Numerical Investigation and Performance Enhancement by Means of Geometric Sensitivity Analysis and Parametric Tuning of a Radial-Outflow High-Pressure Oil–Gas Turbine

Peng Song (), Shengyuan Wang and Jinju Sun
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Peng Song: School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Shengyuan Wang: School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Jinju Sun: School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Energies, 2022, vol. 15, issue 22, 1-21

Abstract: The pressure at the natural gas wellhead typically ranges from tens to hundreds of atmospheres. Traditionally, the wellhead pressure must be throttled into a low level to satisfy the requirement of gathering pipelines, in which a large amount of pressure energy is wasted. The high-pressure oil–gas turbine is a promising approach to convert the wellhead pressure energy into shaft power or electricity. In this paper, a numerical investigation is conducted on a radial-outflow high-pressure oil–gas turbine utilized in a wellhead pressure power generation system. Using the self-defined real oil–gas physical properties and Computational Fluid Dynamics (CFD), the internal flow and performance of the high-pressure oil–gas turbine under complex operating conditions are investigated. To improve the turbine flow and performance, a Latin Hypercube Sampling-based parametric tuning is performed on the stator and rotor blade geometries. The application of such an approach effectively adjusts the flow matching and eliminates the flow separation, by which the turbine performance is significantly enhanced.

Keywords: natural gas; pressure energy utilization; radial-outflow turbine; CFD; oil–gas mixture (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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