<![CDATA[Aluminium A356 alloy is extensively used in automotive and aerospace industries due to its superior castability, high strength-to-weight ratio, and excellent corrosion resistance. However, casting defects such as porosity, air entrapment, and incomplete mold filling remain persistent challenges that significantly compromise product quality and mechanical performance. This study presents a systematic optimization of Aluminium A356 casting parameters through Computational Fluid Dynamics (CFD)-based simulation of flow filling behavior, employing the Volume of Fluid (VOF) method combined with the k-ε turbulence model. Key process parameters investigated include pouring temperature (680–740°C), filling velocity (0.3-0.6 m/s), and gating system geometry. Simulation results indicate that an optimized combination of 720°C pouring temperature, 0.35 m/s filling velocity, and streamlined gating design reduces turbulence intensity by 42.3% and air entrapment volume fraction by 35.1% compared to baseline conditions. A parametric sensitivity analysis reveals that filling velocity exerts the dominant influence on defect formation, followed by gating geometry and pouring temperature. The findings are validated through cross-referencing with existing experimental data from the literature, demonstrating strong agreement. This research bridges a critical gap in integrating real-time defect prediction with gating system topology optimization for A356 gravity sand casting an area insufficiently addressed in prior simulation-based studies.]]>
