Influence of composite admixtures on the freezing resistance and pore structure characteristics of cemented sand and gravel

2.4.1 Compressive strength test

The compressive strength test adopted a WAW-1000 electrohydraulic servo universal testing machine. The specimens was a 100 mm×100 mm×100 mm specimens before and after freezing and thawing. During the test, the specimens was continuously and uniformly loaded at a speed of 5 kN/s until it fractured, and the peak failure load P was recorded to calculate the compressive strength.

2.4.2 Freezing resistance test

The freeze-thaw test was performed with three specimens as a group. First, a 100 mm × 100 mm × 400 mm specimens that had been cured to 24 days of age was soaked in water at 20 °C ± 3 °C for four days. Second, the specimens was removed, and the surface moisture was wiped off. We weighed the initial mass m ₀ and the initial transverse fundamental frequency f ₀ of the specimens, put the specimens into the test box, and tap water was added until the level was 20 mm higher than the top surface of the specimens. Finally, the test box containing the specimens was put into a freeze-thaw box containing a freeze-thaw solution with a temperature of -25 °C to 20 °C, and the parameters of the freeze-thaw machine were set: the cycle lasts 4.0 h, the cooling lasts 2.5 h, and the heating lasts 1.5 h. After 20 freeze-thaw cycles, we measured the mass m ₂₀ and the transverse fundamental frequency f ₂₀ of the specimens again, and calculated the relative dynamic elastic modulus and mass loss rate through Equation [1] and [2] to characterize the freezing resistance of the CSG.

The relative dynamic elastic modulus was calculated using the following formula:

Where P is the relative dynamic elastic modulus (%) of the CSG specimens after the N-th freeze-thaw cycle; E _dn is the dynamic elastic modulus(MPa) of the CSG specimens after the N-th freeze-thaw cycle; E _d0 is the dynamic elastic modulus(MPa) of the CSG specimens before the freeze-thaw cycle test; C is the shape calculation parameter(kg/m²); m is the mass of the specimen(kg); f _n is the transverse fundamental frequency (Hz) of the CSG specimens after the N-th freeze-thaw cycle; f ₀ is the initial transverse fundamental frequency (Hz) of the CSG specimens before the freeze-thaw cycle test.

The mass loss rate was calculated using the following Equation [2]:

Where ∆M is the mass loss rate (%) of the specimens after the N-th freeze-thaw cycle; W ₀ is the mass (g) of the specimens before the freeze-thaw cycle test; and W _n is the mass (g) of the specimens after the N-th freeze-thaw cycle.

2.4.3 Scanning electron microscopy test

A broken specimens from compression tests was randomly selected for scanning electron microscopy (SEM) examination. Before the SEM test, the sample was polished and ground to a size of approximately 10 mm and fixed on the sample base with conductive adhesive for metal spraying. The spraying thickness was 200-300 Å. During the test, a Quanta-650 Environmental Scanning Electron Microscope (ESEM) and an Apollo-X Spectrometer was used. working conditions: Test in BSE mode, the acceleration voltage was 25kV, the SEM scanning time was 45 seconds, and the EDS scanning time was 3~5min. The sample magnification was 500~5000×.

2.4.4 Pore structure analysis

2.4.4.1 Porosity test

A MesoMR12-060H-I nuclear magnetic resonance device was used in the test. First, the specimen with an age of 28 days for 24 hours vacuum saturation, and then the specimen was put into the coil of the nuclear magnetic resonance instrument. NMR relaxation measurements were carried out by a nuclear magnetic resonance analysis system. After the Carr-Purcell-Meiboom-Gill (CPMG) sequence attenuation signal data were collected, the data inversion was performed to obtain the T2 spectrogram which was then converted into a pore size distribution diagram. The pore size was measured between 50 nm and 200 μm.

2.4.4.2 Pore structure characterization based on SEM images

With reference to the technology adopted by Liu et al (2525. Liu, C.; Shi, B.; Zhou, J.; Tang, C. (2011) Quantification and characterization of microporosity by image processing, geometric measurement and statistical methods: Application on SEM images of clay materials. Appl. Clay. Sci. 54 [1], 97-106. https://doi.org/10.1016/j.clay.2011.07.022.
) pore and crack analysis system (PCAS) software was used to obtain the pore binary characteristics. The threshold segmentation method was used to binarize the electron microscope images, and the different gray values of pores and hydration products in the images were used as the basis for distinguishing. Select an SEM image and put it into the software to convert it into a binary image by setting an appropriate threshold. The first step is to set a larger threshold. At this time, many elements that are originally hydration products are identified as pores and appear white. And then reduce the threshold appropriately until the fine hydration products in the pores are just identified, which is a more appropriate threshold at this time. The user determines the threshold for the relationship between pores and hydration products. The microscopic image is usually processed three times in different periods to reduce subjective errors. When the average value of the difference does not exceed 2 degrees, the average value of the three selected thresholds is obtained, which is the final selected threshold. For each series of experimental samples, at least 3 SEM images were recorded, and the average value was taken as the value of digital image quantitative processing. In this study, the SEM image with a magnification of 1000 times was selected as the original image processed by PCAS. Pores of 0~25 μm were collected. The distribution characteristics of irregular pores were quantified by fractal dimension (2626. Guo, L.P.; Zhu,Q.; Ling, S. (2019) Study on basic properties and pore characteristics of recycled aggregate pervious concrete. Water power. 45 [12], 117-122.
). An example of pore structure feature extraction is shown in Figure 1.

3.1.1 Compressive strength

The compressive strength of the CSG before and after freezing and thawing is shown in Figure 2. Compared with the blank group (L1), the pre-freezing compressive strength of the CSG test pieces after being mixed with composite admixtures all decreased to varying degrees. The reasons for this phenomenon are as follows: (1) After the air-entraining agent was introduced, a large number of tiny, closed and uniformly distributed polar bubbles were formed inside the CSG test pieces, which were beneficial to the workability of the mixtures, but reduced the effective compressive area, resulting in different degrees of strength loss of the test pieces mixed with admixtures; (2) both the water reducing agent and the air-entraining agent can reduce water (2727. Du, R.; Zhang, X.; Gu, M.; Ji, T. (2019) The composition effect and mechanism of polycarboxylate superplasticizer and early strength agent. Mater. Rep. 33 [14], 2461-2466. https://doi.org/10.11896/cldb.18040139
); thus, in this study, the actual water-binder ratio was large and interfered with the hardening process of the CSG test pieces. Finally, microcracks appeared on the test pieces, reducing their strength. In accordance with the design requirements of CSG compressive strength specified in the Technical Guideline for Cemented Granular Material Dams (2828. Ministry of Water Resources of the People’s Republic of China. SL678-2014, Technical guidelines for cemented granular materials dam construction (2014), China Water Conservancy and Hydropower Publishing House, Beijing.
) (SL 678-2014), the strength loss rate should be less than 20%; that is, the design strength should reach 8 MPa. Figure 2 shows that the test groups L2, L3, L6, L9, L10, and L13 met the compressive strength requirements.

To clarify the influence of composite admixtures on the mechanical properties of CSG, the strength loss rates of the L2, L3, L6, L9, L10, and L13 groups that met the requirements of the specification were analyzed and calculated, as shown in Figure 3. The compressive strength loss rates before and after freezing and thawing were all lower than that of the blank group (22.50%), indicating that adding composite admixtures is beneficial to improving the freezing resistance durability of CSG. Figure 2 and 3 show that, when the range of strength loss is met, the strength loss rate of L9 before and after freezing and thawing is the smallest, at only 0.92%, and its admixtures include 0.008% sodium dodecyl sulfate, 0.04% graphene oxide, 2.0% nano silicon powder, and 0.40% water reducing agent.

3.1.2 Relative dynamic elastic modulus

The dynamic elastic modulus is a main indicator that reflects the internal structural performance of a material. For freezing resistance, the smaller the relative dynamic elastic modulus is, the more obvious the effect of freeze-thaw damage is (2929. Wang, D.; Zhao, Q.; Yang, C.; Chi, Y.; Qi, W.; Teng, Z. (2020) Study on frost resistance and vegetation performance of seashell waste pervious concrete in cold area. Constr. Build. Mater. 265, 120758. https://doi.org/10.1016/j.conbuildmat.2020.120758.
). Similarly, for CSG, the relative dynamic elastic modulus can also characterize its freeze-thaw damage (3030. Liu, H.S.; Yang, S.F.; Guo, L.X.; Guo, L. (2019) Freeze-thaw test of gelatinized sand and gravel and analysis of influencing factors. Water Resour. Power. 37 [03], 100-102.
). Figure 4 shows changes in the relative dynamic elastic modulus of CSG with different admixtures. Compared with the blank Group L1 (62%), the relative dynamic modulus of CSG with admixtures in the test groups was significantly higher. The relative dynamic elastic moduli of L5, L7, L8, L12, and L13 all exceed 80%, indicating that they have better freezing resistance. However as seen in Figure 2, after 20 freeze-thaw cycles, none of them meets the design standard of compressive strength. Therefore, the relative dynamic elastic modulus cannot be selected as the only indicator to evaluate the freezing resistance of CSG, and other indicators need to be considered together (31-3331. Yun, H-D.; Rokugo, K. (2012) Freeze-thaw influence on the flexural properties of ductile fiber-reinforced cementitious composites (DFRCCs) for durable infrastructures. Cold. Reg. Sci. Technol. 78, 82-88. https://doi.org/10.1016/j.coldregions.2012.02.002.
32. Zhang, D.; Mao, M.; Zhang, S.; Yang, Q. (2019) Influence of stress damage and high temperature on the freeze-thaw resistance of concrete with fly ash as fine aggregate. Constr. Build. Mater. 229, 116845. https://doi.org/10.1016/j.conbuildmat.2019.116845.
33. Zhao, R.; Yuan, Y.; Cheng, Z.; Wen, T.; Li, J.; Li, F.; Ma, Z.J. (2019) Freeze-thaw resistance of Class F fly ash-based geopolymer concrete. Constr. Build. Mater. 222, 474-483. https://doi.org/10.1016/j.conbuildmat.2019.06.166.
).

3.2.1 NMR pore analysis

NMR technology has been widely used in the study of microscopic pore structures and damage mechanisms of rocks and concrete (34-3634. Zhou, C.; Ren, F.; Wang, Z.; Chen, W.; Wang, W. (2017) Why permeability to water is anomalously lower than that to many other fluids for cement-based material? Cem. Concr. Res. 100, 373-384. https://doi.org/10.1016/j.cemconres.2017.08.002.
35. Wang, X.; Shen, X.; Wang, H.; Gao, C.; Zhang, T. (2016) Nuclear magnetic resonance analysis of freeze-thaw damage in natural pumice concrete. Mater. Construcc. 66 [322], e087. https://doi.org/10.3989/mc.2016.09014.
36. Cano-Barrita, P.F. de J.; Castellanos, F.; Ramírez-Arellanes, S.; Cosmes-López, M.F.; Reyes-Estevez, L.R.; Hernández-Arrazola, S.E.; Ramírez-Ortíz, A.E. (2015) Monitoring compressive strength of concrete by nuclear magnetic resonance, ultrasound, and rebound hammer. ACI. Mater. J. 112 [1], 147-154. https://doi.org/10.14359/51686984.
). Figure 5 summarizes the pore size distribution of the test pieces before and after freezing and thawing obtained by NMR. Academician Wu Zhongwei (3737. Wu, Z.W. (1979) An approach to the recent trends of concrete science and technology. J. Chinese Ceram. Soc. [03], 262-270.
) classified pores of 0~0.02 μm into harmless pores, pores of 0.02~0.05 μm into less harmful pores, pores of 0.05~0.2 μm into harmful pores, and pores above 0.2 μm into more harmful pores. Figure 5 shows that the harmless pores, less harmful pores and harmful pores are concentrated in the first peak, and the more harmful pores are mainly in the second and third peaks. The pore size distribution curves of the L5, L11, L12, L13, L14, and L16 groups before and after freezing and thawing have relatively larger changes. After freezing and thawing, the first peak is approximately 0.025%, and the second and third peaks increase. For example, the second peak value of the L13 group before freezing was 0.006%, and the pore diameter was 1.17 μm; after freezing, the second peak value rose to 0.0084%, and the pore size increased to 1.45 μm. The pore size distribution curves of L9 and the rest of the test groups in the first peak are basically the same and show little change before and after freezing and thawing, approximately 0.02%, and the changes of the second and third peaks are different, but both move to the right. For example, the second peak pore size of the test pieces in the L9 group before freezing was 1.35 μm; the corresponding value after freezing was 1.45 μm.

The area occupancy of more harmful pores was calculated according to the pore size distribution diagram, as shown in Figure 6. After 20 freeze-thaw cycles, the area occupancy of more harmful pores of CSG increases to varying degrees, and especially in the L5, L11, L12, L13, and L14 groups, it increased by 48.93%, 49.87%, 30.45%, 36.03%, and 75.50%, respectively, which verifies the above analysis. The reason for such phenomena is that at the beginning of freezing and thawing, harmless, less harmful and harmful pores with small sizes are internally filled with pore water, which may generate a frost heaving force due to the differential pressure inside and outside during freezing and thawing. In such cases, the pore wall is damaged, the pore size increases, and many pores are changed to more harmful pores. More harmful pores themselves are large in size and will become even larger under the frost heaving force until the test pieces undergo freeze-thaw damage.

The CSG test pieces experienced a gradually changing damage process under the action of water freeze-thaw cycles, and the damage pattern of its pore structure is shown in Figure 7. With the increase of the number in freeze-thaw cycles, the pore water in the test piece undergoes repeated volume expansion, resulting in the gradual enlargement of the pores and the increase in the degree of irregularity until penetrating cracks develop. The number of damage points inside the specimen increases, which leads to a decrease in its compressive strength.

3.2.2 Fractal characteristics of pore structure in SEM images

CSG images obtained before and after freezing and thawing in the SEM test are shown in Figure 8. Due to the large number of test groups, only partial SEM images are shown. Figure 8 (a) shows that the microstructure of the blank Group L1 before freezing is needle-shaped, and the surface is flat and has cracks. The energy spectrum analysis reveals that the needle-like substance is ettringite, because it contains Si, Al, Ca and other elements (3838. Sun, H.R.; Zou, C.X.; Xue, H.J.; Zhao, Q.; Wu, J. (2021) Fractal characteristics of dry-wet and freeze-thaw erosion pore structure of mold-bag concrete. J. Build. Mater. 25 [02], 124-130.
, 3939. Zhou, X.; Hao, X.; Peng, J.; Luo, Z. (2017) Effect of compound admixtures on hydration characteristics of ferrochrome slag based composite material. Mater. Rep. 31 [04], 121-125. https://doi.org/10.11896/j.issn.1005-023X.2017.04.026.
). Figure 8 (b) shows the morphology of the blank Group L1 after freezing. In the needle-like substance fractures, the pores gradually expand into connected cavities, and the compactness of the test pieces decreases. Since the selected SEM image size is 100 µm, combined with the pore size distribution of NMR, it is considered a more harmful pore. Figure 8 (c), (e) and (g) show the pre-freezing microstructures of the L5, L12, and L13 groups, which have obvious changes compared with Figure 8 (a). This is because different admixtures have different enhancement mechanisms (4040. Ren, X.; Hu, G.H.; Wu, F.; Huang, L. (2019) Effect of nano silica power on mechanical and shrinkage properties of high volume rubber mortar. Sci. Technol. Engineer. 19 [22], 299-304.
, 4141. Zhang, Z.; Wu, J.; Yang, J.; Zhou, J.; Li, D. (2019) Effect of graphene oxide on properties of cement-based self-leveling mortar. Mater. Rep. 33 [02], 240-245. https://doi.org/10.11896/cldb.201902008
), and they can improve the cementing effect of the gel or the weak area of the aggregate interface to different degrees. After freeze-thaw damage, the deterioration of the pore structure in Figure 8 (d), (f) and (h) changes compared with Figure 8 (b). The connected pores are significantly reduced and gradually become independent pores with smaller sizes, macroscopically indicating the improvement of the freezing resistance of the test samples. This is the same as the pore size distribution law obtained by NMR experiments.

Through EDS analysis, the hydration products of CSG mainly included C-S-H gel, AFm and AFt. After 20 freeze-thaw cycles, the needle-shaped C-S-H gradually became thicker and even lumpy, resulting in no cross-linking at the terminal, so that the voids could not be filled, and the compactness and freezing resistance were reduced.

To further clarify the changes in the internal pore structure during the freezing and thawing process, we calculated the fractal characteristics of the pore structure on the selected SEM images before and after freezing and thawing using PCAS software. The results are shown in Table 7.

It can be seen in the table that the fractal dimension of pores improves to varying degrees after 20 freeze-thaw cycles. Among them, the fractal dimension before and after freezing and thawing in the L5, L11, L12, L13, and L14 groups changes more distinctly, which indicates that the pores deteriorate after freezing and thawing. The fractal dimension change rate of the L9 group before and after freezing and thawing was the lowest, at only 0.30%; meanwhile, its compressive strength was also better. Therefore, the fractal dimension of 1000 times SEM images can be used to characterize the freeze-thaw characteristics of CSG.