A Multi-Parameter Iterative Design-Correction Method and Performance Analysis for sCO2 Axial Turbine Stages
Abstract
To facilitate accurate physical interpretation and representation of various design concepts for sup1ercritical carbon dioxide (sCO2) axial turbines and to improve both the efficiency and accuracy of their thermodynamic design, two conceptual design approaches were proposed in this study. One approach was developed based on the steam turbine concept design method, which involved iterative calculations of dimensionless parameters, such as the velocity ratio and degree of reaction. The other was derived from the gas turbine concept design method, which involved iterative calculations of the flow and loading coefficients. The physical implications of the thermodynamic calculation procedures and characteristics of the loss models associated with different turbine stage design methodologies were systematically investigated. Combined with a one-dimensional thermodynamic design case study of an sCO2 axial turbine stage, the applicability and critical implementation steps of each method in the sCO2 axial turbine design were validated. To address the current limitations of sCO2 axial turbine design methodologies, a unified framework for multiple turbine loss models was introduced, and high-precision loss model parameters were employed to iteratively correct the velocity coefficient. Based on the steam turbine design concept, a novel multi-parameter iterative methodology was established for sCO2 axial turbine stage design. This approach enables comprehensive one-dimensional thermodynamic design. Various performance parameters were examined, and multi-parameter iterations were conducted to derive the optimal design. The results provide solid technical support for the design and optimization of sCO2 axial turbine stages.
Fields of Study & Subjects
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Combustion and flame dynamics
Turbomachinery Performance and Optimization
Publication details
- Journal / source
- Applied Sciences
- Volume
- 16
- Issue
- 10
- Pages
- 4911–4911
- Publication date
- 14 May 2026
- Language
- EN