#
73rd Annual Meeting of the APS Division of Fluid Dynamics

## Volume 65, Number 13

##
Sunday–Tuesday, November 22–24, 2020;
Virtual, CT (Chicago time)

### Session S07: Turbulence: Jets (5:45pm - 6:30pm CST)

5:45 PM,
Monday, November 23, 2020

### Abstract: S07.00008 : Reynolds number effect on jet control and its scaling

Preview Abstract
Abstract

####
Authors:

Dewei Fan

(Harbin Institute of Technology (Shenzhen), China)

Zhi Wu

(Harbin Institute of Technology (Shenzhen), China)

Arun Kumar Perumal

(Indian Institute of Technology Kanpur, India)

Bernd R. Noack

(Harbin Institute of Technology (Shenzhen), China)

Yu Zhou

(Harbin Institute of Technology (Shenzhen), China)

####
Collaborations:

Harbin Institute of Technology (Shenzhen), China, Indian Institute of Technology Kanpur

This work aims to investigate experimentally the effect of Reynolds number
\textit{Re} on the mixing effectiveness of a turbulent jet manipulated using a single
unsteady radial minijet. A novel artificial intelligence (AI) control system
has been developed to manipulate the turbulent jet. The \textit{Re }examined is
8000-50000 based on the time-averaged jet exit velocity $\overline {U_{j} }
$
\begin{figure}[htbp]
\centerline{\includegraphics[width=0.13in,height=0.19in]{030820201.eps}}
\label{fig1}
\end{figure}
and the nozzle exit diameter $D$. The control parameters include the mass flow
rate ratio $C_{m}$ of the minijet to main jet, the frequency ratio
$f_{e}$/$f_{\mathrm{0}}$ of the minijet excitation frequency $f_{e}$ to the
preferred-mode frequency $f_{\mathrm{0\thinspace }}$of main jet, the duty
cycle $\alpha ,$ and the diameter ratio $d$/$D$ of the minijet to the main jet. Jet
mixing is quantified using $K_{e}$/$K_{\mathrm{0}}$, where $K $is the decay rate
of the jet centreline mean velocity, and subscripts $e$ and 0 denote the
manipulated and unforced jets, respectively. Empirical scaling analysis of
the AI-obtained experimental data reveals that the relationship $K_{e} = g_{\mathrm{1}}$
($C_{m}$, $f_{e}$/$f_{\mathrm{0}}$, $\alpha $, $d$/\textit{D, Re, K}$_{\mathrm{0}})$ may be reduced
to $K_{e}$/$K_{\mathrm{0}} \quad = \quad g_{\mathrm{2}}$
\begin{figure}[htbp]
\centerline{\includegraphics[width=0.19in,height=0.17in]{030820202.eps}}
\label{fig2}
\end{figure}
$(\zeta ),$ where $\zeta \quad = \quad \frac{\sqrt {MR} }{\alpha }\left(
{\frac{d}{D}} \right)^{n}\frac{1}{Re}\left( {\frac{f_{e} }{f_{0} }}
\right)^{m}$ ($n$ and $m$ are power indices)
\begin{figure}[htbp]
\centerline{\includegraphics[width=1.04in,height=0.28in]{030820203.eps}}
\label{fig3}
\end{figure}
,$\sqrt {MR} \equiv C_{m} \frac{D}{d}$
\begin{figure}[htbp]
\centerline{\includegraphics[width=0.71in,height=0.23in]{030820204.eps}}
\label{fig4}
\end{figure}
and $g_{\mathrm{2}}$ is approximately a linear function. The scaling law is
discussed, along with the physical meanings of the dimensionless parameters
$K_{e}$/$K_{0}$, $\zeta $, $\frac{\sqrt {MR} }{\alpha }\left( {\frac{d}{D}}
\right)^{n}\frac{1}{Re}$
\begin{figure}[htbp]
\centerline{\includegraphics[width=0.69in,height=0.27in]{030820205.eps}}
\label{fig5}
\end{figure}
and $\left( {\frac{f_{e} }{f_{0} }} \right)^{m}$
\begin{figure}[htbp]
\centerline{\includegraphics[width=0.33in,height=0.28in]{030820206.eps}}
\label{fig6}
\end{figure}
.