Latest paper on shape optimisation of axial turbine blades for supercritical carbon dioxide blends
Another paper from one of the PhD students that I co-supervise at City, University of London. Great to see this paper published after first being presented at the ASME Turbo Expo 2021, and subsequently being recommended for journal publication in the Journal of Engineering for Gas Turbines and Power. The paper explores the shape optimisation of turbine blades for axial turbines operating supercritical carbon dioxide blends and integrates aerodynamic and mechanical design considerations to arrive at optimised geometries that provide maximum efficiency, whilst not exceeding the stress limitations of the material.
Download the open-access article for free here.
Integrated aerodynamic and structural blade shape optimization of axial turbines operating with supercritical carbon dioxide blended with dopants
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.
Acknowledgement
The SCARABEUS project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 814985.