With the increasing depth of mining operations and the emergence of complex geological conditions, pneumatic down-the-hole (DTH) hammers have become an efficient drilling technology. This method utilizes high-pressure air to drive hammering actions for rock fragmentation. However, the layout and durability of tungsten carbide buttons significantly affect the rate of penetration (ROP). This study focuses on optimizing the button arrangement for large-diameter reverse circulation pneumatic DTH hammers to improve drilling efficiency. A numerical model incorporating zero-thickness cohesive elements was developed to simulate rock fracturing. A comparative analysis of 16 mm and 22 mm buttons under varying drilling pressures (1–1.8 kN) and impact energies (20–40 J) was conducted. Key metrics, including penetration depth, fragmentation range, stress-affected zone, and specific energy consumption, were analyzed. The results indicate that 22 mm buttons under 35 J impact energy and 1.4 kN drilling pressure exhibit superior performance, with optimal circumferential (47.2 mm) and radial (51.2 mm) spacing determined through stress superposition analysis. This configuration enhances the weakened rock strength zone, providing critical guidance for DTH hammer design.

The reverse circulation pneumatic down-the-hole (DTH) drilling system employs percussive drilling to achieve high efficiency and strong adaptability across diverse rock formations. However, its cutting removal efficiency remains suboptimal. To enhance reverse circulation performance, a comprehensive understanding of airflow and solid particle dynamics at the borehole bottom is essential. This study investigates rock cutting transportation and distribution under varying drilling parameters and evaluates reverse circulation flow ratio using a Computational Fluid Dynamics (CFD) multiphase flow model, coupled with finite volume analysis of the reverse circulation bit. Simulation results reveal that increasing the input gas flow rate (Q), reducing the equivalent particle diameter (D), and minimizing the borehole enlargement ratio (E) significantly improve cutting removal efficiency, with optimal values identified for each parameter. Additionally, solid volume fraction contours at the borehole bottom indicate that the arrangement of spherical teeth influences the flow field. Optimal values for rock cutting density (ρ), rate of penetration (ROP), and rotational speed (N) were also determined to maximize reverse circulation flow ratio. The Genetic Algorithm–Least Squares Support Vector Machine (GA-LSSVM) method was used to train the response surface data and construct a predictive model, which was then further optimized using Particle Swarm Optimization (PSO) to determine accurate parameter settings. These findings provide operational insights into optimizing drilling parameters to advance efficient drilling performance.