A reduced order model to predict the machining time and cost of small-scale radial-inflow turbines

This paper proposes a novel approach to predict the machining time of small-scale radial-inflow turbine impellers for organic Rankine cycle power systems based on preliminary design parameters. The time prediction method uses machining databases of different milling tools for the estimation of the cutting parameters, on which basis the flow channel volume and surfaces are discretized for the generation of preliminary milling toolpaths. The parameter selection comprises the material selection, the volume removed, the demanded surface quality and the tool selection governed by the accessibility due to geometrical limitations induced by the blades. The model is verified using computer-aided manufacturing software for two radial-inflow turbines cases: a state-of-the-art turbine using air and a turbine using the working fluid Novec 649 for a heat recovery application. The results highlight the governing role of the tool slenderness ratio on the actual manufacturing time. The relative time distribution among roughing, semi-finishing and finishing operations remain similar when considering the same production chain. The tool roughing strategy holds potential for optimization by contributing to approximately 60 % of the total milling time. Furthermore, the results indicate that the turbine manufacturing time can be improved by up to approximately 44 % when the maximum permissible load limits of the tools are exploited by customized cutting data. The presented machining time model can be applied in future works to predict the manufacturing costs of impellers and to quantify the influence of individual design features on the total cost by performing a sensitivity analysis. Moreover, the design space for optimal designs of small-scale radial-inflow turbines for organic Rankine power applications considering both the manufacturing time and the performance of the expander can be explored