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硅酸盐通报 ›› 2022, Vol. 41 ›› Issue (4): 1388-1394.

• 资源综合利用 • 上一篇    下一篇

基于MATLAB随机试验的砂细度模数公式优化研究

秦超宁1, 汪丽娟1, 杨重卿1, 孙呈鹏1, 韩照2, 乔宏霞2   

  1. 1.甘肃建投绿色建材产业发展集团有限公司,兰州 730050;
    2.兰州理工大学土木工程学院,兰州 730050
  • 收稿日期:2021-12-09 修回日期:2021-12-29 出版日期:2022-04-15 发布日期:2022-04-27
  • 通讯作者: 韩 照,博士,讲师。E-mail:westaaron@163.com
  • 作者简介:秦超宁(1980—),男,高工。主要从事智慧矿山建设及绿色建材的研究。E-mail:1181279025@qq.com
  • 基金资助:
    国家自然科学基金(52108219,52008196);国家自然科学基金区域重点联合项目(U21A20150);甘肃省青年科技基金(20JR5RA440)

Optimization of Sand Fineness Modulus Formula Based on MATLAB Random Test

QIN Chaoning1, WANG Lijuan1, YANG Zhongqing1, SUN Chengpeng1, HAN Zhao2, QIAO Hongxia2   

  1. 1. Gansu Jiantou Green Building Materials Industry Development Group Co., Ltd., Lanzhou 730050, China;
    2. School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China
  • Received:2021-12-09 Revised:2021-12-29 Online:2022-04-15 Published:2022-04-27

摘要: 细度模数是衡量砂粗细程度的重要指标。当前国标细度模数公式未涉及粒级为0.15 mm以下的颗粒,本文将粒级0.15 mm以下颗粒进一步细分为0.075~0.15 mm粒级与0.075 mm以下粒级,将这两粒级纳入细度模数公式后形成了三个新的细度模数公式。通过MATLAB软件中rand函数随机大量生成四种不同细度模数试验,结合花岗岩机制砂、凝灰岩机制砂、天然砂的筛分试验进一步验证不同细度模数公式的优劣性,在筛分的同时即可测得机制砂近似石粉含量,将近似石粉含量与标准方法测得的石粉含量进行线性回归,可拟合出两者之间的经验公式。研究表明:原细度模数公式分子上增加0.075~0.15 mm粒级颗粒筛分含量后,更有利于表征砂的粗细程度。近似石粉含量与标准石粉含量差值为1.346 6%,经SEM对不同砂样表面放大100倍后,发现砂样表面越粗糙对石粉的吸附性越大,近似石粉含量与标准石粉含量差值的波动性也越大。

关键词: 砂, 细度模数, 随机试验, 优化, 石粉, MATLAB软件

Abstract: Fineness modulus is an important index to measure the fineness of sand. The current national standard fineness modulus formula does not involve particles with particle size below 0.15 mm. In this paper, the particles with particle size below 0.15 mm were further subdivided into 0.075~0.15 mm and smaller than 0.075 mm,and three new fineness modulus formulas were formed by incorporating these two grades into the fineness mode formula. Four different fineness modulus tests were randomly generated by rand function in MATLAB software, combined with the screening test of granite manufactured sand, tuff manufactured sand and nature sand, the advantages and disadvantages of different fineness modulus formulas were further verified. The approximate stone powder content of manufactured sand measured at the same time of screening. The empirical formula between the approximate stone powder content and the stone powder content measured by the standard method fitted by linear regression. Research shows that the addition of particles with particle size of 0.075~0.15 mm screening content to the numerator of the original fineness modulus formula is more conducive to characterize the fineness of sand. The difference between the content of approximate stone powder and standard stone powder is 1.346 6%.The surface of different sand samples is magnified by 100 times by SEM. It is found that the coarser the surface of sand samples, the greater the adsorption of stone powder, and the greater the volatility of the difference between approximate stone powder content and standard stone powder content.

Key words: sand, fineness modulus, random test, optimization, stone powder, MATLAB software

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