东北大学学报（自然科学版）

东北大学学报（自然科学版） ›› 2021, Vol. 42 ›› Issue (2): 232-241.DOI: 10.12068/j.issn.1005-3026.2021.02.013

• 资源与土木工程 • 上一篇    下一篇

充填体强度影响因素及组合预测模型

张鹏1,2， 高谦1， 温震江1， 张涛1,2   

  1. (1. 北京科技大学 金属矿山高效开采与安全教育部重点实验室， 北京100083; 2. 内蒙古工业大学 矿业学院， 内蒙古自治区 呼和浩特010321)
  • 收稿日期:2020-01-16 修回日期:2020-01-16 接受日期:2020-01-16 发布日期:2021-03-05
  • 通讯作者: 张鹏
  • 作者简介:张鹏(1987-)，男，内蒙古呼和浩特人，北京科技大学博士研究生； 高谦(1956-)，男，江苏徐州人，北京科技大学教授，博士生导师.
  • 基金资助:
    国家重点研发计划项目(2017YFC0602903)； 内蒙古自治区高等学校科学研究项目(NJZY17094)； 内蒙古工业大学自然科学基金资助项目(RZ1900000349).

Influencing Factors on Backfill Strength and a Combined Strength Prediction Model

ZHANG Peng1,2， GAO Qian1， WEN Zhen-jiang1， ZHANG Tao1,2   

  1. 1. Key Laboratory of High Efficient Mining and Safety of Metal Mine， Ministry of Education， University of Science and Technology Beijing， Beijing 100083， China; 2. Institute of Mining Technology， Inner Mongolia University of Technology， Hohhot 010321， China.
  • Received:2020-01-16 Revised:2020-01-16 Accepted:2020-01-16 Published:2021-03-05
  • Contact: ZHANG Peng
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摘要： 水灰比、堆积密实度和比表面积是充填体强度的重要影响因素，但有关各因素对强度影响显著性的研究较少，为此通过3因素5水平正交试验，分别对龄期为3d，7d和28d的试块开展单轴抗压强度试验.对试验结果进行方差分析，获得不同龄期各因素F统计值比(水灰比∶堆积密实度∶比表面积):3d为698.404∶26.148∶0.910，7d为862.626∶35.465∶1.286，28d为1585.404∶31.695∶1.338.分析各因素F统计值和P值，确定因素显著性大小关系为:水灰比>比表面积>堆积密实度;水灰比和比表面积为主要影响因素，堆积密实度为次要因素，所以控制水灰比可以有效控制充填体强度.绘制各因素水平趋势图，以最有利于充填体抗压强度原则确定最优组合为水灰比1.2，比表面积410m2/kg，堆积密实度0.6%.改变最优配比中水灰比值，开展30组不同水灰比的3d，7d和28d试块的抗压强度试验.以试验强度为原始数据，结合灰色预测、模糊分类和马尔可夫理论，建立3d，7d和28d试块强度组合预测模型；分析实测值与GM(1，2)模型、曲线回归模型和组合模型预测平均相对残差，结果表明，组合模型较其他模型具有较高的精度和稳定性.

关键词: 充填体强度;方差分析;正交试验;灰色理论;模糊集合;马尔可夫

Abstract: The water-cement ratio， packing density and specific surface area are important factors that influence backfill strength. However， few studies have investigated the significance of these influencing factors. Hence， uniaxial compressive strength tests were carried out on test blocks aged 3d， 7d and 28d using a 3-factor 5-level orthogonal design. A variance analysis was performed on the experimental results. The results from this statistical analysis indicated the following F-value ratios for the three factors(water-cement ratio∶packing density∶specific surface area) at different ages: 3d(698.404∶26.148∶0.910)， 7d(862.626∶35.465∶1.286) and 28d(1585.404∶31.695∶1.338). According to the analysis results， the influencing factors had the following order of significance: water-cement ratio > specific surface area > packing density. Due to the small F-values of the specific surface area and packing density， these variables were not considered as factors affecting strength when establishing a strength prediction model. To obtain a backfill with the maximum strength， the optimal mixture had a 1.2 water-cement ratio， a specific surface area of 410m2/kg， and a packing density of 0.6%. To study the relationship between the water-cement ratio and strength， the water-cement ratio in the optimal mixture was varied， and 30 groups of strength tests were performed with samples containing different water-cement ratios after ageing for 3d， 7d and 28d. Based on the experimental results， a combined model was established for predicting strength at 3d， 7d and 28d with a combination of grey theory， fuzzy set theory and Markov theory. The measured values were plotted on the same scatter diagram as the values predicted with the GM(1，2) model， the regression analysis model and the combined model. A subsequent analysis verified that the combined model had higher accuracy and robustness than other models.

Key words: backfill strength; variance analysis; orthogonal test; grey theory; fuzzy set; Markov

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