scholarly journals A New Modified Model of the Streaming Potential Coupling Coefficient Depends on Structural Parameters of Soil-Rock Mixture

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xin Zhang ◽  
Mingjie Zhao ◽  
Kui Wang
Keyword(s):  
Experimental Data ◽  
Coupling Coefficient ◽  
Permeability Coefficient ◽  
Prediction Accuracy ◽  
Structural Parameters ◽  
Streaming Potential ◽  
Potential Effect ◽  
Structure Evolution ◽  
Embankment Dam ◽  
Modified Model

The streaming potential effect in soil-rock mixture (SRM) is related to the compactness and rock content, but there is no model to quantitatively describe this behavior. In this paper, the Kozeny–Carman (KC) equation is modified by using the compactness and rock content. Then, the modified KC equation is substituted into the equation of streaming potential coupling coefficient. A new modified model of streaming potential coupling coefficient that depends on the compactness, rock content, particle shape, and particle gradation is proposed. The reliability of the new modified model is tested by experiments, and the applicable scope of the model is obtained. The results show that when the rock content is 30%, the permeability coefficient prediction accuracy of the modified KC equation is higher in the range of 85–95% compactness. The new modified model of the streaming potential coupling coefficient represents well the control of the compactness (75–95%) on the coupling coefficient. When the compactness remains 85%, the permeability coefficient calculated by the modified KC equation in the range of 10–70% rock content is consistent with the experimental data. The influence of the rock content (10–90%) on the coupling coefficient is well described by the new modified model of the streaming potential coupling coefficient. The new modified model of streaming potential coupling coefficient is helpful to quantitatively evaluate the internal structure evolution of embankment dam by using streaming potential phenomenon.

scholarly journals Understanding the Influence of Rock Content on Streaming Potential Phenomenon of Soil–Rock Mixture: An Experimental Study

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 585
Author(s):  
Xin Zhang ◽  
Mingjie Zhao ◽  
Kui Wang
Keyword(s):  
Experimental Study ◽  
Negative Correlation ◽  
Coupling Coefficient ◽  
Structural Factor ◽  
Permeability Coefficient ◽  
Streaming Potential ◽  
Potential Effect ◽  
Test Results ◽  
Test Apparatus ◽  
Potential Test

To applicate streaming potential phenomenon to study the seepage feature in the soil–rock mixture (SRM), research on the variation in the streaming potential phenomenon of SRM is the precondition. This paper deals, in assistance with the streaming potential test apparatus, with the streaming potential effect response of SRM subjected to different rock contents. The test results show that when the rock content increases from 10% to 30%, the streaming potential coupling coefficient increases with the increases in rock content at 85% compactness and 0.01 mol L−1 salinity. When the rock content is more than 30%, the streaming potential coupling coefficient decreases with the increases in rock content. As the rock content increases, the permeability coefficient has a negative correlation with the streaming potential coupling coefficient. The streaming potential increases first and then goes down with the increases in rock content, and the streaming potential decreases significantly when the rock content exceeds 50%. The findings indicate that the rock content is the key structural factor that restricts the streaming potential phenomenon of the SRM.

scholarly journals Examination of a Theoretical Model of Streaming Potential Coupling Coefficient

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
D. T. Luong ◽  
R. Sprik
Keyword(s):  
Experimental Data ◽  
Theoretical Model ◽  
Zeta Potential ◽  
Coupling Coefficient ◽  
Electrolyte Concentration ◽  
Streaming Potential ◽  
Data Sets ◽  
Fluid Temperature ◽  
Potential Measurement ◽  
Streaming Potentials

Seismoelectric effects and streaming potentials play an important role in geophysical applications. The key parameter for those phenomena is the streaming potential coupling coefficient, which is, for example, dependent on the zeta potential of the interface of the porous rocks. Comparison of an existing theoretical model to experimental data sets from available published data for streaming potentials has been performed. However, the existing experimental data sets are based on samples with dissimilar fluid conductivity, pH of pore fluid, temperature, and sample compositions. All those dissimilarities may cause the observed deviations. To critically assess the models, we have carried out streaming potential measurement as a function of electrolyte concentration and temperature for a set of well-defined consolidated samples. The results show that the existing theoretical model is not in good agreement with the experimental observations when varying the electrolyte concentration, especially at low electrolyte concentration. However, if we use a modified model in which the zeta potential is considered to be constant over the electrolyte concentration, the model fits the experimental data well in a whole range of concentration. Also, for temperature dependence, the comparison shows that the theoretical model is not fully adequate to describe the experimental data but does describe correctly the increasing trend of the coupling coefficient as function of temperature.

scholarly journals Experimental Study on the Streaming Potential Phenomenon Response to Compactness and Salinity in Soil–Rock Mixture

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2071
Author(s):  
Xin Zhang ◽  
Mingjie Zhao ◽  
Kui Wang
Keyword(s):  
Coupling Coefficient ◽  
Permeability Coefficient ◽  
Streaming Potential ◽  
Bound Water ◽  
Clay Content ◽  
Water Layer ◽  
Material Structure ◽  
Soil Matrix ◽  
Embankment Dams ◽  
Self Potential

The study on the effect of material structure and solution properties on the streaming potential of the soil–rock mixture (SRM) will be beneficial for improving the reliability of the measurement results for self-potential monitoring in embankment dams. We design two experimental groups and investigate the changes of potential and pressure during seepage of SRM (slightly clay materials) with different compactness and different concentration. The effects of the compaction degree and solution concentration on the streaming potential coupling coefficient and streaming potential were analyzed. The test results demonstrate that when the clay content in soil matrix is slight, the potential has a linear relationship with the hydraulic head difference, and seepage obeys Darcy’s law. The surface conductivity is negligible at 0.01 M (1 M corresponds to a concentration of 58.4 g L−1) salinity, the compactness of the SRM decreases (the permeability coefficient increases), the apparent streaming potential coupling coefficient and pressure difference decrease is the reason streaming potential decreases. The permeability coefficient of the SRM is not affected by the change in salinity (0.0001–1 M) at 85% compactness, and its seepage characteristics are related to the mineral composition, morphology and the thickness of the bound water layer (electric double layer). This study lays a foundation for further research on the self-potential method to monitor the structure of embankment dams.

scholarly journals A Study of Developing a Prediction Equation of Electricity Energy Output via Photovoltaic Modules

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1503
Author(s):  
Minsu Kim ◽  
Hongmyeong Kim ◽  
Jae Hak Jung
Keyword(s):  
Experimental Data ◽  
Real Time ◽  
Air Temperature ◽  
Temperature Difference ◽  
Prediction Accuracy ◽  
Prediction Equation ◽  
Energy Output ◽  
Photovoltaic Modules ◽  
Mean Error ◽  
Pv Module

Various equations are being developed and applied to predict photovoltaic (PV) module generation. Currently, quite diverse methods for predicting module generation are available, with most equations showing accuracy with ≤5% error. However, the accuracy can be determined only when the module temperature and the value of irradiation that reaches the module surface are precisely known. The prediction accuracy of outdoor generation is actually extremely low, as the method for predicting outdoor module temperature has extremely low accuracy. The change in module temperature cannot be predicted accurately because of the real-time change of irradiation and air temperature outdoors. Calculations using conventional equations from other studies show a mean error of temperature difference of 4.23 °C. In this study, an equation was developed and verified that can predict the precise module temperature up to 1.64 °C, based on the experimental data obtained after installing an actual outdoor module.

The Determination of Electrokinetic Coupling-Coefficient and Zeta Potential of Rock Samples by Electrokinetic Measurements

2012 ◽  
Vol 516-517 ◽  
pp. 1870-1873 ◽  
Author(s):  
Jun Wang ◽  
Heng Shan Hu
Keyword(s):  
Zeta Potential ◽  
Coupling Coefficient ◽  
Streaming Potential ◽  
Potential Method ◽  
Surface Conductivity ◽  
Reliable Estimate ◽  
Surface Conductance ◽  
Streaming Current ◽  
Low Concentrations

The electrokinetic effects are important in the understanding of electric properties in porous medium. In this study, the streaming potential and streaming current of saturated samples are measured at different concentrations, then three methods are applied to obtain the zeta-potential and electrokinetic coupling coefficient. The study shows that the results obtained from streaming potential and streaming current methods agree well with each other, but the results obtained from simplified streaming potential method become seriously inaccurate at low concentrations due to the influence of surface conductance. This experimental study also provides a reliable estimate of the surface conductivity and its contribution to zeta-potential at given concentrations.

Streaming potential coupling coefficient in unsaturated carbonate rocks

2017 ◽  
Vol 210 (1) ◽  
pp. 291-302 ◽  
Author(s):  
A. Cerepi ◽  
A. Cherubini ◽  
B. Garcia ◽  
H. Deschamps ◽  
A. Revil
Keyword(s):  
Coupling Coefficient ◽  
Carbonate Rocks ◽  
Streaming Potential

scholarly journals Ba5(IO6)2: crystal structure evolution from room temperature to 80 K

2021 ◽  
Vol 77 (6) ◽  
pp. 634-637
Author(s):  
David Wenhua Bi ◽  
Priya Ranjan Baral ◽  
Arnaud Magrez
Keyword(s):  
Crystal Structure ◽  
Room Temperature ◽  
Structural Transition ◽  
Rietveld Method ◽  
Structural Parameters ◽  
Structure Evolution ◽  
X Ray Diffraction ◽  
Lattice Contraction ◽  
Interatomic Distances ◽  
Crystallographic Axes

The crystal structure of Ba5(IO6)2, pentabarium bis(orthoperiodate), has been re-investigated at room temperature based on single-crystal X-ray diffraction data. In comparison with a previous crystal structure determination by the Rietveld method, an improved precision of the structural parameters was achieved. Additionally, low-temperature measurements allowed the crystal structure evolution to be studied down to 80 K. No evidence of structural transition was found even at the lowest temperature. Upon cooling, the lattice contraction is more pronounced along the b axis. This contraction is found to be inhomogeneous along different crystallographic axes. The interatomic distances between different Ba atoms reduce drastically with lowering temperature, resulting in a closer packing around the IO6 octahedra, which remain largely unaffected.

Systematic ab initio study of the compressibility of silicate garnets

2001 ◽  
Vol 57 (2) ◽  
pp. 163-177 ◽  
Author(s):  
V. Milman ◽  
E. V. Akhmatskaya ◽  
R. H. Nobes ◽  
B. Winkler ◽  
C. J. Pickard ◽  
...  
Keyword(s):  
Experimental Data ◽  
Density Functional ◽  
Structural Parameters ◽  
Applied Pressure ◽  
Basis Set ◽  
Ionic Radii ◽  
Cell Parameters ◽  
The Density Functional Theory ◽  
Dodecahedral Site ◽  
Compression Mechanism

The structural properties of the silicate garnets andradite, Ca3Fe2Si3O12, uvarovite, Ca3Cr2Si3O12, knorringite, Mg3Cr2Si3O12, goldmanite, Ca3V2Si3O12, blythite, Mn^{2+}_3Mn^{3+}_2Si3O12, skiagite, Fe^{2+}_3Fe^{3+}_2Si3O12, calderite, Mn^{2+}_3Fe^{3+}_2Si3O12, and khoharite, Mg3Fe^{3+}_2Si3O12, have been investigated with a quantum-mechanical model as a function of applied pressure. The study has been performed with the density functional theory code CASTEP, which uses pseudopotentials and a plane-wave basis set. All structural parameters have been optimized. The calculated static geometries (cell parameters, internal coordinates of atoms and bond lengths), bulk moduli and their pressure derivatives are in good agreement with the experimental data available. Predictions are made for those cases where no experimental data have been reported. The data clearly indicate that the elastic properties of all silicate garnets are dominated by the compressibility of the dodecahedral site. The compression mechanism is found to be based on a bending of the angle between the centers of the SiO4 tetrahedra and the adjacent octahedra, as in the aluminosilicate garnets. An analysis of the relationship between ionic radii of the cations and the compressibility of silicate garnets is presented.

Colmatage naturel d'un milieu filtrant par les particules en suspension dans l'eau

1979 ◽  
Vol 6 (2) ◽  
pp. 243-252
Author(s):  
Marcel Frenette ◽  
Conrad Anctil
Keyword(s):  
Experimental Data ◽  
Porous Media ◽  
Suspended Sediment ◽  
Permeability Coefficient ◽  
General Study

This paper contains a general study on the natural clogging of porous media by suspended sediment in water. This creates with time a decrease in the permeability coefficient and consequently a reduction of the seepage flow.Two theories are presented and compared for the prediction of the rate of clogging in nature. The two approaches have been verified by experimental data obtained from tests carried out at Laval University. Results have permitted the limits of application of each method to be denned.

Determining Usefulness of Machine Learning in Materials Discovery Using Simulated Research Landscapes

2021 ◽  
Author(s):  
Marcos del Cueto ◽  
Alessandro Troisi
Keyword(s):  
Machine Learning ◽  
Experimental Data ◽  
Data Acquisition ◽  
Prediction Accuracy ◽  
New Materials

When existing experimental data are combined with machine learning (ML) to predict the performance of new materials, the data acquisition bias determines ML usefulness and the prediction accuracy. In this...

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