up HL-31

software/feelpp/WP1/WP1.tex

@@ -611,6 +611,26 @@ \subsubsection{Benchmark \#2: Linear elasticity : NAFEMS LE10}
 
 \paragraph{Input/Output Dataset Description}
 
+\begin{itemize}
+\item \textbf{Input Data:}
+  \begin{itemize}
+  \item Meshes: We have generated three levels of mesh called M2, M3
+    and M4. These meshes are stored in GMSH format. The statistics can be found in
+    \Cref{tab:wp1:feelpp:nafems-le10:discr_stat}. We have also prepared for
+    each mesh level a collection of partitioned mesh.
+    The format used is an in-house mesh format of \Feelpp based on
+    JSON+HDF5 file type.
+    The Gmsh meshes and the partitioned meshes can be found on our Girder
+    database management, in the \Feelpp collections.
+  \item Setup: Use standard setup of \Feelpp toolboxes. It corresponds to a cfg
+    file and JSON file. These config files are present in the Github of feelpp.
+  \item Sif image: feelpp:v0.111.0-preview.10-noble-sif  (stored in the Github registry of \Feelpp)
+  \end{itemize}
+\item \textbf{Output Data:} The output includes the computed values of
+  validation measure in CSV files format, export visualization files (mesh,
+  partitioning, displacement, ...), and the time taken to perform each simulation step.
+\end{itemize}
+
 \begin{table}[!ht]
   \centering
   { \setlength{\parindent}{0pt}
@@ -855,49 +875,12 @@ \subsubsection{Benchmark \#3: Thermo-Electric Coupling}
 
 This benchmark models the temperature field and electric current distribution in an high field resistive magnet of the Laboratoire National des Champs Magnétiques Intenses. The magnet consist in a set of 14 copper alloys cylindrical tubes connected 2 by 2 into series by rings. In each tube, the current path is defined by 2 helical cuts of 0.2 mm width. The rings are machined to let water flow in between each tube
 in a channel of 0.8 mm. The magnet is operated at 12 MW with an imosed total current of 31 kA. The water flow in the magnet is about 140 l/s. The water cooling of the magnet is modelling by using Robin boundary conditions with parameters derived from classical correlation in thermo-hydraulics.
-%% TODO add ref to Cecile or Romain Phd %%
-A more detailled version of the full model is available in Daversion2016. The model is run with \texttt{thermoelectric} \Feelpp toolbox.
-
-\paragraph{Benchmarking Tools Used}
-The benchmark was performed on \textbf{Gaya} supercomputer (see \Cref{sec:arch:gaya}) and \textbf{Discoverer} supercomputer (see
-\Cref{sec:arch:eurohpc-ju}).
-The performance tools integrated into the \Feelpp-toolboxes framework were used to measure
-the execution time.
-Moreover, we need to say that we have used several \Feelpp installations
-\begin{itemize}
-\item \textbf{Gaya} : native application from Ubuntu packages of Jammy OS.
-\item \textbf{Discoverer} : Apptainer with \Feelpp SIF image based on Ubuntu
-  Noble OS.
-\end{itemize}
-Note: the \Feelpp version is identical but the dependencies (like Petsc)
-which are of course more recent with Noble.
-
-The metrics measured are the execution time of the main components of the simulation. We enumerate these parts in the following:
-\begin{itemize}
-\item \textbf{Init}: load mesh from filesystem and initialize solid toolbox (finite element context and algebraic data structure)
-\item \textbf{Assembly}: calculate and assemble the matrix and rhs values obtained using the finite element method
-\item \textbf{Solve}: the linear system by using a preconditioned GMRES. Results
-  are presented in \Cref{sec:WP3:Feelpp:benchmark:hl-31}.
-\item \textbf{PostProcess}: Export on the filesystem a visualization format (EnsighGold) of the
-  solution and other fields of interest such as current density and electric field.
-\end{itemize}
+A more detailled version of the full model is available in \cite{daver2016,Hild2020}. The
+model is run with \texttt{thermoelectric} \Feelpp toolbox.
 
-
-\paragraph{Input/Output Dataset Description}
-
-\begin{itemize}
-    \item \textbf{Input Data:} The input dataset consists in a 3D tetrahedral mesh with about 50 millions of tetras along with the  configuration files necessary to run the simulations.
-    \item \textbf{Output Data:} The output includes the computed temperature, current distribution stored in HDF5 format, as well as some integral quantities such a the total power dissipated by the magnet.
-    \item \textbf{Data Repository:} All input and output datasets are available in a unistra girder repository (collection HiFiMagnet, HL-31).
-\end{itemize}
-
-
-\paragraph{Description}
-
-This benchmark models the temperature field and electric current distribution in an high field resistive magnet of the Laboratoire National des Champs Magnétiques Intenses. The magnet consist in a set of 14 copper alloys cylindrical tubes connected 2 by 2 into series by rings. In each tube, the current path is defined by 2 helical cuts of 0.2 mm width. The rings are machined to let water flow in between each tube
-in a channel of 0.8 mm. The magnet is operated at 12 MW with an imosed total current of 31 kA. The water flow in the magnet is about 140 l/s. The water cooling of the magnet is modelling by using Robin boundary conditions with parameters derived from classical correlation in thermo-hydraulics.
-%% TODO add ref to Cecile or Romain Phd %%
-A more detailled version of the full model is available in Daversion2016. The model is run with \texttt{thermoelectric} \Feelpp toolbox.
+The geometry used in this benchmark performance is illustrated in
+\Cref{fig:wp1:feelpp:hl-31:visualization-geometry}. This is a complex domain
+composed of a large number of components, with some very thin parts.
 
 \paragraph{Benchmarking Tools Used}
 The benchmark was performed on \textbf{Gaya} supercomputer (see \Cref{sec:arch:gaya}) and \textbf{Discoverer} supercomputer (see
@@ -923,16 +906,6 @@ \subsubsection{Benchmark \#3: Thermo-Electric Coupling}
   solution and other fields of interest such as current density and electric field.
 \end{itemize}
 
-
-\paragraph{Input/Output Dataset Description}
-
-\begin{itemize}
-    \item \textbf{Input Data:} The input dataset consists in a 3D tetrahedral mesh with about 50 millions of tetras along with the  configuration files necessary to run the simulations.
-    \item \textbf{Output Data:} The output includes the computed temperature, current distribution stored in HDF5 format, as well as some integral quantities such a the total power dissipated by the magnet.
-    \item \textbf{Data Repository:} All input and output datasets are available in a unistra girder repository (collection HiFiMagnet, HL-31).
-\end{itemize}
-
-
 \begin{figure}[!ht]
   \centering
   \begin{subfigure}[c]{0.49\textwidth}
@@ -949,8 +922,37 @@ \subsubsection{Benchmark \#3: Thermo-Electric Coupling}
 \end{figure}
 
 
+
 \paragraph{Input/Output Dataset Description}
 
+\begin{itemize}
+\item \textbf{Input Data:}
+  \begin{itemize}
+  \item Meshes: We have generated three levels of mesh called M1, M2
+    and M3. These meshes are stored in GMSH format. The statistics can be found in
+    \Cref{tab:wp1:feelpp:thermal_bridges:discr_stat}. We have also prepared for
+    each mesh level a collection of partitioned mesh.
+    The format used is an in-house mesh format of \Feelpp based on
+    JSON+HDF5 file type.
+    The Gmsh meshes and the partitioned meshes can be found on our Girder
+    database management, in the \Feelpp collections.
+  \item Setup: Use standard setup of \Feelpp toolboxes. It corresponds to a cfg
+    file and JSON file. These config files are present in the Github of feelpp.
+  \item[]{\Feelpp distributions}
+    \begin{itemize}
+    \item SIF image (Apptainer): feelpp:v0.111.0-preview.10-noble-sif  (stored in the Github registry of \Feelpp)
+    \item Ubuntu package Jammy (Native) feelpp:v0.111.0-preview.10
+    \end{itemize}
+  \end{itemize}
+\item \textbf{Output Data:} The output includes export visualization files (mesh,
+  partitioning, temperature,  elecric potential, current density, electric
+  field, ...), the time taken to perform each simulation step and
+  some integral quantities such a the total power dissipated by the magnet.
+\item \textbf{Data Repository:} All inputdatasets are available in a unistra girder repository (collection HiFiMagnet, HL-31).
+\end{itemize}
+
+
+
 \begin{table}[h!]
   \centering
   { \setlength{\parindent}{0pt}