Direct numerical simulation of a stationary spherical particle in fluctuating inflows

Yuqi Wang, Zhengping Zhu, Ruifeng Hu, Lian Shen

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Fully resolved direct numerical simulations are conducted to study the effects of fluctuating freestream flow on the drag force and wake characteristics of a stationary spherical particle. Sinusoidal fluctuation around a mean value is adopted as the freestream velocity. The interaction between the particle and fluctuating flow is computed by the direct-forcing immersed boundary method. We principally consider the relative difference between the computed mean drag and the drag law of a uniform flow past the particle and the properties of drag fluctuation in different freestream fluctuation directions. For the influence of streamwise fluctuating inflow, the relative mean drag difference increases with the particle Reynolds number. At small or intermediate particle scale ratios, the relative mean drag difference is very close to zero, indicating that the classical drag law can be used in these cases, while a large particle scale ratio can induce a notable increase in the relative mean drag difference at a large particle Reynolds number and high fluctuation intensity. For the transverse fluctuating inflow, generally, there is an evident increase in the mean drag coefficient when the particle scale ratio is small. Compared with the streamwise fluctuation case, the drag fluctuation intensity is a little smaller with the transverse fluctuating inflow. An explicit empirical drag fluctuation law is obtained by fitting the data for streamwise fluctuating inflow. The wake characteristics are also analyzed, and they are found to be strongly dependent on the direction of inflow fluctuation.

Original languageEnglish (US)
Article number025019
JournalAIP Advances
Volume12
Issue number2
DOIs
StatePublished - Feb 1 2022
Externally publishedYes

Bibliographical note

Funding Information:
This work was financially supported by grants from the National Natural Science Foundation of China (Grant Nos. 11972175 and 92052202) and the Fundamental Research Funds for the Central Universities (Grant No. lzujbky-2020-17). The computation was partly performed at the Tianhe-2A supercomputer of the National Supercomputer Center in Guangzhou.

Publisher Copyright:
© 2022 Author(s).

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