Modeling & Simulation, Testing & Validation (MSTV)


by Bashar AbdulNour; Mohsen Battoei; Mark Doroudian


Cooling and heat protection of the engine compartment significantly impact the performance of combat vehicles. An increased heat load occurs during soak-back after engine shut down, where the fans are shut down. Heat is transferred from the hot components in the engine compartment by natural convection to the surrounding air and by radiation to the armor. The heat is then dissipated to the ambient mostly by convection from the outside surfaces. The objective of this study is to develop a methodology to predict the engine compartment airflow velocity and temperature distributions, as well as the surface temperature of critical engine components following engine shut down. This study was conducted using a full-scale, mock-up engine compartment of a typical wheeled combat vehicle under steady-state and transient operating conditions. The Computational Fluid Dynamics (CFD) package Fluent was used to conduct the simulation. Steady-state simulation was performed first to predict the condition prior to the soak-back. A transient simulation was then performed to predict the flow and temperature fields during soak-back. The developed methodology includes the creation of a conjugate heat transfer model. During soak-back, the stored thermal loads from the engine, transmission, oil pan, and exhaust system start to transfer to the air in the engine compartment by natural convection. This causes a temporary rise in air temperature of the engine compartment environment. This temperature rise causes more heat transfer to the crew compartment. It could also damage thermally sensitive components by approaching their critical design temperature. The engine compartment air temperature starts to drop following the temporary rise until temperature equilibrium is achieved. The rate of the reduction in temperature and the time that is required to reach thermal equilibrium depends on the ambient air temperature and wind speed. A significant advantage of this analytical methodology is that no physical model is required.