This paper describes the methodology used to select an application-based fan that has optimum operating characteristics in terms of cooling air flow rate, fan power, and noise. The selected fan is then evaluated for structural strength.
To evaluate different fans, complete rail coach under-hood simulations were carried out using steady-state 3D computational fluid dynamics (CFD) approach. These simulations considered an actual, highly non-uniform flow field. For each fan option, fan power, air flow rate, and surface acoustic power was evaluated. Pressure profiles on the fan blades were studied to assess the effect of non-uniform downstream air passage designs. Surface acoustic power was calculated using broadband noise source (BNS) model in ANSYS Fluent®. Surface pressure profiles over fan blades imported from 3D CFD were used in finite element analysis (FEA) in ANSYS. Analyses were carried out for blade linear and non-linear properties. Equivalent fully reversed (EFR) stress was calculated based on an internal code that uses Goodman theory.
It can be concluded from simulation study that the fluid structural coupled approach can be used to predict and optimize machine cooling system performance. This is useful for optimum fan selection in the design phase, thus reducing product design cycle-time and re-work cost. It also helps to increase product reliability, which is critical for rail application.