3.8 Proceedings Paper

An investigation into sCO2 compressor performance prediction in the supercritical region for power systems

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.egypro.2019.02.098

关键词

supercritical CO2; turbomachinary desing; computational fluid dynamics; real gas thermodynamics

资金

  1. European Union's Horizon 2020 research and innovation programme [680599]
  2. Centre for Sustainable Energy Use in Food Chains (CSEF)
  3. Engineering and Physical Sciences Research Council (EPSRC) [EP/P04636/1]
  4. Research Councils UK [EP/K011820/1]
  5. H2020 Societal Challenges Programme [680599] Funding Source: H2020 Societal Challenges Programme

向作者/读者索取更多资源

This paper focuses on predicting centrifugal compressor performance in the supercritical region of real gas. For this purpose, thermodynamic changes have been considered in the sub-regions of the supercritical space. It is known that some properties (e.g. compressibility or density) of supercritical fluids behave anomalously in a narrow temperature-pressure band, shaped by pseudocritical lines, which start at the critical point and extend to higher T and P values. To accurately predict the performance of supercritical carbon dioxide (sCO(2)) turbomachinery, the fluid behavior, in three regions (liquid-like, pseudocritical and vapour-like) created by pseudocritical lines, should be considered. For this purpose, computational fluid dynamics (CFD) is employed to calculate compressor performance in different regions of the supercritical space. The selected compressor geometry is the compressor impeller tested in the Sandia sCO2 compression loop facility. The results illustrate that operating points in the liquid-like region achieve the highest pressure rise. In addition, fluctuations in two fluid properties, density and speed of sound, have been observed wherever their pseudocritical lines have been crossed. However, the reason for these variations needs more investigation. The study considers the sudden changes occurring in the supercritical region and should lead to more accurate prediction of compressor performance,. (C) 2019 The Authors. Published by Elsevier Ltd.

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