Numerical Investigation of Radial Turbines Subject to Pulsating Flow

Abstract: In the optic of a more sustainable society, research and development of highlyefficient fluid machines represent a fundamental process to satisfy the rapidlygrowing energy needs of the modern world. Radial turbines are characterizedby higher efficiencies for a larger range of inflow conditions compared to axialturbines. Due to this favorable characteristic, they find their natural applicationin turbocharger systems, where the flow is inherently unsteady due to the enginereciprocating. In a turbocharged engine, to exploit the residual energy containedin the exhaust gases, the radial turbine is fed by the exhaust gases from thecylinders of the engine. The particular inflow conditions to which a turbochargerturbine is exposed, i.e. pulsating flow and high gas temperatures, make the turbocharger turbine a unique example in the turbomachinery field. Indeed,pulsating flow causes performance deviations from quasi-steady to pulsating flowconditions, while heat transfer deteriorates the turbine performance. Modelingcorrectly these phenomena is essential to enhance turbocharger-engine matching.The problem is further complicated since, due to the geometrical diversity of thedifferent parts of the system, each component represents a stand-alone problem both in terms of flow characteristics and design optimization.In this thesis, high-fidelity numerical simulations are used to characterize the performance of a single-entry radial turbine applied in a commercial 4-cylinderengine for a passenger car under engine-like conditions. By treating the hot-sidesystem as a stand-alone device, parametrization of the pulse shape imposedas inlet boundary conditions has let to highlight specific trends of the systemresponse to pulse amplitude and frequency variations. Reduced-order models topredict the deviations of the turbine performance from quasi-steady to pulsating flow conditions are developed. At first, a simple algebraic model demonstratesthe proportionality between the intensity of the deviations and the normalizedreduced frequency. Then, a neural network model is demonstrated to accurately predict the unsteady turbine performance given a limited number of trainingdata. Lastly, a gradient-based optimization method is developed to identify theoptimum working conditions, in terms of pulse shape, to maximize the poweroutput of the turbine. High-fidelity LES simulations are used to improve the understanding of flowphysics. The flow at the rotor blade experiences different characteristics between continuous and pulsating flow conditions. In particular, large separations and secondary flows develop on both the pressure and suction sides of the blade asiiia consequence of the large range of relative inflow angles the blade is exposed to. Such secondary flows are addressed as the main cause of the drop of theisentropic efficiency from continuous to pulsating flow conditions.