A detailed loss assessment of an axial turbine stage operating with a supercritical carbon dioxide (sCO2) based mixture, namely titanium tetrachloride (CO2-TiCl4 85-15%), is presented. To assess aerodynamic losses, computational fluid dynamics (CFD) simulations are conducted using a geometry generated using mean-line design equations which is part of the work delivered to the SCARABEUS project [1]. The CFD simulations are 3D steady state and employ a number of turbulence models to investigate various aerodynamic loss mechanisms. Two categories of turbulence models are used: Eddy Viscosity and Reynold’s Stress models (RSM). The Eddy Viscosity models are the k-ε, k-ε RNG, k-ω, k-ω SST and k-ω Generalized while the RSM models are BSL, LRR, w-RSM and k-ε EARSM. The comparison between different turbulence models showed minor deviations in mass-flow rate, power output and blade loading while significant deviations appear in the loss coefficients and the degree of reaction. It is noted that the k-ε model gives the highest loss coefficients and the lowest isentropic efficiencies while most of the RSM models indicate higher efficiencies and lower loss coefficients. At off-design conditions a sensitivity study revealed that the k-ε RNG model records the sharpest drop in the isentropic efficiency of 8.24% at low mass flowrate reaching 30% off-design. The efficiency sensitivity is found to be less for the other tested models getting 3.1% drop in efficiency for the LRR RSM model.

In this paper, a modified loss breakdown approach is introduced for axial turbines operating with supercritical carbon dioxide (sCO2) mixtures using CFD results. Loss breakdown analysis has been previously developed using two approaches, however each approach has its own uncertainties. The first approach neglects the effects of cross-interaction between the different loss sources, while the second approach ignores the potential changes to the boundary layer thicknesses and the loss source domains. Although the second methodology accounts for the interactions between the different loss sources, it may produce less accurate predictions for compact machines like sCO2 turbines where the boundary layer may dominate the flow passage. The proposed methodology aims to obtain the turbine loss breakdown using a single CFD model where all sources of aerodynamic loss coexist, while considering variable loss regions defined based on the velocity and entropy distribution results. A steady state, single-stage, single-passage, 3D numerical model is set up to simulate the turbine and verify the loss audit methodology. The results are verified against the published loss audit methodologies for a 130 MW axial turbine operating with CO2/C6F6 blend. The results show a good agreement between the proposed approach and the multiple-model approaches from the literature. However, the existing approaches appear to overestimate endwall losses by 13~16% and underestimate the profile losses by 11~31% compared to the proposed approach. Compared to mean line loss models, large differences in loss sources are observed especially for the stator and rotor endwall losses.

Within this study, the blade shape of a large-scale axial turbine operating with sCO2 blended with dopants is optimised using an integrated aerodynamic-structural numerical model to maximise the aerodynamic efficiency whilst meeting stress constraints. Three candidate mixtures are considered, namely CO2 blended with titaniumtetrachloride (TiCl4), hexafluorobenzene (C6F6) or sulfur dioxide (SO2) defined by the EU project, SCARABEUS. The aerodynamic performance is simulated using a single passage, 3D, steady-state, viscous computational fluid dynamic (CFD) model while the blade stress distribution is obtained from a static structural finite element analysis (FEA). A genetic algorithm is used to optimise 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 optimisation using genetic aggregation response surface. The uncertainty of the surrogate model is evaluated using a set of verification points and found 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 optimised blade cross-sections have shown some common trends in optimising the blade design by decreasing stator and rotor trailing edge thickness, increasing stator thickness near the trailing edge, decreasing rotor thickness near the trailing edge and decreasing the rotor outlet angle. Further investigations of the loss breakdown of the optimised and reference blade designs are presented. It has been noted that the performance improvement achieved is mainly due to decreasing the endwall losses of both blade rows.

Within this study, the blade shape of a large-scale axial turbine operating with sCO2 blended with dopants is optimised using an integrated aerodynamic-structural 3D numerical model, whereby the optimisation aims at maximising the aerodynamic efficiency whilst meeting a set of stress constraints to ensure safe operation. Specifically, three candidate mixtures are considered, namely CO2 blended with titaniumtetrachloride (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 multi-stage 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 (FEA). A genetic algorithm is used to optimise 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 optimisation using 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 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 optimised blade cross-sections have shown some common trends in optimising the blade design by decreasing stator and rotor trailing edge thickness, increasing stator thickness near the trailing edge, decreasing rotor thickness near the trailing edge and decreasing the rotor outlet angle. Further investigations of the loss breakdown of the optimised and reference blade designs are presented to highlight the role of the optimisation process in reducing aerodynamic losses. It has been noted that the performance improvement achieved through shape optimisation is mainly due to decreasing the endwall losses of both stator and rotor blades.