Research on efficient numerical method of air flow and heat transfer in a refrigerated truck

This study employs computational fluid dynamics (CFD) simulations to analyze airflow and heat transfer in refrigerated trucks, comparing two turbulence models: the BSL k - ω and SST k - ω . Optimal simulation parameters were determined through validation, including a convergence criterion of 10 -4 and a time step of 0.1 s. The analysis incorporates both iterative (ITA) and non-iterative time-advancement (NITA) schemes to assess computational efficiency. The research aims to compare the accuracy and efficiency of the BSL k - ω and the SST k - ω models, establish an optimal numerical method for reliable simulations, and evaluate the computational benefits of NITA over traditional ITA schemes. This work provides the first systematic comparison of the BSL k - ω and the SST k - ω models for refrigerated truck applications, demonstrating significant computational savings through model selection and NITA implementation. The study also quantifies the impact of turbulent viscosity differences on convergence behavior. Both k - ω models accurately predict the overall temperature field, aligning well with experimental data despite minor local discrepancies. The BSL k - ω model converges faster than the SST k - ω model due to its larger turbulent viscosity, reducing computational cost by 33.1%. The NITA scheme further cuts simulation time to 61.3% of the ITA scheme's duration (690 minutes) when combined with the BSL k - ω model. These findings provide valuable insights for improving the efficiency of refrigerated trucks’ design and optimization.