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T0NGXU commited on Dec 29, 2025

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4fc9416

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CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/Lambda/Lambda_0_300000.vtu +0 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/Lambda/Lambda_1_300000.vtu +27 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/Lambda/Lambda_300000.pvtu +19 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/Surf.pvd +9 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/Grid_0_300000.vtu +0 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/Grid_1_300000.vtu +35 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/Grid_300000.pvtu +27 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/final-grid.dat +0 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/output/grid.300000.dat +0 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/output/lambdakn.300000.dat +0 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/output/surf.300000.dat +209 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/surf/Surf_300000.vtu +38 -0
CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/surf/geom.surf +610 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Grid.pvd +9 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Lambda.pvd +9 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Lambda/Lambda_0_300000.vtu +0 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Lambda/Lambda_1_300000.vtu +27 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Lambda/Lambda_300000.pvtu +19 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Surf.pvd +9 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/config.txt +78 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/cylinder.surf +410 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/gas.species +14 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/gas.vhs +9 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/Grid_0_300000.vtu +0 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/Grid_1_300000.vtu +35 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/Grid_300000.pvtu +27 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/final-grid.dat +0 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/log.sparta +318 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/mir.txt +3 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/output/grid.300000.dat +0 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/output/lambdakn.300000.dat +0 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/output/surf.300000.dat +209 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/runmpirun128.sh +18 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/runmpirun64.sh +18 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/slurm-28429038.out +200 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/surf/Surf_300000.vtu +38 -0
CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/surf/geom.surf +610 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Grid.pvd +9 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Lambda.pvd +9 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Lambda/Lambda_0_300000.vtu +0 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Lambda/Lambda_1_300000.vtu +27 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Lambda/Lambda_300000.pvtu +19 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Surf.pvd +9 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/config.txt +78 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/cylinder.surf +410 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/gas.species +14 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/gas.vhs +9 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/grid/Grid_0_300000.vtu +0 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/grid/Grid_1_300000.vtu +35 -0
CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/grid/Grid_300000.pvtu +27 -0

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/Lambda/Lambda_0_300000.vtu ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/Lambda/Lambda_1_300000.vtu ADDED Viewed

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AQAAAACAAAAUNAAAVgoAAA==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+</VTKFile>

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+<?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"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/Surf.pvd ADDED Viewed

	@@ -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/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/Grid_0_300000.vtu ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/Grid_1_300000.vtu ADDED Viewed

	@@ -0,0 +1,35 @@

+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
+  <UnstructuredGrid>
+    <Piece NumberOfPoints="1111"                 NumberOfCells="1000"                >
+      <PointData>
+      </PointData>
+      <CellData>
+        <DataArray type="Float64" Name="id" format="appended" RangeMin="101"                  RangeMax="11000"                offset="0"                   />
+        <DataArray type="Float64" Name="xc" format="appended" RangeMin="5.05"                 RangeMax="5.95"                 offset="2240"                />
+        <DataArray type="Float64" Name="yc" format="appended" RangeMin="-4.95"                RangeMax="4.95"                 offset="2388"                />
+        <DataArray type="Float64" Name="f_1[1]" format="appended" RangeMin="17.65"                RangeMax="75.687"               offset="2928"                />
+        <DataArray type="Float64" Name="f_1[2]" format="appended" RangeMin="1.9038e+19"           RangeMax="8.164e+19"            offset="8112"                />
+        <DataArray type="Float64" Name="f_1[3]" format="appended" RangeMin="1.2622e-06"           RangeMax="5.4127e-06"           offset="17944"               />
+        <DataArray type="Float64" Name="f_1[4]" format="appended" RangeMin="1239.9"               RangeMax="2090.8"               offset="27712"               />
+        <DataArray type="Float64" Name="f_1[5]" format="appended" RangeMin="-464.56"              RangeMax="465.58"               offset="30996"               />
+        <DataArray type="Float64" Name="f_1[6]" format="appended" RangeMin="-7.9808"              RangeMax="9.0518"               offset="37288"               />
+        <DataArray type="Float64" Name="f_1[7]" format="appended" RangeMin="0.12994"              RangeMax="1.0009"               offset="45644"               />
+        <DataArray type="Float64" Name="f_1[8]" format="appended" RangeMin="286.51"               RangeMax="1444.6"               offset="53928"               />
+        <DataArray type="Float64" Name="f_1[9]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="57856"               />
+        <DataArray type="Float64" Name="f_1[10]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="57920"               />
+      </CellData>
+      <Points>
+        <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="5"                    RangeMax="7.8102496759"         offset="57984"               />
+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="61536"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="67968"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="69816"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
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AQAAAACAAABAHwAAvBwAAA==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AQAAAACAAABAHwAAjQkAAA==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AQAAAACAAABAHwAAMRgAAA==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AQAAAACAAABAHwAAbwsAAA==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AQAAAACAAABAHwAAHAAAAA==eJztwQEBAAAAgJD+r+4ICgAAAAAAAAAYH0AAAQ==AQAAAACAAABAHwAAHAAAAA==eJztwQEBAAAAgJD+r+4ICgAAAAAAAAAYH0AAAQ==AQAAAACAAAAUNAAAVgoAAA==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AQAAAACAAABAHwAAWAUAAA==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eJzj5BwFo2AUDHcAAMOYIyk=
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/Grid_300000.pvtu ADDED Viewed

	@@ -0,0 +1,27 @@

+<?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"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/grid/final-grid.dat ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/output/grid.300000.dat ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/output/lambdakn.300000.dat ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/output/surf.300000.dat ADDED Viewed

	@@ -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      0.00137     0.038352    -0.038347   0.00060241   -1.309e-05  -0.00083329  -0.00060254  -3.6265e-06       12.456            0            0
+129     -0.31871      0.38526     -0.30645      0.39508      0.12764       4.2524       2.6588      -3.3187      0.78439      0.62842     0.054083    -0.042257         1750            0            0
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CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/surf/Surf_300000.vtu ADDED Viewed

	@@ -0,0 +1,38 @@

+<?xml version="1.0"?>
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+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="23824"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="24728"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="25220"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
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AQAAAACAAABABgAA5QUAAA==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AQAAAACAAABABgAA/wUAAA==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AQAAAACAAABABgAAIAYAAA==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AQAAAACAAABABgAAMwYAAA==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AQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro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+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0899_Kn0p40Ma6p8/surf/geom.surf ADDED Viewed

	@@ -0,0 +1,610 @@

+# Surface element file written by SPARTA
+400 points
+200 lines
+Points
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AQAAAACAAABAHwAADRgAAA==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AQAAAACAAAAUNAAAVgoAAA==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AQAAAACAAABAHwAAWAUAAA==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eJzj5BwFo2AUDHcAAMOYIyk=
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Lambda/Lambda_300000.pvtu ADDED Viewed

	@@ -0,0 +1,19 @@

+<?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"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/Surf.pvd ADDED Viewed

	@@ -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/Kn0p40/simulation0900_Kn0p40Ma6p9/config.txt ADDED Viewed

	@@ -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 0.4
+variable   Ma equal 6.9
+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/Kn0p40/simulation0900_Kn0p40Ma6p9/cylinder.surf ADDED Viewed

	@@ -0,0 +1,410 @@

+ surf file from Pointwise
+         200 points
+         200 lines
+ Points
+       1  0.5  0.0
+       2  0.499753280182866E+000 -0.157053795390643E-001
+       3  0.499013364214136E+000 -0.313952597646568E-001
+       4  0.497780982301540E+000 -0.470541566592573E-001
+       5  0.496057350657239E+000 -0.626666167821523E-001
+       6  0.493844170297569E+000 -0.782172325201156E-001
+       7  0.491143625364344E+000 -0.936906572928624E-001
+       8  0.487958380969374E+000 -0.109071620698271E+000
+       9  0.484291580564315E+000 -0.124344943582427E+000
+      10  0.480146842838471E+000 -0.139495553019615E+000
+      11  0.475528258147577E+000 -0.154508497187474E+000
+      12  0.470440384477113E+000 -0.169368960122646E+000
+      13  0.464888242944126E+000 -0.184062276342339E+000
+      14  0.458877312841991E+000 -0.198573945317390E+000
+      15  0.452413526233010E+000 -0.212889645782536E+000
+      16  0.445503262094184E+000 -0.226995249869774E+000
+      17  0.438153340021932E+000 -0.240876837050858E+000
+      18  0.430371013501972E+000 -0.254520707875186E+000
+      19  0.422163962751007E+000 -0.267913397489498E+000
+      20  0.413540287137281E+000 -0.281041688926065E+000
+      21  0.404508497187474E+000 -0.293892626146237E+000
+      22  0.395077506187845E+000 -0.306453526826488E+000
+      23  0.385256621387895E+000 -0.318711994874345E+000
+      24  0.375055534815230E+000 -0.330655932661826E+000
+      25  0.364484313710706E+000 -0.342273552964344E+000
+      26  0.353553390593274E+000 -0.353553390593274E+000
+      27  0.342273552964344E+000 -0.364484313710706E+000
+      28  0.330655932661826E+000 -0.375055534815230E+000
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CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/gas.species ADDED Viewed

	@@ -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/Kn0p40/simulation0900_Kn0p40Ma6p9/gas.vhs ADDED Viewed

	@@ -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/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/Grid_0_300000.vtu ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/Grid_1_300000.vtu ADDED Viewed

	@@ -0,0 +1,35 @@

+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
+  <UnstructuredGrid>
+    <Piece NumberOfPoints="1111"                 NumberOfCells="1000"                >
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+      </CellData>
+      <Points>
+        <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="5"                    RangeMax="7.8102496759"         offset="57784"               />
+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="61336"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="67768"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="69616"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
+  <AppendedData encoding="base64">
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AQAAAACAAABAHwAAWRwAAA==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AQAAAACAAABAHwAARhgAAA==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AQAAAACAAABAHwAA+hcAAA==eJxFWWVYFF0bthU7MbDFxkTFvu1GMbARE7sLG7Ebu7A7EOwECQlRxMCZM7ssbMHuwu4CBor5PWec98M/XIvszJkn7prglRuejQkKh+ufdTFbCkfg3My7GUvvR6BDoZwn6yMi8XDqBqnbqhe4cyrrSszgWPRfklfO8vAVZpa7V6j36HcoEn95os5LwMAtt7fULa5BnwVbnbLzIqBxLrbxcO8oHGvVKrx752j4VH7VImhrHKbOLHlKZAm4UPBZ0YqVPyBRNb/qiUwGteOMDnHOWry1NdzzrrMRMy4NbGrONcFhZ51p9vExWLTWdrxhwXg8Q8qN0Y3eIt2cs+bknyT4zF23/+0RNf70/mHLDNfhza85Zcu/TsP6Wh1n9pltQd1JYitWxorg42vvJuyxoc2D8sazm99hV40hUdkVRHxVixuX9kvBGp+BfifGGxAwt3d0xw0mLKBTtXufAVuZsNbHm9mwv0+rC2MX2FEvYWy7U6fssM7e9rzRXDtKZS2pkLpDizfXEz+OthqROmzP0QUVLTh8ZtTPZV2tkMvS0A7H9se26hpkwfTzWs579yxgzITbz612HK848EvbnXb4R+teB6fbsDMh9v65qRlIHlzjwvJRNuwofcO3wWc7KvXRFK97PwuW3lWTHr7Owslub0uWHpeFww8bBDo+s2NX1HHvhIJ2FO6O3eVr25DTtECM6ywrTAaVR5s3WRBGW1s9bZyNbi5JJ9JrZaPMqJjniY+y0Pe0s5drnh3PjgSUW93BDifWLEK/yIag8ICPQaeteLKJHe9lykTKinOPhzbIxIPNa9/eHZeNp4/2FMt2zIal+QBXR3oe1/l/4wcdtCMieidV1gY6fPueSVZQ83p1N2eictEffU47Z0Iu17gMlOrXcHmhExYckuoe3B2Yhd762oPrPLHDze1yY5ccG4rOjjlvsVqR+l3lOriQFfcvr4pt2jkTy5yP/g1Yn4HdM9++RYQFRQJUL17+NqPI0i/fQ93NaOKS43enqR226YsOPetsw5rt/VaW72LFF639pmZFJmLF0+Mqns1QzmeBKebL5oa1LRiU5eS9xseMmY03XTB+NCHG0b/modYmzIhs9fXzZSvmdzqqv34nE32znx+2sgxcm+N/9WeBDNgzwzs1GGSBtap16/xdZnRsu+9XRLgJ5twDMbNqmWCZ/PtM1Np0fKnxtM9XIQ0PPv9O8rVkKP3IQMKBAu3vz7NggFP/m9FXzEitwRtggpqeqmxfE1yauw/q+TAdfb8K4aMd0hF2sc34/p5paNPL997iF0Zk01a67bBgf+OB4pAws3IuMw65P458OtGEpq/Kxz55lA6+1VV+pin9SsN28WupFVFGtPmQG3yznRErdmQEbQwyIKhVRdWSlmb02er5bP8qE3YU51dKx2J5sNIxotw7c9mpachd/S12zUcjhr7bP/FPb7pOZrTH0HsGdBlpfhbT0oCRq7pEzo7Qw9+UEtUwNh1rVLrglzXS0T6rY9/+S9JQ8ezlI0FfjdjdokinJlOMODjGVC0g1IA0W4krRVsZ8L79wYUPHuvhfu4zVU6PySFOD1rE60DDmT5maRo2LWg1e7dgVPprxNewnPszjxhg6FAjfEJdAzqV4nfUo/20d8tWtNWjw43utHE6nGthGjHRU4ctfIy/auGR2vbKq6lGLK7rXOpYuEG5ngEFlnHk0uP73Dv9utH9A690Nvo80uG3vyZk/nAdFiwYMmysXoupLboXDfel6/yqtlSsqMUnQiVrfwPUycdOh7zQo/mc1mWi+uuV59HBjR+vpw57+n6QXmq1MPDH8dOCo9jSploMD20f4umfinX8eI9TsCG3Qd/pY/Uo1Hybo/RGB7rYi0MDdGj7Mm4c+6DFoYtzG6XO08I//vu36lW18AmtFr9jRSo4alU7nAL5WJ80ODV4sae0UoMry0L+JE7RgX/qm63FkN/Prg3YokWXX+3HXaitRYWC2zwu+aRi5kmnD5WOpODn/vptb+o1QOflaXe7auDeYkLmrs3JqCkDbTL+mlp7T6Lzl19exy+pkVbB2VSMGtP91Wct3T+GL1wKtnazZYvTNQpOJOP2TjfaFDUmLkluWuumGg/OTQ187qBGyJJZ+21rUxW+SEHU1yYT90VqwFknuLAG2rCyga7nk/HhzO8BFaono6hm0vtqQWosP1ityOiyarw9uXNUtQkqGNsUPpyTJSF9P6r52jUouaVEx83NNLgjPiUGSVbmIhmmAhE1u61XY9+lcl4eqSrUvO14ptBkFVot4Aylgs/ZtsSMEm4U4QgrYXhlc6VVB5IxZ4403ts5GaObV1p/7YwalhMv3dTJKpz6wgdRhUkt9V3aZEowb6sQeWGPhNIHr/kPHyihEof7NIZ9i8Znnw9mKHtuUELtWWrgWq7F97UK9kNlhb+dVKAlJ8iXkHHnGFs7UVJwXcKxIVV2D8pgGCY3jMGZ0N/cnMHxYvVdl++KaBaTd9JjuwpTqyycXjtPQqq2FN1Zgmpf5f1TqkhY4hE5RP2cQYaFPQwuZWeub1+coVufC122nxLRZMplm/c4EUNXc+QVERCa8jtnkoRqDhwBGYr8nfByL30vflTE1YtDGQrcmh7bry5D5wOvNgx4LkKGeS8RA5/4fEroICJoyPdL61MEBMs6Q8B8GWAYpg5yfveqCcPIW9ktq+aIqHPqyadxp0W0lR9cxMLTGQEndQJmX3tWS3dPQPW/3Q2RGwWUfJ6UeHKnAK/50X/urBFAy1eszG8RnDX87ogov5pvuojd5wJnjakn4vQkjoACrrXmxC+guDevoIAn3xa9XHxFgCextA/9PvjQjO3TSMdkFGlXoUNXES1kghdx7MeqkftLisq+0XVSOEALkOXPQ/peQ+Om0wkC/ANcJheiz/ZeS0/1Gy/AR/4noOHre7+bNxex+OYu9awCIsIq3Z1UOk1Q+F7Axu4cuQXo+nr3PHFbgCx7DgioYvjl3qSPABqG10erCnC23/5yrpSg6DQR9+fxQgoIqtq707tbAhyc+JMKcHTnDCaAb9ue1QK6yIJEwIFlCcaT8wUQiVKnBMjHchfQqLZHh7SS+X1ylxdZwARibemmoOCIoPCboPRfQGXEJN/fLMC73+3k93ME1L/cp2Io1fXVub5EcQK+bz9GykYAgfmPku8FXHhd7Ph0o4AWDh4jXwkCuLpcwARk6Q4YhloE3DsYMfxThoCf5qTDiZ8ELPnTqHJ9LT2v/E/EoNIcAUVlD0RE72uzsgX111MWRiK26RrQSInYs5oDuAjd6sq3+tP8eKbspU0TFN4WUGLlTNuDUiKm1Ni6b3tTEWtCfxpC54gK7ongKnMOff6nc0Q8Ue38PeObgLflGmzu7yRCu7lXkZq9RJBo8jlJnwOGeuW5JIpo/34EMZ6Ig5zOg0RFp4gK/4vwoelK7iciO2/K5uxZIuLeb2t5daGIVcHjj2cPpnN7nV89d7IIWV6WZpBlWLqIkMKm3U1sIrpUr9kw+A09Z96nQtYLIi4N7VFpShQ9P4dx2rtXjyuPObyO9mhW0a03F4igYZrVuYsIma5nMhwnFHFqxiB5rxhW25GhVt1jF2KzRJzZG1t6VIyI+KheQbNTSA8HcgATMUIWACJmGF1oE6juiaHbBu8VFb5iGN9sYf+OLRgaxZ56H/FDxMMNXLEztPxb73fucgaOftEeDJUaf+tSuSjDo7HDN82uxvCy66fihalefWUjIeLdmAAflxMM3eUBYigsC36m6CGGim0aHjDPYOg4aNKpaT0Ycu9FeR9sz1BG2yLg7HcRVaU330YaREV/iHi8iBN5/vfXcjreyRDyssbX8oRbbouXPO89nOH+joM/a9Hv//E3U/iGYQcf27YMLWib7VT/I4mfuj7qImHa0au0+QyVbc0u/rrIlPlkIJL07SEx8KlKoOe+5MORgfB4jvvnvSPpupuGtF1C9a6dt2mjierLVUPBGRLmpCzeudfIlP1ioOJQCdg/W3CaKfjCwKs9eS/DjQndGocuZDh/z+175HQGGqbCvqWYogclnHjAGyBBhod6EsQf9UnqMORx+ZzE8IOPnSG/P0lJd+6HDWCQ7doUhpItRydNrsEw4YFQ1WG+pOguCfJ4/qbff3hmqFxLQvKsAgs3FpHgJDeA4TNN48gxVAf3qeXHdmLYO3bXsIKtGXIq8MaJim6SwNVv+GhJ8VESisoLLCk6h0GW3wMZiLRdW9ak/u2MC9npRvWYHJcxmuZlbvPco5qDIj4WGf6t4AAJCcHpxNwSojZy4JUwOKRjYN5HpuhaBuO3Dr+lfTSH3FbQOY9/ndqksUqEX9nPaUWZiKnnhHZZHYlnKm4Kjz9Hzytc3TZrmYTT3Oa6SfiYyIWEhGw6TYmXDK22LjnvtYX2MvvLoHE0J2O5XKV+cvTtFU98IRtkEVwdPQiUkNnJss4wV0JtVw+iLgkzuB2JZf+fowbqvPVznjHFdzLF1zJsyRz+qPYWEQMcW2+csJL2RCYI4n9eZrrO83Xc2EqYVy+up4OrBK5C7pGe2DGJAzFD+zVnq1S7w8BdVis654H9d0Ou1GKQx/4s4drjNt2m7JBAxapZ95gE2eaOkNBuy5u51op0/ROFyUrRfMxoczvvEUMmsXCxtQxFednnM+xW8wFgWNXgc1wdwqkCnYmeJtN+UHU9qS+dg28PHrVQwsPVXEGQPpGJns7VlCs1huVcfobR9R++tpC0gZ3b/eukh/b0eHbLm6GdbDgl2LkN+EH357aFvv/EpVGHOiJDj9b996Wq2f/nr4UvRxCGDXIDCW9KVlhUwpNhUPHMvzVpf7naz/WS8LrJkQnjy0goIRsjBlkGUZ2ib3ICZfB72MNfT/3xrDahxBKPfDxwItSwk775Sl3vKIjI9arwa2FDCfs68EmXFD6RsPqSS++amfl1v/6w2INBIaSLxnKFzPAmlRMHQ9yxp+S0Cb+4rY8T/7+vmz/4V11XlM7pNTiueDcJQ49Gv0infZVtwS3aiySHWfXnMcyVjT1Dm7V9huxwZrjQ4PGvbV+Ix3jbn4jwX9rvUG4xSdEvkuKbGEbJhMQUHUXnvJ5k3TiaYcrijp9v0N7+y1cYepvakxUUYZ7DF07El2GLbp+n6zmQem6/hvZyvt64fhtDX3kRaG//+BJEMNwqwxULA0evri6EK3LAQ7h12IEUmwj3zWWGBR+i680bve7WA6boMYaucjBA+C43ksE12S+xXAMG+c8J9+U1I31n5WuRmf9Thv1LhPvkPtYtY1DzGKldfv/+q5NsL/6KKF281x0/B4bipEJcrKTDiM260PcZh4sHImJbcucl/l+fyjEA1WXmo4Jn6vQjfpKNClP8LoMsF6iPu6vwYEdEwdx315qfEVHj6u4NZxaLaLz9SbkepCP++7ttOxcTYzCkleQJiAg9lyvvRHD3sfCDiH5vIk+vID7b1dZp+gHi3Zmknt0ui6hPaK0NJNyavLf284ciDtziBkuEbNtui4rPFFGLX4bu7yzoRxbYTdfnsor0xOxaniTpRIjhox0ciccfes269WGACJ6SjPEVEV5kgSZhJP1/xU89E0n/lKQp811N+lLLBWn+ff75MhHDVU5rp7QVMYlfhnRLcZryjnS+f/tPeM/tCP38NQILm40gXanhwZGo5Cn0HAM4gom4F7ci7EyN//CNdNNCjkwiJt68GtGutKjkgqQTB/MTiDjf5G3jT6TvDp/gwZeo8JmADxE/SBMJIJO653UDEZH8I+nHMjvWuKwzC5DXnPRnjOss8xnSk3d7NqreifTfXLkQAuLnBQzs90ZAzV78ygIXl/Nrkg7fdr7HmbiD+f5DhukHgrKP+Xp41eseM379zNfz//aNfAm3EaH5P+W1OS+A3y3ytKDkX4LCxwJSCnHhQ75G50XOkXQNj0PpeebKAZQAPzkQFdCZ00qigPNHh7s8pHO58nG5m6+/nTe0zk4mXySP/VIBaz+FeMw9ka9n/6s/T0XVpKdvu3LgF9Cx/IGiQ6g+58JmEPSQD7LyAI3u67+LJlyA6qW2ySo65788QMQVHscdEHG9+Zm0VYtEGEPn0ElFlHHTfo4qIaLrt9otO9kFJWcUMFV9nhyAgKrkrrtuEjBvAk/+BBAYEYGT7pOJn8HCY13az395p6jkCyK2PAgcvNiT5rcJ76CIO08+Ln1PdefquEwY9YHHTdSPfzmdpORrktI/pvgdhq2F640LL0I8XKpn2UHH6PlfFI6/PDG/LjJNVRMxrztHNAFyzDZepTw38eUAnvRIcExJqx9WSUKrduLsi5eY4h8Z9gRu4UkHTi7ZsvLxdtrrEpwpRKzk8WkLUdFp+X7/v7ygvizwJJxZwRMnCTKskc9vGbT1RbcjDE0n7ov82iRfP3M1nEt7ylXRti3JSk6iRiq59ftt1cq8qBR9ocLyvQWlTI0E2a6Tn18xr4h+Oem66bJBJH0nAzfxdalj4UFPNQhdyAlBo+T7yciZxplJjZP7eECuVuZDpeChSsn1JZCpJ6IlPcHL8okpfjxV8Z0piJ1WrJkhVYN3fI2aaUCmg4RwMqYvv2G6+E0NOY72UaPZtUpv+zAVvlGVesxQgacHQ75LuFK/CkGJVsnZtQp+pSLtbX1SVCm49bVvrwlvNIp+06Aml5V+yQhMzvKobFZjpbDg6duJahzlt/+pwu7vQ1+vbqNDwy78jYcWMi1O1mLe4cnEjKmoW5pPcqqyVykYVYAnzxrsyHpBykED7ppHXUzGSC4zKiTjYC2njb5eeix6s/19ilaHH9yujdQp99Pi+WQ3Gn0teAo7s7EWnb0cK53clwo+LVkvUrCettvFIQURu8L8203TYA+xia6HAb8MfMH0yhzrFdzX4V/wq4OvvRsxlFbZAy1C9nFjqsUgOXhMVfKbFJT9/qt1L18jePf9NQYEe3PAMuCsWxWiZD3uJuyxOAzWY/jZYcaB73XoIQf6Osgy1qBFtgcPwLTot7axT2g1Lchkk9NOU/YyDTktq+acOmZEgWvuVHID7jr3cG8xwYDETU/vrlDrlVxaj5OeZ24EMR3qPH9oSVyvg2yfaujwYu0qotJ0EMl4tm6WDtTaV/3q7jTINvKHUeFVI2QbpjJgpRzQGlDwYgeSuHrI8r6/HrJcfqWDgVhhQ2szrv0sQH9hUnLmdMhxd8V0bP/CXwClQZYHyUYFh404z2OMJAPkOMvVgK4yYejxexv/ggUjBp7yaxRpRmwFrjTM2LT1j0PL0SYUXld/2IFb6Ygfdn1d59rpIBNHSjgNaz/Gb/bOMCJMSo/5stmIVfJCGtC+eIl0c06G4mcy8JPHTdMsCC3AkxAz7nUtZ3+jMiGBxycuJiX/Slfy8zRcqrxszcBpacp7HiMGDuYJuhVym+9l4vLHgEex7zMwLfC5w5YSGdi8kQfyFuznsn69GXXfL/Qu/saEvFD3DbkNTJDl65J0FJaD0jTl/ZcdIfx43WzIG3h/WOw0KzoJ0fPb+WUq+J6h8KcF6biYGlbWgr7c5s024yNfpziTkg+bcNifB/dZoGV6ZHxkV/S8Dd+Cb7ZrWtSm5KpWJYfNVHgiAyQu6NYW3IwPa+7/1wzZpnYyY2OjyK1XxmSjyfrdj+c6ZEOOKbpkYYfz6urRS+yQ49YjNhxKcQvLfW3Fi/FrS/rlZOJPkq+lUZtMpH2qQxXIQF05CLLgcklOzNkgk0sONRtH6u1dvtgpG9XW8TdSWYrPtCO64wayGnbUj2qWEtfVptTDCm1ghUuhEZkY0fjsjhBdBtqUuFlz/PQMXLvIAxsbuNs5UTcLHGVXXc/CoswFpzMCspT8PQtd5cDZjnKl+BsvG+TXW2VtiOB/3tsKnupu2qhF17Pz4qukGCHHPV/NSt5qRQdZYNqhyeAG1K7oITu+veYvmuyKv7BjJ2/zeRv6Th8b7XT8HZb+M1iQ19YjBXw7vVcY8N7AjbRJyd0y0agg75ANZv8fRzp52SHL23t2HOe2ZrVdeZ8TA2eZCOIVP/ZWyT8/Kj5Freg4vTwtga7paNInvN6oaxaskwHICvl13gYbVHxdGkbCbdjyuIRFUQp+RivvT+JQmNTE1j8JmCMHTR9gWtirXqGyEojcZ/8co4WLDLRGRLFeAZsq0tyEDZj16nE4uEp1dYxQcoEILJvEnXkkZJvu90Lpfyw+8Jju+Cvl/fc7NJUXQkBS8xnV9WM1+B+AFBcHAQAAAACAAABAHwAAZQsAAA==eJxdmXl4zVcax2OJGtRQqSrGOiNJRa1V0yb1IyqxjJEYYcbuQRWDREQWQ2TPb7vZJJaqNCpNTcQWM5YMRWx5QiLSxlYVtLW2lommlpib3/u5cx/uP9/nPed9v+9yzr33nPf4V0e6FTwMVqLcCvyqh4YoLvWfKyFK//pP2RIl/nbAnk4jlipVmxb7NNu4TAnc0yn+9rNIZU79J22l8rl9uGppjOJfz/O7eOH5YIngzFClftjv1TDlVKn9UxiuBNvVN2UvV+ph8c/RyiOPybbDJ2OVdWvtn0kJ4l9JUjrXOw5KFj8PwsR/WYT48Vsh4y1iFNvhGo/JT+KEd2ai+H2QJHxVyRL/EFX8TVGFv1W0xPP7WOF9JUHs/JOEpyBZeCeo4idPlXqcRM5XFbt2pJupin6zRKW+LAFdkkXP7sfiv6cqnvb0atprot9PE9lDE/06Vfz+BN9pVer5vSp1maRJHCvBVE25Y08n3o5W3MHw+CN316Rut1QZL4WvkS52bXSJtwnyTU3qsl8TvUR4Zmuyzn01qaOrplhhV6gyv0qXeGfC4w7vU/xXgtnYTSXudzWpnxt+7xKnrku9JupiNwi5IX6KiSsL3oWa1G00PB005Yi9PLZH1LEAnhW62A3RRb8F8V5D/ytN9kOOptRPRy7WxG8Q/D1Ytxu6rOsuXeJVddmHs3Wl3r2Pty5xuBJ3qSbzO8AoeIdpsq6NDMHzuvjfA08c8hji9yD+RtThmCZ1jnHW1eLpaYjer7rsk0O65PMJcS7RZd/1gde+Ttb34qImfg8gpyOHGbJOww3Jq7khcX1DPGt1vvf488VPa/K/xD4vYv9ohtRzOjzvGRJfO0PW4Qp8X+iSV4hzH1jya9TlDuux3ZA6RBPfEEPiaE4dbusSfyF1S9Mlv/nsU3/i9mT+MTy7DIlbNSSfvxLfAEPyeKLL79lxXb4f6fAEwzOQeR9T7H81xO9eQ/bdx4bso3cMya8tcd9nfx0hzwTi/Av7KsCUdelosg7Eu5Y6zDIkniHUty14jv2aD5+jDotMiXeAKevS1JT6f2eIn3x4F7JOH1CHZsRbRVzHyfefpuSjm1L36fD1Iu5b7PejhqxnGPX1pa72esj33ZB4H5jCn0Wcs0ypn6cp9u0Z/4H1KsE+G/uZ8A6mLs+JZyu8iabYzTElfndT6v+zIXpnWK+D5H+YuhRQ91dsUp86eM+aohdqShz+1LUL8TZk3WpZ/yPUYy917meTffvQFPkE+e5FDiW+pfiLgH86vH1Myfc+eQfbJJ63bBKPvZ7Wup0kvsPIB1mfOPimMj8SeSy8S22CH9pknQfa+P7YpL69kRvgrxT+b+EpMmXfHWV/nLYJHrBJ/IXwf4Z9KOjP/DAbv7M2qcMom+yf95E7p4h+qxTRfwrffeb3w7Od8a2Mn0X+Hvk4eiNTXkQlhX2Kn4FOdOhZ9n7gH5z6Vp6R6Iehv5z5VYzryBqY7pQt/SR4TPQv4edr5FL0fmL82kvzF7CvQK8SuRwclEq84OBUsX8/Vezt81IHMBCciN44cDz2GvM6mMR4KnyZqeI3h/kCsBAsRu8Ydq+myXiTNM4PaeLvTfCNNNF3Q68Fch18HZ3zFs5FLww5A95s5J3I29GLS5M4NjCej9+tzPdIl3n3dBnvjdwmHb/pYtcS7PKSfmf0uqVTL+bjwUTGY9CPQj+B+fSX5HjkBWCPDH5fM4SnaYbEYUeLrwHzLTL43uDnW7AK3mowC/sQ9CeAM+CLAIPRC0SeDwYQx2Lki9j/iH6T1Zyf0XvA/F30q5GPo38CvVzmp2E/d7XMT1zNfl0t892ZH8b8cMYnMO6FfkvkG6vF3xn085gvZ76E8XWMh8IXhTwVeQTYOVPsTsC7F55Spx/L7jrj3yCfwP4IsoqcmEm94R2GPDhT4uqRyT5l/hG8lfgrAzczbmKXBM9H2M3NZJ3he43xCmcdrPEK4vrSkQ88u9AvBPPwEwaOAf3x44vcFnwMXw1yMbxbwU2Mp8EfDi5n3Au5H3iJeF2yxP4Xxg+QXy5x/AP7mWAM8x7IrbBzAy8Tz0nwJvqOvHc647T4xzM+Fv3X0W+C/Bz9C+gVYbcRWUdvPXZx4ETn+ltY69jPzN/C/mrmi+OnnfW0cCU4H5wBtgYPEc9+sAxMxm8merH4mYoc4Nxf8v1Av4g41oEq4451HM24gp93GO8DTwf8nON7uR29ldgNB4c683GsryW7ot8duYb9/B/2izf6gfgZiNwN+RZ1rsXuovN7buFueHKY7+WM2xp/C7kBvPfQ+xr7HeT1OXI8/hy/M0cZr3Lkz3wScgLzq5AXIwcgDyK+PtiNhtcVva5O+YXfy6bMu8LjgnyT3+ly/mdKkI+B+xivRM7j9/0244VgPlgApqC3gd/9KOT1YCx6C+ANBefyfzEUvVGgL+PtsXNBboj8mP/hZvh7xv/rDfA0WIneZf4/NyDngOv4H01FPxMs4HwQjrwceQEYDXaE93V4esHrOD94gW7odUDPcS5x2L2LnxjOM1mcb3KQt4G7OBetQY7nPLQZPM856F/YO85fDuyInieyN/peoD+8fwL90BuIfJTzYpHznGjNfwrmM34JuYTz6CnwEHic8+SH6A8H/cEgcCo8I/E7B/tFzC9gfh58zzlnP+Dc/ZBz9VPO8c+csmXvgl0j+Oqwr2M+F8zD7lN41qOXzXgu/nYjb0H+Ajkf/THIw5HfA73h9cVuBOMjGR/H+J+Jxx9sCTZE77egK37quL/d4V51DfyO+1Y19ywX+Lch54OfYK+D4WA08xPBsdwD/8j9cAD8u7lfhuB3nE3u2z7cs/tyP67lfnqH+3WNKX2OWu7tl7kPp8AXZJP7d2fuu8/oI1RyTy+mD5CG3RxwMn4CkUcTV0+b9DE62eS+f5T7fRbxRHC//xt2b3N/bsl9uoY+QlfyKaa/oRFXGvf3cfSjeprSH2kM3jOk/1FGH2U7eJU4DtHXcfQffEzx19yUOt5F/yt4NtA/+Zj+zijj/3k5+i5W3aZg72lK/+AJPOXof0YfZx59w2H0yzzoQ2XQHwnA3p31umJIPffRp4qgPgH04foTVxvifUjfcRF59oOnDr2T8KQS12z4BiO/SX/oMv3Gw/DNoK/kybrfoi9zln7PFvpVC8lrEH0hV/yeoZ+YS9+uHevxEP//pg4LyPcDxn9DnjfpS+6n/2fnsfQX0k91cfSZ6GtFE98k8u1PPM/pmxfT312vi59FoB995iLijoVvHv3jt1nHp/Q1z6G/hniC6Mf7EG8b+qBZ9C9D4XX0Sxs7+nPEs5H45lEnb2Q3+tTn6fPPpW/Xi3VvQN0qWK8v4YvAbgKyO33oH+g77+Mdwpd1d6Nu1fRBt5FnOHEEsi86kecvvNdcpc+erUm+T/BTjt1O+vXRzvcAi78r8lN4Kuj/b9JkfhHvArXsnyIwhnwm6fz/0weu4Z2jhPxyeaeIBAN5d9rNeseSxxTy8uDdog79Y+Aa4omi/z8eP17IUaz3DLA/+bVmX9zg/eAA70Uq71G+vH90gr9GpY9MPm1Yz7vUp5z1z6NONt45pmHvi15T5Guq6Luxn1qyHvewO0hcYcTlz7g770hteZ9qzD4p433wsSr8wcSTQ52SyOsj4hsBbzve437k3fKgKuu6jvcyr0RZh97Jsm6TVYnDlf3Ul3p3Yz80JK7rvH+W8D6ZTb5domU/94kV++YJMj89SeT7vGsa+DlFHMdU7n2q8Gc43leXybx3pOS3e4XE0TZG9ku7eKnHjkTeLcijGXmOVXlX4f1y2hKpT3wofZowWYf/hvPet1zqfD1a5Auxkk9cgtiPT5J4gpJFr0WIyLNCxM8bS/hfDJV4/r6Uc/AyqU9dpMS7eaXkuSVGeEfFK/8DHO+/fg==AQAAAACAAABAHwAAHAAAAA==eJztwQEBAAAAgJD+r+4ICgAAAAAAAAAYH0AAAQ==AQAAAACAAABAHwAAHAAAAA==eJztwQEBAAAAgJD+r+4ICgAAAAAAAAAYH0AAAQ==AQAAAACAAAAUNAAAVgoAAA==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AQAAAACAAABAHwAAWAUAAA==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eJzj5BwFo2AUDHcAAMOYIyk=
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/Grid_300000.pvtu ADDED Viewed

	@@ -0,0 +1,27 @@

+<?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"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/grid/final-grid.dat ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/log.sparta ADDED Viewed

	@@ -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 0.4
+variable   Ma equal 6.9
+variable    To equal 273.0
+variable    Tb equal 273.0
+variable    theta equal 0.0
+variable    mfp equal ${Kn}*${L}
+variable    mfp equal 0.4*${L}
+variable    mfp equal 0.4*1
+variable    cpmfp equal 4
+variable    nden equal 1.0/sqrt(2.0)/${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}*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.4/${cpmfp}*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.4/4*${Kn})
+variable    nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.4/4*0.4)
+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 6.9*${sos}
+variable    vo equal 6.9*307.815564238681
+variable    vx equal ${vo}*cos(${theta}*2*PI/360)
+variable    vx equal 2123.9273932469*cos(${theta}*2*PI/360)
+variable    vx equal 2123.9273932469*cos(0*2*PI/360)
+variable    vy equal ${vo}*sin(${theta}*2*PI/360)
+variable    vy equal 2123.9273932469*sin(${theta}*2*PI/360)
+variable    vy equal 2123.9273932469*sin(0*2*PI/360)
+variable    ppc equal 30
+variable    xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
+variable    xncells equal (6-${xmin})/${mfp}*${cpmfp}
+variable    xncells equal (6--5)/${mfp}*${cpmfp}
+variable    xncells equal (6--5)/0.4*${cpmfp}
+variable    xncells equal (6--5)/0.4*4
+variable    yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
+variable    yncells equal (5-${ymin})/${mfp}*${cpmfp}
+variable    yncells equal (5--5)/${mfp}*${cpmfp}
+variable    yncells equal (5--5)/0.4*${cpmfp}
+variable    yncells equal (5--5)/0.4*4
+variable    Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(6--5)*(5--5)/30/110/${yncells}
+variable    Fnum equal 3.23595913252916e+19*(6--5)*(5--5)/30/110/100
+variable    tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
+variable    tstep equal (--5+${xmax})/${vx}/${xncells}/10/4
+variable    tstep equal (--5+6)/${vx}/${xncells}/10/4
+variable    tstep equal (--5+6)/2123.9273932469/${xncells}/10/4
+variable    tstep equal (--5+6)/2123.9273932469/110/10/4
+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 3.23595913252916e+19
+global    fnum ${Fnum}
+global    fnum 1.07865304417639e+16
+timestep    ${tstep}
+timestep    1.17706471885472e-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    110 ${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    110 100 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
+Created 48572 child grid cells
+  CPU time = 0.294282 secs
+  create/ghost percent = 0.396658 99.6033
+balance_grid  rcb cell
+Balance grid migrated 48478 cells
+  CPU time = 0.0804596 secs
+  reassign/sort/migrate/ghost percent = 67.6998 0.0395727 9.24489 23.0157
+species   gas.species Ar
+mixture   air Ar frac 1.0
+mixture   air Ar vstream ${vx} ${vy} 0.0 temp ${To}
+mixture   air Ar vstream 2123.9273932469 ${vy} 0.0 temp ${To}
+mixture   air Ar vstream 2123.9273932469 0 0.0 temp ${To}
+mixture   air Ar vstream 2123.9273932469 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
+  324 0 = cells overlapping surfs, overlap cells with unmarked corner pts
+  43392 4856 324 = cells outside/inside/overlapping surfs
+  324 = surf cells with 1,2,etc splits
+  109.215 109.215 = cell-wise and global flow volume
+  CPU time = 0.0904281 secs
+  read/check/sort/surf2grid/ghost/inout/particle percent = 21.3748 29.1439 3.12632 26.3449 20.0101 6.98358 0.182785
+  surf2grid time = 0.0238232 secs
+  map/comm1/comm2/comm3/comm4/split percent = 14.6708 24.5709 3.8663 1.76646 12.3707 6.97854
+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 1125 cells
+  CPU time = 0.0281955 secs
+  reassign/sort/migrate/ghost percent = 8.96573 0.0946959 32.254 58.6855
+create_particles air n 0
+Created 327644 particles
+  CPU time = 0.0126899 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) = 1.59521 0 1.6875
+  grid      (ave,min,max) = 2.75891 1.51379 4.32629
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 4.37473 3.22189 6.03439
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave
+       0            0   327644        0        0        0            0            0
+   10000    9.7171877   367175     3511     3104       13    349003.68      15.7172
+   20000    19.415358   367428     3550     3162       17    358324.17     15.90385
+   30000    29.685823   367658     3587     3196       16    361450.41    15.961867
+   40000    40.166395   367983     3627     3206       13    363082.53    16.002675
+   50000    49.829175   368227     3578     3183       25    364056.65     16.01014
+   60000    59.805893   367071     3505     3091       11    364666.38    16.021917
+   70000    70.884416   367465     3552     3147       23    365115.17    16.011686
+   80000    80.419341   368247     3558     3164       17    365448.92    16.022662
+   90000    90.736007   367792     3502     3106       17    365760.67    16.027989
+  100000    100.49242   367633     3544     3142       16     365956.1     16.02885
+  110000    110.07655   367859     3495     3084       11    366168.06    16.038936
+  120000    119.93364   368423     3603     3214       13    366319.34      16.0399
+  130000    131.10337   367875     3522     3140       12    366437.08    16.038362
+  140000    140.67915   367457     3503     3108        7    366526.13     16.04105
+  150000    150.98568   368503     3537     3178       11    366605.92    16.042067
+  160000     161.4997   367668     3567     3178        8    366707.24    16.045869
+  170000     170.9638   367785     3524     3139       14    366783.13    16.049912
+  180000    181.39174   368054     3545     3163       18    366838.07    16.053156
+  190000    191.44251   366994     3607     3192       18    366892.32    16.050926
+  200000    200.90596   367736     3501     3083       19    366936.33    16.046865
+Loop time of 200.906 on 128 procs for 200000 steps with 367736 particles
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.022907   | 8.8217     | 56.962     | 384.5 |  4.39
+Coll    | 0.25129    | 6.3282     | 49.859     | 325.9 |  3.15
+Sort    | 0.086723   | 1.4495     | 9.7706     | 159.2 |  0.72
+Comm    | 50.878     | 84.528     | 95.451     |  97.3 | 42.07
+Modify  | 0.019864   | 0.10189    | 2.073      |  92.9 |  0.05
+Output  | 0.008796   | 0.011736   | 0.013269   |   0.6 |  0.01
+Other   |            | 99.67      |            |       | 49.61
+Particle moves    = 73387266327 (73.4B)
+Cells touched     = 76622239940 (76.6B)
+Particle comms    = 174418269 (174M)
+Boundary collides = 0 (0K)
+Boundary exits    = 16436852 (16.4M)
+SurfColl checks   = 231074712 (231M)
+SurfColl occurs   = 3209373 (3.21M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 845988413 (846M)
+Collide occurs    = 669327074 (669M)
+Reactions         = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+Particle-moves/CPUsec/proc: 2.85376e+06
+Particle-moves/step: 366936
+Cell-touches/particle/step: 1.04408
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00237668
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.000223974
+Surface-checks/particle/step: 0.0031487
+Surface-collisions/particle/step: 4.3732e-05
+Surf-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0115277
+Collisions/particle/step: 0.00912048
+Reactions/particle/step: 0
+Particles: 2872.94 ave 19703 max 0 min
+Histogram: 84 16 4 12 2 4 2 2 0 2
+Cells:      379.469 ave 380 max 379 min
+Histogram: 68 0 0 0 0 0 0 0 0 60
+GhostCell: 9951.02 ave 18101 max 568 min
+Histogram: 18 12 12 10 14 6 6 4 14 32
+EmptyCell: 219.359 ave 405 max 0 min
+Histogram: 2 7 9 15 23 20 17 18 10 7
+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) = 1.63477 0 3.375
+  grid      (ave,min,max) = 2.75891 1.51379 4.32629
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 4.54192 3.34929 6.16229
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave
+  200000            0   367736     3501     3083        0            0            0
+  210000     20.84445   367845     3537     3160       18    367746.26      16.1035
+  220000    38.656969   367636     3566     3159       18    367833.54     16.10585
+  230000    57.719796   368135     3570     3149       14    367863.73      16.1092
+  240000    76.497788   367609     3618     3219       10    367932.01    16.091925
+  250000    94.527537   367801     3515     3145       18    367889.02      16.1091
+  260000    113.44546   367198     3651     3254       14    367873.98     16.09445
+  270000    131.36664   368726     3618     3258       20    367860.47    16.090929
+  280000     149.8793   367836     3521     3108        9    367879.64    16.077288
+  290000    169.03378   367637     3592     3218       14    367845.08    16.074011
+  300000     187.3619   367147     3591     3186        9     367861.1     16.07365
+Loop time of 187.362 on 128 procs for 100000 steps with 367147 particles
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.011573   | 4.4473     | 28.831     | 272.2 |  2.37
+Coll    | 0.12413    | 3.186      | 25.579     | 232.7 |  1.70
+Sort    | 0.04605    | 0.73369    | 4.9381     | 112.3 |  0.39
+Comm    | 33.288     | 50.007     | 55.914     |  63.4 | 26.69
+Modify  | 1.7501     | 12.335     | 74.662     | 420.5 |  6.58
+Output  | 0.034114   | 0.036934   | 0.042162   |   1.0 |  0.02
+Other   |            | 116.6      |            |       | 62.24
+Particle moves    = 36786109616 (36.8B)
+Cells touched     = 38406588625 (38.4B)
+Particle comms    = 87362486 (87.4M)
+Boundary collides = 0 (0K)
+Boundary exits    = 8237386 (8.24M)
+SurfColl checks   = 115715937 (116M)
+SurfColl occurs   = 1607365 (1.61M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 426063210 (426M)
+Collide occurs    = 337078535 (337M)
+Reactions         = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+Particle-moves/CPUsec/proc: 1.53388e+06
+Particle-moves/step: 367861
+Cell-touches/particle/step: 1.04405
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00237488
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.000223927
+Surface-checks/particle/step: 0.00314564
+Surface-collisions/particle/step: 4.36949e-05
+Surf-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0115822
+Collisions/particle/step: 0.0091632
+Reactions/particle/step: 0
+Particles: 2868.34 ave 19845 max 0 min
+Histogram: 84 16 4 12 2 4 2 2 0 2
+Cells:      379.469 ave 380 max 379 min
+Histogram: 68 0 0 0 0 0 0 0 0 60
+GhostCell: 9951.02 ave 18101 max 568 min
+Histogram: 18 12 12 10 14 6 6 4 14 32
+EmptyCell: 219.359 ave 405 max 0 min
+Histogram: 2 7 9 15 23 20 17 18 10 7
+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 = 48572
+  CPU time = 0.00728568 secs
+write_surf    surf/geom.surf
+  surf elements = 200
+  CPU time = 0.0016793 secs

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/mir.txt ADDED Viewed

	@@ -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/Kn0p40/simulation0900_Kn0p40Ma6p9/output/grid.300000.dat ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/output/lambdakn.300000.dat ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/output/surf.300000.dat ADDED Viewed

	@@ -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      0.00137     0.040426    -0.040421   0.00063499   1.9606e-05     0.001248   -0.0006346   2.9577e-05       13.868            0            0
+129     -0.31871      0.38526     -0.30645      0.39508      0.12854       4.3519        2.721      -3.3964      0.82552      0.66137     0.055706     -0.04296       1864.8            0            0
+2      0.49975    -0.015705      0.49901    -0.031395      0.00138     0.040473    -0.040428    0.0019065   3.8545e-05   0.00081734  -0.00063441   4.2785e-05       11.402            0            0
+130     -0.30645      0.39508     -0.29389      0.40451      0.12249       4.1552       2.4949      -3.3228      0.82504      0.61945     0.052147    -0.042463       1775.5            0            0
+3      0.49901    -0.031395      0.49778    -0.047054      0.00127     0.035397    -0.035288    0.0027772   5.7011e-05   0.00072439  -0.00055338   5.5001e-05       11.994            0            0
+131     -0.29389      0.40451     -0.28104      0.41354       0.1162       3.9026        2.244      -3.1929      0.76963      0.54091     0.047336    -0.041656       1627.4            0            0
+4      0.49778    -0.047054      0.49606    -0.062667      0.00131     0.037308    -0.037083     0.004094   0.00068143    0.0061723  -0.00057177   0.00016126       15.378            0            0
+132     -0.28104      0.41354     -0.26791      0.42216      0.11106       3.7572       2.0628      -3.1403      0.85159      0.55939     0.045777    -0.040539       1597.9            0            0
+5      0.49606    -0.062667      0.49384    -0.078217      0.00144     0.042665    -0.042239    0.0060115     0.000133   0.00093451  -0.00066138    0.0001091       14.133            0            0
+133     -0.26791      0.42216     -0.25452      0.43037      0.10444       3.5545       1.8572      -3.0307      0.85088      0.52142     0.042537    -0.039415       1577.9            0            0
+6      0.49384    -0.078217      0.49114    -0.093691      0.00162     0.047621    -0.046912    0.0081874   0.00092881    0.0053218  -0.00072227   0.00021219        16.59            0            0
+134     -0.25452      0.43037     -0.24088      0.43815      0.09781       3.2845       1.6273       -2.853      0.81706      0.46604     0.038395    -0.037493       1428.6            0            0
+7      0.49114    -0.093691      0.48796     -0.10907        0.001      0.02759    -0.027017    0.0055949   0.00082731    0.0039949  -0.00041137   0.00015063       9.7055            0            0
+135     -0.24088      0.43815       -0.227       0.4455      0.09322        3.143       1.4707      -2.7777      0.86185      0.45633     0.036638    -0.036462       1382.3            0            0
+8      0.48796     -0.10907      0.48429     -0.12434      0.00155     0.040565    -0.039444    0.0094696  -0.00025845   -0.0010765  -0.00062362   0.00013183       12.521            0            0
+136       -0.227       0.4455     -0.21289      0.45241       0.0871       2.9299        1.289      -2.6311      0.83458      0.40886     0.033355    -0.034905         1288            0            0
+9      0.48429     -0.12434      0.48015      -0.1395      0.00133     0.038927    -0.037547     0.010272   0.00088049    0.0032185  -0.00057593   0.00021189       14.538            0            0
+137     -0.21289      0.45241     -0.19857      0.45888       0.0837       2.7866       1.1467      -2.5397      0.80684       0.3643     0.030685     -0.03417         1217            0            0
+10      0.48015      -0.1395      0.47553     -0.15451      0.00137      0.04019    -0.038414     0.011818   0.00051937    0.0016882  -0.00059522   0.00021214       16.294            0            0
+138     -0.19857      0.45888     -0.18406      0.46489      0.07909       2.6716       1.0224      -2.4682       0.8291      0.34342     0.029081    -0.033375       1196.8            0            0
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+189      0.46489      0.18406      0.47044      0.16937      0.00136     0.037674    -0.035242    -0.013317    0.0031942   -0.0084532  -0.00050339  -0.00034195       15.373            0            0
+62     -0.16937     -0.47044     -0.18406     -0.46489      0.07263       2.4636       0.8708       2.3045      0.78433     -0.29637     0.025998     0.031542       1111.5            0            0
+190      0.47044      0.16937      0.47553      0.15451      0.00123     0.033714    -0.031896     -0.01092    0.0031666    -0.009249  -0.00045126  -0.00031681       13.478            0            0
+63     -0.18406     -0.46489     -0.19857     -0.45888      0.07764       2.6198       1.0025       2.4204      0.79375     -0.32878     0.028215     0.032853       1183.9            0            0
+191      0.47553      0.15451      0.48015       0.1395       0.0015     0.041125    -0.039307    -0.012092   0.00089612   -0.0029129  -0.00060333  -0.00023569       15.286            0            0
+64     -0.19857     -0.45888     -0.21289     -0.45241      0.08048       2.7147       1.1171       2.4742      0.79899     -0.36076     0.030097     0.033197       1198.2            0            0
+192      0.48015       0.1395      0.48429      0.12434      0.00134      0.03642    -0.035129   -0.0096101    0.0016493   -0.0060288  -0.00052587  -0.00024565        13.14            0            0
+65     -0.21289     -0.45241       -0.227      -0.4455      0.08855       3.0185        1.328       2.7107      0.82401     -0.40368     0.033802     0.036238         1326            0            0
+193      0.48429      0.12434      0.48796      0.10907      0.00154     0.044157    -0.042937    -0.010308    0.0019876   -0.0082789  -0.00064321  -0.00029195       15.995            0            0
+66       -0.227      -0.4455     -0.24088     -0.43815      0.09334       3.1442       1.4713       2.7787       0.8314      -0.4402     0.036169     0.036732       1362.2            0            0
+194      0.48796      0.10907      0.49114     0.093691       0.0013     0.037331    -0.036555   -0.0075702    0.0006691   -0.0032309  -0.00056367  -0.00016966       13.375            0            0
+67     -0.24088     -0.43815     -0.25452     -0.43037      0.09824       3.3177       1.6438       2.8818      0.78643     -0.44857     0.038172      0.03822         1422            0            0
+195      0.49114     0.093691      0.49384     0.078217      0.00146     0.041826    -0.041203   -0.0071911  -3.4345e-05   0.00019679  -0.00064773  -0.00010986       13.262            0            0
+68     -0.25452     -0.43037     -0.26791     -0.42216      0.10312       3.4928        1.825       2.9781      0.85292     -0.52267     0.042063     0.038569       1518.5            0            0
+196      0.49384     0.078217      0.49606     0.062667      0.00124     0.037355    -0.036982   -0.0052633   0.00082154   -0.0057724  -0.00056799  -0.00017334       14.486            0            0
+69     -0.26791     -0.42216     -0.28104     -0.41354      0.10943       3.6943       2.0282       3.0877      0.82382     -0.54115     0.044798         0.04       1568.3            0            0
+197      0.49606     0.062667      0.49778     0.047054       0.0014     0.040847      -0.0406   -0.0044823  -0.00035719    0.0032354  -0.00064333  -1.9586e-05       13.287            0            0
+70     -0.28104     -0.41354     -0.29389     -0.40451      0.11778       3.9425        2.267       3.2256      0.81918     -0.57573     0.048475     0.041622       1655.6            0            0
+198      0.49778     0.047054      0.49901     0.031395      0.00142     0.040122    -0.039999    -0.003148   9.2741e-05   -0.0011784  -0.00062681  -6.7955e-05       13.754            0            0
+71     -0.29389     -0.40451     -0.30645     -0.39508      0.12422       4.1851       2.5128       3.3468      0.82951     -0.62281     0.052499     0.042786       1764.1            0            0
+199      0.49901     0.031395      0.49975     0.015705      0.00153     0.045482    -0.045431   -0.0021425  -0.00014564    0.0030883  -0.00071589   1.4857e-05        11.94            0            0
+72     -0.30645     -0.39508     -0.31871     -0.38526      0.13076       4.4067       2.7553       3.4391      0.82466     -0.66067     0.056231     0.043642       1852.6            0            0
+200      0.49975     0.015705          0.5            0      0.00135     0.040023    -0.040018  -0.00062865  -4.0549e-06   0.00025812  -0.00062863    -5.82e-06       11.861            0            0
+73     -0.31871     -0.38526     -0.33066     -0.37506      0.13699       4.6087       2.9931       3.5045      0.77414     -0.66118     0.059174     0.044661       1898.7            0            0
+74     -0.33066     -0.37506     -0.34227     -0.36448      0.14416       4.8615       3.2718       3.5957      0.78818     -0.71718     0.063772     0.045214       2023.2            0            0
+75     -0.34227     -0.36448     -0.35355     -0.35355      0.14882       5.0571       3.5193       3.6316      0.76005     -0.73654     0.067217     0.045474       2101.9            0            0
+76     -0.35355     -0.35355     -0.36448     -0.34227      0.15454       5.2083       3.7402       3.6245      0.71195     -0.73468     0.069932     0.045392       2148.4            0            0
+77     -0.36448     -0.34227     -0.37506     -0.33066      0.16477       5.5472       4.1029       3.7333      0.70211     -0.77161     0.075473     0.046521       2249.2            0            0
+78     -0.37506     -0.33066     -0.38526     -0.31871      0.17016       5.7104       4.3422       3.7086      0.66404     -0.77749     0.078635      0.04604       2296.9            0            0
+79     -0.38526     -0.31871     -0.39508     -0.30645      0.17753       5.9793       4.6664       3.7385      0.62393      -0.7788     0.083097     0.046489       2423.6            0            0
+80     -0.39508     -0.30645     -0.40451     -0.29389      0.18367       6.2377       4.9882       3.7453      0.60864     -0.81063     0.087912     0.046095       2540.9            0            0
+81     -0.40451     -0.29389     -0.41354     -0.28104      0.18936       6.4155       5.2489        3.689      0.58031      -0.8257     0.091561     0.044974       2626.8            0            0
+82     -0.41354     -0.28104     -0.42216     -0.26791      0.19767       6.6699       5.5747       3.6619      0.51166     -0.77893     0.095601     0.045284       2642.1            0            0
+83     -0.42216     -0.26791     -0.43037     -0.25452      0.19997        6.784       5.7843       3.5446       0.4899     -0.79945     0.098551     0.043119       2756.1            0            0
+84     -0.43037     -0.25452     -0.43815     -0.24088      0.20868        7.063       6.1351       3.4994      0.45676     -0.80079      0.10354     0.042388       2836.1            0            0
+85     -0.43815     -0.24088      -0.4455       -0.227      0.21528       7.2714       6.4262       3.4025      0.42819     -0.80871      0.10766     0.040742       2892.9            0            0
+86      -0.4455       -0.227     -0.45241     -0.21289      0.22392       7.5704       6.7984       3.3305      0.37972     -0.77511      0.11275     0.040139       3019.2            0            0
+87     -0.45241     -0.21289     -0.45888     -0.19857      0.22778       7.6906       7.0093       3.1648      0.34296     -0.75957      0.11548      0.03778       3074.3            0            0
+88     -0.45888     -0.19857     -0.46489     -0.18406      0.22926       7.7683        7.177       2.9728      0.29046     -0.70123      0.11729      0.03568       3071.4            0            0
+89     -0.46489     -0.18406     -0.47044     -0.16937      0.23895       8.0356       7.5168       2.8404      0.24951      -0.6603      0.12199     0.034243       3146.5            0            0
+90     -0.47044     -0.16937     -0.47553     -0.15451      0.23906       8.1049       7.6679       2.6253      0.22142     -0.64673      0.12392     0.031078       3208.6            0            0
+91     -0.47553     -0.15451     -0.48015      -0.1395      0.24813       8.4149       8.0429       2.4743      0.17126     -0.55669      0.12902     0.030121       3306.3            0            0
+92     -0.48015      -0.1395     -0.48429     -0.12434      0.25141        8.508       8.2065        2.245      0.16091     -0.58819      0.13143     0.026025       3348.9            0            0
+93     -0.48429     -0.12434     -0.48796     -0.10907       0.2549       8.6275       8.3891        2.014      0.11387      -0.4743      0.13356     0.024185       3377.8            0            0
+94     -0.48796     -0.10907     -0.49114    -0.093691      0.25804       8.7788       8.5964       1.7802     0.089882     -0.43402      0.13644     0.021145       3463.3            0            0
+95     -0.49114    -0.093691     -0.49384    -0.078217       0.2611        8.808       8.6769       1.5144     0.060006     -0.34382      0.13723     0.018386       3432.4            0            0
+96     -0.49384    -0.078217     -0.49606    -0.062667      0.26325       8.9235       8.8345       1.2573     0.038932     -0.27355      0.13938     0.015452       3486.1            0            0
+97     -0.49606    -0.062667     -0.49778    -0.047054       0.2636       8.8783       8.8247      0.97426     0.024314     -0.22023      0.13899     0.011844       3443.1            0            0
+98     -0.49778    -0.047054     -0.49901    -0.031395      0.26971       9.0504       9.0225      0.71009     0.012558     -0.15956      0.14192    0.0086473       3415.1            0            0
+99     -0.49901    -0.031395     -0.49975    -0.015705      0.26955       9.0412       9.0311       0.4259    0.0057193     -0.12128      0.14194    0.0047848       3444.1            0            0
+100     -0.49975    -0.015705         -0.5            0       0.2684       9.0881        9.087      0.14275   0.00068703    -0.043734      0.14274    0.0015553       3524.4            0            0
+101         -0.5            0     -0.49975     0.015705       0.2675       9.0924       9.0912     -0.14282    0.0012134     0.077241      0.14282     -0.00103       3588.9            0            0
+102     -0.49975     0.015705     -0.49901     0.031395      0.27098       9.1545       9.1443     -0.43124    0.0051841      0.10993      0.14371   -0.0050469         3534            0            0
+103     -0.49901     0.031395     -0.49778     0.047054      0.26802       8.9804       8.9527     -0.70459      0.01717      0.21816      0.14089   -0.0076405       3452.7            0            0
+104     -0.49778     0.047054     -0.49606     0.062667      0.26663       8.9865       8.9322     -0.98612     0.023527      0.21311      0.14067    -0.012142       3483.5            0            0
+105     -0.49606     0.062667     -0.49384     0.078217      0.26438       8.9442       8.8549      -1.2602     0.041568      0.29207      0.13974    -0.015207       3483.1            0            0
+106     -0.49384     0.078217     -0.49114     0.093691      0.26156       8.8596       8.7277      -1.5232     0.057669      0.33043      0.13799    -0.018736         3511            0            0
+107     -0.49114     0.093691     -0.48796      0.10907      0.25748       8.6789       8.4986        -1.76        0.087      0.42011      0.13486    -0.021046       3397.7            0            0
+108     -0.48796      0.10907     -0.48429      0.12434      0.25814       8.7267       8.4856      -2.0372      0.10786      0.44929      0.13498    -0.024942       3371.4            0            0
+109     -0.48429      0.12434     -0.48015       0.1395       0.2527       8.4794       8.1789      -2.2375      0.14596      0.53353      0.13076    -0.026765         3290            0            0
+110     -0.48015       0.1395     -0.47553      0.15451      0.24726       8.3683       7.9983      -2.4606      0.18686      0.60739      0.12857    -0.029109       3308.2            0            0
+111     -0.47553      0.15451     -0.47044      0.16937      0.24365       8.1979       7.7559      -2.6555      0.20993      0.61315      0.12512    -0.032079       3203.3            0            0
+112     -0.47044      0.16937     -0.46489      0.18406      0.23718       7.9662       7.4519      -2.8158      0.25992      0.68785      0.12113    -0.033425       3070.6            0            0
+113     -0.46489      0.18406     -0.45888      0.19857      0.23145       7.8424       7.2454      -3.0012      0.29285        0.707      0.11841    -0.036035       3089.9            0            0
+114     -0.45888      0.19857     -0.45241      0.21289      0.22493       7.5452       6.8767       -3.105      0.31118      0.68918       0.1129    -0.037946       2926.4            0            0
+115     -0.45241      0.21289      -0.4455        0.227      0.22271       7.5756       6.8031      -3.3328      0.36685      0.74883      0.11262    -0.040587       3073.9            0            0
+116      -0.4455        0.227     -0.43815      0.24088       0.2129       7.1977       6.3611       -3.368      0.40609      0.76696      0.10629    -0.040856       2862.3            0            0
+117     -0.43815      0.24088     -0.43037      0.25452      0.20855       7.0496       6.1235      -3.4928      0.44452      0.77933      0.10317    -0.042621       2840.4            0            0
+118     -0.43037      0.25452     -0.42216      0.26791      0.20295       6.8786        5.865      -3.5941      0.50555      0.82499      0.10006    -0.043495       2761.2            0            0
+119     -0.42216      0.26791     -0.41354      0.28104      0.19658       6.6417       5.5512      -3.6464      0.51014      0.77661     0.095207    -0.045077       2644.4            0            0
+120     -0.41354      0.28104     -0.40451      0.29389      0.19113       6.4538       5.2802       -3.711      0.56548       0.8046      0.09182    -0.045651       2585.5            0            0
+121     -0.40451      0.29389     -0.39508      0.30645      0.18249        6.188       4.9484      -3.7154      0.59198      0.78844     0.087025    -0.045975       2500.9            0            0
+122     -0.39508      0.30645     -0.38526      0.31871      0.17772       6.0196       4.6978      -3.7637      0.60859      0.75964      0.08335    -0.047186       2429.9            0            0
+123     -0.38526      0.31871     -0.37506      0.33066      0.17054       5.7332       4.3595      -3.7234      0.66929      0.78364     0.078989    -0.046176         2322            0            0
+124     -0.37506      0.33066     -0.36448      0.34227      0.16522       5.5813       4.1281      -3.7563      0.73584      0.80867     0.076399    -0.046299       2309.1            0            0
+125     -0.36448      0.34227     -0.35355      0.35355      0.15682       5.3148       3.8167      -3.6986        0.729      0.75227     0.071401    -0.046279       2184.5            0            0
+126     -0.35355      0.35355     -0.34227      0.36448      0.15258       5.1395       3.5766      -3.6908      0.73668       0.7139     0.067751    -0.046759         2114            0            0
+127     -0.34227      0.36448     -0.33066      0.37506      0.14332       4.8715       3.2786      -3.6031      0.78472      0.71404     0.063824     -0.04538       1997.1            0            0
+128     -0.33066      0.37506     -0.31871      0.38526      0.13504       4.5675       2.9663      -3.4731      0.77589      0.66267      0.05878    -0.044145       1898.2            0            0

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/runmpirun128.sh ADDED Viewed

	@@ -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/Kn0p40/simulation0900_Kn0p40Ma6p9/runmpirun64.sh ADDED Viewed

	@@ -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/Kn0p40/simulation0900_Kn0p40Ma6p9/slurm-28429038.out ADDED Viewed

	@@ -0,0 +1,200 @@

+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 48572 child grid cells
+  CPU time = 0.294282 secs
+  create/ghost percent = 0.396658 99.6033
+Balance grid migrated 48478 cells
+  CPU time = 0.0804596 secs
+  reassign/sort/migrate/ghost percent = 67.6998 0.0395727 9.24489 23.0157
+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
+  324 0 = cells overlapping surfs, overlap cells with unmarked corner pts
+  43392 4856 324 = cells outside/inside/overlapping surfs
+  324 = surf cells with 1,2,etc splits
+  109.214731023047 109.214731023047 = cell-wise and global flow volume
+  CPU time = 0.0904281 secs
+  read/check/sort/surf2grid/ghost/inout/particle percent = 21.3748 29.1439 3.12632 26.3449 20.0101 6.98358 0.182785
+  surf2grid time = 0.0238232 secs
+  map/comm1/comm2/comm3/comm4/split percent = 14.6708 24.5709 3.8663 1.76646 12.3707 6.97854
+Balance grid migrated 1125 cells
+  CPU time = 0.0281955 secs
+  reassign/sort/migrate/ghost percent = 8.96573 0.0946959 32.254 58.6855
+Creating particles ...
+Created 327644 particles
+  CPU time = 0.0126899 secs
+Memory usage per proc in Mbytes:
+  particles (ave,min,max) = 1.59521 0 1.6875
+  grid      (ave,min,max) = 2.75891 1.51379 4.32629
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 4.37473 3.22189 6.03439
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave
+       0            0   327644        0        0        0            0            0
+   10000    9.7171877   367175     3511     3104       13    349003.68      15.7172
+   20000    19.415358   367428     3550     3162       17    358324.17     15.90385
+   30000    29.685823   367658     3587     3196       16    361450.41    15.961867
+   40000    40.166395   367983     3627     3206       13    363082.53    16.002675
+   50000    49.829175   368227     3578     3183       25    364056.65     16.01014
+   60000    59.805893   367071     3505     3091       11    364666.38    16.021917
+   70000    70.884416   367465     3552     3147       23    365115.17    16.011686
+   80000    80.419341   368247     3558     3164       17    365448.92    16.022662
+   90000    90.736007   367792     3502     3106       17    365760.67    16.027989
+  100000    100.49242   367633     3544     3142       16     365956.1     16.02885
+  110000    110.07655   367859     3495     3084       11    366168.06    16.038936
+  120000    119.93364   368423     3603     3214       13    366319.34      16.0399
+  130000    131.10337   367875     3522     3140       12    366437.08    16.038362
+  140000    140.67915   367457     3503     3108        7    366526.13     16.04105
+  150000    150.98568   368503     3537     3178       11    366605.92    16.042067
+  160000     161.4997   367668     3567     3178        8    366707.24    16.045869
+  170000     170.9638   367785     3524     3139       14    366783.13    16.049912
+  180000    181.39174   368054     3545     3163       18    366838.07    16.053156
+  190000    191.44251   366994     3607     3192       18    366892.32    16.050926
+  200000    200.90596   367736     3501     3083       19    366936.33    16.046865
+Loop time of 200.906 on 128 procs for 200000 steps with 367736 particles
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.022907   | 8.8217     | 56.962     | 384.5 |  4.39
+Coll    | 0.25129    | 6.3282     | 49.859     | 325.9 |  3.15
+Sort    | 0.086723   | 1.4495     | 9.7706     | 159.2 |  0.72
+Comm    | 50.878     | 84.528     | 95.451     |  97.3 | 42.07
+Modify  | 0.019864   | 0.10189    | 2.073      |  92.9 |  0.05
+Output  | 0.008796   | 0.011736   | 0.013269   |   0.6 |  0.01
+Other   |            | 99.67      |            |       | 49.61
+Particle moves    = 73387266327 (73.4B)
+Cells touched     = 76622239940 (76.6B)
+Particle comms    = 174418269 (174M)
+Boundary collides = 0 (0K)
+Boundary exits    = 16436852 (16.4M)
+SurfColl checks   = 231074712 (231M)
+SurfColl occurs   = 3209373 (3.21M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 845988413 (846M)
+Collide occurs    = 669327074 (669M)
+Gas reactions     = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+Particle-moves/CPUsec/proc: 2.85376e+06
+Particle-moves/step: 366936
+Cell-touches/particle/step: 1.04408
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00237668
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.000223974
+Surface-checks/particle/step: 0.0031487
+Surface-collisions/particle/step: 4.3732e-05
+Surface-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0115277
+Collisions/particle/step: 0.00912048
+Gas-reactions/particle/step: 0
+Particles: 2872.94 ave 19703 max 0 min
+Histogram: 84 16 4 12 2 4 2 2 0 2
+Cells:     379.469 ave 380 max 379 min
+Histogram: 68 0 0 0 0 0 0 0 0 60
+GhostCell: 9951.02 ave 18101 max 568 min
+Histogram: 18 12 12 10 14 6 6 4 14 32
+EmptyCell: 219.359 ave 405 max 0 min
+Histogram: 2 7 9 15 23 20 17 18 10 7
+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) = 1.63477 0 3.375
+  grid      (ave,min,max) = 2.75891 1.51379 4.32629
+  surf      (ave,min,max) = 0.0205994 0.0205994 0.0205994
+  total     (ave,min,max) = 4.54192 3.34929 6.16229
+Step CPU Np Natt Ncoll Nscoll Npave Nscollave
+  200000            0   367736     3501     3083        0            0            0
+  210000     20.84445   367845     3537     3160       18    367746.26      16.1035
+  220000    38.656969   367636     3566     3159       18    367833.54     16.10585
+  230000    57.719796   368135     3570     3149       14    367863.73      16.1092
+  240000    76.497788   367609     3618     3219       10    367932.01    16.091925
+  250000    94.527537   367801     3515     3145       18    367889.02      16.1091
+  260000    113.44546   367198     3651     3254       14    367873.98     16.09445
+  270000    131.36664   368726     3618     3258       20    367860.47    16.090929
+  280000     149.8793   367836     3521     3108        9    367879.64    16.077288
+  290000    169.03378   367637     3592     3218       14    367845.08    16.074011
+  300000     187.3619   367147     3591     3186        9     367861.1     16.07365
+Loop time of 187.362 on 128 procs for 100000 steps with 367147 particles
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Move    | 0.011573   | 4.4473     | 28.831     | 272.2 |  2.37
+Coll    | 0.12413    | 3.186      | 25.579     | 232.7 |  1.70
+Sort    | 0.04605    | 0.73369    | 4.9381     | 112.3 |  0.39
+Comm    | 33.288     | 50.007     | 55.914     |  63.4 | 26.69
+Modify  | 1.7501     | 12.335     | 74.662     | 420.5 |  6.58
+Output  | 0.034114   | 0.036934   | 0.042162   |   1.0 |  0.02
+Other   |            | 116.6      |            |       | 62.24
+Particle moves    = 36786109616 (36.8B)
+Cells touched     = 38406588625 (38.4B)
+Particle comms    = 87362486 (87.4M)
+Boundary collides = 0 (0K)
+Boundary exits    = 8237386 (8.24M)
+SurfColl checks   = 115715937 (116M)
+SurfColl occurs   = 1607365 (1.61M)
+Surf reactions    = 0 (0K)
+Collide attempts  = 426063210 (426M)
+Collide occurs    = 337078535 (337M)
+Gas reactions     = 0 (0K)
+Particles stuck   = 0
+Axisymm bad moves = 0
+Particle-moves/CPUsec/proc: 1.53388e+06
+Particle-moves/step: 367861
+Cell-touches/particle/step: 1.04405
+Particle comm iterations/step: 1
+Particle fraction communicated: 0.00237488
+Particle fraction colliding with boundary: 0
+Particle fraction exiting boundary: 0.000223927
+Surface-checks/particle/step: 0.00314564
+Surface-collisions/particle/step: 4.36949e-05
+Surface-reactions/particle/step: 0
+Collision-attempts/particle/step: 0.0115822
+Collisions/particle/step: 0.0091632
+Gas-reactions/particle/step: 0
+Particles: 2868.34 ave 19845 max 0 min
+Histogram: 84 16 4 12 2 4 2 2 0 2
+Cells:     379.469 ave 380 max 379 min
+Histogram: 68 0 0 0 0 0 0 0 0 60
+GhostCell: 9951.02 ave 18101 max 568 min
+Histogram: 18 12 12 10 14 6 6 4 14 32
+EmptyCell: 219.359 ave 405 max 0 min
+Histogram: 2 7 9 15 23 20 17 18 10 7
+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 = 48572
+  CPU time = 0.00728568 secs
+Writing surface file ...
+  surf elements = 200
+  CPU time = 0.0016793 secs
+Processing  2  grid chunk(s).
+Completed grid chunk number:  1
+Completed grid chunk number:  0
+Done in 0:00:08 (wall clock time)
+Processing  2  grid chunk(s).
+Completed grid chunk number:  1
+Completed grid chunk number:  0
+Done in 0:00:08 (wall clock time)
+Processing SPARTA surface information.
+Processing dump result file:  ['./output/surf.300000.dat']

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/surf/Surf_300000.vtu ADDED Viewed

	@@ -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="0.001"                RangeMax="0.27098"              offset="4512"                />
+        <DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.02759"              RangeMax="9.1545"               offset="6460"                />
+        <DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.12497"             RangeMax="9.1443"               offset="8500"                />
+        <DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-3.7637"              RangeMax="3.7453"               offset="10580"               />
+        <DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.00035719"          RangeMax="0.86185"              offset="12656"               />
+        <DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.8257"              RangeMax="0.82499"              offset="14740"               />
+        <DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.00072227"          RangeMax="0.14371"              offset="16868"               />
+        <DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.047186"            RangeMax="0.046521"             offset="19008"               />
+        <DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="9.7055"               RangeMax="3588.9"               offset="21156"               />
+        <DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="22444"               />
+        <DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="22496"               />
+      </CellData>
+      <Points>
+        <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503"        RangeMax="0.50000001255"        offset="22548"               />
+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="23876"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="24780"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="25272"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
+  <AppendedData encoding="base64">
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AQAAAACAAABABgAA6AUAAA==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AQAAAACAAABABgAAAwYAAA==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AQAAAACAAABABgAAMQYAAA==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AQAAAACAAABABgAANwYAAA==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AQAAAACAAABABgAAtAMAAA==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eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78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+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p40/simulation0900_Kn0p40Ma6p9/surf/geom.surf ADDED Viewed

	@@ -0,0 +1,610 @@

+# Surface element file written by SPARTA
+400 points
+200 lines
+Points
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AQAAAACAAADgCwAAJwoAAA==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AQAAAACAAACAFgAAKgUAAA==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AQAAAACAAACALwAAdQcAAA==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AQAAAACAAADgCwAALgIAAA==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eJzj5BwFAwUA8vkNXQ==
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Lambda/Lambda_300000.pvtu ADDED Viewed

	@@ -0,0 +1,19 @@

+<?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"/>
+</PUnstructuredGrid>
+</VTKFile>

CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/Surf.pvd ADDED Viewed

	@@ -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/Kn0p42/simulation0901_Kn0p42Ma2p0/config.txt ADDED Viewed

	@@ -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 0.42
+variable   Ma equal 2.0
+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/Kn0p42/simulation0901_Kn0p42Ma2p0/cylinder.surf ADDED Viewed

	@@ -0,0 +1,410 @@

+ surf file from Pointwise
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+         200 lines
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+         195         195         196
+         196         196         197
+         197         197         198
+         198         198         199
+         199         199         200
+         200         200           1

CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/gas.species ADDED Viewed

	@@ -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/Kn0p42/simulation0901_Kn0p42Ma2p0/gas.vhs ADDED Viewed

	@@ -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/Kn0p42/simulation0901_Kn0p42Ma2p0/grid/Grid_0_300000.vtu ADDED Viewed

The diff for this file is too large to render. See raw diff

CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/grid/Grid_1_300000.vtu ADDED Viewed

	@@ -0,0 +1,35 @@

+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
+  <UnstructuredGrid>
+    <Piece NumberOfPoints="480"                  NumberOfCells="380"                 >
+      <PointData>
+      </PointData>
+      <CellData>
+        <DataArray type="Float64" Name="id" format="appended" RangeMin="101"                  RangeMax="9880"                 offset="0"                   />
+        <DataArray type="Float64" Name="xc" format="appended" RangeMin="5.6298"               RangeMax="5.9471"               offset="1028"                />
+        <DataArray type="Float64" Name="yc" format="appended" RangeMin="-4.9474"              RangeMax="4.9474"               offset="1140"                />
+        <DataArray type="Float64" Name="f_1[1]" format="appended" RangeMin="21.143"               RangeMax="34.467"               offset="1884"                />
+        <DataArray type="Float64" Name="f_1[2]" format="appended" RangeMin="2.0484e+19"           RangeMax="3.3392e+19"           offset="4140"                />
+        <DataArray type="Float64" Name="f_1[3]" format="appended" RangeMin="1.3581e-06"           RangeMax="2.2139e-06"           offset="7792"                />
+        <DataArray type="Float64" Name="f_1[4]" format="appended" RangeMin="409.99"               RangeMax="623.06"               offset="11524"               />
+        <DataArray type="Float64" Name="f_1[5]" format="appended" RangeMin="-31.225"              RangeMax="28.136"               offset="13244"               />
+        <DataArray type="Float64" Name="f_1[6]" format="appended" RangeMin="-3.5939"              RangeMax="3.2608"               offset="16312"               />
+        <DataArray type="Float64" Name="f_1[7]" format="appended" RangeMin="0.087229"             RangeMax="0.13308"              offset="19984"               />
+        <DataArray type="Float64" Name="f_1[8]" format="appended" RangeMin="267.16"               RangeMax="363.73"               offset="23628"               />
+        <DataArray type="Float64" Name="f_1[9]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="25352"               />
+        <DataArray type="Float64" Name="f_1[10]" format="appended" RangeMin="0"                    RangeMax="0"                    offset="25412"               />
+      </CellData>
+      <Points>
+        <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="5.5771712403"         RangeMax="7.8102496759"         offset="25472"               />
+      </Points>
+      <Cells>
+        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="27260"               />
+        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="29832"               />
+        <DataArray type="UInt8" Name="types" format="appended" RangeMin=""                     RangeMax=""                     offset="30600"               />
+      </Cells>
+    </Piece>
+  </UnstructuredGrid>
+  <AppendedData encoding="base64">
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AQAAAACAAADgCwAA3QoAAA==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AQAAAACAAADgCwAA6wgAAA==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AQAAAACAAADgCwAAmwoAAA==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AQAAAACAAADgCwAAGQAAAA==eJztwQENAAAAwqD3T20PBxQAAPBiC+AAAQ==AQAAAACAAADgCwAAGQAAAA==eJztwQENAAAAwqD3T20PBxQAAPBiC+AAAQ==AQAAAACAAACAFgAAKgUAAA==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AQAAAACAAACALwAAdQcAAA==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AQAAAACAAADgCwAALgIAAA==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eJzj5BwFAwUA8vkNXQ==
+  </AppendedData>
+</VTKFile>

CylinderKnMa/Kn0p42/simulation0901_Kn0p42Ma2p0/grid/Grid_300000.pvtu ADDED Viewed

	@@ -0,0 +1,27 @@

+<?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]"/>
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