Method for mean-line design and performance prediction of one-stage axial turbines

Abstract

Today, expanders for Organic Rankine Cycles (ORC) are either inefficient or expensive. One reason for this is that expanders of power conversion systems usually operate under different conditions over an annual perspective. Still, they are designed to perform best at a single operating point. In view of this limitation, it is suggested that the overall expander performance can be improved by taking into account off-design operation in the design process. As the first step in this direction, this paper presents a two-fold method for design optimization and performance analysis of one-stage axial turbines. The method utilizes the same mean-line model for performance analysis and design optimization, ensuring consistency between the two modes. In addition, the proposed method evaluates the turbine performance at three stations for each blade row: inlet, throat and exit, and employs a novel numerical treatment of flow choking that automatically determines which blade rows are choked as part of the solution. Furthermore, the method was validated against cold-air experimental data from three different one-stage axial turbines, at both on- and off-design conditions. The model predicts design point efficiencies between 1.1 and 4.5 percentage points off the experimental values. The model was also able to capture the trend of mass flow rate as a function of total-to-static pressure ratio and angular speed. However, an unphysical behavior was observed as the pressure ratio approaches the critical value, and further developments of the model are required. It is envisioned that the proposed method will serve as foundation for a robust design methodology that will enable higher expander performance over a range of operating conditions.