• DocumentCode
    3774106
  • Title

    Prediction of the Pore Size Distribution in Spunbond-Needlepunched Nonwoven Geotextiles Based on a Stochastic Simulation

  • Author

    Zhang Heng;Qian Xiaoming

  • Author_Institution
    Coll. of Textiles, Tianjin Polytech. Univ., Tianjin, China
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    655
  • Lastpage
    658
  • Abstract
    Pore size distribution is the key factor of the nonwoven geotextiles for various functions including filtration, separation and reinforcement. The comparison of pore size distributions of spunbond-needle punched nonwoven geotextiles has been made among the theoretical, experimental and the virtual study based on a stochastic simulation. Moreover, the influence of fiber diameter, solid volume fraction, and the thickness of the nonwoven geotextiles on the pore size distribution of the nonwoven geotextiles has been investigated. It is demonstrated that the pore size distribution, which obtained using Geodict® based on a stochastic simulation, shows a good agreement with experimental data and theoretical, and it is feasible for the prediction of pore size distribution in spunbond-needle punched nonwoven geotextiles. The results show that increasing the solid volume fraction would decrease the pore size of the nonwoven geotextiles under the same filament diameter and same thickness of the webs. Increasing fiber diameter would cause the pore size decreasing, while thickness and solid volume fraction kept constant also found. The results also show that the pore size decreasing with the thickness of the nonwoven geotextiles increasing, while the constant of the solid volume fraction and filaments diameter.
  • Keywords
    "Solids","Mathematical model","Optical fiber networks","Geometry","Predictive models","Filtration","Polymers"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2015 8th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICICTA.2015.166
  • Filename
    7473382