Study on prediction model of cumulative plastic strain of Pisha sandstone based on grey systems theory

Abstract

Pisha sandstone (PS) rapidly collapses in water and its performance deteriorates seriously, and its special engineering properties have always been the focus of researchers. In areas where fillers are scarce, it is of great significance to use PS as roadbed fillers to slow down soil erosion and green environmental protection. However, the long-term deformation characteristics after construction need further study. To reveal the long-term dynamic characteristics of Pisha sandstone fillers (PSF) under vehicle load, this study conducted the cyclic loading test of PSF by using the GDS triaxial test system. The deformation characteristics of PSF under different cyclic stress ratios (ζ) and load frequencies (f) were studied. The grey correlation analysis method was used to obtain the correlation degree of each influencing factor to the cumulative plastic strain (CPS) of the PSF. Finally, the grey GM (1,1) model is used to predict the CPS data of PSF. Based on this, the classical semi-logarithmic strain model is modified, and the CPS prediction model of PSF is established. The results reveal that the ζ and f will promote the development of axial deformation of PSF. The axial elastic deformation (ε_e) and CPS of PSF increase with the increase of ζ, and the ζ has a great influence on the CPS. The influence of f on ε_e is more significant at high stress levels and less significant at low stress levels. The influence of f on CPS is opposite to that of ε_e, that is, the influence of high stress level is small, and the influence of low stress level is large. According to the degree of correlation, the factors are sorted according to the degree of influence: static strength (σ_f) > confining pressure (σ₃) > dynamic static stress ratio (η) > load frequency (f) > cyclic stress ratio (ζ). The GM (1,1) model has high accuracy and reliability for the quantitative description and prediction of the CPS of PSF. At the same time, according to the test and GM (1,1) model prediction results, the CPS prediction model of PSF was established. The research can provide insights and references for the establishment of cumulative deformation and prediction model of PSF under cyclic loading.