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Using Grain-Size Distribution Methods for Estimation of Air Permeability.

Tiejun Wang, Yuanyang Huang1,2, Xunhong Chen1

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Estimating air permeability (ka) at dry conditions is challenging. This study found that grain-size distribution (GSD) equations can efficiently estimate ka in river sediments, with improved accuracy after coefficient adjustment.

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Area of Science:

  • Environmental Science
  • Geotechnical Engineering
  • Soil Physics

Background:

  • Accurate air permeability (ka) at dry conditions is crucial for porous media air flow models.
  • Direct measurement of dry ka is often difficult and time-consuming.
  • Estimating dry ka from readily available properties is highly desirable.

Purpose of the Study:

  • To assess the feasibility of using grain-size distributions (GSDs) to estimate dry air permeability (ka).
  • To evaluate the performance of existing GSD-based equations for predicting dry ka.
  • To determine the potential for GSD-based methods as an efficient alternative for ka estimation.

Main Methods:

  • Tested fourteen GSD-based equations originally developed for saturated hydraulic conductivity.
  • Used measured dry ka data from both undisturbed and disturbed river sediment samples.
  • Analyzed estimation accuracy and improved predictions through coefficient adjustment.

Main Results:

  • Most GSD-based equations estimated ka within a factor of ±4 times the measured values.
  • Terzaghi and Hazen-modified methods showed comparable results for both sample types.
  • Adjusting coefficients significantly improved estimation accuracy to within ±4% on average.

Conclusions:

  • GSD-based equations offer a promising and efficient approach for estimating dry air permeability.
  • These methods can reduce the time and effort required for ka measurements.
  • Further refinement of GSD-based equations can enhance their predictive power for porous media.