Merge pull request #14292 from rmcdermo/master

FDS Verification Guide: update impinging jet section

Author: rmcdermo

Manuals/FDS_Verification_Guide/FDS_Verification_Guide.tex

@@ -2166,9 +2166,9 @@ \subsection{Sphere (\texorpdfstring{\ct{free_conv_sphere}}{free\_conv\_sphere})}
 \section{Impinging Jet (\texorpdfstring{\ct{impinging_jet}}{impinging\_jet})}
 \label{sec:impinging_jet}
 
-Impinging jet flow poses a challenge for convective heat transfer models because the stagnation velocity goes to zero numerically near the mean stagnation point and hence the computed Reynolds number is fictitiously low leading to an under-prediction of the local heat transfer coefficient.  To handle this problem, the user may specify a special impinging jet heat transfer model, as discussed in the FDS User Guide \cite{FDS_Users_Guide}, which basically uses the forced convection correlation but with a velocity scale obtained from the stagnation pressure, following Huang \cite{Huang:1963,Livingood:1973}.  In this section, we present results from a series of cases designed to confirm the general trend that the highest heat transfer coefficient is found at the stagnation point.  There is no analytical solution to this case.  We take our target correlation to be that of Martin \cite{Martin:1977,Incropera:1}.  The default coefficients of the impinging jet model have been tuned to match the Martin correlation for the specific case discussed below at coarse grid resolution.
+Impinging jet flow poses a challenge for convective heat transfer models because the stagnation velocity goes to zero numerically near the mean stagnation point and hence the computed Reynolds number is fictitiously low leading to an under-prediction of the local heat transfer coefficient.  To handle this problem, the user may specify a special impinging jet heat transfer model, as discussed in the FDS User Guide \cite{FDS_Users_Guide}.  In this section, we present results from a series of cases designed to confirm the general trend that the highest heat transfer coefficient is found at the stagnation point.  There is no analytical solution to this case.  We take our target correlation to be that of Martin \cite{Martin:1977,Incropera:1}.  The model parameters have been tuned to match the Martin correlation for the specific case discussed below.
 
-The set up for the problem is a simple cubic domain 1 m on a side.  The lateral boundaries are open.  The top boundary is held at a fixed 20 C.  A hot jet of air is injected from a 0.2 m by 0.2 m square vent at 100 C.  Two Reynolds numbers are considered by changing the inlet flow velocity [10, 40] m/s.  Three grid resolutions for each Reynolds number are tested, $D/\delta x$ = [7, 14, 28], representing \emph{coarse}, \emph{medium}, and \emph{fine} resolutions.  The cases are fun for roughly flow through times with statistics collected over the last half of the simulation.
+The set up for the problem is a simple cubic domain 1 m on a side.  The lateral boundaries are open.  The top boundary is held at a fixed 20 C.  A hot jet of air is injected from a 0.2 m by 0.2 m square vent at 100 C.  Two Reynolds numbers are considered by changing the inlet flow velocity [10, 40] m/s.  Three grid resolutions for each Reynolds number are tested, $D/\delta x$ = [7, 14, 28], representing \emph{coarse}, \emph{medium}, and \emph{fine} resolutions.  The cases are fun for roughly 100 flow through times with statistics collected over the last half of the simulation.
 
 Figure \ref{fig_impinging_jet_corr} shows FDS results for three grid resolutions compared to the correlation in Martin \cite{Martin:1977,Incropera:1}.  The plots below in Fig.~\ref{fig_impinging_jet_prof} show the profile of Nu along the ceiling.