Surface strip mining requires coordinated excavation, waste redistribution, and ore recovery under strong geometric and operational constraints. Existing planning models quantify volumes and schedules but do not update terrain explicitly, while most simulation approaches represent equipment flow without reconstructing excavation and spoil geometry. This study proposes a spatially explicit terrain-evolution simulation framework for strip mining that integrates geological surfaces, strip and bench sequencing, equipment-dependent material handling, and dynamic terrain updating within a unified grid-based model. The framework distinguishes between two excavation paradigms: draglines are modeled as surface-following systems with casting-based spoil placement, whereas dozers are represented as elevation-controlled systems with directional push-based placement. Geological surfaces are discretized on a structured grid to compute interval thickness, bench-level bank volumes, and loose volumes. Material is then routed according to bench-specific destination rules, including internal dumping into the corresponding strip of the previously mined trench, external waste routing, and ore extraction outside the terrain-reconstruction domain. The simulator updates terrain after each excavation and placement event and tracks lithology distribution within reconstructed spoil. The case study is designed as a scenario-analysis platform for selective mining, byproduct extraction, and operational efficiency assessment. In addition to reproducing sequential terrain change and spoil geometry, the framework enables comparison of alternative recovery strategies under common geological and operational conditions. The proposed approach provides a computationally efficient bridge between strategic mine planning and operational simulation and supports future scenario testing for recovery improvement, waste management, and mine planning optimization.

Keywords

Strip mining, Terrain-evolution simulation, Internal dumping, Spoil reconstruction, Selective mining.