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Title: Numerical calculation of the particle–fluid–particle stress in random arrays of fixed particles

Journal Article · · Physical Review Fluids
ORCiD logo [1];  [2]; ORCiD logo [1];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of Florida, Gainesville, FL (United States)
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Based on the nearest particle statistics [Zhang, J. Fluid Mech. 910, A16 (2021)], the phase interaction force in a multiphase flow is decomposed into a particle–mean-field force and the divergence of the particle–fluid–particle (PFP) stress. The PFP stress is proportional to the correlation product of the distance from a particle to its nearest neighbor and the force on the particle conditionally averaged on the nearest-neighbor location. In this work, a functional form of the stress is obtained corrected to the first order of the ratio between the interparticle distance and the macroscopic length scale of the flow. Particle-resolved numerical simulations are used to calculate the PFP stress in random arrays of fixed particles and to explore the physics represented by the stress. The numerical results show that the PFP stress is attractive along the direction of the flow and is repulsive in the directions perpendicular to the flow. In the flow regime simulated, this PFP stress can be considered as a macroscopic representation of the drafting–kissing–tumbling mechanism. Finally, the Reynolds stress for the fluid phase is also calculated and compared with the PFP stress.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
US Office of Naval Research (ONR); USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
89233218CNA000001; NA0002378
OSTI ID:
1834526
Report Number(s):
LA-UR--21-20229
Journal Information:
Physical Review Fluids, Journal Name: Physical Review Fluids Journal Issue: 10 Vol. 6; ISSN 2469-990X
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English

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