Search Results

Racing engines are required to be developed quickly in order to adapt to ever-changing regulations. A CFD-based optimization would be a useful tool to discover the best solution given the restrictions of the regulations. However, a CFD approach requires repeated trials and errors until the best solution is found because the numerical goal is unknown and the specifications required for the goal are never calculated back when using CFD. Therefore, this paper proposes an Empirically Integrated CFD Method. It is a combination of a one-dimensional CFD and several empirical equations that are derived from the racing engine database with physical meanings. These empirical equations give the CFD-based optimization a proper goal and primary specifications so as to make the optimization loop converge rapidly. This method is experimentally verified for its practical application with a prototype engine.