Optimizing Grain Milling via Python Simulation and Experimental Validation: Effect of Technical Clearance and Grain Physics

• Integrated a Python-based simulation with experimental validation to optimize hammer mill performance for corn and barley. • Identified a 4 mm technical clearance as the universal optimum for maximizing the 500–1000 µm target particle fraction. • Established a high-fidelity correlation (R2 = 0.96) between physics-based simulation models and empirical milling data. • Demonstrated that grain mechanical resistance (e.g., 240.5 N for barley) significantly dictates clearance sensitivity and energy efficiency. • Provided a robust engineering tool for precision milling automation and reducing specific energy consumption in feed production.