De Vos, S., Haehndel, K., Frank, T., Christel, F. et al., "The Development of Turbine Volute Surface Temperature Models for 3D CFD Vehicle Thermal Management Simulations: Part 3: Exhaust Radial Turbine Volute Systems," SAE Int. J. Passeng. Cars - Mech. Syst. 7(2):714-727, 2014, https://doi.org/10.4271/2014-01-0648.
Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel  implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger. This paper addresses the fluid flow phenomena present in the turbine volute and applies augmented Nusselt correlations to accurately represent the heat transfer coefficients of the internal volute surface. Due to the broad range of operating conditions that are applicable to the turbocharger and the varied states of fluid flow that occur, algorithms are used to apply the appropriate Nusslet correlations and augmentations. Furthermore, the turbocharger extracts enthalpy from the working fluid; therefore to accurately calculate surface temperatures of downstream components and that of the turbocharger itself, an energy extraction model is used. Validation was conducted with four vehicle configurations. The hot-end of each configuration was aimed to be distinctly different to test the robustness of the prediction model. A tolerance range of +50/−20K was used for the study, however temperature differences were generally well within the tolerance range.