Article(id=1322594911183033322, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322594813749350688, 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=1712592000000, receivedDateStr=2024-04-09, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793260799451, onlineDateStr=2026-10-29, pubDate=1740412800000, pubDateStr=2025-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793260799451, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793260799451, creator=13701087609, updateTime=1793260799451, updator=13701087609, issue=Issue{id=1322594813749350688, tenantId=1146029695717560320, journalId=1225396423026438145, year='2025', volume='45', issue='2', pageStart='1', pageEnd='288', issueExtLink='null', onlineDate='null', pubDate='1740412800000', pubDateStr='2025-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793260776220, creator='13701087609', updateTime=1793260776220, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=57, endPage=65, ext={EN=ArticleExt(id=1322594912558765036, articleId=1322594911183033322, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=Experimental Study on Proportion Optimization of High-Concentration Paste Filling Materials Based on RSM, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=

In order to optimize the performance of filling materials while reducing filling costs, the research on filling materials proportion was carried out. Based on the RSM-CCD method, an experiment with 4 factors and 5 levels was designed to construct a response surface regression model with factors of fly ash mass fraction A, cement mass fraction B, calcium carbonate mass fraction C, and slurry mass fraction D. The slump of the filling slurry and the uniaxial compressive strength of the filling body at 7 d and 28 d were the response values, respectively. The influence of single factor and the interaction of various factors on material properties were analyzed, and the lowest cost filling material proportion scheme was sought on the basis of meeting performance requirements. The results show that the slump of high-concentration filling slurry is only affected by a linear single factor, and the interaction has no significant effect on it. The slump increases firstly and then decreases with the increase of A, B, and C, and decreases with the increase of D. Linear and interactive effects have a significant impact on the strength of high-concentration filling body at 7 d and 28 d. There is no significant relationship between the interaction effect AC and the strength of the filling body. The increase of single factor in AB or CD will promote the strengthening effect of the other factors on the compressive strength of the filling material at 28 d, while the increase of single factor in AD, BC, and BD will inhibit the enhancement effect of the other factors on the compressive strength of the filling materials at 28 d. The optimal proportion of filling materials considering cost-effectiveness is 18.0% of fly ash mass fraction, 10.9% of cement mass fraction, 1.3% of calcium carbonate mass fraction, and 84.0% of slurry mass fraction. This proportion scheme meets the design standards for paste filling in engineering examples.

, authors=Peisen ZHANG1, 2, Zhaoqiang JU1, 2, Xin HU3, Daqiang XU1, 2, Peng XIAO1, 2, Zelin XU1, 2, Jiaxin FANG1, 2, authorsList=Peisen ZHANG, Zhaoqiang JU, Xin HU, Daqiang XU, Peng XIAO, Zelin XU, Jiaxin FANG, authorCompany=null, correspAuthors=Zhaoqiang JU, 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=1322594914626556925, articleId=1322594911183033322, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=基于RSM的高浓度膏体充填材料配比优化试验研究, columnId=1226462294490657775, journalTitle=矿业研究与开发, columnName=采矿与矿山充填, runingTitle=null, highlight=null, articleAbstract=

为优化充填材料性能的同时降低充填成本,开展充填材料配比研究。基于RSM-CCD法设计4因素5水平试验,构建粉煤灰质量分数A、水泥质量分数B、碳酸钙质量分数C、料浆质量分数D为因子,充填料浆坍落度及充填体7 d、28 d单轴抗压强度分别为响应值的响应曲面回归模型,分析单因素及各因素交互作用对材料性能的影响,并在满足性能要求的基础上寻求成本最低的充填材料配比方案。结果表明:(1)高浓度充填料浆坍落度仅受线性单因素影响,交互作用对其无显著影响,坍落度随A、B、C增加先增大后减小,随D的增加而减小;(2)线性及交互作用对高浓度充填体7 d、28 d强度均有显著影响,交互作用AC与充填体强度不存在显著关系,AB、CD为一种因素的增加会促进另一种因素对充填体28 d抗压强度的增强作用,交互作用AD、BC、BD为一种因素的增加会抑制另一种因素对充填体28 d抗压强度的增强作用;(3)考虑性价比的充填材料最优配比方案为粉煤灰质量分数为18.0%,水泥质量分数为10.9%,碳酸钙质量分数为1.3%,料浆质量分数为84.0%,该配比方案满足工程实例膏体充填设计标准。

, authors=张培森1, 2, 鞠照强1, 2, 胡昕3, 许大强1, 2, 肖鹏1, 2, 徐泽林1, 2, 方家鑫1, 2, authorsList=张培森, 鞠照强, 胡昕, 许大强, 肖鹏, 徐泽林, 方家鑫, authorCompany=null, correspAuthors=鞠照强, authorNote=

张培森(1977—),男,山东曹县人,博士,教授,博导,主要从事采矿工程与岩石力学等方面的教学和科研工作。E-mail:

, correspAuthorsNote=
鞠照强(1999—),男,山东德州人,硕士研究生,主要从事矿山充填开采技术研究工作。E-mail:
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张培森(1977—),男,山东曹县人,博士,教授,博导,主要从事采矿工程与岩石力学等方面的教学和科研工作。E-mail:

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张培森(1977—),男,山东曹县人,博士,教授,博导,主要从事采矿工程与岩石力学等方面的教学和科研工作。E-mail:

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Chinese Journal of Rock Mechanics and Engineering, 2022, 41(8):1536-1551., articleTitle=Strength evolution law and acoustic-emission characteristics of multi-source coal-based filling body of solid wastes, refAbstract=null)], funds=[Fund(id=1322594924365729865, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, awardId=2018YFC0604702, language=CN, fundingSource=国家重点研发计划资助项目(2018YFC0604702), fundOrder=null, country=null), Fund(id=1322594926043451466, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, awardId=51379119, language=CN, fundingSource=国家自然科学基金资助项目(51379119), fundOrder=null, country=null), Fund(id=1322594926232195147, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, awardId=ZR2021ME086, language=CN, fundingSource=山东省自然科学基金资助项目(ZR2021ME086), fundOrder=null, country=null), Fund(id=1322594926395773004, tenantId=1146029695717560320, 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articleId=1322594911183033322, language=EN, label=Fig.1, caption=Comparison between predicted values and measured values of filling material performance, figureFileSmall=SbRhj6yGR/6xcxhbEotxBQ==, figureFileBig=tSo/D3wF9/jsrbGFTXp46g==, tableContent=null), ArticleFig(id=1322594922096611386, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=图1, caption=充填体性能预测值与实测值对比, figureFileSmall=SbRhj6yGR/6xcxhbEotxBQ==, figureFileBig=tSo/D3wF9/jsrbGFTXp46g==, tableContent=null), ArticleFig(id=1322594922532819003, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=EN, label=Fig.2, caption=The influences of single factor on the fluidity of filling body, figureFileSmall=wy0y+B3nzFEt9+YY7VSxiA==, figureFileBig=k51cqpHsZJ7BjtcNWyuk6Q==, tableContent=null), ArticleFig(id=1322594922616705084, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=图2, caption=单因素对充填体流动性的影响, figureFileSmall=wy0y+B3nzFEt9+YY7VSxiA==, figureFileBig=k51cqpHsZJ7BjtcNWyuk6Q==, tableContent=null), ArticleFig(id=1322594922713174077, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=EN, label=Fig.3, caption=The influences of linear factors on the strength of filling body, figureFileSmall=gnFtR4+w2YODeK6ulNpHCQ==, figureFileBig=1Xn0G5TdiOqzvbL83+snEQ==, tableContent=null), ArticleFig(id=1322594922927083582, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=图3, caption=线性因素对充填体强度的影响, figureFileSmall=gnFtR4+w2YODeK6ulNpHCQ==, figureFileBig=1Xn0G5TdiOqzvbL83+snEQ==, tableContent=null), ArticleFig(id=1322594923015163967, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=EN, label=Fig.4, caption=The influence of different interactions on 28 d compressive strength of filling body, figureFileSmall=ZoIonXsJoAyRiR4vNeMc2g==, figureFileBig=P1E5CI2Kbd38sqISrSGsXQ==, tableContent=null), ArticleFig(id=1322594923128410176, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=图4, caption=不同交互作用对充填体28 d抗压强度的影响, figureFileSmall=ZoIonXsJoAyRiR4vNeMc2g==, figureFileBig=P1E5CI2Kbd38sqISrSGsXQ==, tableContent=null), ArticleFig(id=1322594923258433601, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=EN, label=Table 1, caption=

Parameters of various of each factor in the test

, figureFileSmall=null, figureFileBig=null, tableContent=
水平A/%B/%C/%D/%
–2188183
–1199284
02010385
12111486
22212587
), ArticleFig(id=1322594923375874114, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=表1, caption=

试验各因子水平参数

, figureFileSmall=null, figureFileBig=null, tableContent=
水平A/%B/%C/%D/%
–2188183
–1199284
02010385
12111486
22212587
), ArticleFig(id=1322594923472343107, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=EN, label=Table 2, caption=

Test design and results

, figureFileSmall=null, figureFileBig=null, tableContent=
组别A/%B/%C/%D/%坍落度7 d抗压强度28 d抗压强度
Y/cmY′/cm相对误差/%P7/MPaP′7/MPa相对误差/%P28/MPaP′28/MPa相对误差/%
119928424.626.26.51.821.77–2.74.944.68–5.3
221928422.723.01.31.781.74–2.24.834.881.0
3191128423.725.05.52.462.37–3.76.756.770.3
4211128422.019.4–11.82.752.781.17.577.48–1.2
519948423.825.36.31.811.841.74.694.700.2
621948423.323.61.31.831.851.14.694.63–1.3
7191148421.621.4–0.92.372.33–1.76.115.93–2.9
8211148415.817.18.22.752.791.56.326.380.9
919928612.012.75.82.102.06–1.95.505.591.6
102192868.710.318.41.871.84–1.64.995.041.0
11191128611.512.69.62.592.50–3.57.157.08–1.0
1221112867.17.78.52.812.72–3.26.917.052.0
131994867.511.452.02.362.26–4.27.467.42–0.5
142194869.610.37.31.992.084.56.476.602.0
1519114866.78.425.42.542.581.67.958.051.3
1621114865.24.9–5.82.872.85–0.77.627.751.7
17181038523.219.1–17.71.812.1418.25.575.753.2
18221038511.712.46.02.452.38–2.95.855.65–3.4
1920838522.518.9–16.01.791.821.73.493.490.0
20201238512.112.31.73.163.201.36.776.72–0.7
21201018522.421.8–2.72.042.186.97.237.280.7
22201058520.918.1–13.42.442.38–2.58.078.00–0.9
23201038326.526.4–0.41.841.861.15.385.420.7
2420103874.00.7–82.52.172.222.37.977.71–3.3
25201038522.122.10.01.971.970.06.156.150.0
), ArticleFig(id=1322594923648503876, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=表2, caption=

试验设计与结果

, figureFileSmall=null, figureFileBig=null, tableContent=
组别A/%B/%C/%D/%坍落度7 d抗压强度28 d抗压强度
Y/cmY′/cm相对误差/%P7/MPaP′7/MPa相对误差/%P28/MPaP′28/MPa相对误差/%
119928424.626.26.51.821.77–2.74.944.68–5.3
221928422.723.01.31.781.74–2.24.834.881.0
3191128423.725.05.52.462.37–3.76.756.770.3
4211128422.019.4–11.82.752.781.17.577.48–1.2
519948423.825.36.31.811.841.74.694.700.2
621948423.323.61.31.831.851.14.694.63–1.3
7191148421.621.4–0.92.372.33–1.76.115.93–2.9
8211148415.817.18.22.752.791.56.326.380.9
919928612.012.75.82.102.06–1.95.505.591.6
102192868.710.318.41.871.84–1.64.995.041.0
11191128611.512.69.62.592.50–3.57.157.08–1.0
1221112867.17.78.52.812.72–3.26.917.052.0
131994867.511.452.02.362.26–4.27.467.42–0.5
142194869.610.37.31.992.084.56.476.602.0
1519114866.78.425.42.542.581.67.958.051.3
1621114865.24.9–5.82.872.85–0.77.627.751.7
17181038523.219.1–17.71.812.1418.25.575.753.2
18221038511.712.46.02.452.38–2.95.855.65–3.4
1920838522.518.9–16.01.791.821.73.493.490.0
20201238512.112.31.73.163.201.36.776.72–0.7
21201018522.421.8–2.72.042.186.97.237.280.7
22201058520.918.1–13.42.442.38–2.58.078.00–0.9
23201038326.526.4–0.41.841.861.15.385.420.7
2420103874.00.7–82.52.172.222.37.977.71–3.3
25201038522.122.10.01.971.970.06.156.150.0
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Variance analysis of regression model

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方差来源平方和方差F值P值
Y′P′7P′28Y′P′7P′28Y′P′7P′28Y′P′7P′28
模型1 235.953.84136.94588.2820.2742.63910.0315.8264.43<0.000 1<0.000 1<0.000 1
线性1 141.893.23824.388285.4710.8096.09732.4446.62148.85<0.000 1<0.000 1<0.000 1
A66.670.0940.01566.6670.0940.0157.578.340.350.020 00.016 00.565 0
B64.682.88415.73064.6822.88415.7307.35163.41384.030.022 0<0.000 1<0.000 1
C19.800.0540.78819.8020.0540.7882.253.0719.250.16500.11000.0010
D990.740.2057.855990.7350.2057.855112.5711.63191.76<0.000 10.007 0<0.000 1
平方76.570.3107.30019.1420.0781.8252.174.5844.550.145 00.023 0<0.000 1
A228.460.0610.14328.4630.0610.1433.231.833.500.102 00.205 00.091 0
B229.820.2080.77229.8240.2080.7723.3912.5018.830.095 00.005 00.001 0
C23.260.0671.5663.2630.0671.5660.374.2038.240.556 00.068 0<0.000 1
D251.600.0040.12151.6020.0040.1215.860.322.960.036 00.585 00.116 0
交互17.500.2935.2582.9160.0490.8760.332.7721.390.905 00.075 0<0.000 1
AB6.000.2120.2686.0020.2120.2680.6811.996.540.428 00.006 00.029 0
AC1.960.0010.0721.9600.0010.0720.220.051.750.647 00.826 00.216 0
AD0.490.0310.5590.4900.0310.5590.061.7413.640.818 00.217 00.004 0
BC7.840.0160.7357.8400.0160.7350.890.8917.950.368 00.369 00.002 0
BD1.000.0230.3571.0000.0230.3570.111.278.720.743 00.285 00.014 0
CD0.200.0123.2670.2030.0123.2670.020.6979.760.882 00.427 0<0.000 1
), ArticleFig(id=1322594923950493766, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=表3, caption=

回归模型方差分析

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方差来源平方和方差F值P值
Y′P′7P′28Y′P′7P′28Y′P′7P′28Y′P′7P′28
模型1 235.953.84136.94588.2820.2742.63910.0315.8264.43<0.000 1<0.000 1<0.000 1
线性1 141.893.23824.388285.4710.8096.09732.4446.62148.85<0.000 1<0.000 1<0.000 1
A66.670.0940.01566.6670.0940.0157.578.340.350.020 00.016 00.565 0
B64.682.88415.73064.6822.88415.7307.35163.41384.030.022 0<0.000 1<0.000 1
C19.800.0540.78819.8020.0540.7882.253.0719.250.16500.11000.0010
D990.740.2057.855990.7350.2057.855112.5711.63191.76<0.000 10.007 0<0.000 1
平方76.570.3107.30019.1420.0781.8252.174.5844.550.145 00.023 0<0.000 1
A228.460.0610.14328.4630.0610.1433.231.833.500.102 00.205 00.091 0
B229.820.2080.77229.8240.2080.7723.3912.5018.830.095 00.005 00.001 0
C23.260.0671.5663.2630.0671.5660.374.2038.240.556 00.068 0<0.000 1
D251.600.0040.12151.6020.0040.1215.860.322.960.036 00.585 00.116 0
交互17.500.2935.2582.9160.0490.8760.332.7721.390.905 00.075 0<0.000 1
AB6.000.2120.2686.0020.2120.2680.6811.996.540.428 00.006 00.029 0
AC1.960.0010.0721.9600.0010.0720.220.051.750.647 00.826 00.216 0
AD0.490.0310.5590.4900.0310.5590.061.7413.640.818 00.217 00.004 0
BC7.840.0160.7357.8400.0160.7350.890.8917.950.368 00.369 00.002 0
BD1.000.0230.3571.0000.0230.3570.111.278.720.743 00.285 00.014 0
CD0.200.0123.2670.2030.0123.2670.020.6979.760.882 00.427 0<0.000 1
), ArticleFig(id=1322594924063739975, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=EN, label=Table 4, caption=

Performance indexes of the filling material

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性能指标
坍落度22 cm
7 d抗压强度2.1 MPa
28 d抗压强度4.2 MPa
), ArticleFig(id=1322594924168597576, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322594911183033322, language=CN, label=表4, caption=

充填材料性能指标

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性能指标
坍落度22 cm
7 d抗压强度2.1 MPa
28 d抗压强度4.2 MPa
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基于RSM的高浓度膏体充填材料配比优化试验研究
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张培森 1, 2 , 鞠照强 1, 2 , 胡昕 3 , 许大强 1, 2 , 肖鹏 1, 2 , 徐泽林 1, 2 , 方家鑫 1, 2
矿业研究与开发 | 采矿与矿山充填 2025,45(2): 57-65
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矿业研究与开发 |采矿与矿山充填 2025 , 45 (2) : 57 -65
基于RSM的高浓度膏体充填材料配比优化试验研究
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2.山东科技大学 矿业工程国家级实验教学示范中心,山东 青岛市 266590, bio={"content":"

张培森(1977—),男,山东曹县人,博士,教授,博导,主要从事采矿工程与岩石力学等方面的教学和科研工作。E-mail:

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张培森(1977—),男,山东曹县人,博士,教授,博导,主要从事采矿工程与岩石力学等方面的教学和科研工作。E-mail:

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张培森1, 2 , 鞠照强1, 2 , 胡昕3, 许大强1, 2, 肖鹏1, 2, 徐泽林1, 2, 方家鑫1, 2
作者信息
  • 1.山东科技大学 矿山灾害预防控制国家重点实验室培育基地,山东 青岛市 266590
  • 2.山东科技大学 矿业工程国家级实验教学示范中心,山东 青岛市 266590
  • 3.中国电力工程顾问集团西北电力设计院有限公司,陕西 西安 710075
通讯作者:
鞠照强(1999—),男,山东德州人,硕士研究生,主要从事矿山充填开采技术研究工作。E-mail:
作者简介:

张培森(1977—),男,山东曹县人,博士,教授,博导,主要从事采矿工程与岩石力学等方面的教学和科研工作。E-mail:

Experimental Study on Proportion Optimization of High-Concentration Paste Filling Materials Based on RSM
Peisen ZHANG1, 2 , Zhaoqiang JU1, 2 , Xin HU3, Daqiang XU1, 2, Peng XIAO1, 2, Zelin XU1, 2, Jiaxin FANG1, 2
Affiliations
  • 1.National Key Laboratory for Mine Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao, Shandong 266590, China
  • 2.National Demonstration Center for Experimental Mining Engineering Education, Shandong University of Science and Technology, Qingdao, Shandong 266590, China
  • 3.Northwest Electric Power Design Institute Co., Ltd., of China Power Engineering Consulting Group, Xi’an, Shaanxi 710075, China
出版时间: 2025-02-25
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为优化充填材料性能的同时降低充填成本,开展充填材料配比研究。基于RSM-CCD法设计4因素5水平试验,构建粉煤灰质量分数A、水泥质量分数B、碳酸钙质量分数C、料浆质量分数D为因子,充填料浆坍落度及充填体7 d、28 d单轴抗压强度分别为响应值的响应曲面回归模型,分析单因素及各因素交互作用对材料性能的影响,并在满足性能要求的基础上寻求成本最低的充填材料配比方案。结果表明:(1)高浓度充填料浆坍落度仅受线性单因素影响,交互作用对其无显著影响,坍落度随A、B、C增加先增大后减小,随D的增加而减小;(2)线性及交互作用对高浓度充填体7 d、28 d强度均有显著影响,交互作用AC与充填体强度不存在显著关系,AB、CD为一种因素的增加会促进另一种因素对充填体28 d抗压强度的增强作用,交互作用AD、BC、BD为一种因素的增加会抑制另一种因素对充填体28 d抗压强度的增强作用;(3)考虑性价比的充填材料最优配比方案为粉煤灰质量分数为18.0%,水泥质量分数为10.9%,碳酸钙质量分数为1.3%,料浆质量分数为84.0%,该配比方案满足工程实例膏体充填设计标准。

膏体充填  /  响应面法  /  材料配比优化  /  交互作用  /  高浓度

In order to optimize the performance of filling materials while reducing filling costs, the research on filling materials proportion was carried out. Based on the RSM-CCD method, an experiment with 4 factors and 5 levels was designed to construct a response surface regression model with factors of fly ash mass fraction A, cement mass fraction B, calcium carbonate mass fraction C, and slurry mass fraction D. The slump of the filling slurry and the uniaxial compressive strength of the filling body at 7 d and 28 d were the response values, respectively. The influence of single factor and the interaction of various factors on material properties were analyzed, and the lowest cost filling material proportion scheme was sought on the basis of meeting performance requirements. The results show that the slump of high-concentration filling slurry is only affected by a linear single factor, and the interaction has no significant effect on it. The slump increases firstly and then decreases with the increase of A, B, and C, and decreases with the increase of D. Linear and interactive effects have a significant impact on the strength of high-concentration filling body at 7 d and 28 d. There is no significant relationship between the interaction effect AC and the strength of the filling body. The increase of single factor in AB or CD will promote the strengthening effect of the other factors on the compressive strength of the filling material at 28 d, while the increase of single factor in AD, BC, and BD will inhibit the enhancement effect of the other factors on the compressive strength of the filling materials at 28 d. The optimal proportion of filling materials considering cost-effectiveness is 18.0% of fly ash mass fraction, 10.9% of cement mass fraction, 1.3% of calcium carbonate mass fraction, and 84.0% of slurry mass fraction. This proportion scheme meets the design standards for paste filling in engineering examples.

Paste filling  /  Response surface method  /  Material proportion optimization  /  Interaction  /  High concentration
张培森, 鞠照强, 胡昕, 许大强, 肖鹏, 徐泽林, 方家鑫. 基于RSM的高浓度膏体充填材料配比优化试验研究. 矿业研究与开发, 2025 , 45 (2) : 57 -65 .
Peisen ZHANG, Zhaoqiang JU, Xin HU, Daqiang XU, Peng XIAO, Zelin XU, Jiaxin FANG. Experimental Study on Proportion Optimization of High-Concentration Paste Filling Materials Based on RSM[J]. Mining Research and Development, 2025 , 45 (2) : 57 -65 .
膏体充填是一种将固弃废物与水泥等胶凝材料制成浆状材料,然后利用管道将其输送至井下工作面的绿色采煤技术[1-4],可以实现控制地表沉陷、资源化利用固弃废物、煤炭安全开采和保护生态环境的目的[5-6]。充填材料是充填技术的核心[7],在工程中占据主要成本,同时充填材料的性能参数又决定着充填工艺能否达到预期效果,因此开展充填材料配比优化研究对推广充填开采具有重要意义。
目前,相关学者对充填材料的配比优化已开展了大量的试验研究[8-13]。杨宝贵等[14]通过试验确定了适用于高浓度条件下的胶结充填材料配比为水泥∶粉煤灰∶煤矸石∶水=1∶2∶5∶2。冯国瑞等[15]基于响应面法确定了废弃混凝土替代矸石粗、细骨料的最佳替代率。尹升华等[16]、高谦等[17]基于中心复合试验设计建立了掺有全尾砂、碎石、棒磨砂作为骨料的充填材料强度优化模型,确定了满足强度要求的最低成本配比方案。王树帅等[18-19]在确定最优矸石粒径级配的基础上,基于RSM-BBD法优化充填材料配比并在工程中实现应用。赵国彦等[20]建立了温度、灰砂比和料浆质量分数对抗压强度、坍落度和成本的回归模型,得到不同采场温度下最佳灰砂比及料浆质量分数。邓雪杰[21]建立了基于改进的BP神经网络,对胶结充填体性能进行预测并据此优化料浆配比。
综合前人研究成果可得,RSM等数学统计方法可应用于充填材料性能优化设计,而碳酸钙可有效提升充填料浆输送性能[22],因此,本文利用RSM-CCD法设计充填材料配比试验,探究高浓度条件下粉煤灰质量分数、水泥质量分数、碳酸钙质量分数、料浆质量分数及其交互作用对充填材料性能(坍落度,7 d、28 d强度)的影响规律,在满足工程实际的基础上寻求成本最低的方案配比,以期为膏体充填开采提供理论指导与现场参考。
充填材料以煤矸石、粉煤灰、水泥、碳酸钙、水为原材料,固料按一定比例机械拌合均匀后加水混合成料浆。水泥、碳酸钙分别为P⋅C 42.5和普通碳酸钙。
为保证试验准确,根据文献[23],本次试验矸石粒径统一选择泰波理论理想级配指数n=0.5的级配方案,即0~5 mm∶5~10 mm∶10~15 mm=57.7∶23.9∶18.4。在充填材料制成料浆后,首先进行坍落度测试[21],之后将剩余料浆制备成100 mm×100 mm×100 mm的正方体试块,试块放于标准养护室内,养护至相应龄期后进行抗压强度测试。抗压强度测试采用位移加载路径,速度为0.3 mm/min。每个龄期均制作3个试块以保证试验数据准确。
膏体充填材料的性能是多种因素共同作用的结果,为分析线性单因素及其交互作用对膏体充填材料性能的影响,通过统计软件Minitab Statistical Software创建响应曲面设计试验,构建膏体充填材料流动性、力学性能与不同影响因素的响应曲面回归模型。基于RSM-CCD法设计试验,选取影响充填材料性能的4种因子:粉煤灰质量分数A、水泥质量分数B、碳酸钙质量分数C及料浆质量分数D。考虑到当前膏体充填材料质量分数可达75%~85%[21],因此本次试验高浓度膏体充填材料的料浆质量分数中心水平设置为85%,各因子水平具体参数设置见表1,试验设计与分析结果见表2。表2中分别以Y、P7、P28表征充填材料坍落度、7 d及28 d抗压强度的实测值,以Y′、P′7、P′28表征回归模型响应值的预测值。
利用软件分析响应曲面设计项,即可得到充填材料影响因素与坍落度,7 d、28 d抗压强度之间的响应曲面回归模型如式(1)至式(3)所示。
借助响应曲面回归模型可进一步分析各单因素及其交互作用对充填材料性能的影响规律。在此之前,需要对各响应曲面模型进行方差分析,以验证模型准确性,分析结果见表3。
由方差分析可知,表征充填材料性能的3个回归模型的P值均为<0.000 1,Y′、P′7、P′28模型的拟合度分别为0.933 5, 0.972 4及0.989 0,说明各模型回归效果极显著[24]。
考虑到3种模型的响应值与料浆质量分数均存在显著相关关系,即P<0.05,为直观表达模型的准确性,以料浆质量分数为横坐标,响应值为纵坐标绘制散点图,并进行对比分析(见图1,颜色标识见电子版)。由表2、图1可知,随着料浆质量分数的增加,坍落度实测值与预测值的变化趋势趋于一致,表明该模型具有可信度及实用性;7 d、28 d抗压强度实测值与预测值重合度较高,相对误差大体分别在10%、5%以内,表明充填体抗压强度回归模型预测值与实测值较为吻合,能够用来分析预测相关试验结果。此外,坍落度预测值与实测值的相对误差较大,经计算,料浆质量分数为83%~87%时,所对应的坍落度预测值与实测值的平均相对误差绝对值分别为0.4%、5.23%、8.21%、16.6%、82.5%,即随着料浆质量分数的增加,坍落度回归模型的可靠性逐渐降低。考虑到模型本身拟合度较高,可将该回归模型应用于低水平料浆质量分数条件(83%~85%)下的试验结果预测或规律定性分析。
由表3可知,坍落度线性和交互作用的P值分别为<0.000 1, 0.905,说明充填材料坍落度与多因素交互作用之间无显著关系,仅受线性单因素影响;28 d抗压强度线性和交互作用的P值均<0.000 1,说明线性单因素及交互作用整体对充填材料后期强度有显著影响,具体为单因素水泥质量分数B、碳酸钙质量分数C、料浆质量分数D及交互作用AB、AD、BC、BD、CD;对7 d抗压强度有显著影响的具体为单因素A、B、D及交互作用AB。
基于上述显著性分析可知,高浓度充填料浆坍落度仅受线性单因素影响,交互作用对其无显著影响。充填体强度始终受水泥、料浆质量分数等因素制约,粉煤灰质量分数对其影响较小,碳酸钙质量分数对充填体早期强度影响较小,对后期强度影响极显著,这可能是早期由于粉煤灰活性被碳酸钙抑制,而在后期阶段,填充孔隙的碳酸钙逐渐固化,有效增强充填体强度。
为研究线性单因素对充填料浆流动性能的影响,仅选择单因素线性变化,而其他因素保持不变,设置为中心水平。即粉煤灰质量分数A、水泥质量分数B、碳酸钙质量分数C及料浆质量分数D分别取20%、10%、3%、85%,利用Minitab软件中响应曲面的预测项对不同配比的坍落度进行预测,得到单因素与坍落度的变化曲线,如图2所示。
由图2可知,当粉煤灰质量分数低于19%时,随着粉煤灰质量分数的增加,料浆中细骨料增加,粗骨料减少,使得骨料更易被搬运,因此流动性能得到改善;当粉煤灰质量分数大于19%时,过量的粉煤灰会影响水泥浆的黏结力,使充填料浆和易性和保水性降低,进而导致坍落度下降。因此充填料浆坍落度随着粉煤灰质量分数的增加呈现先增加后降低的规律。
随着水泥质量分数的增加,料浆流动性能呈现先升高后降低的变化规律,且在B=9%时料浆和易性达到最优。原因是随着水泥质量分数的增加,适量的水泥水化产物充填到骨料之间,降低了大粒径矸石之间的碰撞摩擦,使料浆流动性增加;水泥质量分数继续增加,过量水化物会增加料浆的黏度,同时水泥颗粒也会吸附更多的自由水,料浆流动性降低。
随着碳酸钙质量分数的增大,充填料浆流动性能略有提升后随之降低。相比于其他因素,坍落度变化幅度较小,说明碳酸钙质量分数对充填料浆流动性能影响较小。
随着料浆质量分数的增加,料浆坍落度先是趋于稳定,随后急速降低,这主要是因为大部分水分与胶凝材料发生反应,自由水急剧减少,当料浆质量分数过高时,料浆已不具备流动性。
相较于文献[25]所述,高浓度条件下,粉煤灰对充填料浆流动性能的影响规律发生改变,而水泥及料浆质量分数对充填料浆流动性能的影响规律不变。此时,各因素对充填料浆流动性能的影响顺序为:料浆质量分数D>水泥质量分数B>粉煤灰质量分数A>碳酸钙质量分数C。模型预测的各因素影响规律与实测数据基本一致,进一步验证了坍落度回归模型的准确性。
利用Minitab软件中响应曲面中的预测项对抗压强度进行预测,得到线性单因素对充填体强度的影响,如图3所示。
由图3(a)可知,粉煤灰可调整改善充填体颗粒级配,提高材料密实度,因此充填体7 d抗压强度随粉煤灰质量分数的增加而增加;但粉煤灰受碳酸钙影响,火山灰活性不能激发,而当粉煤灰质量分数过多(超过20%)时,还会产生更多的钙钒石结体孔隙[22],因此充填体28 d抗压强度变化趋势发生改变,呈先增加后降低的趋势。
由图3(b)可知,充填体7 d、28 d抗压强度均随水泥质量分数的增加而快速增加。水泥会与水反应生成钙矾石、硅酸基凝胶等一系列胶凝产物[26],这是充填体强度的主要来源。随着水泥质量分数的增加,这些胶凝产物数量也相应增加,同时将更多骨料黏结形成骨架结构,从而提高充填体的整体强度。
由图3(c)可知,随着碳酸钙质量分数的增加,各龄期的充填体强度均表现为先降低后升高的趋势量。碳酸钙一方面减缓水化反应速率,影响水泥与粉煤灰生成钙矾石,另一方面改变充填体空间结构,增加充填体内部孔隙,这是充填体强度降低的主要原因[22]。随着碳酸钙质量分数继续增加,多余的碳酸钙会填充进孔隙之中,并在碳化作用下形成坚硬结构,使充填体强度增大。
由图3(d)可知,高浓度充填体各龄期强度随料浆质量分数增加的变化趋势与低浓度(<80%)相同[19,25],在此不做赘述。
由表3方差分析可知,交互作用对充填体28 d强度有显著影响,图4为不同交互作用对充填体28 d抗压强度的影响。
由图4(a)可知,当粉煤灰质量分数增加时,充填体随水泥质量分数增加的变化趋势由先增加后降低转变为一直增加。当水泥质量分数增加时,充填体强度随粉煤灰质量分数增加的变化趋势始终保持不变,呈先增加后降低趋势,但充填体强度变化幅度增加,抗压强度峰值相较于初始抗压强度的变化量由0.05 MPa增加到1.04 MPa。由上述分析可知,交互作用AB中各因素增加会促进另一因素对充填体强度的增强作用。
由图4(b)可知,在碳酸钙质量分数从低水平增长至高水平的过程中,充填体强度随粉煤灰质量分数增加的变化趋势基本一致,且充填体强度峰值对应的粉煤灰质量分数均处于同一区间(19%~20%);在粉煤灰质量分数从低水平增长至高水平的过程中,充填体强度随碳酸钙质量分数增加的变化趋势同样保持一致,且充填体强度最小值对应的碳酸钙质量分数均处于同一区间(2%~3%)。此现象说明粉煤灰、碳酸钙质量分数并未改变另一因素对充填体抗压强度的影响变化趋势,即交互作用AC与充填体强度之间不存在显著关系。
由图4(c)可知,当粉煤灰质量分数增加时,充填体强度随料浆质量分数增加的变化趋势始终不变。具体而言,当粉煤灰质量分数为18%时,充填体强度随料浆质量分数增加的变化量为3.78 MPa,增长率为88.6%;随着粉煤灰质量分数增加,充填体强度变化量逐渐减少,当粉煤灰质量分数为22%时,充填体强度随料浆质量分数增加的变化量为0.79 MPa,增长率仅为14.0%。此外,当料浆质量分数处于低水平(83%)时,充填体强度与粉煤灰质量分数之间呈正相关关系;随着料浆质量分数的增加,充填体强度随粉煤灰质量分数的增加呈先增加后降低趋势;当料浆质量分数增长至高水平(87%)时,此时充填体强度与粉煤灰质量分数之间呈负相关关系。由上述分析可看出,交互作用AD中各因素增加会抑制另一因素对充填体强度的增强作用。
由图4(d)可知,在水泥质量分数从低水平(8%)增长至高水平(12%)的过程中,充填体强度均随碳酸钙质量分数的增加先降低后增加,且充填体强度最小值对应的碳酸钙质量分数均处于同一区间(2%~3%),但充填体最低强度相较于初始强度的减少率由13.5%增加到22.8%;当碳酸钙质量分数不超过3%时,充填体强度随着水泥质量分数的增加而增大;当碳酸钙质量分数高于3%时,充填体强度随着水泥质量分数的增加先增加后降低。因此,交互作用BC中各因素增加会抑制另一因素对充填体强度的增强作用。
由图4(e)可知,当水泥质量分数处于低水平(8%)与高水平(12%)时,充填体强度均随料浆质量分数的增加而增大,但充填体强度的变化量分别为3.48 MPa、1.09 MPa;当料浆质量分数小于等于85%时,充填体强度随着水泥质量分数的增加而增大;当料浆质量分数高于85%时,充填体强度随着水泥质量分数的增加先增加后降低。这是由于料浆质量分数增加会减少充填体内的自由水含量,而过量的水泥会导致水化反应不充分,因此交互作用BD中各因素增加会抑制另一因素对充填体强度的影响作用。
由图4(f)可知,当料浆质量分数处于低水平(83%)时,充填体强度与碳酸钙质量分数之间呈负相关关系;当料浆质量分数处于高水平(87%)时,充填体强度与碳酸钙质量分数之间呈正相关关系。碳酸钙质量分数与料浆质量分数对充填体强度具有相同的影响规律。由此可得,交互作用CD中各因素增加会促进另一因素对充填体强度的增强作用。
综上所述,在高浓度条件下,各种交互作用中,AC对充填体强度没有显著影响,AB、CD的一种因素增加促进另一因素对充填体强度的增强作用,AD、BC、BD交互作用则是一种因素的增加会抑制另一因素对充填体强度的影响。
充填材料配比研究的基本原则为在满足工程运输要求和强度指标的基础上尽可能地降低充填成本。因此充填材料配比设计应在满足坍落度与抗压强度的基础上,选择成本最低的最优方案。
根据某煤矿要求的膏体充填材料性能参数,充填体性能指标设计值见表4。
利用Minitab软件中响应曲面中的响应优化器项,设定充填材料坍落度、7 d、28 d强度为目标值,并将成本设定为最小化目标。粉煤灰、水泥、碳酸钙、工业用水价格分别为100, 310, 420, 3.2 元/t,则每吨充填材料的成本为:
式中,fmin为性价比最优的充填材料成本,元/t。
经计算,在保证充填体性能要求的基础上,充填材料最低成本配比方案为:粉煤灰质量分数为18.0%,水泥质量分数为10.9%,碳酸钙质量分数为1.3%,料浆质量分数为84.0%。此时,充填料浆坍落度为24 cm, 7 d、28 d抗压强度分别为2.37 MPa、6.91 MPa,充填材料成本为57.762 元/t,满足工程实际需要。
(1)基于RSM-CCD法建立了粉煤灰质量分数A、水泥质量分数B、碳酸钙质量分数C、料浆质量分数D为因子,充填材料坍落度及充填体7 d、28 d抗压强度为响应值的完全二次响应面回归模型,模型预测值与实测值较为吻合,可借助回归方程对充填材料坍落度及抗压强度进行预测。
(2)高浓度充填料浆坍落度仅受线性单因素影响,交互作用对其无显著影响,坍落度随A、B、C增加先增大后减小,随D的增加而减小。
(3)线性及交互作用对高浓度充填体7 d、28 d强度均有显著影响,高浓度充填体强度随A、B、D线性变化的变化趋势较低浓度未发生显著改变,随C的增加表现为其降低后升高;交互作用AC与充填体强度不存在显著关系,AB、CD为一种因素的增加会促进另一种因素对充填体28 d抗压强度的增强作用,交互作用AD、BC、BD为一种因素的增加会抑制另一种因素对28 d强度的增强作用。
(4)利用回归模型得到满足运输要求与强度指标的最低成本的充填材料配比方案为粉煤灰质量分数为18.0%,水泥质量分数为10.9%,磷酸钙质量分数为1.3%,料浆质量分数为84.0%。此时,充填料浆坍落度为24 cm,充填体7 d、28 d抗压强度分别为2.37 MPa、6.91 MPa,充填材料成本为57.762 元/t。
  • 国家重点研发计划资助项目(2018YFC0604702)
  • 国家自然科学基金资助项目(51379119)
  • 山东省自然科学基金资助项目(ZR2021ME086)
  • 中国能建重大科技项目(CEEC2021-ZDYF-18)
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2025年第45卷第2期
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  • 接收时间:2024-04-09
  • 首发时间:2026-10-29
  • 出版时间:2025-02-25
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  • 收稿日期:2024-04-09
基金
国家重点研发计划资助项目(2018YFC0604702)
国家自然科学基金资助项目(51379119)
山东省自然科学基金资助项目(ZR2021ME086)
中国能建重大科技项目(CEEC2021-ZDYF-18)
作者信息
    1.山东科技大学 矿山灾害预防控制国家重点实验室培育基地,山东 青岛市 266590
    2.山东科技大学 矿业工程国家级实验教学示范中心,山东 青岛市 266590
    3.中国电力工程顾问集团西北电力设计院有限公司,陕西 西安 710075

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鞠照强(1999—),男,山东德州人,硕士研究生,主要从事矿山充填开采技术研究工作。E-mail:
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2种不同金属材料的力学参数
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属数
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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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