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CylinderKnMa/Kn0p20/simulation0368_Kn0p20Ma3p7/surf/Surf_300000.vtu

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+<?xml version="1.0"?>
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AQAAAACAAABABgAA6QUAAA==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AQAAAACAAABABgAA8QUAAA==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AQAAAACAAABABgAAEgYAAA==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AQAAAACAAABABgAAMQYAAA==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AQAAAACAAABABgAAMwYAAA==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eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro3/MVfvektb3vHu97zvg986CMf+8SnPvO5L3zpK1/7m7/7h3/6l3/7xrf+47++870f/OgnP/vFr37zP0dFvxfjWMc53gkOONFJDjrZKU51mtOd4UxnOds5znWeQ853gQtd5GKXuNRlLneFK13late41nWud4Mb3eRmt7jVYbe53R3udJcj7naPe93nfg940EMe9ohHPeZxT3jSU572jGc95/9sSVRSAQAAAACAAADIAAAADAAAAA==eJxjZh4eAADsVAJZ
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0368_Kn0p20Ma3p7/surf/geom.surf

@@ -0,0 +1,610 @@
+# Surface element file written by SPARTA
+
+400 points
+200 lines
+
+Points
+
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+5    0.499013364214136  -0.0313952597646568
+6     0.49778098230154  -0.0470541566592573
+7     0.49778098230154  -0.0470541566592573
+8    0.496057350657239  -0.0626666167821523
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+11    0.493844170297569  -0.0782172325201156
+12    0.491143625364344  -0.0936906572928624
+13    0.491143625364344  -0.0936906572928624
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AQAAAACAAABsYwAAohEAAA==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AgAAAACAAAAAegAAiRMAAKISAAA=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AQAAAACAAADQBwAAFwAAAA==eJzj5BwFo2AUjIJRMApGwVAHAOOGRlE=
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/Lambda/Lambda_300000.pvtu

@@ -0,0 +1,23 @@
+<?xml version="1.0"?>
+<VTKFile type="PUnstructuredGrid" version="0.1"
+               byte_order="LittleEndian"
+               compressor="vtkZLibDataCompressor">
+<PUnstructuredGrid GhostLevel="0">
+<PCellData>
+<PDataArray type="Float64" Name="id"/>
+<PDataArray type="Float64" Name="xc"/>
+<PDataArray type="Float64" Name="yc"/>
+<PDataArray type="Float64" Name="c_6[1]"/>
+<PDataArray type="Float64" Name="c_6[2]"/>
+</PCellData>
+<PPoints>
+<PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
+</PPoints>
+<Piece Source="Lambda_0_300000.vtu"/>
+<Piece Source="Lambda_1_300000.vtu"/>
+<Piece Source="Lambda_2_300000.vtu"/>
+<Piece Source="Lambda_3_300000.vtu"/>
+<Piece Source="Lambda_4_300000.vtu"/>
+<Piece Source="Lambda_5_300000.vtu"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/Lambda/Lambda_5_300000.vtu

@@ -0,0 +1,27 @@
+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
+  <UnstructuredGrid>
+    <Piece NumberOfPoints="2121"                 NumberOfCells="2000"                >
+      <PointData>
+      </PointData>
+      <CellData>
+        <DataArray type="Float64" Name="id" format="appended" RangeMin="22201"                RangeMax="44000"                offset="0"                   />
+        <DataArray type="Float64" Name="xc" format="appended" RangeMin="5.025"                RangeMax="5.975"                offset="3352"                />
+        <DataArray type="Float64" Name="yc" format="appended" RangeMin="0.025"                RangeMax="4.975"                offset="3584"                />
+        <DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.0059792"            RangeMax="0.021389"             offset="4128"                />
+        <DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.11958"              RangeMax="0.42778"              offset="22516"               />
+      </CellData>
+      <Points>
+        <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="5"                    RangeMax="7.8102496759"         offset="37088"               />
+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="43124"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="56180"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="59768"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
+  <AppendedData encoding="base64">
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AQAAAACAAABsYwAAmxEAAA==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AgAAAACAAAAAegAAiRMAAKISAAA=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AQAAAACAAADQBwAAFwAAAA==eJzj5BwFo2AUjIJRMApGwVAHAOOGRlE=
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/Surf.pvd

@@ -0,0 +1,9 @@
+<?xml version="1.0"?>
+<VTKFile type="Collection" version="0.1"
+               byte_order="LittleEndian"
+               compressor="vtkZLibDataCompressor">
+   <Collection>    
+    <DataSet timestep="300000" group="" part="0"   
+             file="Surf/Surf_300000.vtu"/>
+   </Collection>    
+</VTKFile>    

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/config.txt

@@ -0,0 +1,78 @@
+variable    BZ equal 1.380649E-23
+variable    PI equal 3.1415926536
+variable    molecular_mass equal 6.63E-26
+variable    molecular_diameter equal 4.17E-10
+variable    gamma equal 1.666666667
+variable    R equal ${BZ}/${molecular_mass}
+variable    L equal 1.0
+variable    xmin equal -5.0
+variable    xmax equal  6.0
+variable    ymin equal -5.0
+variable    ymax equal  5.0
+variable    Kn equal 0.2
+variable   Ma equal 3.8
+variable    To equal 273.0
+variable    Tb equal 273.0
+variable    theta equal 0.0
+variable    mfp equal ${Kn}*${L}
+variable    cpmfp equal 4
+variable    nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
+variable    sos equal sqrt(${gamma}*${R}*${To})
+variable    vo equal ${Ma}*${sos}
+variable    vx equal ${vo}*cos(${theta}*2*PI/360)
+variable    vy equal ${vo}*sin(${theta}*2*PI/360)
+variable    ppc equal 30
+variable    xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
+variable    yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
+variable    Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
+variable    nave equal 10000
+variable    noutput equal 300000
+clear
+shell    mkdir output
+shell    mkdir grid
+shell    mkdir surf
+seed    7
+dimension    2
+global    nrho ${nden}
+global    fnum ${Fnum}
+timestep    ${tstep}
+global    gridcut 1.0 particle/reorder 100 comm/sort yes
+region    1  cylinder z 0.0 0.0 3.50 -0.5 0.5
+region    2  cylinder z 0.0 0.0 2.00 -0.5 0.5
+region    3  cylinder z 0.0 0.0 0.80 -0.5 0.5
+boundary    o o p
+create_box    ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
+create_grid    ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
+balance_grid  rcb cell
+species   gas.species Ar
+mixture   air Ar frac 1.0
+mixture   air Ar vstream ${vx} ${vy} 0.0 temp ${To}
+collide   vss air gas.vhs
+collide_modify    vremax 100 yes remain no nearcp yes 10
+read_surf       cylinder.surf
+surf_collide    1 diffuse 273.0 1.0
+surf_modify     all collide 1
+fix    in emit/face air xlo ylo yhi
+balance_grid  rcb cell
+create_particles air n 0
+stats    10000
+stats_style step cpu np nattempt ncoll nscoll npave nscollave
+run    200000
+compute      1 grid all air n nrho massrho u v w
+compute      2 grid all air trot
+compute      3 tvib/grid all air
+compute      4 thermal/grid all air press temp
+fix          1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
+dump         1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
+dump_modify  1 format float %12.5g
+compute      5 surf all air n press px py shx shy fx fy etot erot evib
+fix          2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
+dump         2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
+dump_modify  2 format float %12.5g
+compute      6  lambda/grid f_1[2] f_1[8] Ar kx
+dump         3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
+dump_modify  3 format float %12.5g
+run    100000
+write_grid    grid/final-grid.dat
+write_surf    surf/geom.surf

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/cylinder.surf

@@ -0,0 +1,410 @@
+ surf file from Pointwise
+ 
+         200 points
+         200 lines
+ 
+ Points
+ 
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CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/gas.species

@@ -0,0 +1,14 @@
+# Species data
+
+# species name
+# molecular weight (atomic mass units, e.g. 16 for oxygen)
+# molecular mass (kg)
+# rotational degrees of freedom (integer, unitless)
+# inverse rotational relaxtion number (unitless)
+# vibrational degrees of freedom (integer, unitless)
+# inverse vibrational relaxation number (unitless)
+# vibrational temperature (K)
+# species weight (unitless)
+# multiple of electon charge (1 for a proton)
+
+Ar    39.95    6.63E-26    0    0.0    0    0.0    0.0    1.0    0.0

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/gas.vhs

@@ -0,0 +1,9 @@
+# VHS collision model parameters for each species
+
+# species name
+# diameter (m)
+# omega (unitless)
+# tref (referenced temperature)
+# alpha (unitless)
+
+Ar    4.17e-10    0.81    273    1.0

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/grid/Grid_300000.pvtu

@@ -0,0 +1,31 @@
+<?xml version="1.0"?>
+<VTKFile type="PUnstructuredGrid" version="0.1"
+               byte_order="LittleEndian"
+               compressor="vtkZLibDataCompressor">
+<PUnstructuredGrid GhostLevel="0">
+<PCellData>
+<PDataArray type="Float64" Name="id"/>
+<PDataArray type="Float64" Name="xc"/>
+<PDataArray type="Float64" Name="yc"/>
+<PDataArray type="Float64" Name="f_1[1]"/>
+<PDataArray type="Float64" Name="f_1[2]"/>
+<PDataArray type="Float64" Name="f_1[3]"/>
+<PDataArray type="Float64" Name="f_1[4]"/>
+<PDataArray type="Float64" Name="f_1[5]"/>
+<PDataArray type="Float64" Name="f_1[6]"/>
+<PDataArray type="Float64" Name="f_1[7]"/>
+<PDataArray type="Float64" Name="f_1[8]"/>
+<PDataArray type="Float64" Name="f_1[9]"/>
+<PDataArray type="Float64" Name="f_1[10]"/>
+</PCellData>
+<PPoints>
+<PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
+</PPoints>
+<Piece Source="Grid_0_300000.vtu"/>
+<Piece Source="Grid_1_300000.vtu"/>
+<Piece Source="Grid_2_300000.vtu"/>
+<Piece Source="Grid_3_300000.vtu"/>
+<Piece Source="Grid_4_300000.vtu"/>
+<Piece Source="Grid_5_300000.vtu"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/log.sparta

@@ -0,0 +1,318 @@
+SPARTA (4 Sep 2024)
+Running on 128 MPI task(s)
+variable    BZ equal 1.380649E-23
+variable    PI equal 3.1415926536
+variable    molecular_mass equal 6.63E-26
+variable    molecular_diameter equal 4.17E-10
+variable    gamma equal 1.666666667
+variable    R equal ${BZ}/${molecular_mass}
+variable    R equal 1.380649e-23/${molecular_mass}
+variable    R equal 1.380649e-23/6.63e-26
+variable    L equal 1.0
+variable    xmin equal -5.0
+variable    xmax equal  6.0
+variable    ymin equal -5.0
+variable    ymax equal  5.0
+variable    Kn equal 0.2
+variable   Ma equal 3.8
+variable    To equal 273.0
+variable    Tb equal 273.0
+variable    theta equal 0.0
+variable    mfp equal ${Kn}*${L}
+variable    mfp equal 0.2*${L}
+variable    mfp equal 0.2*1
+variable    cpmfp equal 4
+variable    nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(${mfp}/${cpmfp}*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.2/${cpmfp}*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.2/4*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.2/4*0.2)
+variable    sos equal sqrt(${gamma}*${R}*${To})
+variable    sos equal sqrt(1.666666667*${R}*${To})
+variable    sos equal sqrt(1.666666667*208.242684766214*${To})
+variable    sos equal sqrt(1.666666667*208.242684766214*273)
+variable    vo equal ${Ma}*${sos}
+variable    vo equal 3.8*${sos}
+variable    vo equal 3.8*307.815564238681
+variable    vx equal ${vo}*cos(${theta}*2*PI/360)
+variable    vx equal 1169.69914410699*cos(${theta}*2*PI/360)
+variable    vx equal 1169.69914410699*cos(0*2*PI/360)
+variable    vy equal ${vo}*sin(${theta}*2*PI/360)
+variable    vy equal 1169.69914410699*sin(${theta}*2*PI/360)
+variable    vy equal 1169.69914410699*sin(0*2*PI/360)
+variable    ppc equal 30
+variable    xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
+variable    xncells equal (6-${xmin})/${mfp}*${cpmfp}
+variable    xncells equal (6--5)/${mfp}*${cpmfp}
+variable    xncells equal (6--5)/0.2*${cpmfp}
+variable    xncells equal (6--5)/0.2*4
+variable    yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
+variable    yncells equal (5-${ymin})/${mfp}*${cpmfp}
+variable    yncells equal (5--5)/${mfp}*${cpmfp}
+variable    yncells equal (5--5)/0.2*${cpmfp}
+variable    yncells equal (5--5)/0.2*4
+variable    Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(6--5)*(5--5)/30/${xncells}/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(6--5)*(5--5)/30/220/${yncells}
+variable    Fnum equal 1.29438365301166e+20*(6--5)*(5--5)/30/220/200
+variable    tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
+variable    tstep equal (--5+${xmax})/${vx}/${xncells}/10/4
+variable    tstep equal (--5+6)/${vx}/${xncells}/10/4
+variable    tstep equal (--5+6)/1169.69914410699/${xncells}/10/4
+variable    tstep equal (--5+6)/1169.69914410699/220/10/4
+variable    nave equal 10000
+variable    noutput equal 300000
+clear
+Running on 128 MPI task(s)
+shell    mkdir output
+shell    mkdir grid
+shell    mkdir surf
+seed    7
+dimension    2
+global    nrho ${nden}
+global    nrho 1.29438365301166e+20
+global    fnum ${Fnum}
+global    fnum 1.07865304417638e+16
+timestep    ${tstep}
+timestep    1.06865086317073e-06
+global    gridcut 1.0 particle/reorder 100 comm/sort yes
+region    1  cylinder z 0.0 0.0 3.50 -0.5 0.5
+region    2  cylinder z 0.0 0.0 2.00 -0.5 0.5
+region    3  cylinder z 0.0 0.0 0.80 -0.5 0.5
+boundary    o o p
+create_box    ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
+create_box    -5 ${xmax} ${ymin} ${ymax} -0.5 0.5
+create_box    -5 6 ${ymin} ${ymax} -0.5 0.5
+create_box    -5 6 -5 ${ymax} -0.5 0.5
+create_box    -5 6 -5 5 -0.5 0.5
+Created orthogonal box = (-5 -5 -0.5) to (6 5 0.5)
+create_grid    ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
+create_grid    220 ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
+create_grid    220 200 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
+Created 191516 child grid cells
+  CPU time = 0.197726 secs
+  create/ghost percent = 0.751132 99.2489
+balance_grid  rcb cell
+Balance grid migrated 191124 cells
+  CPU time = 0.157903 secs
+  reassign/sort/migrate/ghost percent = 33.913 0.0307911 10.0207 56.0355
+species   gas.species Ar
+mixture   air Ar frac 1.0
+mixture   air Ar vstream ${vx} ${vy} 0.0 temp ${To}
+mixture   air Ar vstream 1169.69914410699 ${vy} 0.0 temp ${To}
+mixture   air Ar vstream 1169.69914410699 0 0.0 temp ${To}
+mixture   air Ar vstream 1169.69914410699 0 0.0 temp 273
+collide   vss air gas.vhs
+collide_modify    vremax 100 yes remain no nearcp yes 10
+read_surf       cylinder.surf
+  200 lines
+  -0.5 0.5 xlo xhi
+  -0.5 0.5 ylo yhi
+  0 0 zlo zhi
+  0.0157073 min line length
+  644 0 = cells overlapping surfs, overlap cells with unmarked corner pts
+  171120 19752 644 = cells outside/inside/overlapping surfs
+  644 = surf cells with 1,2,etc splits
+  109.215 109.215 = cell-wise and global flow volume
+  CPU time = 0.166812 secs
+  read/check/sort/surf2grid/ghost/inout/particle percent = 14.0603 12.6344 1.5501 18.8182 52.9369 3.99273 0.114529
+  surf2grid time = 0.031391 secs
+  map/comm1/comm2/comm3/comm4/split percent = 17.3577 18.6412 18.4252 3.68668 8.68144 4.98892
+surf_collide    1 diffuse 273.0 1.0
+surf_modify     all collide 1
+fix    in emit/face air xlo ylo yhi
+balance_grid  rcb cell
+Balance grid migrated 2352 cells
+  CPU time = 0.0977742 secs
+  reassign/sort/migrate/ghost percent = 3.07838 0.05391 8.90709 87.9606
+create_particles air n 0
+Created 1310576 particles
+  CPU time = 0.0232877 secs
+stats    10000
+stats_style step cpu np nattempt ncoll nscoll npave nscollave
+run    200000
+Memory usage per proc in Mbytes:
+  particles (ave,min,max) = 2.16211 0 5.0625
+  grid      (ave,min,max) = 7.30725 1.51379 13.7013
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 9.48996 4.15939 16.1594
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave 
+       0            0  1310576        0        0        0            0            0 
+   10000     37.70329  1404140    45490    38691       22    1336144.5      22.3498 
+   20000    95.680308  1443585    47493    40419       26    1383838.3       22.556 
+   30000    154.33888  1445801    47756    40935       25    1404448.2    22.637233 
+   40000    212.66122  1446444    47765    40809       20    1415021.4    22.667675 
+   50000    271.35277  1447853    47782    40820       13    1421554.7     22.70268 
+   60000    329.83701  1447655    47894    40949       23    1425989.7    22.743883 
+   70000    388.49419  1447517    47793    40905       21    1429198.4    22.747757 
+   80000     447.0694  1447887    47873    41030       18    1431437.9    22.763225 
+   90000    505.54887  1447194    47816    40830       17    1433250.4    22.778522 
+  100000    564.18131  1447883    47872    40951       29      1434638     22.77902 
+  110000    622.87118  1448090    47678    40869       27    1435823.7    22.778491 
+  120000     681.5432  1447591    47840    40949       29    1436812.4    22.779233 
+  130000    740.13531  1446312    48125    41072       19      1437558    22.788692 
+  140000    798.63471  1447713    47985    41009       25    1438260.6    22.795264 
+  150000     856.4965  1448275    47957    40977       12    1438922.7    22.797033 
+  160000    915.07689  1448944    47921    41123       25      1439496    22.804431 
+  170000    974.67697  1447283    47666    40879       25    1440019.3    22.810494 
+  180000    1033.7864  1448126    47900    40993       15    1440459.7    22.814589 
+  190000    1092.5008  1447835    47619    40691       22    1440860.2    22.818626 
+  200000    1150.7441  1447160    47764    40869       32    1441212.2    22.820175 
+Loop time of 1150.75 on 128 procs for 200000 steps with 1447160 particles
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.025986   | 38.857     | 241.6      | 819.6 |  3.38
+Coll    | 0.94116    | 60.652     | 605.33     |1311.6 |  5.27
+Sort    | 0.33291    | 15.062     | 138.49     | 702.2 |  1.31
+Comm    | 103.95     | 135.09     | 148.68     |  82.3 | 11.74
+Modify  | 0.023885   | 0.31403    | 5.2141     | 145.2 |  0.03
+Output  | 0.035957   | 0.092597   | 0.099643   |   3.6 |  0.01
+Other   |            | 900.7      |            |       | 78.27
+
+Particle moves    = 288242448816 (288B)
+Cells touched     = 301602299781 (302B)
+Particle comms    = 351186057 (351M)
+Boundary collides = 0 (0K)
+Boundary exits    = 35231844 (35.2M)
+SurfColl checks   = 198932267 (199M)
+SurfColl occurs   = 4564035 (4.56M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 10910902544 (10.9B)
+Collide occurs    = 8331821709 (8.33B)
+Reactions         = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+
+Particle-moves/CPUsec/proc: 1.9569e+06
+Particle-moves/step: 1.44121e+06
+Cell-touches/particle/step: 1.04635
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00121837
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.00012223
+Surface-checks/particle/step: 0.000690156
+Surface-collisions/particle/step: 1.5834e-05
+Surf-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0378532
+Collisions/particle/step: 0.0289056
+Reactions/particle/step: 0
+
+Particles: 11305.9 ave 73143 max 0 min
+Histogram: 84 14 4 8 8 4 2 0 0 4
+Cells:      1496.22 ave 1497 max 1496 min
+Histogram: 100 0 0 0 0 0 0 0 0 28
+GhostCell: 38710.9 ave 70939 max 2108 min
+Histogram: 20 10 12 10 17 3 6 4 16 30
+EmptyCell: 436.805 ave 731 max 67 min
+Histogram: 7 5 11 19 11 16 15 16 14 14
+Surfs:    200 ave 200 max 200 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+GhostSurf: 0 ave 0 max 0 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+compute      1 grid all air n nrho massrho u v w
+compute      2 grid all air trot
+compute      3 tvib/grid all air
+compute      4 thermal/grid all air press temp
+fix          1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
+fix          1 ave/grid all 1 10000 ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
+fix          1 ave/grid all 1 10000 10000 c_1[*] c_4[*] c_2[*] c_3[*] ave running
+dump         1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
+dump         1 grid all 300000 output/grid.*.dat id xc yc f_1[*]
+dump_modify  1 format float %12.5g
+compute      5 surf all air n press px py shx shy fx fy etot erot evib
+fix          2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
+fix          2 ave/surf all 1 10000 ${nave} c_5[*] ave running
+fix          2 ave/surf all 1 10000 10000 c_5[*] ave running
+dump         2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
+dump         2 surf all 300000 output/surf.*.dat id v1x v1y v2x v2y f_2[*]
+dump_modify  2 format float %12.5g
+compute      6  lambda/grid f_1[2] f_1[8] Ar kx
+dump         3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
+dump         3 grid all 300000 output/lambdakn.*.dat id xc yc c_6[*]
+dump_modify  3 format float %12.5g
+run    100000
+Memory usage per proc in Mbytes:
+  particles (ave,min,max) = 2.37305 0 8.4375
+  grid      (ave,min,max) = 7.30725 1.51379 13.7013
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 10.2034 4.66193 17.5994
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave 
+  200000            0  1447160    47764    40869        0            0            0 
+  210000    92.999999  1446729    47683    40759       19    1446362.3      22.8574 
+  220000    185.41224  1447008    47745    40903       14      1446521      22.8495 
+  230000    277.45155  1446790    47608    40897       12    1446739.4    22.867367 
+  240000    370.31902  1446719    47813    40910       27    1446811.3    22.873225 
+  250000    462.11951  1447614    47786    40787       26    1447056.2     22.88016 
+  260000    554.92231  1447544    47852    40922       29    1447251.5    22.879333 
+  270000    647.18709  1447294    47797    40972       20    1447403.6    22.884043 
+  280000    740.70837  1447044    47728    40764       10      1447271    22.883225 
+  290000    832.18407  1448156    47734    40695       25    1447263.4    22.883022 
+  300000    925.21807  1447866    47697    40791       19    1447319.4     22.88388 
+Loop time of 925.218 on 128 procs for 100000 steps with 1447866 particles
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.015418   | 19.72      | 116        | 564.5 |  2.13
+Coll    | 0.47125    | 32.254     | 319.76     | 975.3 |  3.49
+Sort    | 0.21328    | 7.9486     | 75.411     | 496.1 |  0.86
+Comm    | 58.426     | 74.065     | 81.532     |  59.8 |  8.01
+Modify  | 6.7181     | 53.331     | 314.05     | 894.2 |  5.76
+Output  | 0.062994   | 0.064638   | 0.070643   |   0.6 |  0.01
+Other   |            | 737.8      |            |       | 79.75
+
+Particle moves    = 144731937477 (145B)
+Cells touched     = 151430714397 (151B)
+Particle comms    = 176029618 (176M)
+Boundary collides = 0 (0K)
+Boundary exits    = 17679724 (17.7M)
+SurfColl checks   = 99821614 (99.8M)
+SurfColl occurs   = 2288388 (2.29M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 5518942902 (5.52B)
+Collide occurs    = 4213258702 (4.21B)
+Reactions         = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+
+Particle-moves/CPUsec/proc: 1.22211e+06
+Particle-moves/step: 1.44732e+06
+Cell-touches/particle/step: 1.04628
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00121625
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.000122155
+Surface-checks/particle/step: 0.0006897
+Surface-collisions/particle/step: 1.58112e-05
+Surf-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0381322
+Collisions/particle/step: 0.0291108
+Reactions/particle/step: 0
+
+Particles: 11311.5 ave 72684 max 0 min
+Histogram: 84 14 4 8 8 4 2 0 0 4
+Cells:      1496.22 ave 1497 max 1496 min
+Histogram: 100 0 0 0 0 0 0 0 0 28
+GhostCell: 38710.9 ave 70939 max 2108 min
+Histogram: 20 10 12 10 17 3 6 4 16 30
+EmptyCell: 436.805 ave 731 max 67 min
+Histogram: 7 5 11 19 11 16 15 16 14 14
+Surfs:    200 ave 200 max 200 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+GhostSurf: 0 ave 0 max 0 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+write_grid    grid/final-grid.dat
+  grid cells = 191516
+  CPU time = 0.0269123 secs
+write_surf    surf/geom.surf
+  surf elements = 200
+  CPU time = 0.00328668 secs

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/mir.txt

@@ -0,0 +1,3 @@
+dimension     2
+create_box    -5.0 6.0 -5.0 5.0 -0.5 0.5
+read_grid     grid/final-grid.dat

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/output/surf.300000.dat

@@ -0,0 +1,209 @@
+ITEM: TIMESTEP
+300000
+ITEM: NUMBER OF SURFS
+200
+ITEM: BOX BOUNDS oo oo pp
+-5 6
+-5 5
+-0.5 0.5
+ITEM: SURFS id v1x v1y v2x v2y f_2[1] f_2[2] f_2[3] f_2[4] f_2[5] f_2[6] f_2[7] f_2[8] f_2[9] f_2[10] f_2[11] 
+1          0.5            0      0.49975    -0.015705      0.00835      0.23898     -0.23895    0.0037537    0.0001038    0.0066074   -0.0037516   0.00016274       24.112            0            0 
+129     -0.31871      0.38526     -0.30645      0.39508      0.18435       5.3445       3.3416       -4.171      0.59661      0.47798     0.061859    -0.058008       601.77            0            0 
+2      0.49975    -0.015705      0.49901    -0.031395      0.00889      0.24891     -0.24863     0.011725   -3.775e-05  -0.00080048   -0.0039059    0.0001716       22.852            0            0 
+130     -0.30645      0.39508     -0.29389      0.40451      0.17214       4.9771       2.9884      -3.9801      0.57401      0.43098     0.055955    -0.055747        564.1            0            0 
+3      0.49901    -0.031395      0.49778    -0.047054      0.00825      0.23035     -0.22964     0.018073  -9.6558e-05   -0.0012269   -0.0036085   0.00026461       21.335            0            0 
+131     -0.29389      0.40451     -0.28104      0.41354      0.16747       4.8635       2.7966      -3.9791      0.61222      0.43027     0.053543    -0.055743       573.25            0            0 
+4      0.49778    -0.047054      0.49606    -0.062667      0.00859      0.24544     -0.24396     0.026933   0.00042951    0.0038905   -0.0038252   0.00048416       21.759            0            0 
+132     -0.28104      0.41354     -0.26791      0.42216      0.15797       4.5877       2.5187      -3.8344       0.6288      0.41305     0.049439    -0.053741       545.37            0            0 
+5      0.49606    -0.062667      0.49384    -0.078217      0.00856      0.24123     -0.23883      0.03399  -8.7813e-05  -0.00061701   -0.0037527    0.0005242       20.853            0            0 
+133     -0.26791      0.42216     -0.25452      0.43037      0.15087       4.3687       2.2827      -3.7249      0.63118      0.38679     0.045768    -0.052434       509.45            0            0 
+6      0.49384    -0.078217      0.49114    -0.093691      0.00831      0.23587     -0.23236     0.040553   0.00062011    0.0035531     -0.00364   0.00069279       23.994            0            0 
+134     -0.25452      0.43037     -0.24088      0.43815      0.14197       4.1107       2.0367      -3.5707      0.63362      0.36141     0.041943    -0.050409        484.5            0            0 
+7      0.49114    -0.093691      0.48796     -0.10907      0.00749      0.21317     -0.20874     0.043229   -0.0028378    -0.013703   -0.0033234   0.00046377       20.724            0            0 
+135     -0.24088      0.43815       -0.227       0.4455       0.1325       3.8308       1.7926      -3.3856      0.59922      0.31727     0.037569    -0.048195       459.97            0            0 
+8      0.48796     -0.10907      0.48429     -0.12434      0.00723      0.20228     -0.19669     0.047221   -0.0017911   -0.0074604   -0.0031176   0.00062453       16.638            0            0 
+136       -0.227       0.4455     -0.21289      0.45241      0.12757       3.6807       1.6193      -3.3054      0.65268      0.31974     0.035687    -0.046897        451.6            0            0 
+9      0.48429     -0.12434      0.48015      -0.1395       0.0071      0.20349     -0.19628     0.053695    0.0005006    0.0018299   -0.0030751   0.00087215       19.054            0            0 
+137     -0.21289      0.45241     -0.19857      0.45888      0.11742       3.4287        1.411      -3.1249      0.61522      0.27778     0.031826    -0.044721       407.63            0            0 
+10      0.48015      -0.1395      0.47553     -0.15451      0.00632      0.17562     -0.16786     0.051639  -0.00046359   -0.0015069   -0.0026438   0.00078744       17.829            0            0 
+138     -0.19857      0.45888     -0.18406      0.46489      0.11327       3.2274       1.2351      -2.9817      0.62647      0.25949      0.02924    -0.042758       392.09            0            0 
+11      0.47553     -0.15451      0.47044     -0.16937      0.00666      0.18199     -0.17218     0.058949    0.0031464      0.00919    -0.002655    0.0010703       17.686            0            0 
+139     -0.18406      0.46489     -0.16937      0.47044      0.10575       3.0379       1.0738      -2.8418      0.60964      0.23036     0.026443    -0.041018       370.32            0            0 
+12      0.47044     -0.16937      0.46489     -0.18406      0.00666      0.18103     -0.16934     0.063988  -0.00020136  -0.00053289    -0.002663   0.00099672       18.536            0            0 
+140     -0.16937      0.47044     -0.15451      0.47553      0.09893       2.8441      0.92125      -2.6907      0.58897      0.20165     0.023721    -0.039097        347.6            0            0 
+13      0.46489     -0.18406      0.45888     -0.19857      0.00543      0.14691     -0.13573     0.056221    0.0020998    0.0050694    -0.002099   0.00096271       13.692            0            0 
+141     -0.15451      0.47553      -0.1395      0.48015      0.09097       2.6028      0.76534      -2.4878      0.56419      0.17357     0.020883     -0.03635       316.64            0            0 
+14      0.45888     -0.19857      0.45241     -0.21289      0.00571      0.15526     -0.14151     0.063893    0.0028098    0.0062229   -0.0021786    0.0011013       17.171            0            0 
+142      -0.1395      0.48015     -0.12434      0.48429      0.08738       2.5101      0.66234      -2.4211      0.58125      0.15901     0.019534    -0.035531       316.83            0            0 
+15      0.45241     -0.21289       0.4455       -0.227       0.0055      0.14104     -0.12666     0.062048    0.0040285    0.0082233   -0.0019262    0.0011038       11.912            0            0 
+143     -0.12434      0.48429     -0.10907      0.48796      0.08227       2.3516      0.54897      -2.2866      0.57321      0.13762     0.017626    -0.033755        292.2            0            0 
+16       0.4455       -0.227      0.43815     -0.24088      0.00493      0.12985     -0.11476     0.060762    0.0079811     0.015074   -0.0016772    0.0011912       13.716            0            0 
+144     -0.10907      0.48796    -0.093691      0.49114      0.07628       2.1669      0.43941      -2.1218      0.54956      0.11381     0.015534    -0.031541       266.75            0            0 
+17      0.43815     -0.24088      0.43037     -0.25452      0.00467      0.12414     -0.10783     0.061506    0.0082388     0.014444   -0.0015643     0.001193       13.053            0            0 
+145    -0.093691      0.49114    -0.078217      0.49384      0.06957       1.9972      0.34338      -1.9675       0.5143     0.089759     0.013472    -0.029494       249.13            0            0 
+18      0.43037     -0.25452      0.42216     -0.26791      0.00444      0.11931     -0.10173     0.062341     0.010491      0.01712   -0.0014331    0.0012481       13.775            0            0 
+146    -0.078217      0.49384    -0.062667      0.49606      0.06583       1.8817      0.26513      -1.8629      0.53027     0.075469     0.012494    -0.028075       252.19            0            0 
+19      0.42216     -0.26791      0.41354     -0.28104      0.00418      0.11101    -0.092782     0.060946     0.015352     0.023372   -0.0012162    0.0013244        13.24            0            0 
+147    -0.062667      0.49606    -0.047054      0.49778      0.06044       1.7251      0.18931      -1.7147      0.50182     0.055401     0.010856    -0.026063       226.73            0            0 
+20      0.41354     -0.28104      0.40451     -0.29389      0.00428      0.11071    -0.090578      0.06366     0.018642     0.026526   -0.0011299    0.0014166       11.953            0            0 
+148    -0.047054      0.49778    -0.031395      0.49901      0.05625       1.6067      0.12606      -1.6017      0.45205     0.035577    0.0090805      -0.0246       209.53            0            0 
+21      0.40451     -0.29389      0.39508     -0.30645      0.00429      0.10814    -0.086474     0.064927     0.022982     0.030609  -0.00099729    0.0015006       11.447            0            0 
+149    -0.031395      0.49901    -0.015705      0.49975      0.05181       1.4866     0.070028      -1.4849      0.45729     0.021565    0.0082828    -0.022986       191.15            0            0 
+22      0.39508     -0.30645      0.38526     -0.31871      0.00456      0.11264    -0.087908     0.070427     0.030112     0.037585  -0.00090782    0.0016966       13.986            0            0 
+150    -0.015705      0.49975            0          0.5      0.04846       1.3706     0.021529      -1.3704      0.42083    0.0066109    0.0069483    -0.021422       177.95            0            0 
+23      0.38526     -0.31871      0.37506     -0.33066      0.00435      0.10778    -0.081953     0.069995     0.028604      0.03349  -0.00083798    0.0016255       15.041            0            0 
+151            0          0.5     0.015705      0.49975      0.04419       1.2504     -0.01964      -1.2502      0.41986   -0.0065957    0.0062864    -0.019741       165.67            0            0 
+24      0.37506     -0.33066      0.36448     -0.34227      0.00502      0.12732    -0.094166     0.085685     0.042644     0.046865  -0.00080928     0.002082       17.629            0            0 
+152     0.015705      0.49975     0.031395      0.49901      0.04093       1.1499     -0.05417      -1.1487      0.38065    -0.017951    0.0051281    -0.018324       158.42            0            0 
+25      0.36448     -0.34227      0.35355     -0.35355      0.00473      0.11597    -0.083284     0.080708     0.044574     0.045997  -0.00060803    0.0019902       18.022            0            0 
+153     0.031395      0.49901     0.047054      0.49778      0.03736       1.0496    -0.082352      -1.0464      0.36817    -0.028976    0.0044895    -0.016891       142.96            0            0 
+26      0.35355     -0.35355      0.34227     -0.36448      0.00501      0.12056    -0.083901     0.086579     0.053757     0.052094  -0.00047347    0.0021782       19.864            0            0 
+154     0.047054      0.49778     0.062667      0.49606      0.03368      0.93819     -0.10295     -0.93253      0.34074    -0.037618     0.003735    -0.015238        126.7            0            0 
+27      0.34227     -0.36448      0.33066     -0.37506      0.00548      0.13476    -0.090698     0.099676     0.061532     0.055989  -0.00045813    0.0024451       18.806            0            0 
+155     0.062667      0.49606     0.078217      0.49384      0.03206      0.89121     -0.12557     -0.88232      0.32163    -0.045775    0.0030795    -0.014578       122.06            0            0 
+28      0.33066     -0.37506      0.31871     -0.38526      0.00587      0.14914    -0.096862      0.11341     0.066657      0.05693  -0.00047444    0.0026756       23.378            0            0 
+156     0.078217      0.49384     0.093691      0.49114      0.02968      0.83471     -0.14351     -0.82228      0.32325    -0.056415    0.0028231    -0.013802       118.11            0            0 
+29      0.31871     -0.38526      0.30645     -0.39508      0.00653      0.16786     -0.10495      0.13101     0.076183     0.061034  -0.00045194    0.0030164       27.337            0            0 
+157     0.093691      0.49114      0.10907      0.48796        0.027      0.74637     -0.15135     -0.73086      0.28828    -0.059699    0.0021507    -0.012418       105.77            0            0 
+30      0.30645     -0.39508      0.29389     -0.40451      0.00783      0.19912     -0.11955      0.15923     0.092369     0.069353  -0.00042701    0.0035905       27.474            0            0 
+158      0.10907      0.48796      0.12434      0.48429      0.02467      0.68797      -0.1606     -0.66896        0.285    -0.068423     0.001954    -0.011582        95.67            0            0 
+31      0.29389     -0.40451      0.28104     -0.41354      0.00803      0.20885     -0.12009      0.17087      0.10328     0.072585  -0.00026408     0.003824       33.989            0            0 
+159      0.12434      0.48429       0.1395      0.48015       0.0234      0.64991     -0.17149     -0.62688      0.26117    -0.071449    0.0014086    -0.010969       85.673            0            0 
+32      0.28104     -0.41354      0.26791     -0.42216       0.0083      0.21114     -0.11592      0.17647      0.10345     0.067951  -0.00019592    0.0038392       34.656            0            0 
+160       0.1395      0.48015      0.15451      0.47553      0.01995      0.54436     -0.16006     -0.52029      0.22751     -0.06999    0.0010594   -0.0092717       79.591            0            0 
+33      0.26791     -0.42216      0.25452     -0.43037      0.00934      0.24153      -0.1262      0.20594      0.11852     0.072626  -0.00012066    0.0043755       36.891            0            0 
+161      0.15451      0.47553      0.16937      0.47044      0.01872      0.51368     -0.16639     -0.48599      0.23019    -0.078812    0.0010021   -0.0088715       69.645            0            0 
+34      0.25452     -0.43037      0.24088     -0.43815      0.01146      0.29483     -0.14608       0.2561      0.14672     0.083688   1.0134e-05    0.0053371       48.894            0            0 
+162      0.16937      0.47044      0.18406      0.46489      0.01638      0.44015     -0.15558     -0.41174      0.19387    -0.073258   0.00060144    -0.007618       64.266            0            0 
+35      0.24088     -0.43815        0.227      -0.4455      0.01208      0.31849     -0.14903      0.28147      0.14877      0.07877  -4.0825e-06    0.0056584       46.766            0            0 
+163      0.18406      0.46489      0.19857      0.45888      0.01591      0.42864     -0.16403     -0.39601       0.2038    -0.084415    0.0006246   -0.0075462       64.542            0            0 
+36        0.227      -0.4455      0.21289     -0.45241      0.01295      0.34473     -0.15166      0.30957      0.16487     0.080767   0.00020743    0.0061312       52.217            0            0 
+164      0.19857      0.45888      0.21289      0.45241      0.01383      0.36944     -0.15203     -0.33671      0.16556    -0.074754   0.00021256    -0.006463       53.741            0            0 
+37      0.21289     -0.45241      0.19857     -0.45888      0.01373      0.36292     -0.14935      0.33076      0.16411     0.074099   0.00023192    0.0063593       55.192            0            0 
+165      0.21289      0.45241        0.227       0.4455       0.0126      0.33336     -0.14666     -0.29937      0.15605    -0.076449   0.00014754    -0.005903       51.393            0            0 
+38      0.19857     -0.45888      0.18406     -0.46489       0.0151      0.41007     -0.15693      0.37886      0.18269     0.075672    0.0004046    0.0071395       60.226            0            0 
+166        0.227       0.4455      0.24088      0.43815      0.01129      0.30074     -0.14072     -0.26578      0.14861    -0.078685   0.00012388   -0.0054106       45.441            0            0 
+39      0.18406     -0.46489      0.16937     -0.47044      0.01716      0.46782     -0.16536      0.43762      0.20634     0.077968   0.00064362    0.0080985       69.808            0            0 
+167      0.24088      0.43815      0.25452      0.43037      0.01052      0.27079     -0.13416     -0.23522      0.12907     -0.07362  -8.0033e-05    -0.004851       42.844            0            0 
+40      0.16937     -0.47044      0.15451     -0.47553      0.01863      0.51484     -0.16676      0.48708      0.22379     0.076619   0.00089565    0.0088542       79.563            0            0 
+168      0.25452      0.43037      0.26791      0.42216       0.0091        0.233     -0.12174     -0.19866      0.11928    -0.073097  -3.8576e-05   -0.0042686       38.557            0            0 
+41      0.15451     -0.47553       0.1395     -0.48015      0.02032       0.5592     -0.16443      0.53448      0.22019      0.06774    0.0008759    0.0094593       74.067            0            0 
+169      0.26791      0.42216      0.28104      0.41354      0.00805      0.20919     -0.11485     -0.17484     0.098591    -0.064762  -0.00025534   -0.0037635       34.239            0            0 
+42       0.1395     -0.48015      0.12434     -0.48429       0.0225      0.62127     -0.16394      0.59925      0.26401     0.072226    0.0015719     0.010547       89.231            0            0 
+170      0.28104      0.41354      0.29389      0.40451      0.00738      0.19247     -0.11067     -0.15747     0.089755    -0.063081  -0.00032849   -0.0034642       31.004            0            0 
+43      0.12434     -0.48429      0.10907     -0.48796      0.02532      0.70309     -0.16413      0.68366      0.27958     0.067121    0.0018133     0.011793        96.48            0            0 
+171      0.29389      0.40451      0.30645      0.39508      0.00696      0.17662     -0.10604     -0.14124     0.078058    -0.058608  -0.00043958    -0.003139       24.021            0            0 
+44      0.10907     -0.48796     0.093691     -0.49114      0.02662      0.74202     -0.15047      0.72661      0.27703      0.05737    0.0019879     0.012314       101.89            0            0 
+172      0.30645      0.39508      0.31871      0.38526      0.00659      0.16606     -0.10383      -0.1296     0.076239    -0.061079  -0.00043332    -0.002995       25.887            0            0 
+45     0.093691     -0.49114     0.078217     -0.49384      0.02936      0.82457     -0.14177      0.81229      0.31213     0.054475    0.0026759     0.013615       112.94            0            0 
+173      0.31871      0.38526      0.33066      0.37506      0.00573      0.14769    -0.095915      -0.1123     0.070281    -0.060026  -0.00040263   -0.0027068       23.503            0            0 
+46     0.078217     -0.49384     0.062667     -0.49606      0.03131      0.87231     -0.12291      0.86361      0.33543     0.047739    0.0033382     0.014315        115.9            0            0 
+174      0.33066      0.37506      0.34227      0.36448        0.006      0.15548     -0.10464       -0.115     0.065607    -0.059698  -0.00061315   -0.0027441       22.967            0            0 
+47     0.062667     -0.49606     0.047054     -0.49778      0.03535      0.98533     -0.10812      0.97938      0.36632     0.040442    0.0040556     0.016019       138.28            0            0 
+175      0.34227      0.36448      0.35355      0.35355      0.00529      0.13218    -0.091983    -0.094919     0.052552    -0.050927  -0.00061935   -0.0022908       16.551            0            0 
+48     0.047054     -0.49778     0.031395     -0.49901        0.037       1.0451    -0.082001       1.0419      0.35645     0.028053    0.0043109     0.016806       142.24            0            0 
+176      0.35355      0.35355      0.36448      0.34227      0.00503      0.12866    -0.092396    -0.089538      0.04399    -0.045394  -0.00076033   -0.0021194       17.795            0            0 
+49     0.031395     -0.49901     0.015705     -0.49975      0.04161       1.1675    -0.054996       1.1662      0.39535     0.018644    0.0053461      0.01861       149.07            0            0 
+177      0.36448      0.34227      0.37506      0.33066       0.0047      0.12035    -0.089013    -0.080995     0.039444    -0.043348   -0.0007786   -0.0019531       14.289            0            0 
+50     0.015705     -0.49975            0         -0.5      0.04304       1.2142    -0.019071        1.214      0.39647    0.0062282    0.0059279     0.019167       172.25            0            0 
+178      0.37506      0.33066      0.38526      0.31871      0.00444      0.11617    -0.088337    -0.075447     0.032619    -0.038192  -0.00087518    -0.001785       15.089            0            0 
+51            0         -0.5    -0.015705     -0.49975      0.04845       1.3743     0.021587       1.3742      0.46681   -0.0073332    0.0076714     0.021469       176.88            0            0 
+179      0.38526      0.31871      0.39508      0.30645      0.00398     0.097849    -0.076364    -0.061179     0.021553    -0.026903  -0.00086094   -0.0013835       13.562            0            0 
+52    -0.015705     -0.49975    -0.031395     -0.49901      0.05396       1.5262     0.071896       1.5245       0.4445    -0.020962    0.0081113     0.023617       200.51            0            0 
+180      0.39508      0.30645      0.40451      0.29389      0.00433      0.11062    -0.088464    -0.066421     0.025449    -0.033895   -0.0009898   -0.0015757       15.158            0            0 
+53    -0.031395     -0.49901    -0.047054     -0.49778      0.05639       1.6135      0.12659       1.6085      0.47238    -0.037177    0.0094083     0.024681       211.52            0            0 
+181      0.40451      0.29389      0.41354      0.28104      0.00433       0.1106    -0.090486    -0.063594      0.02148    -0.030563   -0.0010839    -0.001479       14.569            0            0 
+54    -0.047054     -0.49778    -0.062667     -0.49606      0.06086       1.7406        0.191       1.7301      0.47522    -0.052464     0.010465     0.026351       224.37            0            0 
+182      0.41354      0.28104      0.42216      0.26791      0.00418      0.11098    -0.092761    -0.060932     0.013591     -0.02069   -0.0012435   -0.0012821       13.449            0            0 
+55    -0.062667     -0.49606    -0.078217     -0.49384      0.06579       1.8897      0.26626       1.8709      0.51994    -0.073999     0.012349     0.028224       240.54            0            0 
+183      0.42216      0.26791      0.43037      0.25452      0.00478      0.12719     -0.10844    -0.066455     0.015532    -0.025345   -0.0014594   -0.0014419       13.065            0            0 
+56    -0.078217     -0.49384    -0.093691     -0.49114      0.06899       1.9579      0.33663       1.9288      0.52148    -0.091013     0.013479     0.028867       244.61            0            0 
+184      0.43037      0.25452      0.43815      0.24088      0.00495       0.1316     -0.11431    -0.065202    0.0099945    -0.017522   -0.0016385   -0.0012994       11.793            0            0 
+57    -0.093691     -0.49114     -0.10907     -0.48796      0.07567       2.1676      0.43956       2.1225      0.54074     -0.11198     0.015398     0.031581       271.77            0            0 
+185      0.43815      0.24088       0.4455        0.227      0.00527      0.14009     -0.12381    -0.065553    0.0077122    -0.014566   -0.0018236   -0.0012585       16.314            0            0 
+58     -0.10907     -0.48796     -0.12434     -0.48429      0.07967       2.2874      0.53399       2.2242      0.55665     -0.13364     0.017131     0.032837       295.15            0            0 
+186       0.4455        0.227      0.45241      0.21289      0.00486      0.12856     -0.11545    -0.056559    0.0068042    -0.013889   -0.0017066   -0.0011066       14.039            0            0 
+59     -0.12434     -0.48429      -0.1395     -0.48015      0.08677       2.4774      0.65372       2.3896      0.56153     -0.15362     0.019088     0.035121       308.64            0            0 
+187      0.45241      0.21289      0.45888      0.19857       0.0053      0.13971     -0.12733    -0.057493    0.0020995   -0.0046499   -0.0019671   -0.0009761       12.529            0            0 
+60      -0.1395     -0.48015     -0.15451     -0.47553      0.09243       2.6701      0.78512       2.5521      0.60563     -0.18632     0.021845      0.03716       340.34            0            0 
+188      0.45888      0.19857      0.46489      0.18406      0.00552      0.15176     -0.14021    -0.058077    0.0014298   -0.0034518   -0.0021799  -0.00096646       13.331            0            0 
+61     -0.15451     -0.47553     -0.16937     -0.47044      0.09933       2.8562      0.92518       2.7022      0.58227     -0.19936     0.023678     0.039314       345.45            0            0 
+189      0.46489      0.18406      0.47044      0.16937      0.00587      0.15876     -0.14851    -0.056117    0.0013353   -0.0035338   -0.0023117  -0.00093695        13.54            0            0 
+62     -0.16937     -0.47044     -0.18406     -0.46489      0.10715       3.0756       1.0871        2.877      0.62568     -0.23643     0.026904     0.041477       371.25            0            0 
+190      0.47044      0.16937      0.47553      0.15451      0.00655      0.18222      -0.1724    -0.059024   0.00055136   -0.0016104   -0.0026992  -0.00095241       14.481            0            0 
+63     -0.18406     -0.46489     -0.19857     -0.45888      0.11443       3.2819       1.2559        3.032      0.63295     -0.26217     0.029669     0.043507       395.95            0            0 
+191      0.47553      0.15451      0.48015       0.1395      0.00652       0.1824     -0.17434    -0.053633   -0.0013757    0.0044717     -0.00276   -0.0007722       14.816            0            0 
+64     -0.19857     -0.45888     -0.21289     -0.45241      0.12189       3.5026       1.4414       3.1923      0.63289     -0.28576     0.032581     0.045654       416.49            0            0 
+192      0.48015       0.1395      0.48429      0.12434      0.00752      0.21463     -0.20703    -0.056636    0.0012167   -0.0044473   -0.0032327  -0.00095945       24.044            0            0 
+65     -0.21289     -0.45241       -0.227      -0.4455      0.12976       3.7205       1.6368       3.3411      0.61407     -0.30083     0.035355     0.047755       437.52            0            0 
+193      0.48429      0.12434      0.48796      0.10907      0.00763      0.21658     -0.21059    -0.050559  -0.00048939    0.0020384   -0.0033155  -0.00076212       19.502            0            0 
+66       -0.227      -0.4455     -0.24088     -0.43815      0.13616        3.921       1.8348       3.4653      0.61183     -0.32395     0.038429     0.049342       464.84            0            0 
+194      0.48796      0.10907      0.49114     0.093691      0.00753       0.2076     -0.20328    -0.042098    3.578e-06  -1.7278e-05    -0.003193  -0.00066151       19.786            0            0 
+67     -0.24088     -0.43815     -0.25452     -0.43037      0.14085       4.0671       2.0151       3.5328      0.59521      -0.3395        0.041     0.050158       482.01            0            0 
+195      0.49114     0.093691      0.49384     0.078217      0.00786      0.21583     -0.21262    -0.037107  -0.00077816    0.0044587   -0.0033518  -0.00051282       20.912            0            0 
+68     -0.25452     -0.43037     -0.26791     -0.42216      0.14759       4.2774       2.2349       3.6471      0.60466     -0.37054     0.044603     0.051466        506.8            0            0 
+196      0.49384     0.078217      0.49606     0.062667      0.00819      0.23524     -0.23289    -0.033146  -0.00085356    0.0059974   -0.0036716  -0.00042643       22.943            0            0 
+69     -0.26791     -0.42216     -0.28104     -0.41354      0.16014       4.6478       2.5518       3.8847      0.62963     -0.41359     0.049971     0.054522       539.94            0            0 
+197      0.49606     0.062667      0.49778     0.047054      0.00804      0.22691     -0.22554      -0.0249  -0.00028588    0.0025895   -0.0035471  -0.00035044       16.711            0            0 
+70     -0.28104     -0.41354     -0.29389     -0.40451      0.16757       4.8397       2.7829       3.9596      0.62259     -0.43756      0.05349     0.055322       579.76            0            0 
+198      0.49778     0.047054      0.49901     0.031395      0.00859      0.24833     -0.24756    -0.019484   0.00012643   -0.0016065   -0.0038866  -0.00033127       24.051            0            0 
+71     -0.29389     -0.40451     -0.30645     -0.39508       0.1739       5.0263       3.0179       4.0194      0.60761     -0.45621     0.056947     0.055969       577.79            0            0 
+199      0.49901     0.031395      0.49975     0.015705      0.00864      0.24488     -0.24461    -0.011535  -0.00020579    0.0043638   -0.0038454  -0.00011265       21.855            0            0 
+72     -0.30645     -0.39508     -0.31871     -0.38526      0.18416       5.3398       3.3387       4.1674      0.61043     -0.48905      0.06203     0.057777       617.08            0            0 
+200      0.49975     0.015705          0.5            0      0.00855      0.24307     -0.24304    -0.003818  -2.1472e-05    0.0013669   -0.0038179  -3.8502e-05       24.804            0            0 
+73     -0.31871     -0.38526     -0.33066     -0.37506      0.19299       5.5865       3.6281        4.248      0.59456      -0.5078     0.066327     0.058748       653.23            0            0 
+74     -0.33066     -0.37506     -0.34227     -0.36448        0.202       5.8283       3.9225       4.3108      0.55467     -0.50471     0.070324     0.059783       646.19            0            0 
+75     -0.34227     -0.36448     -0.35355     -0.35355      0.21444       6.2168       4.3264       4.4645       0.5541     -0.53696     0.076659     0.061691       693.05            0            0 
+76     -0.35355     -0.35355     -0.36448     -0.34227      0.22163       6.4152       4.6069       4.4644      0.54963     -0.56718     0.080996     0.061216       738.13            0            0 
+77     -0.36448     -0.34227     -0.37506     -0.33066      0.23122        6.715       4.9666       4.5193      0.49814     -0.54745     0.085837     0.062387       768.29            0            0 
+78     -0.37506     -0.33066     -0.38526     -0.31871      0.24011       6.9533       5.2873       4.5158      0.49784      -0.5829      0.09087     0.061776       794.42            0            0 
+79     -0.38526     -0.31871     -0.39508     -0.30645      0.24878       7.2153        5.631       4.5113      0.44512      -0.5556      0.09544     0.062134       809.46            0            0 
+80     -0.39508     -0.30645     -0.40451     -0.29389      0.25649       7.4012       5.9186       4.4438      0.42807     -0.57014     0.099689     0.060845       809.17            0            0 
+81     -0.40451     -0.29389     -0.41354     -0.28104      0.26607       7.7339       6.3274        4.447      0.40702     -0.57914      0.10578     0.060754       846.33            0            0 
+82     -0.41354     -0.28104     -0.42216     -0.26791      0.27327       7.9395       6.6359        4.359      0.38993     -0.59361      0.11036     0.059144       879.53            0            0 
+83     -0.42216     -0.26791     -0.43037     -0.25452      0.28633       8.2916       7.0697       4.3323      0.35693     -0.58245      0.11665     0.058901       896.95            0            0 
+84     -0.43037     -0.25452     -0.43815     -0.24088      0.29527       8.4947       7.3787       4.2088      0.31681     -0.55543      0.12088     0.057384       924.33            0            0 
+85     -0.43815     -0.24088      -0.4455       -0.227      0.30245       8.7299       7.7152        4.085      0.28662     -0.54134      0.12569     0.055661       954.79            0            0 
+86      -0.4455       -0.227     -0.45241     -0.21289      0.31021       8.9829       8.0669       3.9519      0.28744     -0.58674      0.13122     0.052858       1000.9            0            0 
+87     -0.45241     -0.21289     -0.45888     -0.19857      0.31163       9.0745       8.2705       3.7343      0.22846     -0.50599       0.1335     0.050708       1004.7            0            0 
+88     -0.45888     -0.19857     -0.46489     -0.18406      0.32766       9.4299       8.7121       3.6087      0.21056     -0.50834      0.14015     0.048698       1014.4            0            0 
+89     -0.46489     -0.18406     -0.47044     -0.16937      0.33032       9.5532       8.9365       3.3768      0.17456     -0.46197      0.14311     0.045785       1037.4            0            0 
+90     -0.47044     -0.16937     -0.47553     -0.15451      0.33896       9.7775       9.2503       3.1671      0.14191     -0.41447      0.14753     0.043236       1042.8            0            0 
+91     -0.47553     -0.15451     -0.48015      -0.1395      0.34456       9.9596       9.5194       2.9285      0.12756     -0.41464      0.15153     0.039487       1077.6            0            0 
+92     -0.48015      -0.1395     -0.48429     -0.12434      0.34373       9.9608       9.6078       2.6284      0.10468     -0.38265      0.15256     0.035275       1099.2            0            0 
+93     -0.48429     -0.12434     -0.48796     -0.10907       0.3539       10.251       9.9673       2.3929     0.079484     -0.33108      0.15781     0.032386       1114.9            0            0 
+94     -0.48796     -0.10907     -0.49114    -0.093691      0.35469       10.268       10.055       2.0822     0.065297     -0.31531      0.15896     0.027753         1111            0            0 
+95     -0.49114    -0.093691     -0.49384    -0.078217      0.36178       10.472       10.316       1.8005     0.045872     -0.26283      0.16276     0.024153       1111.4            0            0 
+96     -0.49384    -0.078217     -0.49606    -0.062667      0.36509       10.593       10.487       1.4925     0.028089     -0.19737      0.16516     0.020343       1197.2            0            0 
+97     -0.49606    -0.062667     -0.49778    -0.047054      0.36822       10.619       10.554       1.1652      0.02106     -0.19076      0.16611     0.015306       1123.1            0            0 
+98     -0.49778    -0.047054     -0.49901    -0.031395      0.36663       10.598       10.565      0.83152       0.0122     -0.15502      0.16615     0.010626       1135.1            0            0 
+99     -0.49901    -0.031395     -0.49975    -0.015705      0.36949       10.713       10.701      0.50463     0.003613    -0.076614      0.16814     0.006723       1145.4            0            0 
+100     -0.49975    -0.015705         -0.5            0      0.36804       10.703       10.702      0.16812   0.00039792     -0.02533      0.16811    0.0022429         1188            0            0 
+101         -0.5            0     -0.49975     0.015705      0.37263         10.8       10.798     -0.16964   -0.0001088   -0.0069256      0.16961   -0.0027733       1202.9            0            0 
+102     -0.49975     0.015705     -0.49901     0.031395      0.37073       10.709       10.698     -0.50449    0.0033311     0.070636      0.16808   -0.0068146       1167.8            0            0 
+103     -0.49901     0.031395     -0.49778     0.047054      0.37122       10.694       10.661     -0.83903    0.0077438     0.098394      0.16758    -0.011633       1141.5            0            0 
+104     -0.49778     0.047054     -0.49606     0.062667      0.36719       10.635        10.57       -1.167     0.016398      0.14853      0.16629    -0.015997       1185.8            0            0 
+105     -0.49606     0.062667     -0.49384     0.078217      0.36819       10.682       10.575      -1.5051     0.031973      0.22466      0.16661    -0.020112       1188.8            0            0 
+106     -0.49384     0.078217     -0.49114     0.093691      0.35943       10.399       10.244      -1.7878     0.045273       0.2594      0.16161    -0.024007       1132.8            0            0 
+107     -0.49114     0.093691     -0.48796      0.10907      0.35966        10.46       10.243      -2.1212     0.060006      0.28976      0.16183    -0.028766       1162.2            0            0 
+108     -0.48796      0.10907     -0.48429      0.12434      0.35105        10.16       9.8797      -2.3719      0.09491      0.39533      0.15667    -0.031047       1108.2            0            0 
+109     -0.48429      0.12434     -0.48015       0.1395      0.34762       10.108       9.7499      -2.6673      0.10389      0.37974      0.15478    -0.035931       1132.7            0            0 
+110     -0.48015       0.1395     -0.47553      0.15451      0.34389         9.96       9.5197      -2.9286      0.13492      0.43857      0.15165    -0.039112       1078.9            0            0 
+111     -0.47553      0.15451     -0.47044      0.16937      0.33611        9.793        9.265      -3.1721      0.15651      0.45713      0.14799    -0.042645       1074.2            0            0 
+112     -0.47044      0.16937     -0.46489      0.18406      0.32928       9.5495        8.933      -3.3755      0.18582      0.49175      0.14323    -0.045296       1042.4            0            0 
+113     -0.46489      0.18406     -0.45888      0.19857      0.32139       9.3024       8.5943      -3.5599       0.1892      0.45677      0.13797    -0.048742       1032.6            0            0 
+114     -0.45888      0.19857     -0.45241      0.21289      0.31669       9.1643       8.3523      -3.7712      0.23552      0.52163      0.13489    -0.051043       1006.5            0            0 
+115     -0.45241      0.21289      -0.4455        0.227      0.30689       8.8769       7.9717      -3.9053      0.26245      0.53572      0.12934    -0.052927       986.01            0            0 
+116      -0.4455        0.227     -0.43815      0.24088       0.2994       8.6979       7.6869        -4.07      0.29894       0.5646      0.12544    -0.055061       953.12            0            0 
+117     -0.43815      0.24088     -0.43037      0.25452      0.29325       8.4786       7.3648      -4.2008      0.31299      0.54874       0.1206    -0.057364       933.49            0            0 
+118     -0.43037      0.25452     -0.42216      0.26791       0.2858       8.2382       7.0242      -4.3045      0.35423      0.57806       0.1159    -0.058532       915.88            0            0 
+119     -0.42216      0.26791     -0.41354      0.28104      0.27605       8.0063       6.6917      -4.3956      0.37986      0.57828      0.11108     -0.05996          895            0            0 
+120     -0.41354      0.28104     -0.40451      0.29389      0.26791       7.7714       6.3582      -4.4686      0.40907      0.58204      0.10629    -0.061047       884.88            0            0 
+121     -0.40451      0.29389     -0.39508      0.30645       0.2574        7.477       5.9793      -4.4894      0.42269      0.56297      0.10056    -0.061673       841.48            0            0 
+122     -0.39508      0.30645     -0.38526      0.31871      0.24971       7.2134       5.6296      -4.5101      0.45381      0.56644     0.095554    -0.061945       812.49            0            0 
+123     -0.38526      0.31871     -0.37506      0.33066      0.24173       6.9974       5.3208      -4.5444      0.49638      0.58119     0.091373    -0.062252       790.58            0            0 
+124     -0.37506      0.33066     -0.36448      0.34227      0.23494       6.7795       5.0144      -4.5627      0.52704      0.57921      0.08704     -0.06257       752.35            0            0 
+125     -0.36448      0.34227     -0.35355      0.35355      0.22224       6.4153        4.607      -4.4645      0.53528      0.55236     0.080771    -0.061449       720.17            0            0 
+126     -0.35355      0.35355     -0.34227      0.36448      0.21153       6.1304       4.2662      -4.4024      0.53716      0.52054     0.075448    -0.060974          723            0            0 
+127     -0.34227      0.36448     -0.33066      0.37506      0.20558       5.9229       3.9862      -4.3807       0.5859      0.53312     0.071815    -0.060436       669.24            0            0 
+128     -0.33066      0.37506     -0.31871      0.38526      0.19417       5.6025       3.6385      -4.2601      0.59635      0.50934     0.066518    -0.058915       628.47            0            0 

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/runmpirun128.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+#SBATCH -J Cylinder——Kn
+#SBATCH -p wzhcnormal
+#SBATCH -N 2
+#SBATCH --ntasks-per-node=64
+
+
+module purge
+module load compiler/devtoolset/7.3.1
+module load mpi/hpcx/2.11.0/gcc-7.3.1
+export UCX_WARN_UNUSED_ENV_VARS=n
+/public/software/mpi/hpcx/v2.11.0/gcc-7.3.1/bin/mpirun -n 128 ../../../sep2024-sparta/src/spa_mpi <config.txt
+
+/work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Grid -r ./output/grid.*.dat
+
+/work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Lambda -r ./output/lambdakn.*.dat
+
+/work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/surf2paraview.py ./surf/geom.surf Surf -r ./output/surf.*.dat

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/runmpirun64.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+#SBATCH -J Cylinder——Kn
+#SBATCH -p wzhcnormal
+#SBATCH -N 1
+#SBATCH --ntasks-per-node=64
+
+
+module purge
+module load compiler/devtoolset/7.3.1
+module load mpi/hpcx/2.11.0/gcc-7.3.1
+export UCX_WARN_UNUSED_ENV_VARS=n
+/public/software/mpi/hpcx/v2.11.0/gcc-7.3.1/bin/mpirun -n 64 ../../../sep2024-sparta/src/spa_mpi <config.txt
+
+/work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Grid -r ./output/grid.*.dat
+
+/work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Lambda -r ./output/lambdakn.*.dat
+
+/work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/surf2paraview.py ./surf/geom.surf Surf -r ./output/surf.*.dat

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/slurm-28428666.out

@@ -0,0 +1,208 @@
+SPARTA (4 Sep 2024)
+Running on 128 MPI task(s)
+Running on 128 MPI task(s)
+Created orthogonal box = (-5 -5 -0.5) to (6 5 0.5)
+Created 191516 child grid cells
+  CPU time = 0.197726 secs
+  create/ghost percent = 0.751132 99.2489
+Balance grid migrated 191124 cells
+  CPU time = 0.157903 secs
+  reassign/sort/migrate/ghost percent = 33.913 0.0307911 10.0207 56.0355
+Reading surface file ...
+  200 lines
+  -0.5 0.5 xlo xhi
+  -0.5 0.5 ylo yhi
+  0 0 zlo zhi
+  0.0157073 min line length
+  644 0 = cells overlapping surfs, overlap cells with unmarked corner pts
+  171120 19752 644 = cells outside/inside/overlapping surfs
+  644 = surf cells with 1,2,etc splits
+  109.214731023046 109.214731023047 = cell-wise and global flow volume
+  CPU time = 0.166812 secs
+  read/check/sort/surf2grid/ghost/inout/particle percent = 14.0603 12.6344 1.5501 18.8182 52.9369 3.99273 0.114529
+  surf2grid time = 0.031391 secs
+  map/comm1/comm2/comm3/comm4/split percent = 17.3577 18.6412 18.4252 3.68668 8.68144 4.98892
+Balance grid migrated 2352 cells
+  CPU time = 0.0977742 secs
+  reassign/sort/migrate/ghost percent = 3.07838 0.05391 8.90709 87.9606
+Creating particles ...
+Created 1310576 particles
+  CPU time = 0.0232877 secs
+Memory usage per proc in Mbytes:
+  particles (ave,min,max) = 2.16211 0 5.0625
+  grid      (ave,min,max) = 7.30725 1.51379 13.7013
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 9.48996 4.15939 16.1594
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave 
+       0            0  1310576        0        0        0            0            0 
+   10000     37.70329  1404140    45490    38691       22    1336144.5      22.3498 
+   20000    95.680308  1443585    47493    40419       26    1383838.3       22.556 
+   30000    154.33888  1445801    47756    40935       25    1404448.2    22.637233 
+   40000    212.66122  1446444    47765    40809       20    1415021.4    22.667675 
+   50000    271.35277  1447853    47782    40820       13    1421554.7     22.70268 
+   60000    329.83701  1447655    47894    40949       23    1425989.7    22.743883 
+   70000    388.49419  1447517    47793    40905       21    1429198.4    22.747757 
+   80000     447.0694  1447887    47873    41030       18    1431437.9    22.763225 
+   90000    505.54887  1447194    47816    40830       17    1433250.4    22.778522 
+  100000    564.18131  1447883    47872    40951       29      1434638     22.77902 
+  110000    622.87118  1448090    47678    40869       27    1435823.7    22.778491 
+  120000     681.5432  1447591    47840    40949       29    1436812.4    22.779233 
+  130000    740.13531  1446312    48125    41072       19      1437558    22.788692 
+  140000    798.63471  1447713    47985    41009       25    1438260.6    22.795264 
+  150000     856.4965  1448275    47957    40977       12    1438922.7    22.797033 
+  160000    915.07689  1448944    47921    41123       25      1439496    22.804431 
+  170000    974.67697  1447283    47666    40879       25    1440019.3    22.810494 
+  180000    1033.7864  1448126    47900    40993       15    1440459.7    22.814589 
+  190000    1092.5008  1447835    47619    40691       22    1440860.2    22.818626 
+  200000    1150.7441  1447160    47764    40869       32    1441212.2    22.820175 
+Loop time of 1150.75 on 128 procs for 200000 steps with 1447160 particles
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.025986   | 38.857     | 241.6      | 819.6 |  3.38
+Coll    | 0.94116    | 60.652     | 605.33     |1311.6 |  5.27
+Sort    | 0.33291    | 15.062     | 138.49     | 702.2 |  1.31
+Comm    | 103.95     | 135.09     | 148.68     |  82.3 | 11.74
+Modify  | 0.023885   | 0.31403    | 5.2141     | 145.2 |  0.03
+Output  | 0.035957   | 0.092597   | 0.099643   |   3.6 |  0.01
+Other   |            | 900.7      |            |       | 78.27
+
+Particle moves    = 288242448816 (288B)
+Cells touched     = 301602299781 (302B)
+Particle comms    = 351186057 (351M)
+Boundary collides = 0 (0K)
+Boundary exits    = 35231844 (35.2M)
+SurfColl checks   = 198932267 (199M)
+SurfColl occurs   = 4564035 (4.56M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 10910902544 (10.9B)
+Collide occurs    = 8331821709 (8.33B)
+Gas reactions     = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+
+Particle-moves/CPUsec/proc: 1.9569e+06
+Particle-moves/step: 1.44121e+06
+Cell-touches/particle/step: 1.04635
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00121837
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.00012223
+Surface-checks/particle/step: 0.000690156
+Surface-collisions/particle/step: 1.5834e-05
+Surface-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0378532
+Collisions/particle/step: 0.0289056
+Gas-reactions/particle/step: 0
+
+Particles: 11305.9 ave 73143 max 0 min
+Histogram: 84 14 4 8 8 4 2 0 0 4
+Cells:     1496.22 ave 1497 max 1496 min
+Histogram: 100 0 0 0 0 0 0 0 0 28
+GhostCell: 38710.9 ave 70939 max 2108 min
+Histogram: 20 10 12 10 17 3 6 4 16 30
+EmptyCell: 436.805 ave 731 max 67 min
+Histogram: 7 5 11 19 11 16 15 16 14 14
+Surfs:     200 ave 200 max 200 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+GhostSurf: 0 ave 0 max 0 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+Memory usage per proc in Mbytes:
+  particles (ave,min,max) = 2.37305 0 8.4375
+  grid      (ave,min,max) = 7.30725 1.51379 13.7013
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 10.2034 4.66193 17.5994
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave 
+  200000            0  1447160    47764    40869        0            0            0 
+  210000    92.999999  1446729    47683    40759       19    1446362.3      22.8574 
+  220000    185.41224  1447008    47745    40903       14      1446521      22.8495 
+  230000    277.45155  1446790    47608    40897       12    1446739.4    22.867367 
+  240000    370.31902  1446719    47813    40910       27    1446811.3    22.873225 
+  250000    462.11951  1447614    47786    40787       26    1447056.2     22.88016 
+  260000    554.92231  1447544    47852    40922       29    1447251.5    22.879333 
+  270000    647.18709  1447294    47797    40972       20    1447403.6    22.884043 
+  280000    740.70837  1447044    47728    40764       10      1447271    22.883225 
+  290000    832.18407  1448156    47734    40695       25    1447263.4    22.883022 
+  300000    925.21807  1447866    47697    40791       19    1447319.4     22.88388 
+Loop time of 925.218 on 128 procs for 100000 steps with 1447866 particles
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.015418   | 19.72      | 116        | 564.5 |  2.13
+Coll    | 0.47125    | 32.254     | 319.76     | 975.3 |  3.49
+Sort    | 0.21328    | 7.9486     | 75.411     | 496.1 |  0.86
+Comm    | 58.426     | 74.065     | 81.532     |  59.8 |  8.01
+Modify  | 6.7181     | 53.331     | 314.05     | 894.2 |  5.76
+Output  | 0.062994   | 0.064638   | 0.070643   |   0.6 |  0.01
+Other   |            | 737.8      |            |       | 79.75
+
+Particle moves    = 144731937477 (145B)
+Cells touched     = 151430714397 (151B)
+Particle comms    = 176029618 (176M)
+Boundary collides = 0 (0K)
+Boundary exits    = 17679724 (17.7M)
+SurfColl checks   = 99821614 (99.8M)
+SurfColl occurs   = 2288388 (2.29M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 5518942902 (5.52B)
+Collide occurs    = 4213258702 (4.21B)
+Gas reactions     = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+
+Particle-moves/CPUsec/proc: 1.22211e+06
+Particle-moves/step: 1.44732e+06
+Cell-touches/particle/step: 1.04628
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00121625
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.000122155
+Surface-checks/particle/step: 0.0006897
+Surface-collisions/particle/step: 1.58112e-05
+Surface-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0381322
+Collisions/particle/step: 0.0291108
+Gas-reactions/particle/step: 0
+
+Particles: 11311.5 ave 72684 max 0 min
+Histogram: 84 14 4 8 8 4 2 0 0 4
+Cells:     1496.22 ave 1497 max 1496 min
+Histogram: 100 0 0 0 0 0 0 0 0 28
+GhostCell: 38710.9 ave 70939 max 2108 min
+Histogram: 20 10 12 10 17 3 6 4 16 30
+EmptyCell: 436.805 ave 731 max 67 min
+Histogram: 7 5 11 19 11 16 15 16 14 14
+Surfs:     200 ave 200 max 200 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+GhostSurf: 0 ave 0 max 0 min
+Histogram: 128 0 0 0 0 0 0 0 0 0
+Writing grid file ...
+  grid cells = 191516
+  CPU time = 0.0269123 secs
+Writing surface file ...
+  surf elements = 200
+  CPU time = 0.00328668 secs
+Processing  6  grid chunk(s).
+Completed grid chunk number:  2
+Completed grid chunk number:  5
+Completed grid chunk number:  0
+Completed grid chunk number:  4
+Completed grid chunk number:  1
+Completed grid chunk number:  3
+
+Done in 0:00:13 (wall clock time)
+
+Processing  6  grid chunk(s).
+Completed grid chunk number:  2
+Completed grid chunk number:  5
+Completed grid chunk number:  0
+Completed grid chunk number:  1
+Completed grid chunk number:  4
+Completed grid chunk number:  3
+
+Done in 0:00:11 (wall clock time)
+
+Processing SPARTA surface information.
+Processing dump result file:  ['./output/surf.300000.dat']

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/surf/Surf_300000.vtu

@@ -0,0 +1,38 @@
+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
+  <UnstructuredGrid>
+    <Piece NumberOfPoints="400"                  NumberOfCells="200"                 >
+      <PointData>
+      </PointData>
+      <CellData>
+        <DataArray type="Float64" Name="id" format="appended" RangeMin="1"                    RangeMax="200"                  offset="0"                   />
+        <DataArray type="Float64" Name="v1x" format="appended" RangeMin="-0.5"                 RangeMax="0.5"                  offset="432"                 />
+        <DataArray type="Float64" Name="v1y" format="appended" RangeMin="-0.5"                 RangeMax="0.5"                  offset="1468"                />
+        <DataArray type="Float64" Name="v2x" format="appended" RangeMin="-0.5"                 RangeMax="0.5"                  offset="2476"                />
+        <DataArray type="Float64" Name="v2y" format="appended" RangeMin="-0.5"                 RangeMax="0.5"                  offset="3508"                />
+        <DataArray type="Float64" Name="f_2[1]" format="appended" RangeMin="0.00398"              RangeMax="0.37263"              offset="4512"                />
+        <DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.097849"             RangeMax="10.8"                 offset="6520"                />
+        <DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.24863"             RangeMax="10.798"               offset="8536"                />
+        <DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-4.5627"              RangeMax="4.5193"               offset="10600"               />
+        <DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.0028378"           RangeMax="0.65268"              offset="12676"               />
+        <DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.59361"             RangeMax="0.58204"              offset="14768"               />
+        <DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.0039059"           RangeMax="0.16961"              offset="16896"               />
+        <DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.06257"             RangeMax="0.062387"             offset="19040"               />
+        <DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="11.447"               RangeMax="1202.9"               offset="21184"               />
+        <DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="22564"               />
+        <DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="22616"               />
+      </CellData>
+      <Points>
+        <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503"        RangeMax="0.50000001255"        offset="22668"               />
+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="23996"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="24900"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="25392"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
+  <AppendedData encoding="base64">
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AQAAAACAAABABgAA+QUAAA==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AQAAAACAAABABgAAAQYAAA==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AQAAAACAAABABgAADQYAAA==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AQAAAACAAABABgAAKAYAAA==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AQAAAACAAABABgAANAYAAA==eJwdlI0/FIYfx8saWeU3vwxJUfRTUx4iNg/3rbDh1EjOcVHoxnm4mxBK8cMpXJ7l4VAoMRwqnM71vTt3tatl2I6Spbkua9yLS9rykLX9A+/P6/N6vT+fw6cfv2rh0XFEHKTvusLAcVZlW1F+DBJshqrUSQxkijqSFvl0tAuo31o3GIN26n9JW76MwkxTslAnh4bqwUP8OSsaOsVb+cQ1UtHvSaLbLFLRJV/fuXuAiuQE0rpp6xC8c2ftX6OPQ9BmDSVNO/84Wt7PkradoWDzVpnf/2oDsE4tNuLpGX9cHo/uN1T64k1/LblpxhH0VA0szpC8cZz3tpKMhzBmZYqckkDEXTafFvIyPbGpPfNs1rQL8q3DP0/XAFTGrQ3eoU7Ai5Uc9x/0AM2qtZjEGmesst+zpLnkiGqCprdZh62x7ZDD0mLrLsyp1VhDqTXC4lwMbNivIAzMG2hdMhq8K7V4uW2vlTmcT4qpVVEt4Pq2CvF/Mh2g7MBM9EY9N9CJ67xzIOAQ5NBDlSW3vID3bFqiLgwADqVp/cXOIKgJY7cp3U9A9P/Lx8VTVAiZPXOmixwFUt4TWWXVd5A8fjDicGMs0DaUPHigSICCDtOc0a+TQH27TLguOhXMNH8+0FiVBlPDKQ2NrhlgFPFxVgudCdtgcw/dMxsS/E8Ln1fmQtx8WPHSxXx4z11+Lc0pBLU3i+8f5RaDkbbv9uzgy3BjKpuzDsphnp/1nMtiw4BqcIIVUgNiE9XreM5VSPkkTbXeoA4q2AzXP1vq4WGtW9fc8jW4H8o+ajvcAKFWqcwfS5tgMdm38JOwZoif2ue8c2crLMn5kVRRG3BSR8L7F9phN9doVrDqJlhwVBXTV24Bkbw5zKz3NpRESOW0d53gvdqq5oBLN6ip7pwX0rlw+Zhkwp7ZA9Y7in6n6vBghSLNu7S/F9T/qwP3xviwqYD/bFl1F/aUdptU6QrANNTTdPChADzXq5lf0BXCF+GuNMasEJbTf22P8RFBjuIyyWVCBKOnLCR+1D4YEZA0dS/0gff35xy22ohhtq7N+BFZDJY01rCPTAzv+IdS35pIIHtG3KLnIgE8t+UDUgKjxsWsKqYErLs+fXE1UwKWudmP7ndK4CIxz/F6hgSeBfCUB+MkcJ7x85VldwnY/Fa2kOwrgfzvAj9EiIH3od3jLjE4y7bZ920QQ3OpJv7yUx+c/wdP64P37tqbSCoR1O6ZPHLMTwRs4z8Iq5qEsDfwa7+NrkIw/mptvl2eAMiG/UuRWgLYIlXAtfG7sNaZ7XelmQ/NFGczPqMXrn7zwmNoHw8KzTxGvO72gHr6qk0Op7kgudeb98XJbki7EvvbfvcuoOonZkS03obiWNbJfO9b0Mc7Jk4MvQmR4eWjRzQ6YNZKyV5sboMMmj5he0MLfPPx2NwSrRkITsQCbe8mqDKIIEzSb4BeTVnOpeTr4CZriyc41UPQxA8fFbrVQete38BU4lXw5cxa6KmqId1I1j6+kQ0TilfHfDzLITPUPCIwtBQGJ+tZ3FUloMd1GmatL4JrC/2WngP50GRJdNxXlgvnEs2J8ZezYYNez41mxyxQ7Nyv82N5OuwmvykvepsGUZG2OkMJKSCvvtQgxmS4FtwwZrM6Af6xryTsFLCl9k/Hyukgz7N/t8eBBsTFXLck43CIj3N0I9eEwMviz/pkq0+AbyOXp6/jD/aD1bqnKD6gYLA4hlHe0B5zu4DQ6QKK3kCPrERXUDrapB4dM4d7943makgmoCFT6Pc4GcNrv+ik6QUd/JUb7Vr65RpkemnOveBZ4RyH3b/jwj4MSiL1KPudcOYgy2GS6oRKtQ6OWpgDirQ9KpL1XNFv/OjKWaIrPrd952z4h/uHf+wQB2d4oHxgLz+n1QtH6iKKdO280G0DsZFp741Z5qQ+W5EPPpl2n68+fhTVJk4Ofv7KHx0NLiwEPQ7EgDCDMt7zIHxTsfxwZZ6Cq1XHJYe3nEB5bMvLkqchKBDwU5ZmQlG+2+7PWsNv0eTfQX2LtoXy8tNnI1HEdErfvCsKl+sZQ7Y7I/EpGaYdE6JQg1LoPLmRjveIYz/1a8Wgf3xByoNhBn5E5YSHpTGwbi4hvvsrBv4N2IYdUw==AQAAAACAAABABgAANQYAAA==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AQAAAACAAABABgAA+QMAAA==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eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro3/MVfvektb3vHu97zvg986CMf+8SnPvO5L3zpK1/7m7/7h3/6l3/7xrf+47++870f/OgnP/vFr37zP0dFvxfjWMc53gkOONFJDjrZKU51mtOd4UxnOds5znWeQ853gQtd5GKXuNRlLneFK13late41nWud4Mb3eRmt7jVYbe53R3udJcj7naPe93nfg940EMe9ohHPeZxT3jSU572jGc95/9sSVRSAQAAAACAAADIAAAADAAAAA==eJxjZh4eAADsVAJZ
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0369_Kn0p20Ma3p8/surf/geom.surf

@@ -0,0 +1,610 @@
+# Surface element file written by SPARTA
+
+400 points
+200 lines
+
+Points
+
+1                  0.5                    0
+2    0.499753280182866  -0.0157053795390643
+3    0.499753280182866  -0.0157053795390643
+4    0.499013364214136  -0.0313952597646568
+5    0.499013364214136  -0.0313952597646568
+6     0.49778098230154  -0.0470541566592573
+7     0.49778098230154  -0.0470541566592573
+8    0.496057350657239  -0.0626666167821523
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AQAAAACAAABsYwAAohEAAA==eJxN3DGIJVudBvAGQRAmEARhwEAQBgQDYUAQDAYEQbiBIAiCgSAMCAbCgCAYjCiD4iDKiDjussyyy8OiiqKKKoo6VFl7oheN0YteZmRkZrTZbvXp869fR1/yCz76nO92V9/bd3fvnt3dvct3///157f/Gfnp0/+K/Lf3/x35+fMPIt/d/QXbYFtsh+2xA3bETtgZu2BXbMJu2B17YDP53bPnz/8jutd8dq/57F7z2b3ms/tlG2yL7bA9dsCO2Ak7Yxfsik3YDbtjD2wmv3v2t/f/Ht1rPrvXfHav+exe89n9sg22xXbYHjtgR+yEnbELdsUm7IbdsQc2k989e/r036J7zWf3ms/uNZ/daz67X7bBttgO22MH7IidsDN2wa7YhN2wO/bAZvK7Z39++za613x2r/nsXvPZveaz+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/en6F5z2bo/Rfeay9b9KbpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1f4zuNZet+2N0r7ls3R+j+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/eH6F5z2bo/RPeay9b9IbpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1b6J7zWXr3kT3msvWvYnul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3e+je81l634f3WsuW/f76H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59b9LrrXXLbud9G95rJ1v4vul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3W+je81l634b3WsuW/fb6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59a9ju41l617Hd1rLlv3OrpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1v4nuNZet+010r7ls3W+i+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/fr6F5z2bpfR/eay9b9OrpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1v4ruNZet+1V0r7ls3a+i+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/cqutdctu5VdK+5bN2r6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59b9MrrXXLbul9G95rJ1v4zul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3S+ie81l634R3WsuW/eL6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59b9PLrXXLbu59G95rJ1P4/ul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3cvoXnPZupfRveaydS+j+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCaf9/1n0b3mct9/Ft1rLvf9Z9H9sg22xXbYHjtgR+yEnbELdsUm7IbdsQc2k88z/9PoXnM58z+N7jWXM//T6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ52vcT6J7zeU17ifRvebyGveT6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ586/iO41l51/Ed1rLjv/IrpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1P47uNZet+3F0r7ls3Y+j+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/ej6F5z2bofRfeay9b9KLpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1P4zuNZet+2F0r7ls3Q+j+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/c8utdctu55dK+5bN3z6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59b9ILrXXLbuB9G95rJ1P4jul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3feje81l674f3WsuW/f96H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9L7rXXLbue9G95rJ134vul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3Xeje81l674b3WsuW/fd6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9J7rXXLbuO9G95rJ134nul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3beje81l674d3WsuW/ft6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9K7rXXLbuW9G95rJ134rul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3S2611y27hbday5bd4vul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3Teje81l674Z3WsuW/fN6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9I7rXXLbuG9G95rJ134jul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3deje81l674e3WsuW/f16H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Y9i+41l617Ft1rLlv3LLpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1X4vuNZet+1p0r7ls3dei+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/fV6F5z2bqvRveay9Z9NbpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1X4nuNZet+0p0r7ls3Vei+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/c0utdctu5pdK+5bN3T6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9ObrXXLbuy9G95rJ1X47ul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3Zeie81l674U3WsuW/el6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9MbrXXLbui9G95rJ1X4zul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3ZPoXnPZuifRveaydU+i+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/eF6F5z2bovRPeay9Z9IbpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1n4/uNZet+3x0r7ls3eej+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/e56F5z2brPRfeay9Z9LrpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1j6N7zWXrHkf3msvWPY7ul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3Weje81l6z4b3WsuW/fZ6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9JrrXXLbuM9G95rJ1n4nul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3aeje81l6z4d3WsuW/fp6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Y9iu41l617FN1rLlv3KLpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1n4ruNZet+1R0r7ls3aei+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/fJ6F5z2bpPRveay9Z9MrpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1n4juNZet+0R0r7ls3Sei+2UbbIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW3cX3WsuW3cX3WsuW3cX3S/bYFtsh+2xA3bETtgZu2BXbMJu2B17YDP5vO//+z+1e83lvpdc7nvJ5b6XXO57tQ22xXbYHjtgR+yEnbELdsUm7IbdsQc2k88z/6/oXnM58/+K7jWXM/+v6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ52vcP6N7zeU17p/RvebyGvfP6H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ587/I7rXXHb+H9G95rLz/4jul22wLbbD9tgBO2In7IxdsCs2YTfsjj2wmXxu3d+je81l6/4e3WsuW/f36H7ZBttiO2yPHbAjdsLO2AW7YhN2w+7YA5vJ59Z9zNZ9zNZ9zNZ9zNZ9zNZ9HN0v22I7bI8dsCN2ws7YBbtiE3bD7tgDm8nn1n3E1n3E1n3E1n3E1n3E1n0U3S/bYjtsjx2wI3bCztgFu2ITdsPu2AObyefWvWfr3rN179m692zde7bufXS/bIvtsD12wI7YCTtjF+yKTdgNu2MPbCafW/chW/chW/chW/chW/chW/dhdL9si+2wPXbAjtgJO2MX7IpN2A27Yw9sJp9bl9m6zNZlti6zdZmty9H9si22w/bYATtiJ+yMXbArNmE37I49sJl8bl1i6xJbl9i6xNYlti5F98u22A7bYwfsiJ2wM3bBrtiE3bA79sBm8rl1E1s3sXUTWzexdRNbN0X3y7bYDttjB+yInbAzdsGu2ITdsDv2wGbyuXUdW9exdR1b17F1HVvXRffLttgO22MH7IidsDN2wa7YhN2wO/bAZvK5dR+wdR+wdR+wdR+wdR+wdR9E98u22A7bYwfsiJ2wM3bBrtiE3bA79sBm8v3/dGLr3rF179i6d2zdO7buXXS/bIvtsD12wI7YCTtjF+yKTdgNu2MPbCbf/38btu4tW/eWrXvL1r1l695G98u22A7bYwfsiJ2wM3bBrtiE3bA79sBm8v3/+mDr3rB1b9i6N2zdG7buTXS/bIvtsD12wI7YCTtjF+yKTdgNu2MPbCbf/98Dtu41W/earXvN1r1m615H98u22A7bYwfsiJ2wM3bBrtiE3bA79sBm8v1nwNm6V2zdK7buFVv3iq17Fd0v22I7bI8dsCN2ws7YBbtiE3bD7tgDm8n3n4dl616ydS/Zupds3Uu27mV0v2yL7bA9dsCO2Ak7Yxfsik3YDbtjD2wm3382kPv+gvv+gvv+gvv+gvv+IrpftsV22B47YEfshJ2xC3bFJuyG3bEHNpPvPyfFmX/OmX/OmX/OmX/OmX8e3S/bYjtsjx2wI3bCztgFu2ITdsPu2AObyfefGYnuNT98ZiS61/zwmZHoftkG22I7bI8dsCN2ws7YBbtiE3bD7tgDm8n3759n52/s/I2dv7HzN3b+Ft0v22I7bI8dsCN2ws7YBbtiE3bD7tgDm8n37yVm656xdc/Yumds3TO27ll0v2yL7bA9dsCO2Ak7Yxfsik3YDbtjD2wm37+vkq17ytY9ZeuesnVP2bqn0f2yLbbD9tgBO2In7IxdsCs2YTfsjj2wmXz/HjO27glb94Ste8LWPWHrnkT3y7bYDttjB+yInbAzdsGu2ITdsDv2wGby/ftt2LrHbN1jtu4xW/eYrXsc3S/bYjtsjx2wI3bCztgFu2ITdsPu2AObyffvPWDrHrF1j9i6R2zdI7buUXS/bIvtsD12wI7YCTtjF+yKTdgNu2MPbCbf/x2Wrbtj6+7Yuju27o6tu4vul22xHbbHDtgRO2Fn7IJdsQm7YXfsgc3k+79JHbV7zQ9/kzpq95of/iZ11O6XbbAttsP22AE7YifsjF2wKzZhN+yOPbCZfP98PrrX/PB8PrrX/PB8PrpftsG22A7bYwfsiJ2wM3bBrtiE3bA79sBm8v2zyuhe88Ozyuhe88Ozyuh+2QbbYjtsjx2wI3bCztgFu2ITdsPu2AObyffPbaJ7zQ/PbaJ7zQ/PbaL7ZRtsi+2wPXbAjtgJO2MX7IpN2A27Yw9sJt//Dhvda374HTa61/zwO2x0v2yDbbEdtscO2BE7YWfsgl2xCbthd+yBzeT7n+e57zfu+437fuO+37jvt+h+2RbbYXvsgB2xE3bGLtgVm7Abdsce2Ey+/9mGM/+YM/+YM/+YM/+YM/84ul+2xXbYHjtgR+yEnbELdsUm7IbdsQc2k+93/q/X973kh53/6/V9L/lh5/96fd+rbbAttsP22AE7YifsjF2wKzZhN+yOPbCZfH/m6X6j+43uN7rf6H6j+43uN7rf6H6j+43uN7rf6H6j+43uN7rf6H6j+43uN7rfovvdw9fDz3V3tXvNDz/X3dXud/H1F2yDbbEdtscO2BE7YWfsgl2xCbthd+yBzZH/D0ptePQ=AgAAAACAAAAAegAAiRMAAKISAAA=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AQAAAACAAADQBwAAFwAAAA==eJzj5BwFo2AUjIJRMApGwVAHAOOGRlE=
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/Lambda/Lambda_300000.pvtu

@@ -0,0 +1,23 @@
+<?xml version="1.0"?>
+<VTKFile type="PUnstructuredGrid" version="0.1"
+               byte_order="LittleEndian"
+               compressor="vtkZLibDataCompressor">
+<PUnstructuredGrid GhostLevel="0">
+<PCellData>
+<PDataArray type="Float64" Name="id"/>
+<PDataArray type="Float64" Name="xc"/>
+<PDataArray type="Float64" Name="yc"/>
+<PDataArray type="Float64" Name="c_6[1]"/>
+<PDataArray type="Float64" Name="c_6[2]"/>
+</PCellData>
+<PPoints>
+<PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
+</PPoints>
+<Piece Source="Lambda_0_300000.vtu"/>
+<Piece Source="Lambda_1_300000.vtu"/>
+<Piece Source="Lambda_2_300000.vtu"/>
+<Piece Source="Lambda_3_300000.vtu"/>
+<Piece Source="Lambda_4_300000.vtu"/>
+<Piece Source="Lambda_5_300000.vtu"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/Lambda/Lambda_5_300000.vtu

@@ -0,0 +1,27 @@
+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
+  <UnstructuredGrid>
+    <Piece NumberOfPoints="2121"                 NumberOfCells="2000"                >
+      <PointData>
+      </PointData>
+      <CellData>
+        <DataArray type="Float64" Name="id" format="appended" RangeMin="22201"                RangeMax="44000"                offset="0"                   />
+        <DataArray type="Float64" Name="xc" format="appended" RangeMin="5.025"                RangeMax="5.975"                offset="3352"                />
+        <DataArray type="Float64" Name="yc" format="appended" RangeMin="0.025"                RangeMax="4.975"                offset="3584"                />
+        <DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.0059135"            RangeMax="0.021758"             offset="4128"                />
+        <DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.11827"              RangeMax="0.43517"              offset="22516"               />
+      </CellData>
+      <Points>
+        <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="5"                    RangeMax="7.8102496759"         offset="37024"               />
+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="43060"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="56116"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="59704"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
+  <AppendedData encoding="base64">
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AQAAAACAAACAPgAAbyoAAA==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AgAAAACAAAAAegAAiRMAAKISAAA=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AQAAAACAAADQBwAAFwAAAA==eJzj5BwFo2AUjIJRMApGwVAHAOOGRlE=
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/Surf.pvd

@@ -0,0 +1,9 @@
+<?xml version="1.0"?>
+<VTKFile type="Collection" version="0.1"
+               byte_order="LittleEndian"
+               compressor="vtkZLibDataCompressor">
+   <Collection>    
+    <DataSet timestep="300000" group="" part="0"   
+             file="Surf/Surf_300000.vtu"/>
+   </Collection>    
+</VTKFile>    

CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/config.txt

@@ -0,0 +1,78 @@
+variable    BZ equal 1.380649E-23
+variable    PI equal 3.1415926536
+variable    molecular_mass equal 6.63E-26
+variable    molecular_diameter equal 4.17E-10
+variable    gamma equal 1.666666667
+variable    R equal ${BZ}/${molecular_mass}
+variable    L equal 1.0
+variable    xmin equal -5.0
+variable    xmax equal  6.0
+variable    ymin equal -5.0
+variable    ymax equal  5.0
+variable    Kn equal 0.2
+variable   Ma equal 3.9000000000000004
+variable    To equal 273.0
+variable    Tb equal 273.0
+variable    theta equal 0.0
+variable    mfp equal ${Kn}*${L}
+variable    cpmfp equal 4
+variable    nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
+variable    sos equal sqrt(${gamma}*${R}*${To})
+variable    vo equal ${Ma}*${sos}
+variable    vx equal ${vo}*cos(${theta}*2*PI/360)
+variable    vy equal ${vo}*sin(${theta}*2*PI/360)
+variable    ppc equal 30
+variable    xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
+variable    yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
+variable    Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
+variable    nave equal 10000
+variable    noutput equal 300000
+clear
+shell    mkdir output
+shell    mkdir grid
+shell    mkdir surf
+seed    7
+dimension    2
+global    nrho ${nden}
+global    fnum ${Fnum}
+timestep    ${tstep}
+global    gridcut 1.0 particle/reorder 100 comm/sort yes
+region    1  cylinder z 0.0 0.0 3.50 -0.5 0.5
+region    2  cylinder z 0.0 0.0 2.00 -0.5 0.5
+region    3  cylinder z 0.0 0.0 0.80 -0.5 0.5
+boundary    o o p
+create_box    ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
+create_grid    ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
+balance_grid  rcb cell
+species   gas.species Ar
+mixture   air Ar frac 1.0
+mixture   air Ar vstream ${vx} ${vy} 0.0 temp ${To}
+collide   vss air gas.vhs
+collide_modify    vremax 100 yes remain no nearcp yes 10
+read_surf       cylinder.surf
+surf_collide    1 diffuse 273.0 1.0
+surf_modify     all collide 1
+fix    in emit/face air xlo ylo yhi
+balance_grid  rcb cell
+create_particles air n 0
+stats    10000
+stats_style step cpu np nattempt ncoll nscoll npave nscollave
+run    200000
+compute      1 grid all air n nrho massrho u v w
+compute      2 grid all air trot
+compute      3 tvib/grid all air
+compute      4 thermal/grid all air press temp
+fix          1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
+dump         1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
+dump_modify  1 format float %12.5g
+compute      5 surf all air n press px py shx shy fx fy etot erot evib
+fix          2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
+dump         2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
+dump_modify  2 format float %12.5g
+compute      6  lambda/grid f_1[2] f_1[8] Ar kx
+dump         3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
+dump_modify  3 format float %12.5g
+run    100000
+write_grid    grid/final-grid.dat
+write_surf    surf/geom.surf

CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/cylinder.surf

@@ -0,0 +1,410 @@
+ surf file from Pointwise
+ 
+         200 points
+         200 lines
+ 
+ Points
+ 
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+ Lines
+ 
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CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/gas.species

@@ -0,0 +1,14 @@
+# Species data
+
+# species name
+# molecular weight (atomic mass units, e.g. 16 for oxygen)
+# molecular mass (kg)
+# rotational degrees of freedom (integer, unitless)
+# inverse rotational relaxtion number (unitless)
+# vibrational degrees of freedom (integer, unitless)
+# inverse vibrational relaxation number (unitless)
+# vibrational temperature (K)
+# species weight (unitless)
+# multiple of electon charge (1 for a proton)
+
+Ar    39.95    6.63E-26    0    0.0    0    0.0    0.0    1.0    0.0

CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/gas.vhs

@@ -0,0 +1,9 @@
+# VHS collision model parameters for each species
+
+# species name
+# diameter (m)
+# omega (unitless)
+# tref (referenced temperature)
+# alpha (unitless)
+
+Ar    4.17e-10    0.81    273    1.0

CylinderKnMa/Kn0p20/simulation0370_Kn0p20Ma3p9/grid/Grid_300000.pvtu

@@ -0,0 +1,31 @@
+<?xml version="1.0"?>
+<VTKFile type="PUnstructuredGrid" version="0.1"
+               byte_order="LittleEndian"
+               compressor="vtkZLibDataCompressor">
+<PUnstructuredGrid GhostLevel="0">
+<PCellData>
+<PDataArray type="Float64" Name="id"/>
+<PDataArray type="Float64" Name="xc"/>
+<PDataArray type="Float64" Name="yc"/>
+<PDataArray type="Float64" Name="f_1[1]"/>
+<PDataArray type="Float64" Name="f_1[2]"/>
+<PDataArray type="Float64" Name="f_1[3]"/>
+<PDataArray type="Float64" Name="f_1[4]"/>
+<PDataArray type="Float64" Name="f_1[5]"/>
+<PDataArray type="Float64" Name="f_1[6]"/>
+<PDataArray type="Float64" Name="f_1[7]"/>
+<PDataArray type="Float64" Name="f_1[8]"/>
+<PDataArray type="Float64" Name="f_1[9]"/>
+<PDataArray type="Float64" Name="f_1[10]"/>
+</PCellData>
+<PPoints>
+<PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
+</PPoints>
+<Piece Source="Grid_0_300000.vtu"/>
+<Piece Source="Grid_1_300000.vtu"/>
+<Piece Source="Grid_2_300000.vtu"/>
+<Piece Source="Grid_3_300000.vtu"/>
+<Piece Source="Grid_4_300000.vtu"/>
+<Piece Source="Grid_5_300000.vtu"/>
+</PUnstructuredGrid>
+</VTKFile>