AI Summary & Key Takeaways
AI InsightThe findings provide insights into optimizing engine design for improved performance and efficiency.
📌 3 Key Takeaways
Abstract
This study focuses on enhancing the airflow performance and achieving an optimal flow distribution within the cylinder of a 300CC internal combustion engine. Various parameters were analyzed using computational fluid dynamics (CFD) simulations in ANSYS Fluent to identify the most suitable turbulence model for intake manifold flow analysis. The investigation encompassed two different mass flow rates (0.1 kg/s and 0.05 kg/s), four turbulence models (SST k−ω, Realizable k−ϵ, RNG k−ϵ, RSM Reynolds Stress Model), and two flange positions (0 mm and 44 mm). The simulations were conducted with a 0.5-million-cell polyhedral mesh. The analysis evaluated airflow characteristics, pressure losses, and mass flow distribution within the intake manifold and cylinder, as well as swirl patterns. All boundary conditions and external variables were maintained constant across simulations to ensure comparability. The study specifically considered a two-stroke engine configuration, characterized by continuous airflow through ports instead of the intermittent valve operation found in four-stroke engines. The findings provide insights into optimizing engine design for improved performance and efficiency.