Article(id=1236334642836599672, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236334630450819368, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2023.06.004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1687968000000, receivedDateStr=2023-06-29, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772694748839, onlineDateStr=2026-03-05, pubDate=1701360000000, pubDateStr=2023-12-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772694748839, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772694748839, creator=13701087609, updateTime=1772694748839, updator=13701087609, issue=Issue{id=1236334630450819368, tenantId=1146029695717560320, journalId=1235980550691926019, year='2023', volume='43', issue='6', pageStart='1', pageEnd='183', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772694745886, creator=13701087609, updateTime=1772694896382, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236335261735506524, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236334630450819368, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236335261735506525, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236334630450819368, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=15, endPage=19, ext={EN=ArticleExt(id=1236334643176338313, articleId=1236334642836599672, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Experimental Research and Prediction Analysis of Rheological Parameters of Tailings Backfill with Multi-Factors, columnId=1236276106018484431, journalTitle=Mining and Metallurgical Engineering, columnName=MINING, runingTitle=null, highlight=null, articleAbstract=

Tailings slurry with different mass concentration and cement to sand ratio was prepared with a certain kind of tailings, which was taken to study for its rheological properties by adopting Brookfield R/S+ rheometer. It is found that at room temperature, the mass concentration of paste slurry has a stronger effect on the rheological properties of paste than the cement to sand ratio of slurry. When the concentration is lower than 64%, the cement to sand ratio has little effect on the rheological properties. As the slurry concentration increases, its yield stress and viscosity present exponential growth, which increase at the fastest rate when the slurry concentration is 68%. As the cement to sand ratio of slurry increases, its yield stress and viscosity increase approximately linearly. The influences of slurry concentration, cement to sand ratio, gradation and temperature on rheological properties of slurry were studied by experiments, and then the rheological parameters were predicted by using XGBoost based on the obtained experimental data. It is shown that the relative errors and variances between the predicted results and the actual values are within a reasonable range, which has proven the accuracy of the prediction model.

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取某尾砂制备不同质量浓度、灰砂比的尾砂料浆，采用Brookfield R/S+型流变仪对尾砂充填料浆流变特性进行研究。结果表明，室温条件下，膏体料浆质量浓度对膏体流变特性的影响强于料浆灰砂比，且料浆浓度低于64%时，灰砂比对流变特性的影响甚微。料浆浓度增大，其屈服应力和黏度呈指数增长，料浆浓度68%时增长最快。料浆灰砂比增大，其屈服应力和黏度呈近似线性增长。以料浆浓度、灰砂比、级配和温度为变量进行试验，研究以上变量对料浆流变特性的影响，并根据试验数据使用XGBoost对流变参数进行预测，预测结果与实际值相对误差以及均方差均在合理范围内，证实了预测模型的准确性。

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刘金枝（1971—），女，湖南益阳人，博士，副教授，主要研究方向为应用数学与溶浸采矿。

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刘金枝（1971—），女，湖南益阳人，博士，副教授，主要研究方向为应用数学与溶浸采矿。

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