Micro–Macro-Analysis and Model Derivation of Electrical Resistivity of Ningxia Cement–Loess
Abstract
1. Introduction
2. Materials and Methods
2.1. Properties of Loess
2.2. Experimental Apparatus and Procedure
- (1).
- According to the designed water content, dry density, and cement dosage, the corresponding mass of water, loess, and cement was mixed evenly and then layered into the test box to ensure uniform sample density.
- (2).
- The prepared cement–loess samples were wrapped with a plastic bag to prevent water content loss. After the labeling was completed, the samples were placed in a standard curing machine (temperature: 20 °C; humidity: 95%) with the corresponding curing ages (1, 7, 14, and 28 days).
- (3).
- A sample that reached the corresponding curing age was removed from the bag and quickly placed into the electrical resistivity testing box, the digital bridge instrument was connected with the electrical resistivity testing box, and then the electrical resistivity of the cement–loess sample was measured and recorded at the selected frequency of 50 kHz.
- (4).
- Different water contents (8 and 12.5%) and cement dosages (6, 9, and 12%) were selected for microscopic mechanism analysis at curing ages of 1, 7, and 28 days. After the measurement of electrical resistivity, the samples were terminated in their hydration reaction by low-temperature drying and sealed in a plastic bag for preservation [28].
- (5).
- The microscopic structure sample was cut and polished from an intact internal part, and the sample size was 1 cm × 1 cm × 0.5 cm. The SEM (Saimofei QuattroS, Waltham, MA, USA) was adopted to observe the microscopic structure.
- (6).
- Taken from the central part of the cement–loess samples, an agate mortar was used to grind the sample into a powder for XRD and TG/DTG (TA Q600, USA) experiments, which can reflect the changing mineral composition under various conditions.
3. Results and Discussion
3.1. Electrical Resistivity Behavior of Cement–Loess
3.1.1. Dry Density and Water Content
3.1.2. Curing Age and Cement Dosage
3.2. Microstructure and Weight Loss Curve
3.2.1. Microstructure
3.2.2. Weight Loss Curve
3.3. Electrical Resistivity Model
Derivation of Electrical Resistivity Model
4. Conclusions
- (1).
- The electrical resistivity of cement–loess decreased with the dry density and water content, whereas it increased with the cement dosage and curing age. If the water content was higher than its optimal value (11%), the reduction in electrical resistivity was 23.4%, which was 38.1% lower than that at a water content of 8~10%. This included the soluble salts in the loess that dissolve in the pore water. In addition, the hydration reaction potential was insufficient when using a cement dosage of 9% compared to that achieved at 12%. Therefore, the electrical resistivity at a cement dosage of 12% was 22.8% higher than that at a cement dosage of 9% at a curing age of 28 days.
- (2).
- A higher cement dosage, increased water content, and extended curing age contributed to improved hydration reactions within the cement–soil system. As a result, a greater quantity of C-S-H gel was produced. The hydration reaction consumed the water in the soil, and the filling of the pores by the hydration products reduced the pores and increased the resistivity. Additionally, the increase in hydration reduced the orientation microscopically, which induced the increase in cement–loess electrical resistivity.
- (3).
- A modified Archie resistivity formula was used to establish a power-law regression model, which considers ρd·w and aw·T independently. Further, a three-dimensional fitting model was established using water content, dry density, curing age and cement dosage as comprehensive influencing factors. Finally, the prediction accuracy of the electrical resistivity model was 0.94 R2. Therefore, the electrical resistivity could quantitatively express the influencing factors, which proved that the electrical resistivity is very important.
- (4).
- In the practical application, we can adopt the same-sized electrodes from this study, and the electrical resistivity values in the field would be almost identical to the experimental ones. In future studies, the relationship between mechanical characteristics and electrical resistivity should be explored. Moreover, a quick and multi-featured piece of detection equipment will be developed based on the electrical resistivity. In addition, a calibration method will be explored in cement–loess, which can reduce the detection time and cost.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Basic Properties | Value |
---|---|
Liquid limit/wL/% | 24 |
Plastic limit/wP/% | 15.1 |
Maximum dry density/ρmax/g·cm−3 | 1.88 |
Optimal water content/wopt/% | 11.0 |
Specific gravity/Gs | 2.70 |
Materials | CaO | SiO2 | Al2O3 | Fe2O3 | SO3 | MgO | Na2O | Others | LOI |
---|---|---|---|---|---|---|---|---|---|
Loess | 9.31 | 44.4 | 10.49 | 4.38 | 0.11 | 2.64 | 1.42 | 1.01 | 8.51 |
Cement | 47.4 | 21.87 | 5.96 | 3.61 | 3.31 | 1.96 | 0.62 | 0.86 | 3.70 |
Cement Dosage/% | Dry Density/g·cm−3 | Water Content/% | Curing Age/Days |
---|---|---|---|
6 [24], 9, 12 | 1.62 | 8.0 | 1, 7, 14, 28 |
10.0 | 1, 7, 14, 28 | ||
12.5 | 1, 7, 14, 28 | ||
14.0 | 1, 7, 14, 28 | ||
1.71 | 8.0 | 1, 7, 14, 28 | |
10.0 | 1, 7, 14, 28 | ||
12.5 | 1, 7, 14, 28 | ||
14.0 | 1, 7, 14, 28 | ||
1.77 | 8.0 | 1, 7, 14, 28 | |
10.0 | 1, 7, 14, 28 | ||
12.5 | 1, 7, 14, 28 | ||
14.0 | 1, 7, 14, 28 | ||
1.81 | 8.0 | 1, 7, 14, 28 | |
10.0 | 1, 7, 14, 28 | ||
12.5 | 1, 7, 14, 28 | ||
14.0 | 1, 7, 14, 28 |
Parameters | Value |
---|---|
e | −2.18 |
f | −0.302 |
c | 0.837 |
R2 | 0.937 |
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Xue, Z.; Deng, Q.; Gao, J.; Zhang, Y.; Zhang, Z.; Yan, C.; Wang, J.; Han, F.; Li, L.; Ma, Y. Micro–Macro-Analysis and Model Derivation of Electrical Resistivity of Ningxia Cement–Loess. Buildings 2024, 14, 3265. https://doi.org/10.3390/buildings14103265
Xue Z, Deng Q, Gao J, Zhang Y, Zhang Z, Yan C, Wang J, Han F, Li L, Ma Y. Micro–Macro-Analysis and Model Derivation of Electrical Resistivity of Ningxia Cement–Loess. Buildings. 2024; 14(10):3265. https://doi.org/10.3390/buildings14103265
Chicago/Turabian StyleXue, Zhijia, Qiquan Deng, Jianqiang Gao, Ying Zhang, Ziwei Zhang, Changgen Yan, Jie Wang, Fangyuan Han, Longshan Li, and Yongzhi Ma. 2024. "Micro–Macro-Analysis and Model Derivation of Electrical Resistivity of Ningxia Cement–Loess" Buildings 14, no. 10: 3265. https://doi.org/10.3390/buildings14103265
APA StyleXue, Z., Deng, Q., Gao, J., Zhang, Y., Zhang, Z., Yan, C., Wang, J., Han, F., Li, L., & Ma, Y. (2024). Micro–Macro-Analysis and Model Derivation of Electrical Resistivity of Ningxia Cement–Loess. Buildings, 14(10), 3265. https://doi.org/10.3390/buildings14103265