This study develops and validates a meso-parameter prediction model for backfill materials in PFC3D, enabling efficient numerical construction under varying curing ages and mix ratios. A quantitative correlation was established between hydration degree of the backfill and macroscopic mechanical properties, facilitating prediction of performance evolution. Using the parallel bonded contact model, the effective modulus \(\overline{E}\) * was found to exhibit a linear relationship with the macroscopic elastic modulus E, while the stiffness ratio \(\overline{k}\) n/ \(\overline{k}\) s demonstrated a strong correlation with Poisson’s ratio v. Compressive strength σ was shown to depend on both \(\overline{k}\) n/ \(\overline{k}\) s and the bonding parameter σn/σs. Based on these relationships, a coupled chemo-mechanical prediction framework was developed to integrate hydration, mechanical response, and meso-scale input parameters. Validation against uniaxial and biaxial simulations demonstrated good agreement with laboratory tests, with mean errors below 8.5% for strength and 10% for deformation. Simulated failure modes closely reproduced experimental observations, confirming model reliability. Application to real stope conditions further demonstrated its capability to evaluate backfill strength. This work provides a mechanistic foundation for efficient and accurate parameter determination, supporting predictive modeling of cemented backfill systems.
