4.7 Article

Numerical investigation on the drag characteristics of supercritical water flow past a sphere

Journal

SCIENCE CHINA-TECHNOLOGICAL SCIENCES
Volume 63, Issue 8, Pages 1509-1519

Publisher

SCIENCE PRESS
DOI: 10.1007/s11431-020-1684-2

Keywords

supercritical water; numerical simulation; sphere; drag coefficient

Funding

  1. National Natural Science Foundation of China [51922086]
  2. China National Key Research and Development Plan Project [2016YFB0600100]

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Numerical simulation has become a useful approach to explore the complex physical and chemical process inside the supercritical water (SCW) fluidized bed reactor. Due to the drastic and non-linear variation of water properties near pseudocritical point, the flow field and drag coefficient of SCW flow past a cold particle are considerably different from that of conventional flow. Therefore, in this work, particle-resolved numerical investigation is conducted to study the flow field and drag characteristics under the influence of the special water properties variation. Through varying the enthalpy corresponding to the particle surface temperature, which will be called the particle surface enthalpy for short, in a wide range, it realizes the study under different properties variation tendencies. The simulated results demonstrate that the variations of drag coefficient versus Reynolds number (Re) and particle surface enthalpy are in good regularity when taking the freestream temperature as reference temperature. The drag coefficient is enhanced greatly at high enthalpy difference between particle surface and inflow, and the enhancement is mainly contributed by that of the frictional drag coefficient. Moreover, the drag coefficient variations under different pressures are in good agreement when cases are set with the same inflow and particle surface enthalpies, respectively. By fitting the simulated results, a new drag coefficient correlation is developed forRerange of 10-200 with consideration of the influence of the special properties variation. The fitting quality is good that the maximum deviation between the new correlation and simulated data is 13.92%, and the mean deviation is 3.67%.

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