Preliminary design, flow field, and thermal performance analysis of a helium turboexpander: a numerical approach

Abstract

Most studies on cryogenic turboexpanders are focused on parametric studies and mean-line design to increase the performance of cryogenics liquefaction cycle without much attention to the splitter blades which are crucial for the stability of the flow field. This study focuses on a novel mean-line design methodology to develop the radial turbine and nozzle (hereafter renowned as turboexpander) to investigate the performance characteristics. Firstly, Sobol sensitivity analysis is performed to identify the effect of major non-dimensional design variables on isentropic efficiency of the turbine. Secondly, the non-dimensional design variables are optimized using artificial intelligence techniques. Thirdly, three turboexpander models with and without splitter blades are designed within the optimized range of non-dimensional variables. After that, the three-dimensional numerical analysis is carried out to visualize the effect of splitter blades on flow field and thermal characteristics of the turboexpander. It is noticed that the passage vortices and flow separation are minimized using the splitter blades. The numerical results are further validated with available data in the literature. A detailed comparative analysis of Mach number, pressure, temperature, velocity, static enthalpy, static entropy, etc., is carried out at different operating conditions. The results reveal that the use of splitter blades has a tremendous effect on the performance and flow field characteristics of the radial turbine. The proposed methodology specifies the insights for an optimum turbine design methodology of a cryogenic turboexpander, Sobol sensitivity analysis, prediction capability of artificial intelligence methods, numerical techniques to simulate the assimilating performance of turboexpander, as it is the most crucial and expensive component of turboexpander-based cryogenic system.