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M.S. Thesis.Onur_Emine.pdf (2.4 MB)

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PREDICTING THE PERMEABILITY OF SANDY SOILS FROM GRAIN SIZE DISTRIBUTIONS

Onur, Emine Mercan
http://rave.ohiolink.edu/etdc/view?acc_num=kent1389550812

Abstract Details

2014, MS, Kent State University, College of Arts and Sciences / Department of Earth Sciences.
Permeability is one of the most important and frequently used properties of soils. Grain size distribution and density are known to influence the permeability of sandy soils. Although the relationships between grain size distribution and permeability has been quantified in previous studies, the influenced of density has not been quantified. The objective of this research was to investigate the quantitative relationships between permeability and grain size distribution indices such as effective particle size (D10), coefficient of uniformity (Cu), coefficient of curvature (Cc), percentage of coarse sand fraction by weight of sample (%C), percentage of medium sand fraction by weight of sample (%M), and percentage of fine sand fraction by weight of sample (%F) to determine whether these relationships could be used for reliable estimates of permeability. Six samples of sandy soils, ranging from well graded to poorly graded, were tested in the laboratory to determine their grain size distribution, maximum dry density (MDD), and optimum water content (OWC). The D10, Cu, Cc, %C, %M, and %F values for each soil were calculated from the grain size distribution plots. Based on the compaction curves, five replicate samples of each soil were prepared at varying dry density values and tested for permeability using the constant head permeability test. Results show that the lowest permeability for sandy soils is achieved at or slightly on the dry side of OWC. To investigate the relationship between permeability and grain size distribution indices, bivariate and step-wise regression analyses were performed. The results show that D10, density, and %M have the strongest correlation (Adjusted R2 = 0.67) with permeability, explaining 67% of the variability in permeability. Permeability depends on the sizes and shapes of interconnections between adjacent pores which, in turn, are influenced by the entire grain size distribution. This research proposes a new grain size distribution index for predicting permeability, designated as the new permeability index. In addition to considering the entire grain size distribution, the new permeability index assigns different weights to different size fractions in the soil with the finest fraction having the maximum weight and the coarsest fraction having the least weight. The new permeability index values for the six soils were correlated with their corresponding permeability values, resulting in a second order quadratic equation with an R2 value of 0.76. This relationship can reliably be used to predict permeability as is indicated by the small amount of residuals between measured and predicted values of permeability. A 3-D model was developed to show the combined effect of the new permeability index and density on permeability.
Abdul Shakoor (Advisor)
123 p.
Geology
Permeability, Grain size distribution, Grain size distribution indices, Density, Sandy soils, Statistical analysis, Permeability index

Recommended Citations

Citations

  • Onur, E. M. (2014). PREDICTING THE PERMEABILITY OF SANDY SOILS FROM GRAIN SIZE DISTRIBUTIONS [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1389550812

    APA Style (7th edition)

  • Onur, Emine. PREDICTING THE PERMEABILITY OF SANDY SOILS FROM GRAIN SIZE DISTRIBUTIONS. 2014. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1389550812.

    MLA Style (8th edition)

  • Onur, Emine. "PREDICTING THE PERMEABILITY OF SANDY SOILS FROM GRAIN SIZE DISTRIBUTIONS." Master's thesis, Kent State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1389550812

    Chicago Manual of Style (17th edition)

kent1389550812
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This open access ETD is published by Kent State University and OhioLINK.