Numerical investigation and performance enhancement of an ammonia-water radial-outflow turbine through the flow-oriented optimization. (5th March 2023)

• Record Type: Journal Article
• Authors: Song, Peng; Sun, Jinju; Wang, Xuesong
• Is Part Of: Applied thermal engineering. Volume 222(2022)
• Publication Date: 2023-03-05
• Subjects: Kalina cycle -- Radial-outflow turbine -- Geometry optimization -- Flow-oriented objective function -- Adaptive optimization algorithm; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2022.119909
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: The flow mechanism in the ammonia-water radial-outflow turbine is revealed. Flow losses and flow matching oriented optimization is performed. An efficient design optimization method is developed for designing highly-efficient radial-outflow turbines with significantly reduced computational cost. The simultaneously optimization of the stator/rotor blades and their interactions is much favorable for the performance improvement of radial-outflow turbine. Abstract: The radial-outflow turbine has advantages due to its liquid-rich gas adaptability when applied in a Kalina ammonia-water cycle system for the utilization of geothermal energy and waste heat. However, the existing radial-outflow turbine shows relatively lower efficiency than the conventional radial-inflow turbines due to its distinct stage configuration and the lack of efficient design method. In the present study, numerical investigation has been conducted on a radial-outflow turbine adopted in Kalina cycle system, by which the turbine flow losses are analyzed. To enhance the turbine performance, a design optimization method has been developed, which includes the following features: the flexible geometry variations are realized to explore the optimization potentials, where the stator and rotor blades are optimized simultaneously; the flow-oriented objective function is established to drive the optimizer to suppress the flow losses in blade passages while adjust the flow matching. To solve the complex geometry optimization problem, adaptive optimization algorithm is imported to accelerate global searching and reduce the costly Computational Fluid Dynamics evaluations. The developed optimization method has been applied in the geometry optimization of a radial-outflow ammonia-water turbine. Benefitting from the fine-tuned blade geometries, the flow matching between stator and rotor is adjusted and the flow losses are mitigated. Thus, the turbine efficiency and shaft power are improved by 6.46% and 5.85%, respectively.