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tag A mean-line model to predict the design efficiency of radial inflow turbines in Organic Rankine Cycle (ORC) systems
Luca Da Lio, Giovanni Manente, Andrea Lazzaretto
Session: Poster session & Welcome drinks
Session starts: Wednesday 13 September, 17:30



Luca Da Lio (University of Padova)
Giovanni Manente ()
Andrea Lazzaretto ()


Abstract:
The favorable thermodynamic properties of an organic fluid make the Organic Rankine Cycle (ORC) systems the best option for power generation from low-to-medium temperature heat sources due to the lower heat transfer irreversibilities and higher efficiencies compared to steam power systems. The lack of extensive experimental data on the efficiency of turbines operating with high molecular weight fluids makes turbine design a very challenging task. In particular, a low enthalpy drop, large volume flow ratios per expansion stage and low speed of sound represent very different flow conditions from those generally experienced by steam or air. In this paper the preliminary results obtained by a 1D model of single stage radial inflow turbines operating with R245fa are presented. The model takes into account the real gas properties and is organized into two main consecutive steps: the “preliminary design” (PD) and the “performance analysis” (PA). In the former a first turbine geometry is defined starting from the cycle design specifications and non-dimensional parameters (velocity ratio and specific speed). In the latter the turbine efficiency is calculated using the loss correlations specifically developed by Aungier (2005) for radial inflow turbines or adapted from the centrifugal compressor field. As the preliminary design requires first attenpt values for the efficiency and the total rotor inlet pressure, several cascaded PDs-PAs are needed until convergence. The first runs of the model at different cycle design specifications and non-dimensional parameters already provide a clear indication of their influence on the efficiency of single stage radial inflow turbines for ORC systems.