Micro-pore structure has a decisive effect on the physical and mechanical properties of porous materials. To further improve the composition of rock-like materials, the internal relationship between microscopic characteristics (porosity, pore size distribution) and macroscopic mechanical properties of materials needs to be studied. This study selects portland cement, quartz sand, silica fume, and water-reducing agent as raw materials to simulate sandstone. Based on the Nuclear magnetic resonance (NMR) theory and fractal theory, the study explores the internal relationship between pore structure and mechanical properties of sandstone-like materials, building a compressive strength prediction model by adopting the proportion of macropores and the dimension of macropore pore size as dependent variables. Test results show that internal pores of the material are mainly macropores, and micropores account for the least. The aperture fractal dimension, the correlation coefficient of mesopores and macropores are quite different from those of micropores. Fractal characteristics of mesopores and macropores are obvious. The macropore pore volume ratio has a good linear correlation with fractal dimension and strength, and it has a higher correlation coefficient with pore volume ratio, pore fractal dimension and other variable factors. The compressive strength increases with the growth of pore size fractal dimension, but decreases with the growth of macropore pore volume ratio. The strength prediction model has a high correlation coefficient, credibility and prediction accuracy, and the predicted strength is basically close to the measured strength.

In this paper, the evolution process of microstructures of fine-grained marble and coarse-grained marble under cyclic dynamic impact is studied. The split Hopkins pressure bars (SHPB) are used to apply multiple impacts on rock samples with a constant dynamic stress. And the microstructural changes caused by each impact were detected by a nuclear magnetic resonance (NMR) system. Porosity, transverse relaxation time (T 2) spectral distribution, pore size distribution and magnetic resonance imaging under different dynamic impact cycles were obtained, and the evolution of the T 2 cutoff value (T 2c) of the rock was obtained by combining the centrifugal technique to calculate the permeability. The pores were classified into two categories according to the pore size and the fluidity of the fluid in the pores to study the effect of impact on the pore connectivity. According to the results of X-ray fluorescence (XRF) and X-ray diffractometry (XRD), it is found that the two marbles are the same in mineral composition but different in composition ratios. Due to the difference in particle size of marble and the difference in the number of pores, the magnitudes of microstructure changes of the two marbles are different, but they have a consistent trend: under the cyclic dynamic impact, the porosity of the two marbles gradually decreases, the pore size continues to decrease, the marble framework is compacted, the pore structure is gradually closed, and the permeability is weakened. The weakening of rock permeability is mainly caused by the overall decrease in pore size and loss of pore connectivity. INDEX TERMS Cyclic dynamic impacts, nuclear magnetic resonance, pore size, pore connectivity, permeability.

At present, the filling mining method is widely used. To study strength evolution laws of cemented tailings backfill (CTB) under different curing ages, in the experiment, mine tailings were used as aggregates, ordinary Portland cement (PC32.5) was used as cementing materials, and different additives (lime and fly ash) were added to make filling samples with the solids mass concentration at 74% and the cement-sand ratios 1:4, 1:6 and 1:8. Based on the nuclear magnetic resonance (NMR) technology, the porosity test of filling samples with curing ages of 3 d, 7 d and 28 d was carried out, and the uniaxial compressive strength test was carried out on the servo universal material testing machine. The relationship between the uniaxial compressive strength and porosity of backfills and the curing age in the three groups was studied, and change laws of the porosity variation and strength growth rate of backfills were analyzed. Based on the variation in porosity, the strength evolution model of the CTB under different curing ages was established, and the model was fitted and verified with test data. Results show that the uniaxial compressive strength, porosity, porosity variation, and strength growth rate of the three groups of backfills gradually increase with the increase of the curing age, the porosity of backfill basically increases with the decrease of the cement–sand ratio, and the porosity of backfill decreases with the increase of the curing age. Porosity variations and relative strength values of the three groups of backfills under different cement-sand ratios obey an exponential function, and the two have a good correlation, indicating that the established filling strength evolution model can well reflect strength evolution laws of the CTB with the change of curing age.

Freeze-thaw weathering changes the pore structure, permeability, and groundwater transportation of rock material. Meanwhile, the change in rock material structure deduced by frost heaving deteriorates mechanical properties of rock material, leading to instability and insecurity of mine slopes in cold regions. In this paper, rock-like specimens containing prefabricated cracks at different angles and having undergone various freeze-thaw cycles are used as the object. Their pore structure, compressive mechanical properties, strain energies, failure characteristics, and the connection between pore structure and mechanical properties are analyzed. Results show that the porosity, spectrum area of mesopores, and spectrum area of macropores increase with the increase in freeze-thaw cycles, while crack angle shows no obvious influence on pore structure. Peak stress and elastic modulus drop with the increase in freeze-thaw cycles, while peak strain shows an increasing trend. Peak stress and elastic modulus decrease in the beginning, and then increase with the increase in crack angle, while peak strain shows a reverse trend. Elastic strain energy and pre-peak strain energy drop with the increase in freeze-thaw cycles. Elastic strain energy decreases first, and then increases with the increase in crack angle. The correlation between the spectrum area of macropores and elastic modulus is the strongest among different pores. Elastic modulus and peak stress decrease with the increase in macropore spectrum area, and peak strain increases with the increase in macropore spectrum area.

In order to further study the internal relationship between the microscopic pore characteristics and macroscopic mechanical properties of cemented tailings backfill (CTB), in this study, mine tailings and ordinary Portland cement (PC32.5) were selected as aggregate and cementing materials, respectively, and different additives (anionic polyacrylamide (APAM), lime and fly ash) were added to backfill samples with mass concentration of 74% and cement–sand ratios of 1:4, 1:6 and 1:8. After 28 days of curing, based on the uniaxial compressive strength test, nuclear magnetic resonance (NMR) porosity test and the fractal characteristics of pore structure, the relationships of the compressive strength with the proportion and fractal dimension of pores with different radii were analyzed. The uniaxial compressive strength prediction model of the CTB with the proportion of harmless pores and the fractal dimension of harmful pores as independent variables was established. The results show that the internal pores of the material are mainly the harmless and less harmful pores, and the sum of the average proportions of the two reaches 73.45%. Some characterization parameters of pore structure have a high correlation with the compressive strength. Among them, the correlation coefficients of compressive strength with the proportion of harmless pores and fractal dimension of harmful pores are 0.9219 and 0.9049, respectively. The regression results of the strength prediction model are significant, and the correlation coefficient is 0.9524. The predicted strength value is close to the actual strength value, and the predicted results are accurate and reliable.