Research on PFC3D meso-parameters prediction model and strength simulation of backfill based on hemical-mechanical coupling - Scientific Reports

In summary, this study utilizes the parallel bond contact model in PFC3D to calibrate meso-parameters, with the aim of establishing a mathematical correlation among hydration degree, macroscopic mechanical properties, and meso-parameters. This ultimately facilitates the construction of a chemical-mechanical coupling prediction model for the mesoscopic parameters of backfill materials. The predictive model enables the rapid construction of numerical models for the backfill under different ratios and curing ages, ensuring alignment with existing experimental data on uniaxial and biaxial loading strengths. The model's reliability is subsequently verified. Finally, based on the lithological conditions of the actual project, the minimum required strength of the filling body for the one-step goaf following the two-step excavation process is determined through numerical simulation. This study contributes to the theoretical understanding of backfill mechanical properties and holds practical significance for enhancing the understanding of backfill property evolution, as well as achieving cost reduction and efficiency improvements in mine filling operations.

As cement undergoes hydration within the backfill material, its mechanical properties -- including elastic modulus, Poisson's ratio, and compressive strength -- exhibit time-dependent evolution with progressing hydration degree. Consequently, parameters obtained through "trial-and-error method" fail to quantitatively describe the intrinsic meso-macro relationships, limiting their predictive capacity for mechanical behavior under advanced hydration stages. Therefore, it is essential to establish a correlation between hydration degree and macroscopic mechanical properties. Subsequently, the interdependence between macroscopic mechanical response and meso-scale parameters must be integrated to develop a chemo-mechanically coupling prediction model for PFC meso-parameters. The mechanical properties formulas and model paramet