From 1f4191c02ec16ac1f7ac5516516cc0706954d06e Mon Sep 17 00:00:00 2001
From: Wenqing Wang <wenqing.wang@ufz.de>
Date: Thu, 24 Jun 2021 11:48:45 +0200
Subject: [PATCH] [Test/postLIE] added a 3D test for post LIE
---
Applications/Utils/Tests.cmake | 12 ++++
.../post_single_joint_3D_ts_1_t_1.000000.vtu | 56 ++++++++++++++++++
.../LIE/PostProcessing/single_joint_3D.pvd | 7 +++
.../single_joint_3D_ts_0_t_0.000000.vtu | 58 +++++++++++++++++++
.../single_joint_3D_ts_1_t_1.000000.vtu | 58 +++++++++++++++++++
5 files changed, 191 insertions(+)
create mode 100644 Tests/Data/LIE/PostProcessing/post_single_joint_3D_ts_1_t_1.000000.vtu
create mode 100644 Tests/Data/LIE/PostProcessing/single_joint_3D.pvd
create mode 100644 Tests/Data/LIE/PostProcessing/single_joint_3D_ts_0_t_0.000000.vtu
create mode 100644 Tests/Data/LIE/PostProcessing/single_joint_3D_ts_1_t_1.000000.vtu
diff --git a/Applications/Utils/Tests.cmake b/Applications/Utils/Tests.cmake
index 9b7c30e948b..b3a7fa577ce 100644
--- a/Applications/Utils/Tests.cmake
+++ b/Applications/Utils/Tests.cmake
@@ -44,6 +44,18 @@ AddTest(
expected_post_single_joint_ts_1_t_1.000000.vtu post_single_joint_ts_1_t_1.000000.vtu u u 1e-14 1e-14
)
+AddTest(
+ NAME postLIE3D
+ PATH LIE/PostProcessing
+ WORKING_DIRECTORY ${Data_SOURCE_DIR}/LIE/PostProcessing
+ EXECUTABLE postLIE
+ EXECUTABLE_ARGS -i single_joint_3D.pvd -o ${Data_BINARY_DIR}/LIE/PostProcessing/post_single_joint_3D.pvd
+ REQUIREMENTS NOT OGS_USE_MPI AND OGS_BUILD_PROCESS_LIE
+ TESTER vtkdiff
+ DIFF_DATA
+ post_single_joint_3D_ts_1_t_1.000000.vtu post_single_joint_3D_ts_1_t_1.000000.vtu u u 1e-14 1e-14
+)
+
AddTest(
NAME identifySubdomains_2D_Create
PATH MeshGeoToolsLib/IdentifySubdomains
diff --git a/Tests/Data/LIE/PostProcessing/post_single_joint_3D_ts_1_t_1.000000.vtu b/Tests/Data/LIE/PostProcessing/post_single_joint_3D_ts_1_t_1.000000.vtu
new file mode 100644
index 00000000000..77147a9dabd
--- /dev/null
+++ b/Tests/Data/LIE/PostProcessing/post_single_joint_3D_ts_1_t_1.000000.vtu
@@ -0,0 +1,56 @@
+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="1.0" byte_order="LittleEndian" header_type="UInt64">
+ <UnstructuredGrid>
+ <Piece NumberOfPoints="484" NumberOfCells="210" >
+ <PointData>
+ <DataArray type="Float64" Name="displacement" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="6.9239316787e-06" offset="0" />
+ <DataArray type="Float64" Name="displacement_jump1" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="3.4469071319e-06" offset="15500" />
+ <DataArray type="Float64" Name="epsilon_xx" format="appended" RangeMin="1.1051757433e-05" RangeMax="1.1051776337e-05" offset="31000" />
+ <DataArray type="Float64" Name="epsilon_xy" format="appended" RangeMin="-1.7402646215e-12" RangeMax="5.8525415179e-12" offset="36176" />
+ <DataArray type="Float64" Name="epsilon_xz" format="appended" RangeMin="-6.3208107792e-19" RangeMax="8.6198291128e-19" offset="41352" />
+ <DataArray type="Float64" Name="epsilon_yy" format="appended" RangeMin="-3.9183542255e-05" RangeMax="-3.9183522546e-05" offset="46528" />
+ <DataArray type="Float64" Name="epsilon_yz" format="appended" RangeMin="-4.3952392273e-19" RangeMax="2.7416907164e-19" offset="51704" />
+ <DataArray type="Float64" Name="epsilon_zz" format="appended" RangeMin="0" RangeMax="0" offset="56880" />
+ <DataArray type="Float64" Name="sigma_xx" format="appended" RangeMin="-0.0010950779118" RangeMax="0.0017107783291" offset="62056" />
+ <DataArray type="Float64" Name="sigma_xy" format="appended" RangeMin="-0.00024249588989" RangeMax="0.00081551808037" offset="67232" />
+ <DataArray type="Float64" Name="sigma_xz" format="appended" RangeMin="-8.8076871513e-11" RangeMax="1.2011237288e-10" offset="72408" />
+ <DataArray type="Float64" Name="sigma_yy" format="appended" RangeMin="-7000.0019108" RangeMax="-6999.9988075" offset="77584" />
+ <DataArray type="Float64" Name="sigma_yz" format="appended" RangeMin="-6.1245136775e-11" RangeMax="3.8203887032e-11" offset="82760" />
+ <DataArray type="Float64" Name="sigma_zz" format="appended" RangeMin="-1540.0001472" RangeMax="-1539.9996783" offset="87936" />
+ <DataArray type="Float64" Name="u" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="6.9239316787e-06" offset="93112" />
+ </PointData>
+ <CellData>
+ <DataArray type="Int32" Name="MaterialIDs" format="appended" RangeMin="0" RangeMax="1" offset="108612" />
+ <DataArray type="Float64" Name="aperture" format="appended" RangeMin="0" RangeMax="9.9971073346e-06" offset="109744" />
+ <DataArray type="Float64" Name="f_stress_n" format="appended" RangeMin="-2892.6675958" RangeMax="0" offset="111996" />
+ <DataArray type="Float64" Name="f_stress_s" format="appended" RangeMin="0" RangeMax="0" offset="114248" />
+ <DataArray type="Float64" Name="levelset1" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="116500" />
+ <DataArray type="Float64" Name="strain_xx" format="appended" RangeMin="0" RangeMax="1.1051773603e-05" offset="118752" />
+ <DataArray type="Float64" Name="strain_xy" format="appended" RangeMin="-7.5721579911e-12" RangeMax="1.0740749907e-11" offset="121004" />
+ <DataArray type="Float64" Name="strain_xz" format="appended" RangeMin="-5.6526214339e-19" RangeMax="3.6734760131e-19" offset="123256" />
+ <DataArray type="Float64" Name="strain_yy" format="appended" RangeMin="-3.9183538336e-05" RangeMax="0" offset="125508" />
+ <DataArray type="Float64" Name="strain_yz" format="appended" RangeMin="-6.1155778792e-19" RangeMax="6.8440262138e-19" offset="127760" />
+ <DataArray type="Float64" Name="strain_zz" format="appended" RangeMin="0" RangeMax="0" offset="130012" />
+ <DataArray type="Float64" Name="stress_xx" format="appended" RangeMin="-0.0007569174495" RangeMax="0.001530794289" offset="132264" />
+ <DataArray type="Float64" Name="stress_xy" format="appended" RangeMin="-0.0010551367692" RangeMax="0.0014966618724" offset="134516" />
+ <DataArray type="Float64" Name="stress_xz" format="appended" RangeMin="-7.8766036375e-11" RangeMax="5.1187780511e-11" offset="136768" />
+ <DataArray type="Float64" Name="stress_yy" format="appended" RangeMin="-7000.0017255" RangeMax="0" offset="139020" />
+ <DataArray type="Float64" Name="stress_yz" format="appended" RangeMin="-8.5217068808e-11" RangeMax="9.5367578389e-11" offset="141272" />
+ <DataArray type="Float64" Name="stress_zz" format="appended" RangeMin="-1540.0004819" RangeMax="0" offset="143524" />
+ <DataArray type="Float64" Name="w_n" format="appended" RangeMin="-2.8926675958e-09" RangeMax="0" offset="145776" />
+ <DataArray type="Float64" Name="w_s" format="appended" RangeMin="0" RangeMax="0" offset="148028" />
+ </CellData>
+ <Points>
+ <DataArray type="Float64" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="0.11224972324" offset="150280" />
+ </Points>
+ <Cells>
+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="165780" />
+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="183284" />
+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="185536" />
+ </Cells>
+ </Piece>
+ </UnstructuredGrid>
+ <AppendedData encoding="base64">
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/6M7G0yRZ7z4eGa+aPBjuPnggaXKZaek+drKLcN2H3T6o6rsKtJXDvnLuU+kOFfG+ehwC7XehAL86CNl7CEsGv1bWLSCDXwu/2TyiuNBHGL/n2tQfUB4hv70GD9rZee0+g/6/lc+X6z58nr+PxA/lPuHfCWnOT88+Hip4987Q2r4vHBvtazL0vji/EmTcwgC/3NG6vEveBr+VaL7fukkOv+YbkAbZvAu/gvPHNkjw/j6BfOFo4FHoPiI29vOoPeY+NJJibuyi3j54Kp5HiCSyPrxmSc5j2OC+sf0QpK+f875KoMRmmd3+vuDd+3SyEwW/vMuHna8SCb8NbDgphZEKv8p6QblKRAo/ZokuCil04T7YXxxA0GLfPteBQdvg6NM+iCDMUpx+ir72UftBHKPdvkwJwh4dBu++43N2mn8H975UCbGM45b7vrKU1QgYMvu+yhlkz/YK975A5ZyX2/L5Ph4ozEGF1tQ+1uRWqmGp0j5AJlnm2SrHPi8Wi1YkepC+MOXolyxP0r71yjNFzrHivrgdSIiXQei+QQ11j4aM0r58z1X24PPyPh5skvHEdSK/ocjf5hbxUb/abKjc00bEPo+ygibcWcI+kbrwgUERuD4ocOsfEbh4PgVcdveSvb2+QNZ7EKWo0b4daK/Bej7cvhkVWEeDH9q+bI5fuXBP6j6IRhAMQJ4YP2xY9wrkoTm/Utly3DINwj49m/IhTxLGPkRYCNnxs9A+b9t0skyW2D67nO1sjYzePhV9xiA8Sto+Kjh8xBnf3j55joPunY4HP2+mX8PpUTU/StBdMevfST+0sbbGZUhWP1n2JvJSjtK+MkfSYmFU7L6fkdStNTXsvlaedJSUDeK+0LZvPgloor4uXLA8lKzgvgjGUtIbruA+t5cu0rjg5b7CTfMewDHkPqzskoXiGuy+hnbkMDLC2T6ihRhiRNDwvuSYDhMInsw+tjU/CPRc8b6UvAXdSAfJPi7aklBn0/a+TIiyjNM80r5WWTLleOQKv9AO2+cuK94+ZC4UyYEhGT94fKm5baQFvz6QrJGz1f2+EC/N+sc5uL787pKxUTXzPqZn9OmGEvo+md/b8Z6I8z6BeReXFsTkPqrSiCpUjdo+0qqasNUm4T5ynjldolnwPvNaaQjKEBe/Rs0JQaAkCr9qN15xpULYvssiXgCQaP8+vrjhfgTYCD+oOBNc+PQFP4gAnRIg2/g+/hhUsXaM7D4MADQ9wmPnPquRslohiv8+CigT0dYJI7+GQaCn5ksUvzWoIJ3WZfG+0JcEbq/+Aj/D+xk7i8ASP2/HfqytDRQ/fAb8ELM7Cz/rkHla4x/4Pi4bd086p/c+nq4VxtxP4j7qSIgVpXoqv3zbpyJpchy/JH8SVhD1Ar8h0Emb0Jj/PtknJtawwxY/EqsfWDk2Hj+0+6VrlO0ZP7ud4mGjKAs/tCP+AyJD6j6YgnPZxysJPyPJZylMnC+/lhPaM1jCIb+N11MlxXQQv8i7J5lknd0+Cc+1U7MnFT+odkR4ho4iP8A+qHcHYyQ/T+qf8wjYGz+U+xhAj1cGP2LwZC2NkPq+oJ2VkvNDL78HtARLugUjv3Vr3/2VwBa/LUQ5GqRo/b5nVyzmJRYJP7CnjjFxGSI//syyBEsiKz94AWIgtigpP1qxyhqR3xI/wraX543BCz+6A1TH9SknvwlElYhrOCC/iGUGd+rgF7+Ci9y8WeMNv4DgB2GdHqe+8j+PP5TqGD+CJEeeMnYtP8dc52S8oTU/pMdfD6D4MT/5hM69OZUfv1PkRJutZha/DE4zP/HPE7+qvMZ5aSISvzQVdeoF3BC/g/9ZBQchCL8QGb2HcxnnPhJ0ZquiECI/AiissescNz/mTHgn3ANEPyh6PF9yskY/eKfTugSXA79TqfVEfXYFv9TY2zzx0ga/q/kzAU84EL8YFLsq5v4YvykUxw+14iC/tNPWT9s7H794gi/WmJoAPwrMW6YNDkE/A25i5oUHXD+6AiRblPUuv74ORJJdDCA/hbzLWJffEz+tNcS50PoGP7RH7JFKHiG/DPcaDEDw/j7+FIKrTUQKPzgnXS7m8vk+cHtX9BbxUb9mxw3m5KE5vypV8kVmSFY//3kYf471Lr+joKu+WgwgP95LFcuV3xM/fBrdbNL6Bj/n2tQfUB4hv4LzxzZI8P4+ynpBuUpECj9A5ZyX2/L5PqHI3+YW8VG/bFj3CuShOb+0sbbGZUhWPw==IA8AAAAAAADB18dSPZGCPmJOuIPz6IE+/v/x1L+Nx76sOYqBHIDBvnECq/dvjde+vyRy4fg20r4irwfLLpfhvjy3Go+LBN2+6V5OJzUX576+QBSfusbkvm1wr24oq+u+wNRn2f3Q676KiZ903v/tvsW6XBfqSfG+TLUEaeY57L5EQvDf5kPyvkd0lFIpZ+i+37fNCyKu4b5nRZ6wto32viG9mZKhlAE/MMwcfka+9L6MVR14Wv/3PjXyi7ImepU+sruq1KZTyr40uvkA1RrZvnH6uLJZKOG+mk3rqdlu476OmM4LOn7ivjPontQ2IN6+2QvAHpv0374PWxfPSMr0vhYNFERtMw6/sCcVGUmp6D5yyX2U3vOhPoIhn9HKp7y+giiSqPAQyL4Yz8U3u1XJvtCEWunSZsG+2NHvGLitsb4eYWKqgwTLvmSoSeRaPO2+/Oi/oD+fAb9jE0LFrGcDv58omjc/Wfw+ok0Ltgvooz7/Ch7aAsWXPkLWVD/t5rI+9+U/ZQZ/wz4yKPF7l9rIPp05mLuBn6I+bkruewXk4L5beP6pUFv3vkqvdTKf1QC/ZsKvLvbgAb9Ay5aF0vmvPvzHEgthP50+RRQfJIwuwj6Vr/ykcLzRPjH+dZma8tY+oP0cxYem0T5KEK8me5W6vv1hbZWEjei+VrR7gklg9r4VO70454T9vlOhc9+zMwm/6v32MSzQ7D5aJCN18U+BPhzECGu0pMw+Xj3ap7lx2T4mB3zEYBvcPlkjuaeTOs8+1nz1ybhLzb54L/pfFrHrvqwcZY62G/m+tOZOpFvtBL8hAGQneOMMv8Le997nj9S+WLhwbYw4jb4sebEQ6gHRPs6dckq0qNw+Y3zBgCi13D4LoiZIUcnHPioCB8C6g9a+OBo74wqO8r4KkyoGg4oDv3YF8qEiuBG/GBYT/D15F783vGsRTe8Mv/D6xgaOnKG+CmWTVEiK0D6Oy9yXIBbbPhjteIrvkdk+Blf7k+FlvT4HQcei5gjevq2mSC5Wsva+RHQAkFkYB7+IrlPyObMWv/R8h9bwJy2/LSP3CLb9Jb9cYsnJEGqqvv4uW9DWVMU+7mVgUh520T6dyN1iqm/QPmH20TbGQbA+Icdyx9ny1b5fKAQJLuzrvpIVQMbRdfC+adEJHc8T6r7Ykv1dGsopv+QI6lFzYBK/Te7pGCuDsr6uYHxlOimrPhyvIRLxZqQ+pLOt1wsftb52oX6/ppLTvhwvcnNqI+K+4DZcBSIl7b6VEaoPyWEBv4y67tGNFRq/Ve98qc/IL78olMpbbFcmP+HRRU7Kx9W+MFg3jWNk5b6HuhShpR7zvhQCIZCUIeG+JxVDhwqq+L7yhYlaVDTgvixytvxb7vC+AEJYkxwxiD4kxODo4GvKvm5E6iYHn+Q+ULwqKUXA4D64OJi6kC7xPmOq3w7ULvA+STBwbGap9D4awGNEcw/1Pl/6FeKq0fc+gBkTL/Wy+T4JT8ArSlD8PgCCsht4IQc/OvKjWscADD+6pcsyjZTyvtlwQ28jsgC/qFhTymJ8Bb+9PYMyU9T9vsljqmt24di+5PEOZ8wR7T78/fYM2bT7PkMnaBsvOwM//K2M1bkpCD+Wn/VRNrYOP24C/Yz22fa+C0vOesRpBL/oNdhxLdAKv0NkUEwFxAO/U3jHaPx14749KjQ9okXzPjHEGBs52wE/4nDKnRWOBj+j1+siDdsNP2aDhMxvxBE/PSkSyO2a9r7y1ZR0CL8Ev5wDO6H0wgy/A07oJ/ZdB7/ovCZ/aEPtvi6cHb8CDvg+CNLJTJC1Bz/iJ0ge5WwJP07V7uxHrAs/oz+ATJ5fET8dOYGobmPxvtxPWBL9zgC/Zl3igG6SCb8fUGV/tVUIvy+nGxR3X/a+5t/EHKeY9z6eFm7tZwAQPwfCGcZSOBE/mmdWXbaKCj+ejrpJU4URP2aKvAmpOtq+Z/3WqI1l7b7GdoT+fAP8vpwSykqO3QG/y3faFh0D+r4AhZAvNsXqPuYQoiSIWhI/TQhbmPUiGz9NOx7MCn8RP2UjG3ZoleI+OMCMGB+U4D4dn6n+y33sPo3hzJgPzO4+8rWJTtXY0z5cXbtjj8fPvurp97v2zeQ+SKLUMRevED/QgqZudNwiP4K31vLZEyc/NRTM67wiDz9xEBjUOrzzPh25hOYpcgQ/4UKIvRFAED+FfJBZHhsRP0t/XTx8Sw0/B9Ow+bSWCT9k8T6wU7oSP/YXKzHWHyQ/KDg4eMD5Mj+MjSA4Wtc3P/tzM6/eyfI+Dz7Gpu8KBT8ArlpGdGwTPxjF7SywPxk/tLzZf5XNGz8aUIYChdMbP4PRFc7X2Bw/3hRNHxDQIz8N3GKuANcyP0xyQbAyF0M/yKVFNzw/6T72sf3Uhzv7PlrfZVq0rQw/tgRiKCzhFz9PHs4Qx8khP1KHtU7SwSg/cu+RMlZ4MD+njvGKG9A1Pzs2M9HnQz8/bwQDvg+5Sj9e+B3LaJGCPvo5u2tr6YE+aeS8xLyNx77bts+bGYDBvjSvkAhwjde+9HiL//c20r4CkrH3LpfhvkxfuwWMBN2+qIuWxzUX576Wnu4WusbkvjEvrIsnq+u+kyrS8wHR677sfrai2v/tvj7Fdq/oSfG+UCeOjuI57L5gf6lJ50PyvkohhmksZ+i+/pgxvyeu4b468pEEto32vivd1aOZlAE/8P9n9D6+9L4I1L7gTP/3PiLQU0XpeZU+FPTz+KpTyr5J9/R/1BrZvs2lwolZKOG+QNybXNlu474xPIzZN37ivmDewewzIN6+tyPKM570375LeegBScr0vgA4BO5sMw6/jM9H3Emp6D7kCNbVz/OhPoCEa9nLp7y+BJot6e0QyL5yg1MNwFXJvmx47SvYZsG+Z1RK4LKtsb4iPAoAhwTLvnk01+JZPO2+qo3E8j6fAb9eD4v9p2cDv7uiqhxHWfw+5v54//Tnoz50bEjN5cSXPjRDJA325rI+oO9bOBR/wz7lvFEUjNrIPmqB2hJYn6I+wle1YQbk4L6Mz8GfUFv3vhIItdOf1QC/RCBSivbgAb9A21OIDfqvPj2vYvRAP50+H3/rAY0uwj4sWkfAcbzRPuB2hjuc8tY+6TlsA4im0T72UX0tc5W6vhT5ml2Djei+d0YfxEtg9r65enjn5YT9vkKiBAi2Mwm/CJou5C/Q7D4eDMtJXFCBPnT39dmxpMw+KllHQLlx2T5RV2NaYxvcPhWqIa2GOs8+bpe4GM1Lzb4ibc3HEbHrvs7PToW0G/m+8Sak1FvtBL9FzXqVeeMMv36k927fj9S+bqn7oWw4jb5OXPo86AHRPpG2g0OxqNw++aNltCu13D7D+gKhX8nHPj7JS3jBg9a+IM7dvAyO8r40AdhxgooDv8eJG5QiuBG/TCPp3D55F78KSTrsTu8Mv5Tk369tnKG+FXrZGUiK0D6lOaPJGhbbPjVA5C70kdk+1Lf9tQNmvT660LP83wjevi0XA25Vsva+GKNOC1kYB7+Q2DroObMWv3sbytDwJy2/9LuHo7X9Jb9s5KXrPWqqvqKmnQzRVMU+xqPydh920T5ppGPRqW/QPjTqjaC2QbA+XKZ/0tzy1b6KKDvxL+zrvoS7uorPdfC+y/0Ivc8T6r52l3CiGsopv/xItA50YBK/UOVQ7DODsr51MD8fQCmrPry+7i4LZ6Q+fP1idTkftb4iZ0WGqpLTvliCC4tsI+K+VyXiDiwl7b4fGW0iymEBvw0ves2NFRq/qvQ71c/IL7/ccWKoalcmP/TIBIfWx9W+uuIbI1hk5b5lN22Lnx7zvoRRS+GUIeG+zAD+jw6q+L7BGNdOQTTgvsOlDzNb7vC+gFyzFIwviD4e9wRnvWvKvuZ36goRn+Q+PBi/8EfA4D6BpLt1mS7xPkPAlq3VLvA+2jGb83Gp9D5NvuhCcg/1PhgDIWCu0fc+oIQzHPKy+T6UcyDeRVD8PjVgDA51IQc/aDqOKcQADD+RYEYNkJTyvpOa0N8ksgC/KLAR7mN8Bb9BIGXlUNT9vq9lhnqJ4di+Jk55zMgR7T6TuyIu0rT7PkwVrhwvOwM/r9LXrLopCD868wLqNbYOP4qEM9r82fa+8a8x08ZpBL+VlCZoKdAKv8AeVrEExAO/RM3Pbgp2474yUnUbnkXzPiAhCLc42wE/eg0BwhSOBj/04u7eDtsNP7yw601wxBE/F4XyY/Wa9r6uk8t3Cb8Ev2aux0P0wgy/NM7TY/hdB7+AJ4/pZUPtvuIT7XcADvg+NqT5jJK1Bz8ezGFy5WwJPywpGO1FrAs/+JsNKJxfET+FsKWweGPxviEB5Gf/zgC/u+ryXGySCb8Btpg7tVUIvyKLwLpvX/a+kzrtOamY9z6c16ttZgAQP53xLPBSOBE/0jAeqbWKCj9mbhGYU4URPwBsb76jOtq+Z3jaNoNl7b7YmxcHewP8vqrw+L6S3QG/hkJ4IB0D+r7U0XnhLsXqPgy5jieGWhI/EwbeAvYiGz8J4/KEC38RP0jxMoR3leI+pUCc6BOU4D4XBOlPx33sPhWg9Ebzy+4+2tz38NHY0z7kzNSlpsfPvv4NcpQBzuQ+WGeOhRevED/2si/EdNwiP9hitmLaEyc/hndoOsAiDz+vEOYrRbzzPuaTohsqcgQ/I/awyRFAED+sMei1IBsRP6RCxBl9Sw0/iQtMJrSWCT/HgX93VLoSPyyXSQvXHyQ/s7y/08D5Mj/KNbRdWtc3Pw4yJDPWyfI+IDL0Zu0KBT98K/RTdWwTPxoD5P2xPxk/oHav8JTNGz9vr16TgtMbPwNsTZ7Z2Bw/DMXGCxLQIz9u8xuIAdcyP8dPi64yF0M/mNBehSo/6T6vRxHkjjv7PkQ21n+zrQw/65+rKCzhFz9Y1oj0xMkhP1h4fMPSwSg/GtK70FZ4MD+knZpoHNA1P07FtTfmQz8/6Kq1mA+5Sj8wzBx+Rr70voxVHXha//c+sCcVGUmp6D6fKJo3P1n8PkDLloXS+a8+6v32MSzQ7D7C3vfe54/Uvje8axFN7wy/LSP3CLb9Jb/kCOpRc2ASvyiUyltsVyY/8P9n9D6+9L4I1L7gTP/3PozPR9xJqeg+u6KqHEdZ/D5A21OIDfqvPgiaLuQv0Ow+fqT3bt+P1L4KSTrsTu8Mv/S7h6O1/SW//Ei0DnRgEr/ccWKoalcmPw==IA8AAAAAAACjr1ltLKgwPWw/empRwdM8MHwl4nbidT3ETlNj25RhvejTgXfPgne9jmuL7QrJeb12dqaqB3OGvSJKrKGvlnm9fiTiy+9kcz38V/nAnBONvaaF7Yiobpu9Cgh9vLFflj0Mlt3Zil5rPXyan6ORBl09mlHK7DbJsr11b5r4Cy1qvQNMgGybBby97aowWrgxnz0iCG85gd/Svbpix6PXhb09sgoDrQgYyb0Y+QU9u+2hPdjE0EPpgRU9g10E5g2jfL07K+KcUzKRvfmKrHM84iI9/Gf5XSETVT0EwtuxL+OGvYeBqkWAyaK9NUQrDfNXq70CydYzbsuwvRRRUCkkr7y9k/mLJdUwxD22+PFwUcE7Pa5br92GWJG9ZAPuul2ugb0iM37FT5NtvXo/1Ng/Do49oUYpcY9reb2ie4FqhzCHPWHrgbKKiW49IPAUyxUvlT0ujNZ2qYGvPWDgKXWFgbG9cNdsRPTYCL2IZSC82AdwvV5AY4v4O2u9zB16y7ZSlb2kXVdN726VvWBRYGAUtaM9ioLSSDzvhL07cBrvXnqePf7mARAAY649PIoidOuqrj2ARPhPVjyBPdiiaaW4vUe9KPv/5rxiYj1ta/kJWeyAPWzpoE2HtW294MBhxK05e70h4DfNaupWvRkCMzacsrO94WmGB2uQnj2ooxbnRlqhPZSFwGA285o9qQqWmVYmwj3/hoTpaVtDvcZ+DeOIeG892VRtSJvLlL2UJ4VmdQBsvVSNBee2wp29qEiXBt0lmj3RJm2aqeCwPVKNBee2wq29TFeRZ1g/l71MbDnukju/vdJnA0RWKcA9fA41yKVYPD1tOmzayYeEPRCCTr1ve5E9pAVgCkYHkD2hco6blKKrvT6kK5fL1LG92ASzyLdqlr1OlqXSFnVkPYjF8MUB6589BKTKE2lElD1itwPpv1q7PcVMktSfqhO9Z1ZSQhjGdD0BUoWGqs6hvYwHe67pG0g93tD4GhXgqT2o49xG+yKhvYKUCvKNa549AKjTLKOypr1IAJ0rRHOrPelTpSruPL29s0OG1gnQsD3iGygLVeJNvSYE4mIpv2Y9vaNDcs8Uor3U+MVkdXGbPVQ/eQM1w6A9TMQvckLNqD2FXPbePuiYveuENn9geMQ9FmHz/OC8pL0AaXNLo7yQvTS/dV3fI989j+sXrXNaWT2n28HtSwZ9PfAwUV6xApO9n6COSYaNn700Ne8ba5RQPaIC2GyFOq699vBT8FWot722GtDD35vAPfg0iRjfXje9QAcHicpUuD2J/gVi8l3HPaoSVYUh6MG9GaUSA0iowb2wP6aUN2etvaywC2IiO7O9v4PFmp5Syj3i3wXPx6SoveN8Wz0Yca09uD6Qo/tIrj1IANQ56wTHPYLUcGwznZM9dKdmw1qSwz1qzFojiMy8vTPlUcfcKrs9hjN32rtFxL06UvDRxrisvcIDOds1wbq9j3og/Napur0Ahod3/1/DPVQsi062v8I9NWvwP7oB1j3zA5IyTWDQPZGK9c02/dA954qQe4fE1L27KfzFYaWXvfyBLtFMPcY96gSzyLdqtj3dfHS86ZO8Pfl1Cl9jsq+9boeDkwCuw73iLC/GpXHBvacCv+2zF6+9qgqjOLyipz26xPNTl++PPSH4P3xbLqk9UP0SEJD6sb0IgD6w44jMPRICNPWViL+9QKzqvYpuQr04APLIwHOjPeIP7zDRKLq9xss9R7hgxD0ueOW6leKnvSp/r/0qW7893+rI0gCpsr1hjp1jDtvFvVMmeZVBere9cgVXQKcctT1PnyKTQ3CgvcX+DiyRSMI90rTdbLUXur24ZdKLrSLUvRWWQdbQ6Zc9iLMDmiTXw72MkWdXCNC1vcYDOds1wbo9i2uL7QrJub1pTOfi8F28PcGxU1EBn4C9pOswLEV9qL343x5OmcfHvcwx4BBqMLC9Tbx9Jd2Hzr1YSG2RISfYPW4n2gPyALS9loDiJ9M6yz2T88n52J+zvdlxb2J3Z8S9xADIPlNrsL2wyTYhwew/vVIAnStEc7u9BUoavv25sD2CBdCkh9a+PSKeqKXBxqQ9Gjzn3Ns12L08i+R6sMt5vXoQXJoZSc29EntsugK21r3sZytcxFiTPTDi4Cr61LC9uhI8BlDFkr1wY9OX1N92PQbYU4JiX6690jGpAsOe1L1QE4vgwna5vYzrmjFcrI092MAiiru21z1qyBr8pszOvWJMGeGTo3o9qxXfoNVgyz24A9n1JiqwPQTvs1xlqMg9SErsefUSwD009/eMfMqLvTpHm+rb17k9GAMc/2VVsj01NMa0Lve6valziLfkdpE9Pvg/fFsuqT2LiOXAqgrcPRRFEnlvK9s9Rx41ZSpYtL1RU1FAdz+5PWh6jhglzcG9X18lJegV1T2wZYL+NG6pvaYwf6K5qbO9Up8ik0NwsD222GnQOtPRPXCuMAbwCsu9cBBIK0xyu70DRfXBwDcxverHGRrkIi49hM0blcKmcT2jHcPr3etDvfouerwZcXi9ar1lL61UYb33TEwg7oyHvXDbCLEl0Hy97DhVtoKobz0EWPnAnBONvdvGNQIq0p69M2C016BDkj34X5KOMDaIPaYt8I0Lk1c99EtvN5CQsr3axD7RC1h9vZdA4SPS57u9snnvsDlnoD11QEp9MqXSvawOYzHPd7s9/U6egPayxL2sRjdLMqKhPSB513X5sbs8bboFOZiVeb1+d9qNLz+SvZHkrU/teGw9wMY2IcHsL73bOSRBgVKTvc/dJKSXUqe9D81QhT0Cpb1mgEnXz0K2vXlbVjac3ri9BlwBG92rwz1GsqTXRqs2PUTGTQL/P5G9JmSWl2ZYfb3Yz69sPKZwvVEvFKtwYpA9GPSG8Jl0gb0IjgK2vROSPS7P8nV70YK96P1/edgapT0X+Lg92D2nPdi9tAkgBpi9Fuc8ZJuPKL0mPK8PO85wvW4vUDKsaFW93nZhRHt4lb1XTG5+EKSSvdd4qR6o0qE9uq3Plz+EXr2IzdQQCnaYPY6gFeWl06U9rOdWmMpZtT0AwWHErTmLPUE92W9Ew0E9sMXCgflDXz3TIsRmfgl5PQi5XvEC6Fq9uEWqREzPQ70cN7cBnUVivbpos6Era7S9MALEWlS5oD3a+V3hzImTPaHxC9cSMag9pKfIBbf4vD2kT6YxvGZFvWBqwc+swFc96ecIaJ90mb3zVxJAbjZcvQdHAprY36S9Ls3p1UD6mT3gqTPoTTavPeY+vmnBvbG9ASpgwqcwZD2M/XRS7GC7vdVzD/ZnZ7M9vMJ4f/kIGb1f0A3djm+FPYV2xpYqsZE9zHC+Zk4sjT0++fE2fj+svZHIAhspo7K9PmJt6mJmkL1k8oEK+juGPaC0S4kDO6E9OTZfKlNnbr06PhiVhDy0PURj05fU3yY99JKagbCvcT3ezxsyt+OkvaVs7Fu7T4a9FdGpK/Akoj3v8KN9zlyivUiOdgqagY49wvxumKBIk73bCx0mPkyTPao3EtenkL+992d22TjBoD3QZeb6evlFPW4mEIn3om09CozyqDEhnb3+Z7UTK0SkPV1Dm5tAVKI9wnzi2De3oz2tVRMd2EyCvQVCzArIwMI9IKnqvYpuMr3254UdiqSUvSo2VRMUguA9GG82/MWhTT1VWTH7SD92PRGXTv1tHZy9cLb70SZzlL06VC1muSBQvZ7ONX+6/KS9XmwBIfLTt72H3Gkf1la5PThFDkGSWnC9W9R1fDfpwD2rze2P25i3PV01JyPffae9GKUSA0iowb1BZG+bjlR6vQl3a80TOby9crKiK3RQxz1aXGT7jAugPZY30IBuaKE9/ufpGdAvsT1mJ4JKLlvRPYRFDkGSWoC93e1S7rQhzD35tp9JFiXDvaRQYtITjsM9HllBsHt3ur2usAtiIjujvWXMc6JZ77u9hXog/Napur0EWOBBy/C9PWmDYfv0HMI9z0L3I1Gi0z0ACLTKWPHRPZ/hy3p1WtA9WF0UWWJN1L04vRqyOOyTvcoLBKdsKcQ9wt1ccTi6vj0OlGZ6nrmvPTZLDRBgHba9eME3OkAxuL2TucXFIGjEvfA6mMZs/Eo9JRylhmyQmT3wrOq9im4yvXSxIVNeWXI9NHGU3OAjmr3iYOoyQtLJPbKS4USKeaG98gX7t5bOs70atCB29EKsPTka9T1JWLa9/tTi5X8JxD3x5qEq8cujvZaIbRvEJp49/DXvG2uUYL02A5SkTDnQvb3eK/w2ZLK9MFZJeHnbuT0upaTm+YS6vSGUjdMSE8c9jACm9eJdxr3UZjP6XanQvR41wyaZ8pq9nDfp/z+LsL0sYlRrkUPBvbpHWOGcrMc9bFxk+4wLsL1R8e6dpm+7PcdA7oMWy4o9ooJkLO7Lvb0wjl2LyF6/vVJmP/X1Qse9jaRui1j2wr1y9hnrnuHWPXo2AfZvvr29accwdONTxD1Jlg/YLaSZvenmOB6n9Mm9HmVlImUCsb1U3+jy9ziwvaaR+Tq6rL69gJrLmGOogj3cNcuazi+2PfjUyWau5rQ944cHH80h172wyDYhwexPPYS2xMN/4ci9SGQuKXB61r29MeAQajCwPRvgN81q6pa9rr9jiDONbD3c+V3hzInDveTLtquYGr69ULWaY3bs1714wTc6QDG4vWqmsLctC6+9cpgpblJX1T1vG88Q2pjMvUTi4Cr61JA9pGiTtQgtyT02pb1ly6e5PaiR+Tq6rM49hHGEJ67rxT3VwHpDf1y6vS+CN5vrJ8E9L0MUXb1jkD1qNoiRjwS0vShvBP4iXJ89ahTsTnP9tT09RjzZeCDcPWRNB7phktY9wTHgEGow0L2oXVdN727FPdhA7oMWy6q9HWjWvkdYyz2Jr6rzcbSmvVb5oOoLtaW9H0PJ30j7oj1VXbyfnqfRPUetz5c/hM69yfcMhEJGeL2yCgOtCBjJvRj5BT277aE9k/mLJdUwxD1g4Cl1hYGxvYBE+E9WPIE9qQqWmVYmwj3SZwNEVinAPWK3A+m/Wrs9s0OG1gnQsD00v3Vd3yPfPYn+BWLyXcc9/U6egPayxL2sRjdLMqKhPQZcARvdq8M92L20CSAGmL0AwWHErTmLPaSnyAW3+Lw91XMP9mdnsz06PhiVhDy0Pfdndtk4waA9KjZVExSC4D2rze2P25i3PQ==IA8AAAAAAACjiRj+/1e7wARk1v7/V7vAu87Q/v9Xu8Ba8Av+/1e7wHFbwP7/V7vA4Cvm/f9Xu8B4raX+/1e7wAiYp/3/V7vAEMOA/v9Xu8AM91H9/1e7wHq3Tf7/V7vAhEfr/P9Xu8AX6/j9/1e7wH9nhfz/V7vAPMM3/f9Xu8A09FD8/1e7wP4SHPv/V7vAvFrE/P9Xu8Cg1R71/1e7wCnr2v7/V7vAAr488/9Xu8Cyv3UBAFi7wGtT7P//V7vAzezz//9Xu8CGDQwAAFi7wMB9OAAAWLvAQY1+AABYu8Crw+IAAFi7wMm6ZwEAWLvARgklAgBYu8BO5NEDAFi7wNT7ugkAWLvAgnLsBABYu8BBBMcAAFi7wJUP1wAAWLvAqswGAQBYu8Bw1VMBAFi7wAqWtgEAWLvAptIgAgBYu8DX24oCAFi7wCRAIwMAWLvAOFZyBABYu8D6otgFAFi7wNY3eAIAWLvAkHMvAQBYu8ByND8BAFi7wBpgagEAWLvAbR2kAQBYu8A8CdgBAFi7wJrE9QEAWLvAlL4KAgBYu8DHSTwCAFi7wOCeCAIAWLvA78HQ/v9Xu8CupSP5/1e7wMQFKgEAWLvAzpU0AQBYu8A3qE4BAFi7wDBXagEAWLvAGBd9AQBYu8DxrpQBAFi7wOQM3AEAWLvAxINaAgBYu8BNR9MCAFi7wLAOlgUAWLvAxkZMAQBYu8CXz9EAAFi7wHSi1gAAWLvARGXhAABYu8BtjuwAAFi7wEux/gAAWLvA1dkvAQBYu8DIsIcBAFi7wKkv2gEAWLvADGB2AgBYu8CHo2ADAFi7wGzuHf7/V7vArMREAABYu8DzI0QAAFi7wAVRQgAAWLvAfMpDAABYu8BcIVYAAFi7wDXEgAAAWLvAEvikAABYu8ABEJcAAFi7wKSS5///V7vAFehJ//9Xu8BMojQDAFi7wDZvn///V7vAtL+W//9Xu8CQrIH//1e7wAe7b///V7vAtS52//9Xu8CubaP//1e7wBbLDgAAWLvArd3cAABYu8At83QBAFi7wNQ/DfT/V7vA0pyL0P9Xu8AujQD//1e7wMnv5v7/V7vAHxWn/v9Xu8DU+WX+/1e7wEFaWf7/V7vAcj3J/v9Xu8BpPS4AAFi7wD7XpgMAWLvArzo/CgBYu8BI7QohAFi7wDetvwQAWLvAZ1qO/v9Xu8BKCE3+/1e7wPpTpf3/V7vAQILq/P9Xu8AYjKH8/1e7wFb0XP3/V7vArvn6/v9Xu8DUwQX//1e7wKhaYQEAWLvAab8dRgBYu8CT1jl9AFi7wEGlqAAAWLvAxjG0AABYu8DTK58BAFi7wNu8GgIAWLvA6fNLAwBYu8CJJkwFAFi7wLIqrAQAWLvAwnwiCABYu8Ab3x4FAFi7wNpTBQkAWLvA60ygBABYu8BybB4IAFi7wGK9WQMAWLvA0BoaBgBYu8AKQlwBAFi7wJjTvwMAWLvAgY8C//9Xu8DExvv//1e7wH7G2vf/V7vA8ZBr/f9Xu8BCnn8AAFi7wMfYAQEAWLvAlO8CAgBYu8CML7QCAFi7wH46pAIAWLvAuHb/AQBYu8AlmxgBAFi7wNO85P//V7vAlfx9/v9Xu8BSvMr9/1e7wCApfgAAWLvAV8V9AABYu8BlnxABAFi7wDZNYAEAWLvAmLj6AABYu8Bm1PD//1e7wJSL4P7/V7vABEAT/v9Xu8CUZyP9/1e7wFn5P/7/V7vAq3KPAABYu8DI6/n//1e7wNbNIwAAWLvAyFoyAABYu8CHEcH//1e7wPCVef7/V7vAFi7j/P9Xu8Akm+n7/1e7wO+lBvv/V7vAUXBD9/9Xu8C954wAAFi7wDr0U///V7vAnhnf/v9Xu8AfpH7+/1e7wE7HJP7/V7vA16Mr/f9Xu8BDhFj7/1e7wEdtBvr/V7vAuMsv+v9Xu8AvA4r6/1e7wOoEYAAAWLvAlEGQ/v9Xu8BlRS39/1e7wHh7zPv/V7vAalXv+v9Xu8A9hzn6/1e7wLdA0fj/V7vAtTcZ9/9Xu8DrMWr4/1e7wFpmffv/V7vA1p8WAABYu8DzkBH+/1e7wC/g0fv/V7vATpsO+f9Xu8BSW3v2/1e7wGwZQPT/V7vAUsS28f9Xu8A4HQzu/1e7wKCFvev/V7vAyNDw+P9Xu8DuWAMAAFi7wNgWp/7/V7vAgWe0/P9Xu8CVn8f5/1e7wPmE/fX/V7vAxFFb8f9Xu8AGrjjr/1e7wMA/W+H/V7vAHjOKz/9Xu8ByYdmx/1e7wOzcyAAAWLvAxsP9AABYu8A83nwBAFi7wAjclQEAWLvA6Lr6AABYu8AgInD//1e7wG5BlPz/V7vA6Qco9/9Xu8BfRR3r/1e7wEVNkc3/V7vAsyKsAABYu8D8IoMBAFi7wFQ1HAQAWLvAkSvbCABYu8AMdoMPAFi7wNIz2xcAWLvAWszWIQBYu8D/kPAtAFi7wCre0z0AWLvArihIVQBYu8CmiRj+/1e7wOxj1v7/V7vAwM7Q/v9Xu8Bg8Av+/1e7wIxbwP7/V7vA8Cvm/f9Xu8BhraX+/1e7wCiYp/3/V7vAHcOA/v9Xu8Di9lH9/1e7wIK3Tf7/V7vAaEfr/P9Xu8Bd6/j9/1e7wKZnhfz/V7vAz8M3/f9Xu8Au9FD8/1e7wPsTHPv/V7vAUlrE/P9Xu8DE2B71/1e7wETq2v7/V7vAiMA88/9Xu8DnvXUBAFi7wG5T7P//V7vA4uzz//9Xu8B7DQwAAFi7wLB9OAAAWLvAUo1+AABYu8DRw+IAAFi7wPm6ZwEAWLvAcAklAgBYu8Bv5NEDAFi7wJ76ugkAWLvAzHHsBABYu8BQBMcAAFi7wJ4P1wAAWLvAoswGAQBYu8Bc1VMBAFi7wAOWtgEAWLvArtIgAgBYu8DW24oCAFi7wBlAIwMAWLvA/lVyBABYu8D/o9gFAFi7wKQ5eAIAWLvAmXMvAQBYu8B/ND8BAFi7wC5gagEAWLvAhB2kAQBYu8AOCdgBAFi7wJLE9QEAWLvAr74KAgBYu8CcSTwCAFi7wKCeCAIAWLvAm8DQ/v9Xu8D9oyP5/1e7wLoFKgEAWLvAv5U0AQBYu8A4qE4BAFi7wDhXagEAWLvAIRd9AQBYu8Ajr5QBAFi7wMsM3AEAWLvAaoNaAgBYu8BmR9MCAFi7wIwOlgUAWLvAWkdMAQBYu8B/z9EAAFi7wHCi1gAAWLvAQ2XhAABYu8B5juwAAFi7wDSx/gAAWLvAj9kvAQBYu8APsYcBAFi7wNwv2gEAWLvAIGB2AgBYu8BOo2ADAFi7wMruHf7/V7vAosREAABYu8DsI0QAAFi7wARRQgAAWLvAscpDAABYu8CRIVYAAFi7wCnEgAAAWLvA2vekAABYu8DyD5cAAFi7wMqS5///V7vAbedJ//9Xu8BooTQDAFi7wCpvn///V7vA17+W//9Xu8CbrIH//1e7wO26b///V7vA0C52//9Xu8DBbaP//1e7wBbLDgAAWLvAid3cAABYu8Bj83QBAFi7wOI/DfT/V7vACZyL0P9Xu8AmjQD//1e7wOLv5v7/V7vAChWn/v9Xu8Cx+WX+/1e7wF5aWf7/V7vAhz3J/v9Xu8AsPS4AAFi7wGbXpgMAWLvA9Do/CgBYu8B97AohAFi7wGStvwQAWLvAYlqO/v9Xu8BWCE3+/1e7wPZTpf3/V7vANILq/P9Xu8BJjKH8/1e7wHD0XP3/V7vAXPn6/v9Xu8D4wQX//1e7wHpaYQEAWLvAsr4dRgBYu8C51jl9AFi7wISlqAAAWLvAGDK0AABYu8BZLJ8BAFi7wOi8GgIAWLvABPRLAwBYu8CoJkwFAFi7wL0qrAQAWLvAmHwiCABYu8Cy3x4FAFi7wJpTBQkAWLvA5EygBABYu8AWbB4IAFi7wOS8WQMAWLvA7hoaBgBYu8BhQVwBAFi7wPHTvwMAWLvAvI8C//9Xu8CZx/v//1e7wErH2vf/V7vAaJBr/f9Xu8Aenn8AAFi7wL7XAQEAWLvABO8CAgBYu8CgMLQCAFi7wJQ6pAIAWLvAenb/AQBYu8DKmhgBAFi7wGy85P//V7vAf/x9/v9Xu8DvvMr9/1e7wJ4pfgAAWLvAS8V9AABYu8CInxABAFi7wP1MYAEAWLvAD7n6AABYu8Ap1PD//1e7wDeL4P7/V7vAX0AT/v9Xu8BkZyP9/1e7wLP5P/7/V7vAn3GPAABYu8B+6/n//1e7wKjNIwAAWLvA2lkyAABYu8BzEcH//1e7wKyWef7/V7vA9C3j/P9Xu8Bdm+n7/1e7wG6lBvv/V7vA5m5D9/9Xu8BK6YwAAFi7wNj0U///V7vAdBnf/v9Xu8DHpH7+/1e7wF7HJP7/V7vA0qMr/f9Xu8BfhFj7/1e7wJFsBvr/V7vAgMsv+v9Xu8C7A4r6/1e7wOIDYAAAWLvA/EKQ/v9Xu8CKRS39/1e7wMx6zPv/V7vAbVXv+v9Xu8BOhjn6/1e7wEVA0fj/V7vAbDgZ9/9Xu8DmMWr4/1e7wORmffv/V7vAWqEWAABYu8CykBH+/1e7wOLe0fv/V7vAApsO+f9Xu8D7W3v2/1e7wNkXQPT/V7vAXsW28f9Xu8COHgzu/1e7wICFvev/V7vAlNDw+P9Xu8BUWQMAAFi7wPQVp/7/V7vAgGe0/P9Xu8DVoMf5/1e7wKaG/fX/V7vA2FBb8f9Xu8CKrDjr/1e7wCRBW+H/V7vASTOKz/9Xu8CcYNmx/1e7wKbbyAAAWLvAasL9AABYu8Dj3XwBAFi7wHbclQEAWLvAILr6AABYu8BoIXD//1e7wGVClPz/V7vASQoo9/9Xu8DCRx3r/1e7wIROkc3/V7vA+yWsAABYu8AUJIMBAFi7wB83HAQAWLvARCvbCABYu8BLc4MPAFi7wHw02xcAWLvAlM7WIQBYu8BAj/AtAFi7wPDb0z0AWLvAHypIVQBYu8ACvjzz/1e7wLK/dQEAWLvAgnLsBABYu8DWN3gCAFi7wK6lI/n/V7vAxkZMAQBYu8Bs7h3+/1e7wEyiNAMAWLvA0pyL0P9Xu8A3rb8EAFi7wJPWOX0AWLvAiMA88/9Xu8DnvXUBAFi7wMxx7AQAWLvApDl4AgBYu8D9oyP5/1e7wFpHTAEAWLvAyu4d/v9Xu8BooTQDAFi7wAmci9D/V7vAZK2/BABYu8C51jl9AFi7wA==IA8AAAAAAADkTEI6eu/9vJqJaeuKFnq9DYS2+sGkgz3YHVMLkz1vPVYErQ4AZYE9QHSrg+q1Zj3YsUe0mr6GPTavBZT614I9rqt3QrNzPb3KWnMhpGpWPTwIuymTW4y9tIX7c/lrgj1GA0XRBHehPTETCBhrJ/m8tHEvHOx5oz1fhdHhC02BPZWXLSoZf5g9/x7MBuA3sj207N2q8srDvaKj090JbcQ9tBkdWQ2ytL2AfQeZhDldPZvfbToBjok9eByp4K3kfL2W+9CGHpBBvfDty+HSuXw9rkKlyMj8cD22d7VS5xtjPcYvtQI3iIg9aP+hSaRXhb2gHWXr4SS6vZuWISMAZcW9jnuYi9+xYr3X2cAp0q+GPVJipxRRnVa9uWAlHU/RgT1CDISck6RjPYG5lm9FsYE9rvvDQzB3ir1CDmvGEvORvYdl3LBzOqC9pkVIhq7Slb2Ai05c1cmgvczxsvAGHom9FuEe+sUkgD0T2VR8xnCJvRRLj3y0WaG9mt340Y6EVj3GNBz5Nc+nPcC5/g21jqK9znqg7kAwhL3BA+Ehcht4vcAPPBPFWYO9XOssvuQ8n72srF+QY4ChPbJHH3aoS329E5qqFx1vl72l98Yyp2d8vaoh6pPtyII9O1ubXQdAc726F/y9ifGOPVVoyGZi72U9hgdu2yoHbz1Gb1cj3S+ePZAsWrJJ/L49OD8Hq//CrD0L2wRUJ4djPRsa4cclEKA93KXL1+Kamr2iRcjAAFeQPSfSgaEzlmm9yp09mcZ1cL0/uaSBaqWuvfPWnqdfLKI9SK2vYuhGoj20Bx9+AB+UvVZV5yosObu9P/jChJJwoT2ErmZ5SQKnPS3JHNuxaWC9flmkkCvXdj3cHz1kVEGUPc9wPxX1k4w91+AhxxV3oL1yRGJG5QClPTQSM1rjLKg92qFGsgDkgj3a3xK07ZWmvdjhnvVmiYu9kfFJCY50oT3DfjkdHYqXvV4MHe2WnJi9YJ+GviQlrD2wVOnCSEGNPUQ19SQ8OIm9VryXe9F4sT0qvi5Zap+xvWXDfD3BaIw9DD04Q4BKmj1WRsZOAX6gPaSLFV/nvKK9d5JRBJ12or3BRFcHikikvT5s0/deiqE9xrOUeBxpqL3X9DiHx9+Kvbgz/yh5Lbw9AJHjCBDNEr2NL0K20VmGPUFj6ATkEqu9WoZBOUzqb70hTsW/OIKgvcZ214wUjYQ9WkhM5gQTgb3YlplW7d+vvbYEsWtqm4e9OS3rrVAroz1xLtkb1uGhvVjeSOOlc7E9zp4ys77gsb16BFpanMXOvfXIExETf3W9RFHPO1yupr2GxOCCHRKhPYazA5ok16O9C61+Efp3aL0gWNo4+kx1Pf/mrC3o38M9BqwORIBml73zK+AqVFnBvcSg56CdLKU9ZP6rS+Hotb1OCGj3etuUvemigiSK4Ia9Tail6JoLtj1c7V0qU+WmvWhfib4XYsG9jJMgasryo73ArRMqIJ+SPRHX2jI0r6U9EvfYBNoDhD28qhmV0DOzvdLBmhrwkLQ9uJ9ooxc3nD2mqKCZdSbCvVSNBCi97LG97TWUjCeeur2UJJI+d7CoPRP6G5ENS7E9TBr8qppzoj2X3JLHgLV7vRO72mDz2JM9wrEKAvZxtT3eylbbO42UvXiN7QU5mZG9sVliQGyYpL14qkiY0rCfvZNiIm3u/WK9ojnendYwwr3qxzLXqgyvPX7zY5VWV7W9NA/omRB+uL2kEyaOEz6NPQnnZQxG7no9MUUHN1d+pL3xFIBQURCnPS5Cxh1P4qs9+P335Ot8Y70KlyhX/8ZYPXV6p5f275C9k6ckc5tToT0+oCqq3Fenva9DLo4ITLc9pJX6J6kpmT2qFTTQTDSwPdJyQGtpvZ+9QOXEysTvvr2c8pqJy151PRjTjIgiL8Q97vqsDhl1sL26h+ylxG6pvRacHzRVGqa9svVal5A9mj3E2NH/Dxiivaix26sau6I9rwZFrizTsz2AUjPGU9qdvTDXpYHa7Kg9uONFNco9rT2xNIi78xeWvdvhhsTMGr+9vhImMgMmxb2QLSbnVH2lvbbqMEH3hqm92HNwuOuQp71+cEOlIKOUPTIe3atmspG9OtbREv+Vvr3kNdNVV/+0PZJIyn7evqE9I+oSiLKIpz0UM0SbYVynveriVZhILsG9NqgliCtYub2qrYIFaJjFvVY6sdUNSqi9SXXHZFynoj2wBctSpfy0vZmqi4mi3bq9O51CJw30ir2PLXWXWJ+mPXpIW1N6gM69RxuOeZpGur0gbSE3hKGovWSiys/HKsO9vKrIijw3ub12sFaasrbAvXqAveYQLrC9EuOrnsGKcj36Wl8Yqse6vRnnM152g8+9p4qT9Gq/g73cvav9oo3AvRjiAMcAzsu9bpJnQlbGtL0koUMU/HClvcXYZDTdimM9lukNTj+tpD3Qjh1ZNVa1vdBlVQWnhsW96+mzz6L0y73V8wExs3oePRLyjssqh3q9tBr89YoWhD1lhM+X/5NtPd/vQiNl54E9VSg3Gx4oYz1KjJJTLieIPXnUdeN6t4I9G/IuY5KGKr35I1Jgt0pWPRHmrbqZnoy9mb+cUKUagj13eyEu0YahPTpQmhK/nPu8H425mMNcoz2l+EOTukeBPWCZN9/WqJg9KSrbzf47sj1T++iDqefDvRRmA5ozdcQ9q3HTwCdGtb0AAEofesfnPAi5GZOo5oY9kCoBlYxIfb2cIOhLUgNVvUo4mhlSrno9HCAPIEyacz1Uys94w/ZoPeoC4X+hjoc9VYXFvVAlhb2iY/sNChC6vY5tyZk8c8W9/tzhuvkeeT079eHf1kmKPThnFqw/3lI93npBQI1sgD0z72GWlMpoPSjLtZNLIYA9YjaEIy/Eir3G9M25XreQvcex5/u0PqG9UF+BR94Tlb1RnNnrJaWfvQyIYe6KBHW9DsXdcso/fj2wui3jAJiJvXpWh6uJiqC9ToD/YD/8Rz3Kuy2wHDyoPZSuJANtlKK9tt5n7rqihL1bkSd/wlNvvT/VagQ1gYW9pjjNTlDHn70YfIV09amXPY2V7YhDrYO9y190syBpl70u4Xdyg6B+vcmR4Vk8g4I9PPhk25j3cb0wAY4dnBKMPX4QnTFZm289EzuZu+hwcT1Q3xu36sWePY7BH8JRCb89zNX9MGG5qD2HZmE+ZlBxPQQx1QTz06A9GKxLsx/tmL2agyQA1ayPPRMtYWesYWu9u6pTv75qeb3QfHRzbCquvRJJdAfziqM96p64JFOuoT3GiYjS8wmRvROZbGrKVbi9CbN3U8+ToT1vGiCXz1qmPWmsgZ+PfEg9ilj0MlaVcj2gooYleBGYPYp6bXDFrZA9E6D/L2cOob2Q6I4vynClPcadfD0lqag9UuukF5HCiD2ypkdn3RywvV6+HbnNh329tQtmLMwPoD2K3nggCSOYvYhlaP+KDpW94HqV9VyCrj2WXAZVUIeGPYOSxmhrh4O9TtnIxWucsT1xG9MUziixvXJ0svP4xYg9F2rctrqgmD3m2GPjwfSaPTzBttFZPqG9Etm7DZEmpL1KiGU8jxujvbIaolSM3aE9zzZg9/y7p72cc/fBEASRvR62VkTzWbs9gNwBxpGCUz3KFOKMM42EPWxdpHHBLau9yBlBnYBqVL10AjM8FpyfvUS/M6oJpnw9RtnWOYPzlL3aiCi1NyytvaoULeayT4i9uX6FhbJnpz0iKIGXKFidvVIN4NkHLq893sskWuEQsr2t9VoQFhfPvZ2h1jhl8Xy9mA7jX52ilb2OyAIbKaOiPRCW3dmKXns9kPYhF+rSjj2wxIlOgMB6PX71WRe4AMU9rtEPKOcpqb1w2WgdNdC9vXOb4mticJI9vbMNI72Xur1161PLHjiSPXpzCzzNyIU9LcBE6N3Nsj3JhO2dWnisvTgiAANsGb+9An7VKpoamb0JxPNTl+9vvdmaZK+THqg9b657g2RzqD1q2wfyK/qwvSYczN/g6bA9X7c152KgmT3YSGGWiY3BvZo9qys8HLG9Wnme4gkPt73NE2ZmWbqjPR56rOYb1bQ9A6ojMxv+mj3AcupIxmiLvT5KjhLaJ5092lwu/7iJtj2qIn85mb6ivWemeWTr9qC9ar+HMD6Sq71TyNw7E52kvRkEgcoUJVg94uZ633G/wr12ifA9LfOxPa745psSb7O9BP4EviR7uL04GOydDoGNPVW4pgpGX4o9OlCHTH1Kib37XeVb2rmjPb5PXxAadaw9ANVTHhXSlb3oKdI79Jx0Pb5SxkdZsIm9KfuZFDXtoD0tiRpdUsOnvVrBvHvPnLU92ICst3+ikj1MvNFI+zStPZixSoditJW9TRBYcnl9vL3JNiM/4MuXPRkCjByoxcI9fpI0ylQtrb13/rax7jumvehF+eTr/qq9eLFPl2YAgz3M+07BLxSZvSY5XoAhk5o9wR7sa7VZtT30g8rOl0ShvT0NAMNtd6Q9XDvdbm9orj1fJHD1BqOevYy9DyMKWcC9mKOoxztCxL3o+4csJHWjvQUsYpj0lqy9juvT/2ZMqL1nChyXInOlPVbMiQXkbJC9uscmYtAIwL3hunparJC1PaTz0SUkkZs9MjOZPlhGqz0VnixqNeqyvQb9DSJXfcO9uhZ+zFwivL1Ih+jobNvFvaIdRtPcfKi9A8QSOdYLjD07RjNf9nqxvUmFaSVqHcC9lsld24Hkjr0MD+KmHbalPSJF4Vr+bMy94amT69eJt73fjkcNEu6tvXRj/3lBoMG9NJHRjZS1uL3TOpXVJjO9vVit6BYRp629w7oNWGN2fT09L+wDxVS2vX2s9Uy+1dC9KEPiXhoeor3k4GZ8mcS7vY6TJxn6m8y9eM4stRsSur1EvmUa+0qgvUb15CnWsHy9Mv3ZpJuZpz2x4eiP7HWzvYpCF72apsi9QQ8D5DSdyb20GR1ZDbK0vYB9B5mEOV09jnuYi9+xYr3M8bLwBh6JvaysX5BjgKE9OD8Hq//CrD1WVecqLDm7vdrfErTtlaa9DD04Q4BKmj1BY+gE5BKrvXoEWlqcxc69q3HTwCdGtb0AAEofesfnPP7c4br5Hnk9DIhh7ooEdb0YfIV09amXPczV/TBhuag9E5lsaspVuL2ypkdn3RywvRdq3La6oJg9bF2kccEtq72t9VoQFhfPvQ==IA8AAAAAAADDVBP+/w+YwHbVpv7/D5jAwlGf/v8PmMAcDgb+/w+YwJl4if7/D5jAh3rd/f8PmMB5cmf+/w+YwOB/l/3/D5jABEQ9/v8PmMBQ+zD9/w+YwH8PEv7/D5jAtsqk/P8PmMCnQ/T9/w+YwKAJ5vv/D5jA3LIH/v8PmMAgw8z6/w+YwEnMs/7/D5jAKwji+P8PmMAoeTEBABCYwGA76PT/D5jAcRFkAgAQmMDVNzn6/w+YwBIzWv//D5jAONNf//8PmMDfcnT//w+YwEFapP//D5jAH6MHAAAQmMBiuMcAABCYwBD8JAIAEJjAb4txBAAQmMARudIHABCYwFB3HAsAEJjAb+z1//8PmMDH/eX//w+YwJth9///D5jAiFIwAAAQmMA8y54AABCYwJnFVwEAEJjA7FNvAgAQmMBS/eQDABCYwPZzgAUAEJjAPG+2BgAQmMBEBlsHABCYwAY+pf//D5jAeFguAAAQmMCXCEUAABCYwHP8iwAAEJjAr8AJAQAQmMB43MEBABCYwB0TqgIAEJjAJFagAwAQmMA+Y2sEABCYwDL5zAQAEJjAZJ9MBAAQmMAenn4BABCYwLa/NgAAEJjA9UxNAAAQmMB/OZIAABCYwErABwEAEJjA/L+tAQAQmMCcfoACABCYwDXregMAEJjAnC+WBAAQmMAKZdEFABCYwGKL9wcAEJjAHspw//8PmMAibA0AABCYwKxNIAAAEJjACIJaAAAQmMAyNMAAABCYwHi4VgEAEJjAJrEfAgAQmMBcRgsDABCYwF7P8gMAEJjAP8nsBAAQmMCiDOUFABCYwDAbdPv/D5jAPKTB//8PmMAkfM3//w+YwMpG9P//D5jA45E+AAAQmMAkHrQAABCYwBS5SwEAEJjA/mzVAQAQmMDLZAkCABCYwB5raQEAEJjAjjOkAAAQmMBmzGQBABCYwDOsYf//D5jAbLBh//8PmMDsDmj//w+YwNWqhP//D5jASCvH//8PmMBzJTIAABCYwB7ItwAAEJjAwqcDAQAQmMCgVz0AABCYwCWjm/3/D5jAPRhlFQAQmMC4hPv+/w+YwKpd6P7/D5jALku7/v8PmMC90ZX+/w+YwKQ9pv7/D5jApbAs//8PmMA4HIwAABCYwLKckgMAEJjA/DdLCAAQmMB4XKkXABCYwCZDvBoAEJjAiPCa/v8PmMD0YVr+/w+YwPDasv3/D5jAp7Py/P8PmMDKgZ38/w+YwFlrUf3/D5jA1aGt/v8PmMB2aoz8/w+YwFD9c+7/D5jAca4pEAAQmMBOacMfABCYwFq51QAAEJjAuwJmAQAQmMAp7zMCABCYwPUuWQIAEJjAAsfuAgAQmMCMzB4FABCYwJYypwMAEJjAqJzCBwAQmMB5ZfMDABCYwLYQtggAEJjAmIO3AwAQmMDyvhEIABCYwOhxwAIAEJjAXB9TBgAQmMBNawYBABCYwNwIjgQAEJjAmith//8PmMAok/ECABCYwInPavj/D5jA+XEz+P8PmMBAwNECABCYwN36hgIAEJjAW3baAQAQmMAFq1IBABCYwIz74wAAEJjAIg6vAAAQmMDhvWQAABCYwKqLiv//D5jAko8z/v8PmMAxWyj9/w+YwAYTggUAEJjA2N1OAwAQmMDPTUUBABCYwMLLe///D5jAawgh/v8PmMBWWIj9/w+YwEARpf3/D5jAgGWF/f8PmMAFp9b8/w+YwOqoufz/D5jAYrneCAAQmMCnv3EEABCYwDR4FAEAEJjAFmsV/v8PmMBPgKj7/w+YwFEGP/r/D5jAYOlD+v8PmMCHgBP7/w+YwK1pUvr/D5jAQejO9/8PmMBKmSIMABCYwMG6qgUAEJjA05oXAQAQmMC8/+/8/w+YwG22W/n/D5jAkgjd9v8PmMCjOjP2/w+YwJUvwff/D5jAFX4p+v8PmMCW9Gz4/w+YwKIbPQ4AEJjAPMaMBgAQmMCdziIBABCYwPRM5fv/D5jAxnrj9v8PmMAkt8Dy/w+YwIqHtfD/D5jAWIAK8v8PmMBGD972/w+YwBz7ff3/D5jAXKXVDQAQmMDek6s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+ </AppendedData>
+</VTKFile>
diff --git a/Tests/Data/LIE/PostProcessing/single_joint_3D.pvd b/Tests/Data/LIE/PostProcessing/single_joint_3D.pvd
new file mode 100644
index 00000000000..a76464819cd
--- /dev/null
+++ b/Tests/Data/LIE/PostProcessing/single_joint_3D.pvd
@@ -0,0 +1,7 @@
+<?xml version="1.0"?>
+<VTKFile type="Collection" version="0.1" byte_order="LittleEndian" compressor="vtkZLibDataCompressor">
+ <Collection>
+ <DataSet timestep="0" group="" part="0" file="single_joint_3D_ts_0_t_0.000000.vtu"/>
+ <DataSet timestep="1" group="" part="0" file="single_joint_3D_ts_1_t_1.000000.vtu"/>
+ </Collection>
+</VTKFile>
diff --git a/Tests/Data/LIE/PostProcessing/single_joint_3D_ts_0_t_0.000000.vtu b/Tests/Data/LIE/PostProcessing/single_joint_3D_ts_0_t_0.000000.vtu
new file mode 100644
index 00000000000..8a5a32cab6a
--- /dev/null
+++ b/Tests/Data/LIE/PostProcessing/single_joint_3D_ts_0_t_0.000000.vtu
@@ -0,0 +1,58 @@
+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="1.0" byte_order="LittleEndian" header_type="UInt64" compressor="vtkZLibDataCompressor">
+ <UnstructuredGrid>
+ <FieldData>
+ <DataArray type="Int8" Name="OGS_VERSION" NumberOfTuples="26" format="appended" RangeMin="45" RangeMax="121" offset="0" />
+ </FieldData>
+ <Piece NumberOfPoints="462" NumberOfCells="210" >
+ <PointData>
+ <DataArray type="Float64" Name="displacement" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="0" offset="92" />
+ <DataArray type="Float64" Name="displacement_jump1" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="0" offset="180" />
+ <DataArray type="Float64" Name="epsilon_xx" format="appended" RangeMin="0" RangeMax="0" offset="268" />
+ <DataArray type="Float64" Name="epsilon_xy" format="appended" RangeMin="0" RangeMax="0" offset="348" />
+ <DataArray type="Float64" Name="epsilon_xz" format="appended" RangeMin="0" RangeMax="0" offset="428" />
+ <DataArray type="Float64" Name="epsilon_yy" format="appended" RangeMin="0" RangeMax="0" offset="508" />
+ <DataArray type="Float64" Name="epsilon_yz" format="appended" RangeMin="0" RangeMax="0" offset="588" />
+ <DataArray type="Float64" Name="epsilon_zz" format="appended" RangeMin="0" RangeMax="0" offset="668" />
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+ <DataArray type="Float64" Name="stress_yz" format="appended" RangeMin="0" RangeMax="0" offset="2404" />
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+ <DataArray type="Float64" Name="w_s" format="appended" RangeMin="0" RangeMax="0" offset="2632" />
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+ <Cells>
+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="5536" />
+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="8780" />
+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="9232" />
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+ </Piece>
+ </UnstructuredGrid>
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+</VTKFile>
diff --git a/Tests/Data/LIE/PostProcessing/single_joint_3D_ts_1_t_1.000000.vtu b/Tests/Data/LIE/PostProcessing/single_joint_3D_ts_1_t_1.000000.vtu
new file mode 100644
index 00000000000..9bb9aab7482
--- /dev/null
+++ b/Tests/Data/LIE/PostProcessing/single_joint_3D_ts_1_t_1.000000.vtu
@@ -0,0 +1,58 @@
+<?xml version="1.0"?>
+<VTKFile type="UnstructuredGrid" version="1.0" byte_order="LittleEndian" header_type="UInt64" compressor="vtkZLibDataCompressor">
+ <UnstructuredGrid>
+ <FieldData>
+ <DataArray type="Int8" Name="OGS_VERSION" NumberOfTuples="26" format="appended" RangeMin="45" RangeMax="121" offset="0" />
+ </FieldData>
+ <Piece NumberOfPoints="462" NumberOfCells="210" >
+ <PointData>
+ <DataArray type="Float64" Name="displacement" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="6.9239316787e-06" offset="92" />
+ <DataArray type="Float64" Name="displacement_jump1" NumberOfComponents="3" format="appended" RangeMin="0" RangeMax="3.4469071319e-06" offset="5508" />
+ <DataArray type="Float64" Name="epsilon_xx" format="appended" RangeMin="1.1051757433e-05" RangeMax="1.1051776337e-05" offset="5932" />
+ <DataArray type="Float64" Name="epsilon_xy" format="appended" RangeMin="-1.7402646215e-12" RangeMax="5.8525415179e-12" offset="8600" />
+ <DataArray type="Float64" Name="epsilon_xz" format="appended" RangeMin="-6.3208107792e-19" RangeMax="8.6198291128e-19" offset="13200" />
+ <DataArray type="Float64" Name="epsilon_yy" format="appended" RangeMin="-3.9183542255e-05" RangeMax="-3.9183522546e-05" offset="17992" />
+ <DataArray type="Float64" Name="epsilon_yz" format="appended" RangeMin="-4.3952392273e-19" RangeMax="2.7416907164e-19" offset="20476" />
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+</VTKFile>
--
GitLab