Improving Hydraulic Conductivity Estimation for Soft Clayey Soils, Sediments, or Tailings Using Predictors Measured at High-Void Ratio: Fid-Bau Portal

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Improving Hydraulic Conductivity Estimation for Soft Clayey Soils, Sediments, or Tailings Using Predictors Measured at High-Void Ratio

Babaoglu, Y. / Simms, P.

Consolidation parameters are required to support the disposal management of soft soils or mine tailings. The estimation of these parameters from simple correlations using easily measured properties can be advantageous, and considerable work has been done on this topic. This paper proposes two innovations that advance this work: (1) hydraulic conductivity–void ratio ( $k - e$ ) estimation can be substantially improved by using a single measured value at a high-void ratio, and (2) the compressibility curve itself can be a useful predictor of $k - e$ . Using these findings, general equations are derived that describe $k - e$ using a power law, where the power is either 4 or 5. Examining 79 $k - e$ data sets from clays, clayey tailings, and dredged materials, 94% of all predicted $k$ values are within an order of magnitude of measured $k - e$ values. This level of accuracy, coupled with the advantage of anchoring the $k - e$ function by a measured value at a high-void ratio, is shown to result in robust predictions of settlement in large strain consolidation analyses.

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Improving Hydraulic Conductivity Estimation for Soft Clayey Soils, Sediments, or Tailings Using Predictors Measured at High-Void Ratio

Babaoglu, Y. / Simms, P.

Consolidation parameters are required to support the disposal management of soft soils or mine tailings. The estimation of these parameters from simple correlations using easily measured properties can be advantageous, and considerable work has been done on this topic. This paper proposes two innovations that advance this work: (1) hydraulic conductivity–void ratio ( $k - e$ ) estimation can be substantially improved by using a single measured value at a high-void ratio, and (2) the compressibility curve itself can be a useful predictor of $k - e$ . Using these findings, general equations are derived that describe $k - e$ using a power law, where the power is either 4 or 5. Examining 79 $k - e$ data sets from clays, clayey tailings, and dredged materials, 94% of all predicted $k$ values are within an order of magnitude of measured $k - e$ values. This level of accuracy, coupled with the advantage of anchoring the $k - e$ function by a measured value at a high-void ratio, is shown to result in robust predictions of settlement in large strain consolidation analyses.

Improving Hydraulic Conductivity Estimation for Soft Clayey Soils, Sediments, or Tailings Using Predictors Measured at High-Void Ratio

Babaoglu, Y. / Simms, P.

Consolidation parameters are required to support the disposal management of soft soils or mine tailings. The estimation of these parameters from simple correlations using easily measured properties can be advantageous, and considerable work has been done on this topic. This paper proposes two innovations that advance this work: (1) hydraulic conductivity–void ratio ( $k - e$ ) estimation can be substantially improved by using a single measured value at a high-void ratio, and (2) the compressibility curve itself can be a useful predictor of $k - e$ . Using these findings, general equations are derived that describe $k - e$ using a power law, where the power is either 4 or 5. Examining 79 $k - e$ data sets from clays, clayey tailings, and dredged materials, 94% of all predicted $k$ values are within an order of magnitude of measured $k - e$ values. This level of accuracy, coupled with the advantage of anchoring the $k - e$ function by a measured value at a high-void ratio, is shown to result in robust predictions of settlement in large strain consolidation analyses.

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Title:

Improving Hydraulic Conductivity Estimation for Soft Clayey Soils, Sediments, or Tailings Using Predictors Measured at High-Void Ratio

Contributors:

Babaoglu, Y. (author) / Simms, P. (author)

Published in:

Journal of Geotechnical and Geoenvironmental Engineering ; 146

Publication date:

2020-07-23

ISSN:

1090-0241 , 1943-5606

DOI:

https://doi.org/10.1061/(ASCE)GT.1943-5606.0002344

Type of media:

Article (Journal)

Type of material:

Electronic Resource

Language:

Unknown

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