The aim of this paper is to conduct a generalised assessment of both optimal working fluids and radial turbine designs for small-scale organic Rankine cycle (ORC) systems across a range of heat-source temperatures. The former has been achieved by coupling a thermodynamic model of subcritical, non-recperated cycles with the Peng–Robinson equation of state, and optimising the working-fluid and cycle parameters for heat-source temperatures ranging between 80 $°\mathrm{C}$ and 360 $°\mathrm{C}$ . The critical temperature of the working fluid is found to be an important parameter governing working-fluid selection. Moreover, a linear correlation between heat-source temperature and the optimal critical temperature that achieves maximum power output has been found for heat-source temperatures below 300 $°\mathrm{C}$ ( $T_{\mathrm{cr}}=0.830T_{\mathrm{hi}}+41.27$ ). This correlation has been validated against cycle calculations completed for nine predefined working fluids using both the Peng–Robinson equation of state and using the REFPROP program. Ultimately, this simple correlation can be used to identify working-fluid candidates for a specific heat-source temperature. In the second half of this paper, the effect of the heat-source temperature on the optimal design of a radial-inflow turbine rotor for a 25 kW subcritical ORC system has been studied. As the heat-source temperature increases, the optimal blade-loading coefficient increases, whilst the optimal flow coefficient reduces. Furthermore, passage losses are dominant in turbines intended for low-temperature applications. However, at higher heat-source temperatures, clearance losses become more dominant owing to the reduced blade heights. This information can be used to identify the most direct route to efficiency improvements in these machines. Finally, it is observed that the transition from a conventional converging stator to a converging-diverging stator occurs at heat-source temperatures of approximately 165 $°\mathrm{C}$ , whilst radially-fibered turbines seem unsuitable as the heat-source temperature exceeds 250 $°\mathrm{C}$ ; these conclusions can be used to inform expander design and selection at an early stage.

Supercritical carbon dioxide (sCO${}_2$) power cycles are promising candidates for concentrated-solar power and waste-heat recovery applications, having advantages of compact turbomachinery and high cycle efficiencies at heat-source temperature in the range of 400 to 800 ${}^{\circ }$C. However, for distributed-scale systems (0.1–1.0 MW) the choice of turbomachinery type is unclear. Radial turbines are known to be an effective machine for micro-scale applications. Alternatively, feasible single-stage axial turbine designs could be achieved allowing for better heat transfer control and improved bearing life. Thus, the aim of this study is to investigate the design of a single-stage 100 kW sCO${}_2$ axial turbine through the identification of optimal turbine design parameters from both mechanical and aerodynamic performance perspectives. For this purpose, a preliminary design tool has been developed and refined by accounting for passage losses using loss models that are widely used for the design of turbomachinery operating with fluids such as air or steam. The designs were assessed for a turbine that runs at inlet conditions of 923 K, 170 bar, expansion ratio of 3 and shaft speeds of 150k, 200k and 250k RPM respectively. It was found that feasible single-stage designs could be achieved if the turbine is designed with a high loading coefficient and low flow coefficient. Moreover, a turbine with the lowest degree of reaction, over a specified range from 0 to 0.5, was found to achieve the highest efficiency and highest inlet rotor angles.

For small-scale organic Rankine cycles (ORCs) to be a competitive technology, it is reasonable to assume that the same turbine design will be implemented into a range of different applications. It is therefore critical to be able to predict turbine off-design performance over a range of different operating conditions while utilizing different working fluids. Similitude theory can be used for this purpose, and it has been well validated for ideal gases. However, the same cannot be said for its applications to the organic fluids found within ORCs. This paper considers a candidate subsonic turbine design operating with R245fa and the corresponding turbine performance map. Similitude theory is used to predict the performance of the same turbine operating at different inlet conditions using R245fa, R123, and R1234yf. The similitude predictions are compared to computational fluid dynamics (CFD) results obtained using ansys CFX. The original similitude theory using turbine total inlet conditions was found to only apply within a small range of operating conditions, so a modified similitude theory has been suggested that uses the choked flow conditions instead. This modified similitude theory agrees with the CFD predictions to within 2%, right up until the choked mass flow rate. Further studies considering supersonic turbines are required to establish the applicability of similitude for applications beyond the choked pressure ratio.

Within this study, the blade shape of a large-scale axial turbine operating with sCO2 blended with dopants is optimized using an integrated aerodynamic-structural three-dimensional (3D) numerical model, whereby the optimization aims at maximizing the aerodynamic efficiency whilst meeting a set of stress constraints to ensure safe operation. Specifically, three candidate mixtures are considered, namely, CO2 blended with titanium tetrachloride (TiCl4), hexafluorobenzene (C6F6), or sulfur dioxide (SO2), where the selected blends and boundary conditions are defined by the EU project, SCARABEUS. A single passage axial turbine numerical model is setup and applied to the first stage of a large-scale multistage axial turbine design. The aerodynamic performance is simulated using a 3D steady-state viscous computational fluid dynamic (CFD) model while the blade stress distribution is obtained from a static structural finite element analysis simulation (FEA). A genetic algorithm is used to optimize parameters defining the blade angle and thickness distributions along the chord line while a surrogate model is used to provide fast and reliable model predictions during optimization using a genetic aggregation response surface. The uncertainty of the surrogate model, represented by the difference between the surrogate model results and the CFD/FEA model results, is evaluated using a set of verification points and is found to be less than 0.3% for aerodynamic efficiency and 1% for both the mass-flow rate and the maximum equivalent stresses. The comparison between the final optimized blade cross section has shown some common trends in optimizing the blade design by decreasing the stator and rotor trailing edge thickness, increasing the stator thickness near the trailing edge, and decreasing the rotor thickness near the trailing edge and decreasing the rotor outlet angle. Further investigations of the loss breakdown of the optimized and reference blade designs are presented to highlight the role of the optimization process in reducing aerodynamic losses. It has been noted that the performance improvement achieved through shape optimization is mainly due to decreasing the endwall losses with both the stator and rotor passages.