Microscopic Mechanisms and Evolution Models of Crack Development in an Expansive Soil under Conditions of Rainfall Evaporation Cycles
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Rainfall Simulation
2.3. Nuclear Magnetic Resonance Test
2.4. Experimental Procedure
2.4.1. Test Block Preparation
- (1)
- Pre-treatment of Soil Samples: Soil was initially air-dried naturally and then crushed with a crushing hammer, as depicted in Figure 3a.
- (2)
- Screening and Drying: In compliance with GBT 50123-2019 [32] (Chinese standard), the crushed soil was sifted using a 2 mm sieve and subsequently oven-dried at 100 °C for 24 h.
- (3)
- Adjustment of Water Content: The soil’s water content was adjusted to 14%. This step involved gradual water addition and frequent stirring to prevent clumping.
- (4)
- Sealing and Resting of Soil Samples: The adjusted soil samples were sealed with plastic film and left for 24 h, as shown in Figure 3b, to ensure uniform soil water integration.
- (5)
- Water Content: After resting, the water content was tested again to confirm that it remained within 14 ± 1%.
- (6)
- Preparation of the Specimen: To prevent interference with the NMR test’s magnetic field from steel and iron, petroleum jelly was applied between the specimen and the ring cutter for separation.
- (7)
- Compacting and Shaping: After the soil samples were smothered, some of the soil samples were placed into a ring knife mold coated with petroleum jelly. The soil samples were compacted 25 times with a percussive tester according to ASTM D698-12 [35], and then the specimens were removed and the ends were flattened with a paring knife, as shown in Figure 3c.
- (8)
- Separation and Weighing: The specimen block was detached from the ring cutter, and its mass was weighed, as shown in Figure 3d.
- (9)
- Repeat Preparation: This preparation process was repeated for multiple test blocks for subsequent experiments.
2.4.2. Rainfall Evaporation Cycle Experiment
- (1)
- Preparation for Simulated Rainfall Test: Considering the small area of soil samples affected by rainfall and the minimal flow rate required, the water level change in the storage tank was negligible. Initially, the tank was filled with water, and ring knife-prepared soil samples were placed in the soil-bearing container. Rainfall intensity was regulated using a controller, as detailed in Table 1, to execute the simulated rainfall test.
- (2)
- Rainfall Evaporation Cycle Treatment: The cycle comprised one day of rainfall followed by one day of drying using a 202-4A electric constant temperature drying oven (temperature range: 10–300 °C). Under simulated hot weather conditions, the oven was set to 40 °C with a relative humidity of 50 ± 2%.
- (3)
- Saturation Treatment: Kerosene, instead of water, was used to saturate the expansive soil test blocks due to the interactions between water and expansive soil, which could skew results. Kerosene’s inertness prevents such reactions, preserving the soil’s original state. The soil blocks were fully immersed in kerosene for 24 h to ensure complete saturation, as shown in Figure 4a.
- (4)
- NMR Observation: Post-saturation, the internal pore structure of the test blocks was observed using an NMR instrument to analyze the effects of the rainfall evaporation cycle on the soil’s microstructure.
2.5. Digital Image Processing
- (1)
- Image preparation: The image preparation stage is a crucial step in the experiment. When using a Canon EOS 1500D DSLR camera (Canon, Tokyo, Japan) to take pictures of the test surface, make sure that the camera is fixed on a stable tripod and adjust the height until the camera is able to cover an area of 61.8 mm × 61.8 mm. This ensures that the images captured are of high quality and accuracy, which facilitates subsequent image processing and analysis work.
- (2)
- Binarization: Binarization is a common image processing technique that highlights target features by converting a color or gray scale image into a binary image with only two colors (typically black and white). In MATLAB, code can be written to implement this process. First, the original color image needs to be converted to a greyscale image, and then the binarization threshold is determined automatically using an appropriate algorithm. For expansive soil test block images, the threshold is usually determined in the range of 0–1. By binarizing the image, the shape of the cracks in the image can be highlighted in black and white contrast, thus showing more clearly the intact part of the soil sample structure and the open part of the cracks.
- (3)
- Noise and error handling: The effects of noise and error must be considered when processing and analyzing image data. Image noise and the roughness of the soil sample surface may lead to stray dots in the binarized image, and these can cause errors in the black pixel statistics. In this case, the stray dots may form a fragmented distribution in the crack region, thus interfering with the accurate extraction of crack shape parameters. In order to effectively eliminate the effect of clutter, a professional image processing software, Adobe Photoshop, was used to morphologically process the binarized images for accurate distortion correction [36].
- (4)
- Parameter extraction: Fracture parameters were extracted using Image-Pro Plus 6.0 (IPP). First, import the binarized image and select the “Measurement” function in “Analysis”. This will present a measurement result window with various parameters that can be found in relation to the fissure. Using these parameters, information such as the number, total length, and average width of the cracks in the specimen section can be calculated.
3. Results and Analysis
3.1. Effect of Rainfall Evaporation Cycles on the Pore Structure of Expansive Soils
3.2. Changing Law of Pore Characteristic Parameters of Expansive Soil
3.3. Characteristics and Quantitative Analysis of Cracks Development in Expansive Soil
3.3.1. Digital Image Processing and Analysis
3.3.2. Cracking Quantification Results and Analysis
3.3.3. Developmental Pattern of Main Cracks in Expansive Soils
3.4. Modeling of Cracking Development in Expansive Soils
4. Conclusions
- (1)
- In the presence of light and medium rainfall cycles, the pore space within a soil sample is predominantly composed of micropores, small pores, and medium-sized pores, which together typically account for over 85% of the total pore volume. As the number of rainfall evaporation cycles increases, the micropores and small- and medium-sized pores in expansive soils gradually transform macropores. The extent of this transformation is directly proportional to the level of rainfall intensity.
- (2)
- Expansive soils exhibit enhanced porosity resulting from the significant accumulation of free water during hygroscopicity, but partially contract during dehumidification, which restores a portion of the internal pores and leads to a gradual reduction in porosity. Once dehumidification reaches a steady state, the soil sample undergoes a process of expansion and contraction, resulting in the formation of irreversible pores. As the number of cycles increases, the irreversible pores also multiply, leading to a gradual rise in effective porosity, ultimately culminating in the disintegration of the soil sample due to dispersion.
- (3)
- Based on the grayscale processing and binarization of cracking images on the surface of expansive soil, the development of cracking under rainfall evaporation cycles can be categorized into four stages. By extracting cracking from expansive soil samples and conducting quantitative analysis, including the main cracking length, average width, and area measurements, it was observed that the development of primary cracking in expansive soil was more rapid during evaporation cycles accompanied by middle-intensity rainfall events.
- (4)
- When assessing the structural deterioration of expansive soil, the average width of cracks serves as a crucial indicator, with larger widths indicating a higher risk of sample failure. Under varying rainfall conditions, the relationship between the number of rainfall cycles and the mean crack width was modeled using both a linear regression model and a modified logistic function. These models demonstrated high accuracy, with correlation coefficients (R2) of 0.98 and 0.96, respectively. Moreover, a significant positive correlation exists between the porosity and average crack width, evidenced by a correlation coefficient (R2) of 0.84. This suggests that as porosity increases, so does the average width of cracks in expansive soil, further emphasizing the importance of porosity as a predictive factor in soil structural integrity.
- (5)
- Further studies will need to investigate the whole process of evaporation. The cycles modify the fine structure of expansive soil, changing the whole process of the rainfall evaporation cycle, meaning it will be necessary to investigate the evaporation (dehumidification) of expansive soil.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Elmashad, M.E.; Sharaf, M.; Abdelaziz, T. Improvement of swelling soil by using lime sludge and sodium chloride. Arab. J. Geosci. 2022, 15, 1761. [Google Scholar] [CrossRef]
- Krisnanto, S.; Rahardjo, H.; Fredlund, D.G.; Leong, E.C. Mapping of cracked soils and lateral water flow characteristics through a network of cracks. Eng. Geol. 2014, 172, 12–25. [Google Scholar] [CrossRef]
- Wang, F.; Kong, L.; Zhou, Z. Study on Pore Structure and Mechanical Property of Expansive Soil under Different Dehydration Conditions. Appl. Sci. 2022, 12, 5981. [Google Scholar] [CrossRef]
- Wu, J.-H.; Yuan, J.-P.; Ng, C.W. Theoretical and experimental study of initial cracking mechanism of an expansive soil due to moisture-change. J. Cent. South Univ. 2012, 19, 1437–1446. [Google Scholar] [CrossRef]
- Li, J.H.; Zhang, L.M. Geometric parameters and REV of a crack network in soil. Comput. Geotech. 2010, 37, 466–475. [Google Scholar] [CrossRef]
- Yang, Y.; Yao, H.-L.; Chen, S.-Y. Characteristics of microcosmic structure of Guangxi expansive soil. Yantu Lixue (Rock Soil Mech.) 2006, 27, 155–158. [Google Scholar]
- Lang, Y.-X.; Liang, Z.-Z.; Duan, D.; Cao, Z. Three-dimensional parallel numerical simulation of porous rocks based on CT technology and digital image processing. Rock Soil Mech. 2019, 40, 1204–1212. [Google Scholar]
- Bravo, D.; Benavides-Erazo, J. The use of a two-dimensional electrical resistivity tomography (2D-ERT) as a technique for cadmium determination in Cacao crop soils. Appl. Sci. 2020, 10, 4149. [Google Scholar] [CrossRef]
- Ito, M.; Azam, S. Relation between flow through and volumetric changes in natural expansive soils. Eng. Geol. 2020, 279, 105885. [Google Scholar] [CrossRef]
- Zheng, J.; Guo, Z.; Cui, L.; Zhang, Z. Stability analysis of expansive soil tunnel considering unsaturated seepage and moistening swelling deformation. Rock Soil Mech. 2017, 38, 3271–3277. [Google Scholar]
- Hou, D.; Zhou, Y.; Zheng, X. Seepage and stability analysis of fissured expansive soil slope under rainfall. Indian Geotech. J. 2023, 53, 180–195. [Google Scholar] [CrossRef]
- Dai, Z.; Guo, J.; Luo, H.; Li, J.; Chen, S. Strength characteristics and slope stability analysis of expansive soil with filled fissures. Appl. Sci. 2020, 10, 4616. [Google Scholar] [CrossRef]
- Estabragh, A.; Parsaei, B.; Javadi, A. Laboratory investigation of the effect of cyclic wetting and drying on the behaviour of an expansive soil. Soils Found. 2015, 55, 304–314. [Google Scholar] [CrossRef]
- Tang, C.-S.; Zhu, C.; Leng, T.; Shi, B.; Cheng, Q.; Zeng, H. Three-dimensional characterization of desiccation cracking behavior of compacted clayey soil using X-ray computed tomography. Eng. Geol. 2019, 255, 1–10. [Google Scholar] [CrossRef]
- Ribeiro Filho, J.C.; de Andrade, E.M.; Guerreiro, M.S.; de Queiroz Palácio, H.A.; Brasil, J.B. Climate Data to Predict Geometry of Cracks in Expansive Soils in a Tropical Semiarid Region. Sustainability 2022, 14, 675. [Google Scholar] [CrossRef]
- Zhu, H.; Zhang, Y.; Li, Z.; Xue, X. Study on crack development and micro-pore mechanism of expansive soil improved by coal gangue under drying–wetting cycles. Materials 2021, 14, 6546. [Google Scholar] [CrossRef] [PubMed]
- Li, X.-W.; Wang, Y.; Yu, J.-W.; Wang, Y.-l. Unsaturated expansive soil fissure characteristics combined with engineering behaviors. J. Cent. South Univ. 2012, 19, 3564–3571. [Google Scholar] [CrossRef]
- Li, T.; Kong, L.; Guo, A. The deformation and microstructure characteristics of expansive soil under freeze–thaw cycles with loads. Cold Reg. Sci. Technol. 2021, 192, 103393. [Google Scholar] [CrossRef]
- Wei, G.; Dong, J. Swelling Research of Expansive Soil Under Drying-Wetting Cycles: A NMR Method. Soils Rocks 2020, 43, 21–30. [Google Scholar] [CrossRef]
- Dong, J.; Lyu, H.; Xu, G.; He, C. NMR-based study on soil pore structures affected by drying–wetting cycles. Arab. J. Sci. Eng. 2020, 45, 4161–4169. [Google Scholar] [CrossRef]
- Shi, F.; Zhang, C.; Zhang, J.; Zhang, X.; Yao, J. The changing pore size distribution of swelling and shrinking soil revealed by nuclear magnetic resonance relaxometry. J. Soils Sediments 2017, 17, 61–69. [Google Scholar] [CrossRef]
- Chi, Z.-C.; Dai, Z.-J.; Chen, S.-X.; Li, F.-F.; Wang, W.; Li, J.-B. Effect of hydration on mechanical properties and microstructure of expansive soil. Environ. Earth Sci. 2023, 82, 133. [Google Scholar] [CrossRef]
- Wang, W.; Lv, B.; Zhang, C.; Li, N.; Pu, S. Mechanical and micro-structure characteristics of cement-treated expansive soil admixed with nano-MgO. Bull. Eng. Geol. Environ. 2023, 82, 48. [Google Scholar] [CrossRef]
- Cui, S.L.; Wang, J.D.; Wang, X.D.; Du, Y.F.; Wang, X.P. Mechanical behavior and micro-structure of cement kiln dust-stabilized expensive soil. Arab. J. Geosci. 2018, 11, 1–8. [Google Scholar] [CrossRef]
- Kong, L.-W.; Wang, M.; Guo, A.-G.; Wang, Y. Effect of drying environment on engineering properties of an expansive soil and its microstructure. J. Mt. Sci. 2017, 14, 1194–1201. [Google Scholar] [CrossRef]
- Liu, K.; Ye, W.; Gao, H.; Dong, Q. Multi-scale effects of mechanical property degradation of expansive soils under drying-wetting environments. Chin. J. Rock Mech. Eng. 2020, 39, 2148–2159. [Google Scholar]
- Lin, B.; Cerato, A.B. Applications of SEM and ESEM in microstructural investigation of shale-weathered expansive soils along swelling-shrinkage cycles. Eng. Geol. 2014, 177, 66–74. [Google Scholar] [CrossRef]
- Gould, S.J.; Kodikara, J.; Rajeev, P.; Zhao, X.-L.; Burn, S. A void ratio–water content–net stress model for environmentally stabilized expansive soils. Can. Geotech. J. 2011, 48, 867–877. [Google Scholar] [CrossRef]
- Wang, S.; Wang, X.; Li, D.; Li, X.; Liang, G.; Muhammad, Q. Evolution of fissures and bivariate—Bimodal soil—Water characteristic curves of expansive soil under drying—Wetting cycles. Chin. J. Geotech. Eng. 2021, 43, 58–63. [Google Scholar]
- Banafian, N.; Fesharakifard, R.; Menhaj, M.B. Precise seam tracking in robotic welding by an improved image processing approach. Int. J. Adv. Manuf. Technol. 2021, 114, 251–270. [Google Scholar] [CrossRef]
- Song, X. Research on Fragmentation Distribution of Rock Based on Digital Image Processing Technology. J. Phys. Conf. Ser. 2021, 1744, 042034. [Google Scholar] [CrossRef]
- General Institute of Water Resources and Hydropower Planning and Design MoWRM, Institute NHR. Standard for Geotechnical Testing Ministry of Housing and Urban-Rural Development of the People's Republic of China; State Administration of Market Regulation: Beijing, China, 2019; p. 717. [Google Scholar]
- ASTM International. Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System); ASTM International: West Conshohocken, PA, USA, 2017. [Google Scholar]
- National Meteorological Center. Grade of Precipitation; General Administration of Quality Supervision; Inspection and Quarantine of the People’s Republic of China; Standardization Administration of the People’s Republic of China: Beijing, China, 2012; p. 8. [Google Scholar]
- ASTM Committee D-18 on Soil and Rock. Standard Test Methods for Laboratory Compaction Characteristics of Soil Using Modified Effort (56,000 Ft-Lbf/Ft3 (2,700 KN-M/M3)) 1; ASTM International: West Conshohocken, PA, USA, 2009. [Google Scholar]
- Abu-Faraj, M.; Alqadi, Z.; Zubi, M. Creating Color Image Features Based on Morphology Image Processing. Trait. Signal 2022, 39, 797–803. [Google Scholar] [CrossRef]
- Zhang, Y.; Bing, H.; Yang, C.-S. Influences of freeze-thaw cycles on mechanical properties of silty clay based on SEM and MIP test. Chin. J. Rock Mech. Eng. 2015, 34, 3597–3603. [Google Scholar]
- Chen, X.; Jing, X.; Li, X.; Chen, J.; Ma, Q.; Liu, X. Slope Crack Propagation Law and Numerical Simulation of Expansive Soil under Wetting–Drying Cycles. Sustainability 2023, 15, 5655. [Google Scholar] [CrossRef]
- Liu, Y.; Chen, D.; Wang, H.; Yu, J. Response analysis of residual soil slope considering crack development under drying-wetting cycles. Rock Soil Mech. 2021, 42, 1933–1943. [Google Scholar]
- Pulat, H.F.; Yukselen-Aksoy, Y.; Egeli, I. The effect of soil mineralogy and pore fluid chemistry on the suction and swelling behavior of soils. Bull. Eng. Geol. Environ. 2014, 73, 37–42. [Google Scholar] [CrossRef]
Natural Water Content/% | Dry Density/(g/cm3) | Liquid Limit/% | Plastic Limit/% | Plasticity Index | Maximum Dry Density/(g/cm3) | Optimum Moisture Content/% | Free Swelling Ratio/% |
---|---|---|---|---|---|---|---|
14.42 | 1.70 | 43.6 | 20.2 | 23.4 | 1.71 | 17.42 | 43.7 |
Rainfall Intensity Level | Total 24 h Precipitation/mm | Total 12 h Precipitation/mm | Simulated Rainfall Flow mL/h |
---|---|---|---|
light rainfall | 0.1–9.9 | ≤4.9 | 12.5 |
medium rainfall | 10.0–24.9 | 5.0–14.9 | 31.25 |
heavy rainfall | 25.0–49.9 | 15.0–29.9 | 93.75 |
storm rainfall | 50.0–99.9 | 30.0–69.9 | 187.5 |
Rainfall Intensity | Characteristic Parameters | Number of Cycles | ||||||
---|---|---|---|---|---|---|---|---|
0 | 1 | 2 | 3 | 4 | 5 | 6 | ||
light rainfall | Total peak area | 3850.8 | 3874.9 | 3902.9 | 3925.9 | 4085.3 | 5974.0 | 6445.1 |
advantageous pore size /μm | 1.092 | 1.092 | 1.018 | 0.886 | 0.886 | 0.950 | 1.018 | |
Porosity/% | 5.94 | 9.14 | 9.38 | 9.53 | 10.04 | 10.41 | 11.28 | |
medium rainfall | Total peak area | 4263.4 | 6502.2 | 7554.9 | 7838.1 | 7937.5 | 7447.5 | — |
advantageous pore size /μm | 1.092 | 0.886 | 1.254 | 1.092 | 1.345 | 1.254 | — | |
Porosity/% | 6.58 | 8.28 | 9.54 | 11.92 | 12.35 | 11.65 | — |
Rainfall Intensity | Rift Indicator | Number of Evaporative Cycles of Rainfall | ||||||
---|---|---|---|---|---|---|---|---|
0 | 1 | 2 | 3 | 4 | 5 | 6 | ||
Light rainfall | Number of crack bars | 0 | 23 | 111 | 86 | 67 | 39 | 27 |
Total crack length/mm | 0 | 53.34 | 166.96 | 127.28 | 84.07 | 70.00 | 31.73 | |
Average crack width/mm | 0 | 0.29 | 0.5 | 0.57 | 0.53 | 0.48 | 0.52 | |
Surface cracking rate/% | 0 | 0.41 | 2.28 | 1.89 | 1.36 | 1.05 | 0.49 | |
medium rainfall | Number of crack bars | 0 | 14 | 64 | 44 | 46 | 32 | — |
Total crack length/mm | 0 | 6.77 | 100.18 | 88.89 | 78.10 | 84.15 | — | |
Average crack width/mm | 0 | 0.17 | 0.45 | 0.62 | 0.65 | 0.85 | — | |
Surface cracking rate/% | 0 | 0.04 | 1.11 | 1.99 | 2.34 | 2.31 | — |
Rainfall Intensity | Main Crack Indicator | Number of Evaporative Cycles of Rainfall | ||||
---|---|---|---|---|---|---|
2 | 3 | 4 | 5 | 6 | ||
Light rainfall | Crack length/mm | 16.752 | 18.939 | 21.436 | 27.909 | 11.796 |
Average crack width/mm | 0.833 | 0.838 | 0.823 | 0.835 | 0.635 | |
Crack area/mm2 | 13.947 | 15.869 | 17.635 | 23.316 | 7.488 | |
Medium rainfall | Crack length/mm | 12.199 | 30.991 | 22.685 | 33.486 | — |
Average crack width/mm | 0.660 | 1.248 | 1.717 | 1.329 | — | |
Crack area/mm2 | 8.053 | 38.672 | 38.947 | 44.507 | — |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Han, L.; Ji, W.; Ma, L.; Guo, R.; Zhang, Y.; Zhang, H. Microscopic Mechanisms and Evolution Models of Crack Development in an Expansive Soil under Conditions of Rainfall Evaporation Cycles. Sustainability 2024, 16, 7617. https://doi.org/10.3390/su16177617
Han L, Ji W, Ma L, Guo R, Zhang Y, Zhang H. Microscopic Mechanisms and Evolution Models of Crack Development in an Expansive Soil under Conditions of Rainfall Evaporation Cycles. Sustainability. 2024; 16(17):7617. https://doi.org/10.3390/su16177617
Chicago/Turabian StyleHan, Liwei, Wenhui Ji, Liyuan Ma, Ruibin Guo, Yifan Zhang, and Hongyang Zhang. 2024. "Microscopic Mechanisms and Evolution Models of Crack Development in an Expansive Soil under Conditions of Rainfall Evaporation Cycles" Sustainability 16, no. 17: 7617. https://doi.org/10.3390/su16177617