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Article(id=1322594599101645694, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322594503278580030, 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=1708617600000, receivedDateStr=2024-02-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793260725044, onlineDateStr=2026-10-29, pubDate=1737734400000, pubDateStr=2025-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793260725044, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793260725044, creator=13701087609, updateTime=1793260725044, updator=13701087609, issue=Issue{id=1322594503278580030, tenantId=1146029695717560320, journalId=1225396423026438145, year='2025', volume='45', issue='1', pageStart='1', pageEnd='276', issueExtLink='null', onlineDate='null', pubDate='1737734400000', pubDateStr='2025-01-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793260702199, creator='13701087609', updateTime=1793260702199, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=85, endPage=94, ext={EN=ArticleExt(id=1322594601152660354, articleId=1322594599101645694, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=Numerical Simulation Study on Pipeline Transportation State of Tailings Slurry in a Tin Mine in Yunnan Based on ANSYS-FLUENT, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=

In the process of pipeline transportation of tailings slurry from beneficiation plant to filling preparation station, changing the feed parameters will change the spatial distribution of tailings solid particles in the pipeline, which will affect the safety and stability of slurry pipeline transportation. Taking the sulfide ore tailings transported by pipeline from a tin ore beneficiation plant in Yunnan to filling preparation station as the research object, the rheological parameters of the tailings slurry were obtained by rheological test. The ANSYS-FLUENT numerical simulation software was used to simulate and analyze the pipeline transportation of the tailings slurry. The relationship between the relative height of the bottom bed layer and the feed parameters was fitted, and a three-dimensional relationship model between the relative height of the bottom bed layer and the feed speed and volume concentration was established. The results show that the three-dimensional relationship model between the relative height of the bottom bed layer and the feed speed and volume concentration has a good fitting effect. Most of the coarse particles with a size of +120 mesh have sedimentation in the bottom bed layer. Some of the fine particles with 120−200 mesh have sedimentation at the bottom bed layer of the pipeline when the feed speed is 1 m/s, and distributed in the carrier layer when the feed speed is above 2 m/s. More fine particles of －200 mesh are distributed in the carrier layer. There is water in the boundary layer of the top wall of the pipeline and the slurry formed by some very fine particles and water, which together form the boundary layer. The change of volume concentration of tailings slurry along the radial direction can be divided into four regions. There is a gradient decreasing effect from the bottom wall of the pipeline to the carrier-bottom bed interface, it gradually increases to stability from the carrier-bottom bed interface to the stable radial volume concentration of the slurry. It remains stable after reaching the maximum value in the stable constant region of radial volume concentration, the radial volume concentration gradually decreases from the stable point to the top wall of the pipe.

, authors=Baidong LIANI, Dengpan QIAOI, Tianyu YANGI, Jun WANGI, Yongming LII, Cong ZHENGI, Bo GAOI, Gan LONGI, authorsList=Baidong LIAN, Dengpan QIAO, Tianyu YANG, Jun WANG, Yongming LI, Cong ZHENG, Bo GAO, Gan LONG, authorCompany=null, correspAuthors=Dengpan QIAO, 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=1322594603769906083, articleId=1322594599101645694, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=基于ANSYS-FLUENT 的云南某锡矿尾砂料浆管输状态数值模拟研究, columnId=1226462294490657775, journalTitle=矿业研究与开发, columnName=采矿与矿山充填, runingTitle=null, highlight=null, articleAbstract=

尾砂料浆从选矿厂向充填制备站的管输过程中，改变进料参数会使管道内的尾砂固体颗粒空间分布发生变化，进而影响料浆管输的安全性与稳定性。以云南某锡矿选矿厂向充填制备站进行管道输送的硫化矿尾砂为研究对象，通过流变试验获得尾砂料浆的流变参数，采用ANSYS-FLUENT数值模拟软件对尾矿料浆管输进行模拟计算与结果分析，并对底床层相对高度与进料参数的关系进行拟合，建立了底床层相对高度与进料速度及体积浓度的三维关系模型。结果表明：底床层相对高度与进料速度及体积浓度的三维关系模型拟合效果良好；大部分+120目的较粗颗粒在底床层中有沉淤现象，120~200目之间的细颗粒在进料速度为1 m/s时，部分在管道底部有沉淤现象，在进料速度为2 m/s以上时分布于载体层中，－200目的更细颗粒均分布于载体层中；管道顶壁边界层中存在水以及部分极细颗粒与水形成的稀浆，共同形成边界层；尾砂料浆沿径向的体积浓度变化可分为4个区域，在管道底壁至载体–底床分界面处存在梯度递减效应，在载体–底床分界面至料浆径向体积浓度稳定不变处逐渐升高至稳定，在径向体积浓度稳定不变区达到最大值后保持稳定，径向体积浓度稳定不变处至管道顶壁处逐渐降低。

, authors=廉柏栋I, 乔登攀I, 杨天雨I, 王俊I, 李勇明I, 郑聪I, 高博I, 龙赣I, authorsList=廉柏栋, 乔登攀, 杨天雨, 王俊, 李勇明, 郑聪, 高博, 龙赣, authorCompany=null, correspAuthors=乔登攀, authorNote=

廉柏栋（1995—），男，河南洛阳人，硕士研究生，主要从事现代采矿理论与技术研究。E-mail:

, correspAuthorsNote=
乔登攀（1969—），男，甘肃白银人，博士，教授，博士生导师，主要从事现代采矿工艺及理论研究。E-mail:
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廉柏栋（1995—），男，河南洛阳人，硕士研究生，主要从事现代采矿理论与技术研究。E-mail:

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廉柏栋（1995—），男，河南洛阳人，硕士研究生，主要从事现代采矿理论与技术研究。E-mail:

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Nonferrous Metals Engineering, 2022, 12(8):139-148., articleTitle=Flocculation and sedimentation characteristics of ultra-fine full tailing sand in dynamic shear environment, refAbstract=null)], funds=[Fund(id=1322594611810386926, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, awardId=202301AU070185; 202101AU070022, language=CN, fundingSource=云南省基础研究专项青年项目(202301AU070185; 202101AU070022), fundOrder=null, country=null), Fund(id=1322594611898467311, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, awardId=KKZ3202021040, language=CN, fundingSource=昆明理工大学人培基金项目(KKZ3202021040), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322594604008981412, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, xref=null, ext=[AuthorCompanyExt(id=1322594604021564325, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, companyId=1322594604008981412, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Faculty of land and Resources Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650093, China), AuthorCompanyExt(id=1322594604029952934, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, companyId=1322594604008981412, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=昆明理工大学 国土资源工程学院，云南　昆明　650093)])], figs=[ArticleFig(id=1322594608475915226, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Fig.1, caption=Pipeline model grid, figureFileSmall=d1Dp+2im5j+aDLcaIiTd/g==, figureFileBig=3KS7XHXBxGnBniwWNQz6sQ==, tableContent=null), ArticleFig(id=1322594610069750747, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=图1, caption=管道模型网格, figureFileSmall=d1Dp+2im5j+aDLcaIiTd/g==, figureFileBig=3KS7XHXBxGnBniwWNQz6sQ==, tableContent=null), ArticleFig(id=1322594610313020380, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Fig.2, caption=Cloud maps of water phase volume fraction of tailings slurry at various feed speeds when the feed volume concentration is 12.17%, figureFileSmall=YdBUU2FT8018owUjSsnN0w==, figureFileBig=Wc+ZOwoC9l+J6piuqDF8SA==, tableContent=null), ArticleFig(id=1322594610375934941, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=图2, caption=进料体积浓度为12.17%时各进料速度下的尾砂料浆水相体积分数云图, figureFileSmall=YdBUU2FT8018owUjSsnN0w==, figureFileBig=Wc+ZOwoC9l+J6piuqDF8SA==, tableContent=null), ArticleFig(id=1322594610451432414, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Fig.3, caption=The relationship between the relative height of the bottom layer and the feed speed, figureFileSmall=oKnYwTllsr32tI6k3kr9AA==, figureFileBig=HAOCuO0Gys90Hz/pGj0+Kg==, tableContent=null), ArticleFig(id=1322594610531124191, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=图3, caption=底床层相对高度与进料速度的关系, figureFileSmall=oKnYwTllsr32tI6k3kr9AA==, figureFileBig=HAOCuO0Gys90Hz/pGj0+Kg==, tableContent=null), ArticleFig(id=1322594610615010272, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Fig.4, caption=The relationship between the relative height of the bottom layer and the feed volume concentration, figureFileSmall=NHn7d7uF2eCTREsBCMmAbA==, figureFileBig=l+yXyOtjvbcItEHFobInIA==, tableContent=null), ArticleFig(id=1322594610694702049, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=图4, caption=底床层相对高度与进料体积浓度的关系, figureFileSmall=NHn7d7uF2eCTREsBCMmAbA==, figureFileBig=l+yXyOtjvbcItEHFobInIA==, tableContent=null), ArticleFig(id=1322594610770199522, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Fig.5, caption=The three-dimensional relationship between the relative height of the bottom layer and the feed speed and volume concentration, figureFileSmall=mrHdxjmws85eOhcUi1QyJQ==, figureFileBig=PEA2Q6tbHNXRJn+ZROcugg==, tableContent=null), ArticleFig(id=1322594610833114083, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=图5, caption=底床层相对高度与进料速度及体积浓度的三维关系, figureFileSmall=mrHdxjmws85eOhcUi1QyJQ==, figureFileBig=PEA2Q6tbHNXRJn+ZROcugg==, tableContent=null), ArticleFig(id=1322594610912805860, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Fig.6, caption=The relationship between radial volume concentration and relative height of particles at each levels, figureFileSmall=X6nk9iJUCaqyrCpaRX3jmQ==, figureFileBig=e6exNDQbDfvOHxlvFv332Q==, tableContent=null), ArticleFig(id=1322594610971526117, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=图6, caption=各级颗粒径向体积浓度与相对高度的关系, figureFileSmall=X6nk9iJUCaqyrCpaRX3jmQ==, figureFileBig=e6exNDQbDfvOHxlvFv332Q==, tableContent=null), ArticleFig(id=1322594611034440678, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Fig.7, caption=The relationship between radial volume concentration and relative height of tailings slurry under different mass concentrations, figureFileSmall=Qb8B2SKbB/OdH66bMD4VWQ==, figureFileBig=bWRJEndayqTXqNswt8s9Jw==, tableContent=null), ArticleFig(id=1322594611105743847, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=图7, caption=各质量浓度下尾砂料浆径向体积浓度与相对高度的关系, figureFileSmall=Qb8B2SKbB/OdH66bMD4VWQ==, figureFileBig=bWRJEndayqTXqNswt8s9Jw==, tableContent=null), ArticleFig(id=1322594611168658408, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Table 1, caption=

Numerical simulation scheme and parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
方案编号进料质量浓度/%进料体积浓度/%进料速度/(m·s－1)塑性黏度/(Pa·s)屈服应力/Pa
A1~A5103.471,2,3,4,50.006 770.077 82
B1~B5207.481,2,3,4,50.010 970.179 66
C1~C53012.171,2,3,4,50.014 430.297 17
D1~D54017.731,2,3,4,50.017 930.325 45
E1~E55024.431,2,3,4,50.023 470.737 24
), ArticleFig(id=1322594611235767273, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=表1, caption=

数值模拟方案及参数

, figureFileSmall=null, figureFileBig=null, tableContent=
方案编号进料质量浓度/%进料体积浓度/%进料速度/(m·s－1)塑性黏度/(Pa·s)屈服应力/Pa
A1~A5103.471,2,3,4,50.006 770.077 82
B1~B5207.481,2,3,4,50.010 970.179 66
C1~C53012.171,2,3,4,50.014 430.297 17
D1~D54017.731,2,3,4,50.017 930.325 45
E1~E55024.431,2,3,4,50.023 470.737 24
), ArticleFig(id=1322594611307070442, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Table 2, caption=

Regression equation for the relationship between the relative height of the bottom layer and the feed speed

, figureFileSmall=null, figureFileBig=null, tableContent=
进料质量浓度/%底床层相对高度h/D与进料速度u关系的回归方程R2
10h/D=0.156 66exp(－0.48881u)0.992 43
20h/D=0.306 57exp(－0.45772u)0.989 08
30h/D=0.395 51exp(－0.39352u)0.985 08
40h/D=0.496 05exp(－0.34407u)0.997 45
50h/D=0.639 00exp(－0.32657u)0.998 04
), ArticleFig(id=1322594611374179307, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=表2, caption=

底床层相对高度与进料速度关系的回归方程

, figureFileSmall=null, figureFileBig=null, tableContent=
进料质量浓度/%底床层相对高度h/D与进料速度u关系的回归方程R2
10h/D=0.156 66exp(－0.48881u)0.992 43
20h/D=0.306 57exp(－0.45772u)0.989 08
30h/D=0.395 51exp(－0.39352u)0.985 08
40h/D=0.496 05exp(－0.34407u)0.997 45
50h/D=0.639 00exp(－0.32657u)0.998 04
), ArticleFig(id=1322594611625837548, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=EN, label=Table 3, caption=

Regression equation for the relationship between the relative height of the bottom layer and the feed volume concentration

, figureFileSmall=null, figureFileBig=null, tableContent=
进料速度/(m/s)底床层相对高度h/D与进料体积浓度CV关系的回归方程R2
1h/D=1.957 67CV0.982 06
2h/D=1.508 50CV0.953 77
3h/D=1.165 67CV0.968 96
4h/D=0.793 85CV0.991 17
5h/D=0.423 73CV0.959 43
), ArticleFig(id=1322594611688752109, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594599101645694, language=CN, label=表3, caption=

底床层相对高度与进料体积浓度关系的回归方程

, figureFileSmall=null, figureFileBig=null, tableContent=
进料速度/(m/s)底床层相对高度h/D与进料体积浓度CV关系的回归方程R2
1h/D=1.957 67CV0.982 06
2h/D=1.508 50CV0.953 77
3h/D=1.165 67CV0.968 96
4h/D=0.793 85CV0.991 17
5h/D=0.423 73CV0.959 43
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基于ANSYS-FLUENT 的云南某锡矿尾砂料浆管输状态数值模拟研究
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廉柏栋 I , 乔登攀 I , 杨天雨 I , 王俊 I , 李勇明 I , 郑聪 I , 高博 I , 龙赣 I
矿业研究与开发 | 采矿与矿山充填 2025,45(1): 85-94
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矿业研究与开发 |采矿与矿山充填 2025 , 45 (1) : 85 -94
基于ANSYS-FLUENT 的云南某锡矿尾砂料浆管输状态数值模拟研究
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廉柏栋I , 乔登攀I , 杨天雨I, 王俊I, 李勇明I, 郑聪I, 高博I, 龙赣I
作者信息
  • 昆明理工大学 国土资源工程学院，云南　昆明　650093
通讯作者:
乔登攀（1969—），男，甘肃白银人，博士，教授，博士生导师，主要从事现代采矿工艺及理论研究。E-mail:
作者简介:

廉柏栋（1995—），男，河南洛阳人，硕士研究生，主要从事现代采矿理论与技术研究。E-mail:

Numerical Simulation Study on Pipeline Transportation State of Tailings Slurry in a Tin Mine in Yunnan Based on ANSYS-FLUENT
Baidong LIANI , Dengpan QIAOI , Tianyu YANGI, Jun WANGI, Yongming LII, Cong ZHENGI, Bo GAOI, Gan LONGI
Affiliations
  • Faculty of land and Resources Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650093, China
出版时间: 2025-01-25
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摘要
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尾砂料浆从选矿厂向充填制备站的管输过程中，改变进料参数会使管道内的尾砂固体颗粒空间分布发生变化，进而影响料浆管输的安全性与稳定性。以云南某锡矿选矿厂向充填制备站进行管道输送的硫化矿尾砂为研究对象，通过流变试验获得尾砂料浆的流变参数，采用ANSYS-FLUENT数值模拟软件对尾矿料浆管输进行模拟计算与结果分析，并对底床层相对高度与进料参数的关系进行拟合，建立了底床层相对高度与进料速度及体积浓度的三维关系模型。结果表明：底床层相对高度与进料速度及体积浓度的三维关系模型拟合效果良好；大部分+120目的较粗颗粒在底床层中有沉淤现象，120~200目之间的细颗粒在进料速度为1 m/s时，部分在管道底部有沉淤现象，在进料速度为2 m/s以上时分布于载体层中，－200目的更细颗粒均分布于载体层中；管道顶壁边界层中存在水以及部分极细颗粒与水形成的稀浆，共同形成边界层；尾砂料浆沿径向的体积浓度变化可分为4个区域，在管道底壁至载体–底床分界面处存在梯度递减效应，在载体–底床分界面至料浆径向体积浓度稳定不变处逐渐升高至稳定，在径向体积浓度稳定不变区达到最大值后保持稳定，径向体积浓度稳定不变处至管道顶壁处逐渐降低。

尾砂料浆  /  管道输送  /  底床层  /  载体层  /  数值模拟

In the process of pipeline transportation of tailings slurry from beneficiation plant to filling preparation station, changing the feed parameters will change the spatial distribution of tailings solid particles in the pipeline, which will affect the safety and stability of slurry pipeline transportation. Taking the sulfide ore tailings transported by pipeline from a tin ore beneficiation plant in Yunnan to filling preparation station as the research object, the rheological parameters of the tailings slurry were obtained by rheological test. The ANSYS-FLUENT numerical simulation software was used to simulate and analyze the pipeline transportation of the tailings slurry. The relationship between the relative height of the bottom bed layer and the feed parameters was fitted, and a three-dimensional relationship model between the relative height of the bottom bed layer and the feed speed and volume concentration was established. The results show that the three-dimensional relationship model between the relative height of the bottom bed layer and the feed speed and volume concentration has a good fitting effect. Most of the coarse particles with a size of +120 mesh have sedimentation in the bottom bed layer. Some of the fine particles with 120−200 mesh have sedimentation at the bottom bed layer of the pipeline when the feed speed is 1 m/s, and distributed in the carrier layer when the feed speed is above 2 m/s. More fine particles of －200 mesh are distributed in the carrier layer. There is water in the boundary layer of the top wall of the pipeline and the slurry formed by some very fine particles and water, which together form the boundary layer. The change of volume concentration of tailings slurry along the radial direction can be divided into four regions. There is a gradient decreasing effect from the bottom wall of the pipeline to the carrier-bottom bed interface, it gradually increases to stability from the carrier-bottom bed interface to the stable radial volume concentration of the slurry. It remains stable after reaching the maximum value in the stable constant region of radial volume concentration, the radial volume concentration gradually decreases from the stable point to the top wall of the pipe.

Tailings slurry  /  Pipeline transportation  /  Bottom bed layer  /  Carrier layer  /  Numerical simulation
廉柏栋, 乔登攀, 杨天雨, 王俊, 李勇明, 郑聪, 高博, 龙赣. 基于ANSYS-FLUENT 的云南某锡矿尾砂料浆管输状态数值模拟研究. 矿业研究与开发, 2025 , 45 (1) : 85 -94 .
Baidong LIAN, Dengpan QIAO, Tianyu YANG, Jun WANG, Yongming LI, Cong ZHENG, Bo GAO, Gan LONG. Numerical Simulation Study on Pipeline Transportation State of Tailings Slurry in a Tin Mine in Yunnan Based on ANSYS-FLUENT[J]. Mining Research and Development, 2025 , 45 (1) : 85 -94 .
正文
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0　引言
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尾砂料浆是由选矿厂产生的尾砂固体颗粒与水形成的固-液两相混合物，尾砂料浆管道输送是地下采空区顺利进行充填作业的重要环节[1-2]。为确保安全稳定地料浆管输，需要合理设置尾砂料浆的进料参数，使管输阻力损失与成本最小化。目前，对尾砂料浆管道输送的研究主要采用理论计算[3-4]、数值模拟[5-6]和室内环形管道模拟试验[7-11]等方法。其中，理论计算较为繁琐复杂，室内环形管道模拟试验成本高、误差大，数值模拟方法因其建模和参数设置的便利性、准确性以及可视化的特点受到广泛青睐。针对固-液两相混合物管道输送研究，常用的数值模拟软件有ANSYS-FLUENT、EDEM和PFC等，通过在软件中设定尾砂固体颗粒物理参数以及料浆的流变参数等，设置不同进料速度与浓度条件，模拟尾砂料浆的管道输送，深入了解尾砂颗粒在不同进料参数下的分布规律。郝宇鑫等[12]利用CRT流变仪对充填料浆进行了流变参数测试，运用流体力学及粒状物料水力学等方法分析了矸石颗粒在似膏体料浆中的受力情况，结合FLUENT软件进行数值模拟，发现矸石颗粒的粒径和浓度均对管输临界流速产生影响。刘振等[13]通过流变试验和环管试验研究了三山岛金矿高浓度充填料浆的流动特性和管输阻力，认为随着料浆质量浓度的增加，料浆屈服应力、塑性黏度和流动阻力显著增大，导致输送倍线减小，当灰砂比为1:4、料浆质量浓度为76%、流速约为1.5 m/s时，管道压力损失最大。侯永强等[14]通过尾矿膏体流变试验和坍落度试验，发现料浆的屈服应力和塑性黏度均与浓度成正相关，屈服应力与料浆浓度的关系为二次函数递增曲线，塑性黏度与料浆浓度的关系为指数函数曲线，并建立了基于料浆浓度的管道输送阻力计算模型。杨天雨等[15]基于数值模拟方法研究了废石-风砂的高浓度充填料浆进行自流输送的管道输送特性，发现充填料浆沿管径方向有明显的速度梯度，料浆质量浓度对管输阻力的影响非常大。刘志双等[16]认为充填管道内料浆的流态影响了管输阻力特性，采用SWAMEE修正方法得出过渡流速与实测回归值的相对误差较小，仅为0.9%~6.4%。
以上学者采用了理论计算、数值模拟和环管试验等方法研究了尾砂料浆管道输送的状态和规律。然而，这些研究多采用不同物料组成的混合充填料浆，在高浓度下接近均质流体，并呈现出结构流的特性。在实际生产中，选矿厂向充填制备站输送的尾砂料浆为尾砂固体颗粒与水形成的固-液两相混合物，在不同的进料速度和浓度条件下呈现出均质流体、非均质流体或两种特征兼具的流态。在20世纪下叶，一些国外研究人员提出，固-液两相混合料浆在管道输送中可分为液相载体层和固相底床层，这两部分具有不同的运动状态和阻力计算方法。目前对于尾砂料浆管输过程中载体层和底床层的深入研究较少，费祥俊等[17]于2015年提出了一种判别矿浆稳定性的标准，即当管道内矿浆非均匀指数小于0.01时，矿浆近似于均质流；管道内煤浆非均匀指数小于0.034时，煤浆近似于非均质流。此外，针对细颗粒含量较高的尾砂料浆管输情况的研究也十分匮乏。
本文基于数值模拟方法，利用ANSYS-FLUENT软件进行了管输过程的模拟计算，对模拟结果及相关影响因素进行了深入分析，最终得出了云南某锡矿尾砂料浆管输状态及尾砂颗粒在管道中的分布规律，并建立了底床层相对高度与进料速度及体积浓度之间的关系模型。研究结果对尾砂料浆管道输送的理论和实践具有一定的指导意义，对于充填骨料中细颗粒含量较高的充填矿山具有推广应用的价值。
1　流变试验
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1.1　试验材料
流变试验材料采用云南某锡矿选矿厂排放的硫化矿尾砂。尾砂的颗粒密度为3 093 kg/m3，松散密度为1 335 kg/m3，堆积密实度为43.2%，孔隙率为56.8%。尾砂的颗粒级配共分为 <25 μm、25~38.5 μm、38.5~50 μm、50~75 μm、75~125 μm、125~250 μm、>250 μm 共7个粒级，各粒级对应占比分别为44.56%、8.18%、3.83%、11.22%、8.23%、16.57%，7.41%。可以看出，500目以下的尾砂占比高达44.56%，接近超细尾砂范畴（小于20 μm)，超细尾砂的自然沉降速度缓慢[18]。经化学成分的测定，硫化矿尾砂中的活性物质含量均较少，因此，尾砂料浆在管道输送过程中受化学特性的影响较小。
1.2　试验方法
流变试验采用了RheoCAD500型混凝土流变仪进行硫化矿尾砂料浆流变参数的测定。试验采用直接法，并选用专家方案和1#双螺旋转子进行剪切应力、剪切速率等流变参数的测定，采用斜坡加载方式，加载程序设置转速从20 r/min逐渐增加至200 r/min，加载时间为250 s，每隔1 s记录一个数据点，每5个数据点取平均值，共得到50个转速点的数据。
2　数值模拟基本原理
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使用ANSYS-FLUENT软件进行尾砂料浆管道输送数值模拟时，考虑到实际料浆特性与数值模拟中的固-液两相混合物模型的关系，需要做出一系列基本假设，包括流体质点、连续介质、不可压缩流体、固体颗粒球体和恒温等。ANSYS-FLUENT基于有限体积法，相比于有限单元法与有限差分法，具有控制方程对任意控制体积均遵循质量、动量和能量守恒定律的优点，适用于尾砂料浆流态的模拟。根据管道中尾砂颗粒的粒径与分布的复杂性，模拟设置为最适合的Mixture(混合)模型和Realizable（可实现的）k-ε紊流模型。
2.1　尾砂料浆的连续性方程
在尾砂料浆管道输送过程中，其流体质点遵循如式(1)所示的连续性方程。
式中：ρ为尾砂料浆的密度，kg/m3；t为时间，s；∇为哈密顿算子；v为管内尾砂料浆的平均速度，m/s。
2.2　尾砂料浆的动量方程
尾砂料浆的连续性方程主要体现料浆流动的质量守恒及运动学规律，还需要遵循如式（2）所示的动量方程。
式中：p为流体质点受到的面力合力，Pa;μ为尾砂料浆的塑性黏度，Pa∙s;vT 为各相间的相对滑移产生的滑移速度，m/s;Fx、Fy、Fz为沿x、y、z轴的三向面力分量，Pa;αi为各相的体积分数，%;ρi为各相的密度，kg/m3;vi为各相的平均速度，m/s;vdr,i为次级相的滑移速度，m/s。
2.3　尾砂料浆的能量方程
根据前文提到的不可压缩和恒温假设，尾砂料浆需遵循如式（3）所示的能量方程。
式中：Wi为各相在某一位置的总能量，J;Wo为其他形式的能量，J。
2.4　紊流模型
在尾砂料浆的Realizable k-ε紊流模型中，紊流脉动动能k与耗散率ε的控制方程如式（4）、式（5）所示。
式中：k为紊流脉动动能，J;μt为紊流黏度，Pa · s;σk为k方程的普朗特数；Gk为料浆平均速度梯度引起紊流脉动动能的产生项，J;Gb为料浆中的浮力引起的紊流脉动动能的产生项，J;ε为紊流耗散率，%;Yc为紊流脉动动能的扩张贡献，J;σε为ε方程的普朗特数；Gε1、Gε2、Gε3为经验常数。
3　管道模型建立与数值模拟设置
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3.1　模型创建与网格划分
根据云南某锡矿选矿厂至充填制备站的实际管道参数，结合建模软件的特点，采用Workbench 19.0软件的SpaceClaim模块建立了管径为0.2 m、长度为100 m的几何模型，然后利用Meshing模块对几何模型进行网格划分，并针对尾砂料浆管道输送的实际情况，设置了边界层网格。管道模型网格如图1所示，包含2 333 430个网格单元和2 578 635个节点，经检验得出网格质量良好。
3.2　边界条件
尾砂料浆输送管道的进料口断面位置设定为速度入口，出料口断面位置则设定为自由出口。在数值模拟环境中，操作压力设定为标准大气压（101.325 kPa)，重力加速度设定为沿y轴的竖直方向(－9.8 m/s2)，操作密度设定为空气密度(1.225 kg/m3)。
3.3　数值模拟方案
数值模拟的对象为云南某锡矿硫化矿尾砂料浆，针对不同进料质量浓度(10%、20%、30%、40%、50%)和进料速度(1 m/s、2 m/s、3 m/s、4 m/s、5 m/s)，设定了25个方案进行模拟。在模拟设置中，所需的物理力学与流变参数均采用流变试验结果。数值模拟方案见表1。
4　尾砂料浆管输状态数值模拟结果分析
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4.1　载体–底床分界面判定
较细的尾砂颗粒在一定的管输流速下悬浮在管道上部的水中，并进行悬移运动，与水共同形成液相载体层，这些颗粒从水的紊流作用中获得动能，导致颗粒基本与水等速流动。较粗的尾砂颗粒则在管道下部进行推移运动，形成固相底床层，由于颗粒受到颗粒间离散力的影响，导致其流速低于载体层流速。
鉴于篇幅有限，本文仅列出了C1至C5方案下数值模拟结果中尾砂料浆的水相体积分数云图，如图2所示。
根据图2中底床层相对高度（底床层高度h与管径D的比值，体现为图中的分界线）的位置可以观察到，随着进料速度的增加，底床层相对高度呈现逐渐减小的趋势。底床层摩阻损失是由于进行推移运动的固体颗粒受颗粒间离散力而造成的，尽管底床层相对高度不大，但底床层摩阻损失占整体摩阻损失的比例较大，因此载体–底床分界面的判定（即底床层相对高度的变化规律）对管输摩阻损失的计算十分重要。
4.2　底床层相对高度与进料速度及体积浓度的关系
4.2.1　底床层相对高度与进料速度的关系
根据数值模拟结果绘制底床层相对高度与进料速度的关系折线，如图3(a)所示。由图3(a)可知，底床层相对高度随进料速度的增大呈现下降趋势，该关系近似指数函数模型。因此使用式(6)对底床层相对高度与进料速度之间的关系进行拟合，绘制的回归曲线如图3(b)所示，回归方程见表2。
式中：A、B为拟合参数；u为进料速度，m/s。
分析拟合后的回归方程发现，所有R2均高于0.95，表明采用指数函数模型进行拟合得到的结果具有较高的准确性。回归曲线的分析表明，随着进料速度的增加，进入载体层中进行悬移运动的固体颗粒含量增加，同时底床层中的固体颗粒含量减少，从而导致底床层相对高度减小。
4.2.2　底床层相对高度与进料体积浓度的关系
根据数值模拟结果绘制底床层相对高度与进料体积浓度的关系折线，如图4(a)所示。由图4(a)可知，底床层相对高度随进料体积浓度的增加呈现上升趋势，当进料体积浓度为0时，底床层不存在，即纵轴截距为0，该关系近似正比例函数模型。因此，使用式(7)对底床层相对高度与进料体积浓度之间的关系进行拟合，绘制的回归曲线如图4(b)所示，回归方程见表3。
式中：C为拟合参数；Cv为进料体积浓度，%。
分析拟合后的回归方程发现，所有R2均高于0.95，表明采用正比例函数模型进行拟合得到的结果具有较高的准确性。回归曲线的分析结果表明，随着进料体积浓度的增加，管道中进入底床层进行推移运动的固体颗粒含量增加，同时载体层中的固体颗粒含量减少，从而导致底床层相对高度抬升。
4.2.3　底床层相对高度与进料速度及体积浓度的三维关系
在实际尾砂料浆的管道输送中，给定的进料速度和体积浓度并非固定数值，因此需要建立底床层相对高度与进料速度及体积浓度的三维关系模型，以便在给定任意进料速度和体积浓度时，能够准确得到对应的底床层相对高度。根据数值模拟结果，绘制了底床层相对高度与进料速度及体积浓度的三维关系曲面，如图5(a)所示。根据曲面的变化趋势，结合底床层相对高度与进料速度及体积浓度的拟合模型，得到了如式(8)所示的三维关系曲面方程的拟合模型，绘制三维关系回归曲面如图5(b)所示，拟合的三维关系回归方程见式(9)。
式中，E、F为拟合参数。
分析拟合后的回归方程发现，R2为0.982 49，高于0.95，表明采用三维关系模型进行拟合得到的结果具有较高的准确性。回归曲面的分析表明，在给定任意进料速度和体积浓度时，可以获得唯一对应的底床层相对高度值。这一结果为实际尾砂料浆管道输送中载体–底床分界面的判定以及两层的摩阻损失计算提供了依据，具有一定的普适性。
4.3　管道中尾砂颗粒的径向粒径分布规律
根据数值模拟结果进一步分析，发现在不同的进料体积浓度下，各级颗粒的径向体积浓度随着进料速度的变化规律相似，为深入了解这种趋势，以进料质量浓度为30%为例，绘制了C1至C5方案的各级颗粒径向体积浓度与进料速度之间的关系折线，如图6所示。
分析图6(a)和图6(b)可以得出，+120目的颗粒较粗，导致大部分颗粒淤在管道下部底床层中。分析图6(c)可以得出，120~200目之间的细颗粒受进料速度变化的影响显著，当进料速度为1 m/s时，大部分颗粒仍然在管道底床层中；当进料速度超过2 m/s时，大部分颗粒已脱离底床层，进入载体层并进行悬移运动。分析图6(d)至图6(g)可以得出，－200目的颗粒更细，导致大部分颗粒在管道载体层中。另外从图6(g)可以看出，在管道顶壁区域中，部分极细颗粒仍具有较高的体积浓度，表明管道顶壁边界层中不仅有水的存在，还存在部分极细颗粒与水形成的稀浆，共同形成了边界层。
4.4　管道中尾砂料浆的径向体积浓度分布规律
根据数值模拟结果显示，在不同的进料速度下，尾砂料浆的径向体积浓度呈现出不同的变化趋势。因此绘制了不同进料质量浓度下尾砂料浆径向体积浓度与进料速度的关系折线，如图7所示。
分析图7(a)至图7(e)可以得出，在不同进料质量浓度下，尾砂料浆的径向体积浓度随相对高度的变化趋势基本一致。从图7(d)可以看出，尾砂料浆的径向体积浓度变化可划分为4个区域。在a区域，即管道底壁至载体–底床分界面处，底床层的存在限制了尾砂颗粒的自由移动，导致径向体积浓度降低，从而减缓了料浆流动。从图7(c)的局部放大图中可以观察到，随着进料速度的增加，底床层对流动的阻碍作用呈梯度递减趋势。在b区域，即载体–底床分界面至料浆径向体积浓度稳定不变处，随着相对高度的增加，尾砂颗粒受到管道中心最大流速的影响，发生了分散现象。在c区域，即径向体积浓度稳定不变区，料浆在这一区域的流动稳定性较好。在d区域，即径向体积浓度稳定不变处至管道顶壁处，由于重力作用，粗颗粒含量降低，导致料浆径向体积浓度降低。
5　结论
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（1）分别构建了底床层相对高度与进料速度及体积浓度的关系模型，以及底床层相对高度与进料速度及体积浓度的三维关系模型，模型拟合效果均较好。其中，三维关系模型可为实际尾砂料浆管输过程提供有益指导，具有一定的普适性。
（2）分析了各级颗粒径向体积浓度与进料速度的关系，结果表明，大部分+120目的较粗颗粒淤在管道下部底床层中；120~200目之间的细颗粒在进料速度为1 m/s时，部分在管道底部有沉淤现象，在进料速度为2 m/s以上时分布于载体层中；－200目的更细颗粒均分布于载体层中。管道顶壁边界层中不仅有水的存在，还存在部分极细颗粒与水形成的稀浆，共同形成了边界层。
（3）分析了不同进料质量浓度下尾砂料浆径向体积浓度与进料速度的关系，结果表明，尾砂料浆径向体积浓度变化共分4个区域。在管道底壁至载体–底床分界面处，径向体积浓度降低，且存在梯度递减效应；在载体–底床分界面至料浆径向体积浓度稳定不变处，尾砂颗粒逐渐发生分散；在径向体积浓度稳定不变区，料浆流动稳定性较好；在径向体积浓度稳定不变处至管道顶壁处，径向体积浓度降低。
基金
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  • 云南省基础研究专项青年项目(202301AU070185; 202101AU070022)
  • 昆明理工大学人培基金项目(KKZ3202021040)
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2025年第45卷第1期
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  • 接收时间：2024-02-23
  • 首发时间：2026-10-29
  • 出版时间：2025-01-25
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  • 收稿日期：2024-02-23
基金
云南省基础研究专项青年项目(202301AU070185; 202101AU070022)
昆明理工大学人培基金项目(KKZ3202021040)
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    昆明理工大学 国土资源工程学院，云南　昆明　650093

通讯作者:

乔登攀（1969—），男，甘肃白银人，博士，教授，博士生导师，主要从事现代采矿工艺及理论研究。E-mail:
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
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
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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