 20.616 50.979 5
4.500.578 20.635 50.977 0
6.000.582 30.528 00.971 6
), ArticleFig(id=1322164723869667650, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164716156342490, language=CN, label=表5, caption=

不同含水率下的辊压产品R-R方程回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
含水率/%mb决定性系数R2
0.110.583 60.526 80.969 7
1.500.556 60.579 80.979 3
3.000.600 20.616 50.979 5
4.500.578 20.635 50.977 0
6.000.582 30.528 00.971 6
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Crushing ratio of rolled products under different moisture contents

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0.1117.185.412.83
1.5022.246.213.00
3.0023.196.863.21
4.5023.636.443.24
6.0018.005.412.84
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不同含水率下的辊压产品破碎比

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矿石含水率对高压辊磨机粉碎效果影响的仿真模拟研究
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刘三阳 1 , 张成龙 2 , 赵礼兵 1 , 来有邦 2 , 吴照永 3 , 张迪 1 , 栗明媚 1
矿业研究与开发 | 选矿与资源综合利用 2025,45(11): 277-284
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矿业研究与开发 |选矿与资源综合利用 2025 , 45 (11) : 277 -284
矿石含水率对高压辊磨机粉碎效果影响的仿真模拟研究
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刘三阳1 , 张成龙2, 赵礼兵1 , 来有邦2, 吴照永3, 张迪1, 栗明媚1
作者信息
  • 1.华北理工大学 矿业工程学院,河北 唐山市 063210
  • 2.河北钢铁集团矿山设计有限公司,河北 唐山市 063701
  • 3.昆明佩思矿业工程设计有限公司,云南 昆明 650032
通讯作者:
赵礼兵(1978—),男,河北廊坊人,教授,硕士生导师,主要从事矿产综合利用、选矿自动化方面的研究工作。E-mail:
作者简介:

刘三阳(1999—),男,山东临沂人,硕士研究生,研究方向为矿产综合利用。E-mail:

Simulation Study on the Influence of Ore Moisture Content on the Crushing Effect of High-Pressure Roller Grinding
Sanyang LIU1 , Chenglong ZHANG2, Libing ZHAO1 , Youbang LAI2, Zhaoyong WU3, Di ZHANG1, Mingmei LI1
Affiliations
  • 1.School of Mining Engineering, North China University of Science and Technology, Tangshan, Hebei 063210, China
  • 2.Hebei Iron and Steel Group Mining Design Co., Ltd., Tangshan, Hebei 063701, China
  • 3.Kunming Peisi Engineering Design Co., Ltd., Kunming, Yunnan 650032, China
出版时间: 2025-11-25
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优化高压辊磨机的粉碎效果对于提高矿石加工效率、降低能耗和提高产品质量具有重要意义。为探究矿石含水率对高压辊粉碎效果的影响,以冀东地区磁铁矿石为研究对象,采用颗粒表面能表征物料的含水率,结合SolidWorks建模和EDEM仿真,对不同入料含水率条件下高压辊与颗粒间的相互作用开展模拟研究。仿真结果表明,当颗粒表面能从0增加到25 J/m2时,颗粒在高压辊中的粉碎效果呈先增强后减弱的趋势,颗料表面能达到20 J/m2时粉碎效果最优。不同入料含水率条件下的高压辊开路试验结果表明,入料含水率由0.11%增大到6%时,高压辊粉碎效果不断优化后变差,与仿真结果规律一致;入料含水率在1.5%~4.5%范围时,高压辊磨机粉碎后的产品粒度更细,粉碎效果较好。

高压辊磨  /  磁铁矿  /  含水率  /  颗粒表面能  /  粉碎效果

The optimization of the crushing effect of high-pressure roller grinding is of crucial importance in relation to the enhancement of ore processing efficiency, the reduction of energy consumption, and the elevation of product quality. In order to investigate the influence of ore moisture content on the crushing effect of high-pressure rollers, with the magnetite ore from eastern Hebei selected as the research specimen, the interaction between high-pressure rollers and particles under different feed moisture content conditions was simulated by the combination with SolidWorks modeling and EDEM simulation. The simulation results indicate that, as the particle surface energy increases from 0 to 25 J/m2, the crushing effect in the high-pressure roller initially strengthens and then weakens, when the particle surface energy reaches 20 J/m2, the crushing effect is the best. Open-circuit test results under different feed moisture conditions show that as the feed moisture content rises from 0.11% to 6%, the crushing performance of the high-pressure roller first improves and then deteriorates, aligning with the simulation trends. When the feed moisture content is within the 1.5% to 4.5% range, the product particle size after crushing is finer, and the crushing effect is more favorable.

High-pressure roller grinding  /  Magnetite ore  /  Moisture content  /  Particle surface energy  /  Crushing effect
刘三阳, 张成龙, 赵礼兵, 来有邦, 吴照永, 张迪, 栗明媚. 矿石含水率对高压辊磨机粉碎效果影响的仿真模拟研究. 矿业研究与开发, 2025 , 45 (11) : 277 -284 .
Sanyang LIU, Chenglong ZHANG, Libing ZHAO, Youbang LAI, Zhaoyong WU, Di ZHANG, Mingmei LI. Simulation Study on the Influence of Ore Moisture Content on the Crushing Effect of High-Pressure Roller Grinding[J]. Mining Research and Development, 2025 , 45 (11) : 277 -284 .
对高压辊磨机进行离散元仿真可以模拟矿石破碎过程[1],探寻颗粒破碎行为并深入理解磨机内部颗粒流动、碰撞及受力情况,从而揭示颗粒破碎的微观机理,为优化设备设计、调整操作参数、提高粉碎效率和降低能耗提供指导。影响高压辊磨机粉碎效果的因素有很多,比如高压辊压力、转速、入料含水率等[2]。当前在高压辊入料含水率方面的理论研究仍不够完善。
仿真中颗粒的表面能可以作为表征物料含水率的参数,当物料含水率≤10%时,表面能随含水率的增大快速增大;当物料含水率>10%时,表面能随含水率增大而增大的趋势有所平缓[3]。基于此,通过仿真模拟不同含水率条件下颗粒的运动、碰撞和破碎过程,可以深入分析物料含水率变化对颗粒破碎特性的影响机制,为优化高压辊工作条件、提高破碎效率提供重要的理论指导。
因此,本文以冀东地区磁铁矿石为研究对象,通过SolidWorks软件建立高压辊和不同颗粒形状的三维仿真模型[4],在三维模型的基础上,通过改变Hertz-Mindlin with bonding接触模型的JKR表面能参数,可模拟矿物的含水率,结合EDEM中的Tavares破碎模型[5]进行一系列工况条件的仿真研究。最后,使用EDEM Post-Processor软件进一步分析不同工况下的高压辊粉碎特性,研究不同矿石含水率对高压辊粉碎效果的影响。研究结果对后续磨矿效果提升、能耗降低、设备保护和工艺优化等方面具有重要意义,同时也为相关工业领域的矿石粉碎和颗粒材料加工等提供参考。
为提高高压辊仿真的准确性和可信度,在进行仿真之前需要通过试验确定关键参数,如高压辊的辊间距、工作压力和转速等[6-7]。因此,结合后续工艺要求,对试验原料进行高压辊开路试验时,高压辊辊间距固定为6 mm,压力和转速分别选取实验室高压辊常用推荐参数,工作压力选择8~12 MPa,转速选择15~25 r/min。根据探索试验结果,选定工作压力为10 MPa,转速为20 r/min。
通过SolidWorks建立高压辊的三维仿真模型[8-10]如图1所示。在仿真模型中,高压辊参数按照实际试验高压辊进行设置,高压辊的直径为25 cm,宽度为10 cm,柱钉直径为8 mm,露出辊面的高度为3 mm。动辊施加压力为实际投影压力,工作压力10 MPa的投影压力为4 MPa。
对实际工况下的贫磁铁矿而言,贫磁铁矿颗粒形态并非球形。为更加符合实际工况条件,颗粒模型采用SolidWorks三维软件进行建模,将建立好的三维颗粒模型导入EDEM中进行填充。以球形颗粒的坐标和半径为基础进行设置,最终得到表面颗粒模型的形态[11]。试验中高压辊的入料粒度在20 mm以内,根据试验原料粒级分布对仿真中的颗粒大小进行了规划,共分为6种不同大小的颗粒。3种大尺寸颗粒模型见图2。
由图2可知,以最长边来定义,则大颗粒尺寸分别为18 mm、16 mm和13 mm。对于小尺寸颗粒,使用直径为1 mm、3 mm和6 mm的简化球形颗粒模型,这是由于小尺寸颗粒在实际工程中往往具有较为规则的形状,球形颗粒能够有效地近似描述这一特征,简化了建模过程,提高了仿真效率,同时保证了仿真模型的准确性[12-13]。通过在SolidWorks中进行几何建模,分别得到这3种小颗粒的三维模型,并将其导入到EDEM软件中。通过导入不同尺寸和形态的颗粒模型,并进行颗粒工厂的设置,最终得到的仿真效果更为真实和可靠[14]。
含水率较大的矿石颗粒与含水率较小的矿石颗粒存在明显差异,主要集中表现在颗粒的流动性和摩擦方面[15]。通过表面能表征颗粒间的黏结力大小,进而反映出颗粒物料间的流动特性。物料表面能的大小与颗粒间的黏结力呈正相关,与颗粒物料的流动性呈负相关[16]。
在仿真模型中使用的材料特性参数见表1。部分参数参照里约热内卢联邦大学Luís Marcelo Tavares教授关于中试规模高压辊磨机DEM仿真的标定结果[17-19]。颗粒的密度为3.639 g/cm3。泊松比、剪切模量、碰撞恢复系数相对统一,几何体的材料选择钢材,泊松比为0.3,杨氏模量为7×1010 Pa,密度为7.8 g/cm3,无需为颗粒工厂平面定义材料属性。
颗粒之间的摩擦特性是通过滚动摩擦因数和静摩擦因数来进行表征,模型中材料间的接触参数设置见表2。
为贴近实际情况,对颗粒模型进行参数设置,重力加速度的方向为Z轴负方向,加速度为9.81 m/s2。含水颗粒之间的接触模型为标准的Hertz-Mindlin with JKR,颗粒与几何体之间的接触模型选用Hertz-Mindlin(no slip)。
EDEM软件仿真过程中,颗粒由方形颗粒工厂生成,所设置的颗粒中70%为大尺寸颗粒,设置的仿真时间主要包括仿真起始时间、总仿真时间和瑞丽时间步。网格尺寸的大小依据仿真中所设置的最小颗粒半径来进行设置,一般为最小颗粒半径的3倍。结合实际工况,本次高压辊粉碎颗粒仿真所设置的瑞丽时间步长为20%,总仿真时长为10 s,网格半径为3R,网格划分为21 557个。
使用EDEM Post-Processor软件进行后处理操作,导出速度云图、能量云图和颗粒占比统计等结果,并根据仿真结果分析不同含水率条件下矿石颗粒经高压辊粉碎的过程、特性和效果。
不同颗粒表面能条件下颗粒的平均速度曲线和颗粒速度云图分别如图3和图4所示。
由图3可知,随着颗粒表面能由0增大到15 J/m2,颗粒的平均速度增大。这是因为当表面能增大时,颗粒表面更容易吸附其他颗粒或者吸引其他颗粒靠近,颗粒之间的吸引力增加,导致颗粒更紧密地结合或聚集。此条件下,大颗粒受高压辊压力的作用,更容易破碎,破碎后产生的小颗粒之间的碰撞频率增加,促进了颗粒平均速度增大。当颗粒表面能由20 J/m2持续增大后,颗粒的平均速度下降。其原因为:增大的表面能增强了颗粒之间的吸引力,但同时也增加了颗粒之间的抵抗力,颗粒之间更加紧密地结合或聚集,增加了摩擦阻力,阻碍了颗粒的运动和能量转移,大颗粒难以完全破碎,使得颗粒的整体速度下降。
由图4可知,速度较小的多为大颗粒,小颗粒多为红色(颜色标识见电子版),速度较快。相同时间下不同表面能颗粒被破碎后,粒径的分布大小并不统一,尤其是在表面能为15~20 J/m2的工况下,颗粒的分布更均匀,且小颗粒相对较多。与图3中颗粒平均速度随不同表面能的变化规律一致,随表面能的增加,颗粒的速度先增加再趋于平稳,最后再下降。其中,表面能为15~20 J/m2时,颗粒间的黏结力达到了临界状态。对于初始时刻的大颗粒,表面能小或者为0的工况下,大颗粒在与高压辊的接触过程中,其速度较小,其动能也小,颗粒内部的破碎临界条件难以满足;而小颗粒在表面能的影响下,其破碎的临界条件更容易满足,且其速度较大,在相同表面能下,大颗粒破碎需要更多的时间。而表面能在15~20 J/m2区间时,表面能对大粒径颗粒的影响更强,大粒径颗粒的破碎速度更快,在相同时间下,大颗粒更容易破碎,破碎成小颗粒后整体速度增加。
综上所述,在不同表面能的影响下,颗粒破碎会存在一定的累积效应,表面能适量增大,在一定程度上提高颗粒的速度,尤其是颗粒与高压辊反复的接触过程中,速度会逐渐提高,进而发生破碎。由不同表面能的速度变化曲线可知,表面能对速度的影响存在一个边界,超过这个范围时,其颗粒的速度呈下降趋势。
不同颗粒表面能条件下颗粒的平均能量如图5所示,不同颗粒表面能条件下的颗粒能量云图如图6所示。
由图5可知,当颗粒的表面能从0增大到25 J/m2时,颗粒的平均能量出现先增大后减小的趋势,这与颗粒平均速度变化规律一致。表面能对颗粒能量的影响也存在一个阈值,如果超过了阈值范围,颗粒的动能会呈现迅速下降的趋势。
结合图6可知,当颗粒的表面能从0增加到20 J/m2时,颗粒的能量增大,而当表面能继续增加后,能量大幅度减小。因此,颗粒表面能为20 J/m2时,颗粒的能量最大,高压辊施加在颗粒上的压力作用最明显,能量转移更完全。这与颗粒速度变化规律一致,表明大部分能量来自大颗粒受力破碎时产生的动能。
分别对5组仿真结束后的产品粒径分布进行数据提取,得到高压辊粉碎后的直径为-0.24 mm、-1.93 mm及-5.39 mm的3种粒级占比曲线,结果见图7。由图7可知,随着颗粒表面能的增加,矿物颗粒占比增加,颗粒尺寸为-0.21 mm、-1.93 mm、-5.39 mm的颗粒数量占比均呈先缓慢增加后下降的趋势,高压辊破碎后-5.39 mm粒级范围在80%左右。随着表面能从0增加到20 J/m2,-0.24 mm颗粒的占比逐渐增加,但增加的幅度是先上升后下降。表面能从0增加到15 J/m2时,-0.24 mm颗粒占比由37.26%增加到45.73%,增加了8.47个百分点,表面能从15 J/m2增加到20 J/m2时,-0.24 mm颗粒占比由45.73%增加到56.44%,增加了10.71个百分点。-5.39 mm和-1.93 mm粒级颗粒在表面能从0增加到15 J/m2阶段均为平缓增加,表面能从15 J/m2增加到20 J/m2阶段无明显变化。当表面能从20 J/m2增加到25 J/m2时,3种小颗粒累积含量占比均呈大幅下降。
EDEM仿真结果表明,随着表面能从0增加到20 J/m2,高压辊粉碎效果不断变化。这主要是因为增大的表面能会加强颗粒之间的吸附力和黏结力,使颗粒更容易形成团块或团聚体,增加了颗粒受到外部应力时的破碎概率。当颗粒表面能从20 J/m2持续增大后,在颗粒之间的黏结力过强、颗粒的表面过硬以及颗粒之间的连接方式过于紧密等因素的共同作用下,形成团块或团聚体,使得颗粒更难被分离和破碎,整体结构更加坚固,从而出现颗粒难破碎的情况。因此,表面能在20 J/m2左右存在一个阈值,一旦超越此表面能阈值,颗粒破碎效果将会下降。
试验矿样为冀东地区的磁铁矿石,实验室来料粒度约50 mm以下,取样后过20 mm筛网筛分,筛上矿样使用颚式破碎机破碎至20 mm以下,然后和筛下混匀,再利用割环法对试样进行缩分,制备高压辊粉碎试验原料,试验原料筛析结果见表3。
由筛析数据可知,高压辊试验原料中-1 mm和-6 mm粒级颗粒的累积含量分别为10.86%和24.71%,高压辊入料中含有75.29%的大颗粒需破碎,已含有的合格粒级占比较少。
通过在0.11%含水率物料中添加水分实现对入料含水率的调整,对试验原料进行高压辊压力为10 MPa,转速为20 r/min,入料含水率分别为0.11%、1.5%、3%、4.5%和6%的高压辊开路试验,粒度筛分结果见表4,各粒级颗粒累积含量见图8。
由表4可知,随着高压辊入料含水率增加,辊压后的产品粒度分布发生明显变化。入料含水率从0.11%增大到6%时,+6 mm粒级范围辊压产品的产率从15.30%降低到11.43%后又迅速增大到16.38%,其中入料含水率为3%时产率最低。由-0.074 mm细粒级颗粒产率数据得知,入料含水率的增加同样对高压辊粉碎物料过程中细粒级颗粒的产生有影响。入料含水率为4.5%时,高压辊-0.074 mm细粒级的颗粒产率最高。
由图8可知,随着入料含水率的增加,-6 mm粒级颗粒累积含量呈先增加后减小的趋势。4.5%含水率条件下辊压产品的各粒级颗粒累积含量明显高于0.11%、1.5%和6%含水率条件下的累积含量,且在-6~+2 mm粒级累积条件下略高于3%含水率条件,表明3%和4.5%含水率条件下高压辊粉碎效果较好,4.5%含水率条件下高压辊粉碎产生的细粒级产品较多。
采用罗辛拉姆勒(Rosin-Rammler,R-R)粒度特性方程式对不同入料含水率条件下的辊压产品进行粒度特性分析,R-R粒度方程如式(1)所示,回归拟合结果见表5。
式中:C为粒度大于x的正累计产率,%;x为颗粒直径或筛孔宽,mm;b为与产物颗粒相关的参数,b越大,产物粒度越细;m为均匀性系数,表示粒度分布范围的宽窄程度,m越大,粒度分布越集中,标准偏差越小。
从表5可以看出,矿石含水率为3%时,辊压产品均匀性系数m较大,粒度分布更为集中,标准差较小。参数b随矿石含水率的增加先增大后减小,高压辊粉碎产品有先变细后增粗的趋势,其中矿石含水率4.5%时b值最大,此条件下高压辊粉碎产品粒度最细。含水率为3%时,b值与最高值的差距最小,高压辊粉碎产品粒度分布更集中于偏细粒级。
破碎比(FX/PX)为给料中X%通过的粒度与产品中X%通过粒度的比值,由R-R公式推导得出FX和PX计算公式:
经计算得到的辊压产品破碎比结果见表6。由表6可知,矿石含水率由0.11%增加到1.5%时,破碎比F20/P20由17.18增大至22.24,增幅约30%,细颗粒产品明显增多。矿石含水率在1.5%~4.5%时,各破碎比指标趋于稳定(F20/P20约23,F50/P50约6.5,F80/P80约3.2)。矿石含水率由4.5%增加至6%时,破碎比F20/P20由23.63降至18,降幅为23.83%,细颗粒产品明显减少;破碎比F50/P50和F80/P80分别下降了15.99%和12.35%,表明高压辊粉碎产品整体粒度变粗,粉碎效果变差。
综上所述,入料含水率在1.5%~4.5%范围时,高压辊粉碎过程较为稳定,细粒级产品占比较高,整体粉碎效果优于入料含水率为0.11%(低水分)和6%(高水分)条件。结合实际的粒度分布可确定,该类矿物在高压辊粉碎过程中的较优入料含水率范围为1.5%~4.5%。
本文以冀东地区磁铁矿石为研究对象,通过设置颗粒表面能表征物料的含水率,结合SolidWorks建模和EDEM仿真,开展了不同入料含水率条件下高压辊与颗粒间的相互作用的模拟研究,并进行了不同入料含水率条件下的高压辊开路试验,得出如下主要结论。
(1)仿真结果表明,当颗粒表面能从0增加到25 J/m2时,颗粒的平均速度、平均能量和破碎出小颗粒的占比都呈现比增加后降低的趋势,颗粒在高压辊中的粉碎效果先增强后减弱,在表面能为20 J/m2时达到最优。这表明颗粒的表面能存在某个阈值,一旦超越该阈值,高压辊粉碎效果将会下降。矿石含水率同样存在一个较优值范围。
(2)不同入料含水率条件下高压辊开路试验结果与仿真结果基本一致。入料含水率为3%和4.5%时,高压辊磨机的粉碎效果均优于其他含水率条件下的粉碎效果。入料含水率超过4.5%后,各项参数大幅减小,辊压产品中细粒级产品减少,高压辊粉碎效果变差。该试验所用高压辊磨机粉碎冀东地区磁铁矿石的较优入料含水率为1.5%~4.5%。
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2025年第45卷第11期
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  • 接收时间:2024-11-16
  • 首发时间:2026-10-28
  • 出版时间:2025-11-25
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  • 收稿日期:2024-11-16
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河钢集团有限公司重点科技项目(HG2022137)
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    1.华北理工大学 矿业工程学院,河北 唐山市 063210
    2.河北钢铁集团矿山设计有限公司,河北 唐山市 063701
    3.昆明佩思矿业工程设计有限公司,云南 昆明 650032

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赵礼兵(1978—),男,河北廊坊人,教授,硕士生导师,主要从事矿产综合利用、选矿自动化方面的研究工作。E-mail:
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
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