首页> 外文OA文献 >Computer simulation of random parckings for self-similar particle size distributions in soil and granular materials: porosity and pore size distribution
【2h】

Computer simulation of random parckings for self-similar particle size distributions in soil and granular materials: porosity and pore size distribution

机译:土壤和颗粒状材料中自相似粒径分布的随机堆放的计算机模拟:孔隙率和孔径分布

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

A 2D computer simulation method of random packings is applied to sets of particles generated by a self-similar uniparametric model for particle size distributions (PSDs) in granular media. The parameter p which controls the model is the proportion of mass of particles corresponding to the left half of the normalized size interval [0,1]. First the influence on the total porosity of the parameter p is analyzed and interpreted. It is shown that such parameter, and the fractal exponent of the associated power scaling, are efficient packing parameters, but this last one is not in the way predicted in a former published work addressing an analogous research in artificial granular materials. The total porosity reaches the minimum value for p = 0.6. Limited information on the pore size distribution is obtained from the packing simulations and by means of morphological analysis methods. Results show that the range of pore sizes increases for decreasing values of p showing also different shape in the volume pore size distribution. Further research including simulations with a greater number of particles and image resolution are required to obtain finer results on the hierarchical structure of pore space.
机译:将二维随机堆积计算机模拟方法应用于由自相似单参数模型生成的颗粒集,用于颗粒介质中的粒度分布(PSD)。控制模型的参数p是与标准化大小间隔[0,1]左半部分相对应的粒子质量比例。首先,分析和解释对参数p的总孔隙率的影响。结果表明,这样的参数以及相关功率定标的分形指数是有效的填充参数,但是这最后一个并没有像以前发表的针对人工颗粒材料的类似研究那样进行预测。当p = 0.6时,总孔隙率达到最小值。孔径分布的有限信息是通过堆积模拟和形态分析方法获得的。结果表明,随着p值的减小,孔径范围增加,体积体积分布的形状也有所不同。为了获得关于孔隙空间的分层结构的更好结果,需要进一步的研究,包括使用更多数量的粒子和图像分辨率进行模拟。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号