Numerical and experimental investigation to visualize the fluid flow and thermal characteristics of a cryogenic turboexpander
Manoj Kumar,
Suraj K. Behera,
Amitesh Kumar and
Ranjit K. Sahoo
Energy, 2019, vol. 189, issue C
Abstract:
The increasing demand for cryogenic fluids is acquiring the research attention to develop efficient machines to produce cryogenic temperature such as turboexpander based system. The expansion turbine and nozzle of a turboexpander are the critical components of such systems, and its performance has a significant effect on the overall efficiency of the system. In this paper, the effective design methodology of a radial inflow turbine by considering different loss models is presented. The methodology consists of one-dimensional modeling to describe the geometrical parameters of the nozzle and turbine. The optimal range of important non-dimensional variables such as blade speed, pressure ratio, ratio of hub and shroud radius to turbine inlet radius are predicted using artificial intelligence techniques for better performance of the turbine. This approach improves the turbine efficiency and power output by 4% and 18.9% respectively as compared to the existing model. The three-dimensional numerical investigation is carried out to visualize the fluid flow and thermal characteristics of the designed turbine and nozzle. The study also focuses on to identify the flow separation zone, tip leakage flow, vortex formation, secondary losses and its reasons at different spanwise locations of the turbine. Additionally, Sobol sensitivity analysis method is used to distinguish the significance of different assumed constants on the total losses and non-dimensional design variables on total-to-static efficiency. Finally, the numerical results are validated with experimental data of a case study. The study highlights the importance of the design methodology, the prediction capability of artificial intelligence method, Sobol sensitivity analysis, the experimental techniques and benchmarking model for numerical analysis at different cryogenic temperature.
Keywords: Turboexpander; Experimental techniques; Artificial intelligence techniques; Sobol sensitivity analysis (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319620
DOI: 10.1016/j.energy.2019.116267
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