Abstract: It is of great practical value to know the degradation process of coarse-grained soil particles, but the research on predicting the process of particle gradation has not been sufficiently executed yet. To compensate this insufficiency, the study on predicting model for coarse-grained soil particle breakage process was carried out using logarithmic probability regression mathematic method. Based on the probability theory, a logarithmic probability regression method was first set up to simulate the particle gradation process of coarse-grained soil in integral distribution curve frame. And then, a ratio of survival probability to death probability (also called breakage probability) was introduced into this setup logarithmic probability regression method to develop a prediction model for the coarse-grained soil particle degradation. The sensitivity analysis of the predicting model parameters was presented, and the degradation imitation for coarse-grained soil was discussed in the frame system of integral distribution curves. After that, a new formula to calculate the Hardin relative particle breakage index was presented to replace traditional formula for Hardin relative particle breakage index. The new model was applied to predict the coarse-grained soil particle breakage process of several experimental data reported by other authors. Application results show that the model-predicted integral distribution curves were very close to the experimental integral distribution curves. The good agreement between the predicted particle breakage process and the tested particle breakage process verifies the feasibility of this predicting model for coarse-grained soil particle breakage process. The results of this study are helpful for the understanding of particle evolution of coarse-grained soil with intermediate process.

Key words: logarithmic probability, evolution of grain size distribution, particle breakage, relative particle breakage index, coarse-grained soil