Study of Activation Energy in Soil through Elastic Wave Velocity and Electrical Resistivity

Lee, Jong-Sub; Byun, Yong Hoon; Yoon, Ho‐Geun

doi:10.2136/vzj2016.08.0073

Cited by 4 publications

(10 citation statements)

References 36 publications

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“…In addition, the elastic wave velocity seems to be a good indicator of soil stiffness, and the detailed analyses associated with activation energy analyzed in the context of V p and V s are discussed in the sections below. The results revealed that the water-to-ice phase transformation resulted in a sharp increase in E a near the freezing temperature and a decrease in its bandwidth with a decrease in ∆T, which is consistent with the findings of Lee et al (2017). Particularly, the homogeneously mixed and evaporation-driven specimens exhibited higher E a , whereas the horizontally layered specimen exhibited the lowest E a .…”

Section: Wave Velocitysupporting

confidence: 87%

“…In this study, the effects of the water distribution patterns on the activation energy of unsaturated soils subjected to phase transformations were investigated using elastic wave velocity. This study utilized the physical concepts and fundamental observations reported by Lee et al (2017). We then extend their works to the activation energy of partiallysaturated soils with different water distribution patterns subjected to a freeze-thaw cycle.…”

Section: Introductionmentioning

confidence: 99%

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Effect of water distribution patterns on the activation energy of unsaturated soils during phase transformation

Park

Yoon

Kim

2021

Vadose Zone Journal

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Unsaturated soils in vadose zones often experience periodic phase changes during seasonal temperature fluctuations. The liquid in partially saturated soils significantly affects the physical and chemical processes associated with the phase transformations. This study examined the role of water distribution patterns on the activation energy of unsaturated soils. The results revealed that the homogeneously mixed and evaporation‐driven specimens exhibited higher activation energy than the horizontally layered specimen, which exhibited the lowest activation energy. In addition, the activation energy results indicated that the induction time, increased with an increase in the water saturation, requires a longer induction time and results in a more significant difference in the final products, such as elastic wave velocities, during the freezing process. In addition, the activation energy and soil stiffness results revealed that the homogeneous system required a higher activation energy than the heterogeneous system. The higher heterogeneity degree of the vertically and horizontally layered water specimens delayed the primary water‐to‐ice phase change. This study recognizes the significance of heterogeneity in activation energy for phase transformation in unsaturated particulate media.

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Section: Wave Velocitysupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Effect of water distribution patterns on the activation energy of unsaturated soils during phase transformation

Park

Yoon

Kim

2021

Vadose Zone Journal

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“…Many researchers have tried to study pore structure with experimental techniques that consider component analysis, pore size distribution and the saturated condition. Meanwhile, the geophysical method is an alternative method to determine the contact mechanism in porous materials at a small strain range [3,4].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Cementation Factor of Unconsolidated Granular Materials Through Time Domain Reflectometry with Variable Saturated Conditions

2019

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The cementation factor is necessary to determine porosity via the Archie equation, and its range of values has been suggested in many previous studies. However, the cementation factors in the literature are limited to fully saturated conditions, and it may thus be inaccurate to use the same value in other saturation conditions. The objective of this study is to characterize how the cementation factor varies depending on the saturation percentage. In this study, glass beads and soil are selected as the specimens, and two relative density values, 40% and 80%, are selected. Time domain reflectometry (TDR) is used to obtain both the saturation and electrical resistivity of the specimens. TDR is installed in the cell, and fluid is continuously circulated from the bottom to the top of the porous material for 30 min. The estimated saturation increases with time and the electrical resistivity is reduced during the circulation. Finally, the cementation factor at every saturated stage is determined, and the error ratio based on the porosity is calculated to show the importance of the cementation factor. The results show that there is a high error ratio when an unsuitable cementation factor that does not consider the saturation condition is used. This study demonstrates that the method for determining the actual cementation factor using TDR and the Archie equation can be applied in various saturation conditions.

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“…Equation (2) is often used in the field of geotechnical and geological engineering to derive porosity as a design parameter [ 17 , 18 ]. In addition, studies to understand particle properties were performed by linking the contact characteristics and cementation effects of soil materials since α and m values were related to particle shape [ 19 , 20 ].…”

Section: Background Theorymentioning

confidence: 99%

Discontinuity Predictions of Porosity and Hydraulic Conductivity Based on Electrical Resistivity in Slopes through Deep Learning Algorithms

Lee

Yoon

2021

Sensors

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Electrical resistivity is used to obtain various types of information for soil strata. Hence, the prediction of electrical resistivity is helpful to predict the future behavior of soil. The objective of this study is to apply deep learning algorithms, including deep neural network (DNN), long-short term memory (LSTM), and gated recurrent unit (GRU), to determine the reliability of electrical resistivity predictions to find the discontinuity of porosity and hydraulic conductivity. New DNN-based algorithms, i.e., LSTM-DNN and GRU-DNN, are also applied in this study. The electrical resistivity values are obtained using 101 electrodes installed at 2 m intervals on a mountaintop, and a Wenner array is selected to simplify the electrode installation and measurement. A total of 1650 electrical resistivity values are obtained for one measurement considering the electrode spacing, and accumulated data measured for 15 months are used in the deep learning analysis. A constant ratio of 6:2:2 among the training, validation, and test data, respectively, is used for the measured electrical resistivity, and the hyperparameters in each algorithm are moderated to improve the reliability. Based on the deep learning model results, the distributions of porosity and hydraulic conductivity are deduced, and an average depth of 25 m is estimated for the discontinuity depth. This paper shows that the deep learning technique is well used to predict electrical resistivity, porosity, hydraulic conductivity, and discontinuity depth.

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Study of Activation Energy in Soil through Elastic Wave Velocity and Electrical Resistivity

Abstract: Core Ideas• The Arrhenius equation was applied to predict geophysical properties. • Elastic and electromagnetic waves were selected. • The activation energy exhibited a nonlinear curve.

Cited by 4 publications

References 36 publications

Effect of water distribution patterns on the activation energy of unsaturated soils during phase transformation

Effect of water distribution patterns on the activation energy of unsaturated soils during phase transformation

Characterization of Cementation Factor of Unconsolidated Granular Materials Through Time Domain Reflectometry with Variable Saturated Conditions

Discontinuity Predictions of Porosity and Hydraulic Conductivity Based on Electrical Resistivity in Slopes through Deep Learning Algorithms

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