Mixing in Low Reynolds Number Reacting Impinging Jets in Crossflow

Hubbard, Joshua A.; Cheng, Meng-Dawn; Domino, Stefan P.

doi:10.1115/1.4056894

Title: Mixing in Low Reynolds Number Reacting Impinging Jets in Crossflow

Journal Article · Tue Mar 07 00:00:00 EST 2023 · Journal of Fluids Engineering

DOI:https://doi.org/10.1115/1.4056894· OSTI ID:1969827

Hubbard, Joshua A. ^[1];

^[2]; Domino, Stefan P. ^[3]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Institute for Computational and Mathematical Engineering, Stanford, CA (United States)

Previous efforts to model uranyl fluoride formation in an impinging jet gas reactor underpredicted spatial mixing and overpredicted chemical conversion into particulates. The previous fluid dynamics model was based on the solution of the Reynolds Averaged Navier Stokes equations. After simulating fluid dynamics, aerosol dynamics were superimposed onto CFD-simulated gas reactant species concentrations. The current work explores the influence of complex unsteady flow features on the overall flow physics and chemistry for a low Reynolds number, opposed flow, impinging jet gas reactor where there is a low Reynolds number cross flow. The objective of this study was to assess the impact of model formulation on scalar mixing and transport. Here, transient flow simulations were performed using Scale Resolving Simulations. Large-Eddy Simulations with the dynamic Smagorinsky turbulence model were performed along with simulations which directly resolved the flow. Average and root-mean-square (RMS) velocities and species concentrations were computed along with modeled and resolved turbulence kinetic energy (TKE), modeled turbulence dissipation, and modeled turbulent viscosity. Lagrangian flow tracers were also used to quantify species concentrations along path lines emanating from the jet tips. Transient simulation data were compared to results from RANS simulations using the k-ω shear stress transport (SST) model and Reynolds Stress Model (RSM). Transient simulations showed spatial mixing patterns which were more consistent with experimental data and helped elucidate the process of particle formation observed in experiments.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC05-00OR22725; NA0003525

OSTI ID:: 1969827

Journal Information:: Journal of Fluids Engineering, Vol. 145, Issue 5; ISSN 0098-2202

Publisher:: ASMECopyright Statement

Country of Publication:: United States

Language:: English

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