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"source": [
"ChEn-5310: Computational Continuum Transport Phenomena Spring 2021 UMass Lowell; Prof. V. F. de Almeida **06Apr21**\n",
"\n",
"# 06b. Poisson 2D with Dirichlet Boundary Conditions\n",
"$ \n",
" \\newcommand{\\Amtrx}{\\boldsymbol{\\mathsf{A}}}\n",
" \\newcommand{\\Bmtrx}{\\boldsymbol{\\mathsf{B}}}\n",
" \\newcommand{\\Mmtrx}{\\boldsymbol{\\mathsf{M}}}\n",
" \\newcommand{\\Imtrx}{\\boldsymbol{\\mathsf{I}}}\n",
" \\newcommand{\\Pmtrx}{\\boldsymbol{\\mathsf{P}}}\n",
" \\newcommand{\\Lmtrx}{\\boldsymbol{\\mathsf{L}}}\n",
" \\newcommand{\\Umtrx}{\\boldsymbol{\\mathsf{U}}}\n",
" \\newcommand{\\Smtrx}{\\boldsymbol{\\mathsf{S}}}\n",
" \\newcommand{\\xvec}{\\boldsymbol{\\mathsf{x}}}\n",
" \\newcommand{\\avec}{\\boldsymbol{\\mathsf{a}}}\n",
" \\newcommand{\\bvec}{\\boldsymbol{\\mathsf{b}}}\n",
" \\newcommand{\\cvec}{\\boldsymbol{\\mathsf{c}}}\n",
" \\newcommand{\\rvec}{\\boldsymbol{\\mathsf{r}}}\n",
" \\newcommand{\\fvec}{\\boldsymbol{\\mathsf{f}}}\n",
" \\newcommand{\\mvec}{\\boldsymbol{\\mathsf{m}}}\n",
" \\newcommand{\\gvec}{\\boldsymbol{\\mathsf{g}}}\n",
" \\newcommand{\\flux}{\\boldsymbol{q}}\n",
" \\newcommand{\\normal}{\\boldsymbol{n}}\n",
" \\newcommand{\\xpoint}{\\boldsymbol{x}}\n",
" \\newcommand{\\zerovec}{\\boldsymbol{\\mathsf{0}}}\n",
" \\newcommand{\\norm}[1]{\\bigl\\lVert{#1}\\bigr\\rVert}\n",
" \\newcommand{\\transpose}[1]{{#1}^\\top}\n",
" \\DeclareMathOperator{\\rank}{rank}\n",
" \\DeclareMathOperator{\\div}{div}\n",
" \\DeclareMathOperator{\\grad}{grad}\n",
" \\newcommand{\\Reals}{\\mathbb{R}}\n",
" \\newcommand{\\thetavec}{\\boldsymbol{\\theta}}\n",
"$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"\n",
"## Table of Contents\n",
"* [Objectives](#obj)\n",
"1. [Plotting Functions](#plotting)\n",
"
\n",
"1. [Problem Statement](#problem)\n",
" + [Strong Form](#dbcstrong)\n",
" + [Variational Form](#dbcweak)\n",
" + [Poisson-Dirichlet Energy](#energy)\n",
"
\n",
"1. [Problem Solution](#solution)\n",
" + [MOOSE Application Development](#dbcapp)\n",
"
\n",
"1. [Linear Lagrange FEM Results](#dbclinearfemresults)\n",
"
\n",
"1. [Quadratic Lagrange FEM Results](#dbcquadfemresults)\n",
"
\n",
"1. [Energy Postprocessing](#energypostpro)\n",
"
\n",
"1. [Application Tree](#tree)\n",
"---"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Objectives](#toc)\n",
"\n",
" + Extend the Poisson 1D problem covered in [Notebook 06a](https://nbviewer.jupyter.org/github/dpploy/engy-5310/blob/main/notebooks/06a-poisson-2d-dirichlet.ipynb) to a *generic* 2D case. Notes for the 1D problem must be thoroughly reviewed.\n",
" + Introduce the Galerkin variational (weak) form of the Poisson 2D problem below ([OneNote notes here](https://studentuml-my.sharepoint.com/:o:/g/personal/valmor_dealmeida_uml_edu/Eib-vZHIpRlPlOMtz0Gf_asBegEFKsl9dOK4nHyDbgSeUA?e=sLu1td)).\n",
" + Employ a robust (but very slow) solver as an example of how to debug your code. This is particularly important as the model problem becomes more complex, in particular when it is non-linear. See the *[Preconditioning]* `MOOSE` block of the `input.hit` file below.\n",
" + Some initial code is provided in the course repository but no full source code is given out. A significant effort in programing is often necessary to learn the subject well. However the material in this course is helpful with this task. Hands-on work during lectures will try to fill in existing gap. The steps in this notebook are necessary for a basic understanding of the subject.\n",
" + You are supposed to consult the [`MOOSE source documentation`](https://mooseframework.inl.gov/source/index.html) to fill in gaps in reproducing the steps below."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Plotting Functions](#toc)\n",
"\n",
"This is an auxiliary section for holding plotting functions used later."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"code_folding": [
2
]
},
"outputs": [],
"source": [
"'''Plot function for FEM Solution'''\n",
"\n",
"def plot_solution(df, \n",
" title='No Title', \n",
" basis_functions_type='No basis functions type',\n",
" flux_basis_functions_type='No basis functions type'):\n",
" \n",
" import matplotlib.pyplot as plt\n",
" %matplotlib inline\n",
" plt.style.use('dark_background')\n",
"\n",
" (fig, ax1) = plt.subplots(1, figsize=(14, 5))\n",
"\n",
" ax1.plot(df['x'], df['u'],'r*-',label=basis_functions_type)\n",
"\n",
" ax1.set_xlabel(r'$x$ [cm]', fontsize=18)\n",
" ax1.set_ylabel(r'$u_h(x)$ [g/cc]', fontsize=18, color='red')\n",
" ax1.tick_params(axis='y', labelcolor='red', labelsize=14)\n",
" ax1.tick_params(axis='x', labelsize=14)\n",
" ax1.legend(loc='center left', fontsize=12)\n",
" #ax1.set_ylim(0,1)\n",
" ax1.grid(True)\n",
"\n",
" if 'diffFluxU_x' in df.columns:\n",
" # create a twin x axis to be shared\n",
" ax2 = ax1.twinx()\n",
"\n",
" ax2.plot(df['x'], df['diffFluxU_x'],'*-', color='yellow', label='$q_{n,x}$ flux_basis_functions_type')\n",
" ax2.set_ylabel(r\"$q_h(x)$ [g/cm$^2$-s]\", fontsize=16, color='yellow')\n",
" \n",
" if 'diffFluxU_y' in df.columns:\n",
" ax2.plot(df['x'], df['diffFluxU_y'],'o', color='yellow', label='$q_{n,y}$ flux_basis_functions_type')\n",
" \n",
" ax2.set_ylabel(r\"$q_h(x)$ [g/cm$^2$-s]\", fontsize=16, color='yellow')\n",
" ax2.tick_params(axis='y', labelcolor='yellow', labelsize=14)\n",
" ax2.legend(loc='center right', fontsize=12)\n",
" #ax2.set_ylim(0,2)\n",
" #ax2.grid(True)\n",
" \n",
"\n",
"\n",
" plt.title(title, fontsize=20)\n",
" fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
" plt.show()\n",
" print('')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Problem Statement](#toc)\n",
"\n",
"The following sections describe what is referred in the literature as the two-dimensional Poisson problem with Dirichlet boundary condition."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### [Strong Form of Problem Statement](#toc)\n",
"\n",
"Solve the Poisson model problem. Find $u:\\Omega\\in\\Reals^2\\rightarrow\\Reals$ such that:\n",
"\n",
"\\begin{align*}\n",
" -\\div_\\xpoint(-D\\, \\grad_\\xpoint u) + S &= 0 \\quad &\\forall \\quad \\xpoint\\in \\Omega, \\\\\n",
" u(\\xpoint) &= u_\\text{b}(\\xpoint) \\quad &\\forall \\quad \\xpoint\\in \\partial\\Omega\n",
"\\end{align*}\n",
" \n",
"This problem has an analytical solution for certain domains $\\Omega$ however this solution is not required here. The *flux*, $\\flux:\\Omega\\rightarrow\\Reals^2$, associated to the quantity $u$, is denoted $\\flux := -D\\,\\grad u$, and it is often of interest as a derived quantity.\n",
"\n",
"The value of the dependent variable is given on the boundary of the domain $\\partial\\Omega$. This is the extension of the *essential* boundary condition or *Dirichlet boundary condition* to 2D."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### [Variational Form of Problem Statement](#toc)\n",
"\n",
"The Galerkin variational formulation is as follows. Find $u \\in H^1\\!\\bigl(\\Omega\\bigr)$ so that \n",
"\n",
"\\begin{align*}\n",
" \\int\\limits_\\Omega -D\\, \\grad_\\xpoint u \\cdot \\grad_\\xpoint v\\,d\\xpoint + \\int\\limits_\\Omega S\\,v(\\xpoint)\\,d\\xpoint &= 0 \\quad \\forall \\quad v \\in H^1_0\\!\\bigl(\\Omega\\bigr), \n",
"\\end{align*}\n",
"\n",
"where $H^1\\!\\bigl(\\Omega\\bigr) := \\bigl\\{ u:\\Omega\\subset\\Reals\\rightarrow \\Reals \\mid \\int_\\Omega \\grad_\\xpoint u\\cdot\\grad_\\xpoint u\\,d\\xpoint < \\infty \\bigr\\}$ and \n",
"$H^1_0\\!\\bigl(\\Omega\\bigr) := \\bigl\\{ v \\mid v \\in H^1(\\Omega), v|_{\\partial\\Omega} = 0 \\bigr\\}$. Both function sets as just defined are Hilbert spaces. The function $v$ is called a test function. Because $v$ and $u$ are sought in very similar sets of functions, this variational form is called Galerkin's variational form.\n",
"\n",
"The two integrals in the variational formulation are the key terms to be computed. Since the MOOSE framework performs the integration, and provides the implementation of the test function, we need to provide the integrand of the integrals, that is, the kernels. Therefore the kernels needed are:\n",
"\n",
" 1. $-D\\, \\grad_\\xpoint u \\cdot \\grad_\\xpoint v$ ,\n",
" 1. $S\\,v(\\xpoint)$.\n",
" \n",
"The kernels are to be evaluated at quadrature points provided by the MOOSE framework."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### [Poisson-Dirichlet Energy](#toc)\n",
"\n",
"It is of theoretical and practical importance to compute the associated energy that the variational form minimizes, that is the **Poisson-Dirichlet total energy**:\n",
"\n",
"\\begin{align*}\n",
" \\Phi[u] := \\int\\limits_\\Omega \\,\\frac{1}{2}\\flux(\\xpoint)\\cdot\\flux(\\xpoint) - D\\,S\\,u(\\xpoint) \\,d\\xpoint.\n",
"\\end{align*}\n",
"\n",
"Since this is done after the solution is computed, it is characterized as a *postprocessing* operation. In `MOOSE` this is implemented in a *Postprocessors* class. First however, any derived quantity used in the integrand needs to be passed to the preprocessor for integration. Here we need to compute the local *flux*, $q$. In `MOOSE` this is done by creating an *auxiliary* variable and a corresponding *auxiliary kernel*. Therefore there are two additional components to [setup](#energypostpro):\n",
"\n",
"1. Create the auxiliary variable $\\flux=-D\\,\\grad u$,\n",
"1. Create the posprocessor for computing $\\Phi$."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Problem Solution](#toc)\n",
"\n",
"There is very little to do in order to extend the work done in 1D ([Notebook 06](https://nbviewer.jupyter.org/github/dpploy/engy-5310/blob/main/notebooks/06-poisson-1d-dirichlet.ipynb)) if the programming was done with an eye towards 2D and 3D. The major work to be done is in the `MOOSE` input file."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### [MOOSE Application Development](#toc)\n",
"\n",
"We will use the same application development as in [Notebook 06](https://nbviewer.jupyter.org/github/dpploy/engy-5310/blob/main/notebooks/06-poisson-1d-dirichlet.ipynb), namely `engy5310p1`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Linear Lagrange FEM](#toc)\n",
"\n",
"Solve problem with parameter values:\n",
"\n",
"> + See domain below\n",
"> + u_left = 3 g/cc\n",
"> + u_right = 0 g/cc\n",
"> + u_bottom = 0 g/cc\n",
"> + u_top = 2 g/cc\n",
"> + D = 0.1 cm^2/s\n",
"> + S = 1e-3 g/cc-s\n",
"\n",
"FEM parameters:\n",
"\n",
"> + Basis Functions: First Order Lagrange\n",
"> + num. of finite elements in the *x* direction: 20\n",
"> + num. of finite element in the *y* direction: 10"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"'''Domain'''\n",
"\n",
"x_left = 0.0\n",
"x_right = 25.0\n",
"x_length = x_right - x_left\n",
"\n",
"y_length = x_length/2\n",
"y_bottom = -y_length/2\n",
"y_top = -y_bottom"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import pyvista as pv\n",
"import numpy as np\n",
"p1 = np.array([x_left, y_bottom, 0])\n",
"p2 = np.array([x_right, y_bottom, 0])\n",
"p3 = np.array([x_right, y_top, 0])\n",
"p4 = np.array([x_left, y_top, 0])\n",
"center = (p1+p2+p3+p4)/4\n",
"plane = pv.Plane(center=center, i_size=x_length, j_size=y_length)\n",
"\n",
"plt = pv.Plotter()\n",
"plt.add_mesh(plane, color='tan')\n",
"plt.show_bounds()\n",
"plt.set_viewup([0,1,0])\n",
"cpos = plt.show(window_size=[800,600])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"'''Parameters and data'''\n",
"\n",
"diff_coeff = 0.1\n",
"source_s = 1e-3\n",
"\n",
"u_left = 3.0\n",
"u_right = 0.0\n",
"\n",
"u_bottom = 0\n",
"u_top = 2"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"code_folding": [
12
]
},
"outputs": [],
"source": [
"'''FEM Solution'''\n",
"\n",
"n_felem_x = 20\n",
"n_felem_y = 10\n",
"\n",
"order = 'first'\n",
"\n",
"n_plot_pts_x = n_felem_x + 1\n",
"n_plot_pts_y = n_felem_y + 1\n",
"\n",
"from engy_5310.toolkit import write_engy5310_p1_2d_input_file\n",
"\n",
"write_engy5310_p1_2d_input_file(x_left=x_left, x_right=x_right, y_bottom=y_bottom, y_top=y_top, \n",
" u_left=u_left, u_right=u_right, u_bottom=u_bottom, u_top=u_top,\n",
" diff_coeff=diff_coeff, source_s=source_s, n_felem_x=n_felem_x, n_felem_y=n_felem_y, \n",
" order=order, \n",
" n_plot_pts_x=n_plot_pts_x, n_plot_pts_y=n_plot_pts_y, \n",
" compute_diffusion_flux=True,\n",
" solver='fdp-newt-full')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"# Engy-5310 Problem: Poisson 2D FEM\r\n",
"# UMass Lowell Nuclear Chemical Engineering\r\n",
"# Prof. Valmor F. de Almeida\r\n",
"# 19Apr21 12:58:37\r\n",
"\r\n",
"# Parameters\r\n",
"xmin = 0.00000e+00\r\n",
"xmax = 2.50000e+01\r\n",
"ymin = -6.25000e+00\r\n",
"ymax = 6.25000e+00\r\n",
"diff_coeff = 1.00000e-01\r\n",
"source_s = 1.00000e-03\r\n",
"u_left = 3.00000e+00\r\n",
"u_right = 0.00000e+00\r\n",
"u_bottom = 0.00000e+00\r\n",
"u_top = 2.00000e+00\r\n",
"\r\n",
"[Problem]\r\n",
" type = FEProblem\r\n",
" coord_type = XYZ\r\n",
"[]\r\n",
"\r\n",
"[Mesh]\r\n",
" [2d]\r\n",
" type = GeneratedMeshGenerator\r\n",
" dim = 2\r\n",
" xmin = ${replace xmin}\r\n",
" xmax = ${replace xmax}\r\n",
" ymin = ${replace ymin}\r\n",
" ymax = ${replace ymax}\r\n",
" nx = 20\r\n",
" ny = 10\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Variables]\r\n",
" [u]\r\n",
" order = first\r\n",
" family = lagrange\r\n",
" initial_condition = ${fparse (u_left+u_right+u_bottom+u_top)/4}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[AuxVariables]\r\n",
" [diffFluxU]\r\n",
" order = CONSTANT\r\n",
" family = MONOMIAL_VEC\r\n",
" []\r\n",
" [diffFluxU_x]\r\n",
" order = CONSTANT\r\n",
" family = MONOMIAL\r\n",
" []\r\n",
" [diffFluxU_y]\r\n",
" order = CONSTANT\r\n",
" family = MONOMIAL\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Kernels]\r\n",
" [diffusion-term]\r\n",
" type = DiffusionTerm\r\n",
" variable = u # produced quantity\r\n",
" diffCoeff = ${replace diff_coeff}\r\n",
" []\r\n",
" [source-term]\r\n",
" type = SourceTerm\r\n",
" variable = u # add to produced quantity\r\n",
" sourceS = ${replace source_s}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[AuxKernels]\r\n",
" [diffusion-flux]\r\n",
" execute_on = timestep_end\r\n",
" type = DiffusionFlux # new kernel\r\n",
" field = u\r\n",
" diffCoeff = ${replace diff_coeff}\r\n",
" variable = diffFluxU # produced quantity\r\n",
" []\r\n",
" [diffusion-flux-x]\r\n",
" execute_on = timestep_end\r\n",
" type = VectorVariableComponentAux # provided by MOOSE\r\n",
" variable = diffFluxU_x # produced quantity\r\n",
" component = x\r\n",
" vector_variable = diffFluxU \r\n",
" []\r\n",
" [diffusion-flux-y]\r\n",
" execute_on = timestep_end\r\n",
" type = VectorVariableComponentAux # provided by MOOSE\r\n",
" variable = diffFluxU_y # produced quantity\r\n",
" component = y\r\n",
" vector_variable = diffFluxU \r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[BCs]\r\n",
" [east]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = left\r\n",
" value = ${replace u_left}\r\n",
" []\r\n",
" [west]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = right\r\n",
" value = ${replace u_right}\r\n",
" []\r\n",
" [south]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = bottom\r\n",
" value = ${replace u_bottom}\r\n",
" []\r\n",
" [north]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = top\r\n",
" value = ${replace u_top}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Preconditioning]\r\n",
" active = 'fdp-newt-full'\r\n",
" [fdp-newt-full]\r\n",
" type = FDP\r\n",
" full = true\r\n",
" solve_type = 'NEWTON'\r\n",
" petsc_options_iname = '-pc_type -mat_fd_coloring_err -mat_fd_type'\r\n",
" petsc_options_value = 'lu 9.9999999999999995474811182588626e-07 ds'\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Executioner]\r\n",
" type = Steady\r\n",
"[]\r\n",
"\r\n",
"[VectorPostprocessors]\r\n",
" [x-line]\r\n",
" type = LineValueSampler\r\n",
" execute_on = 'timestep_end final'\r\n",
" variable = 'u diffFluxU_x diffFluxU_y' # output data\r\n",
" start_point = '${replace xmin} ${fparse (ymax+ymin)/2} 0'\r\n",
" end_point = '${replace xmax} ${fparse (ymax+ymin)/2} 0'\r\n",
" num_points = 21\r\n",
" sort_by = id\r\n",
" []\r\n",
" [y-line]\r\n",
" type = LineValueSampler\r\n",
" execute_on = 'timestep_end final'\r\n",
" variable = 'u diffFluxU_x diffFluxU_y' # output data\r\n",
" start_point = '${fparse (xmax+xmin)/2} ${replace ymin} 0'\r\n",
" end_point = '${fparse (xmax+xmin)/2} ${replace ymax} 0'\r\n",
" num_points = 11\r\n",
" sort_by = id\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Outputs]\r\n",
" console = true\r\n",
" [vtk]\r\n",
" type = VTK\r\n",
" execute_on = final\r\n",
" file_base = out\r\n",
" []\r\n",
" [x]\r\n",
" type = CSV\r\n",
" execute_on = 'final'\r\n",
" show = 'x-line'\r\n",
" file_base = out-x\r\n",
" []\r\n",
" [y]\r\n",
" type = CSV\r\n",
" execute_on = 'final'\r\n",
" show = 'y-line'\r\n",
" file_base = out-y\r\n",
" []\r\n",
"[]\r\n"
]
}
],
"source": [
"'''Display MOOSE input file created'''\n",
"\n",
"!cat engy5310p1/input.hit"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"Framework Information:\n",
"MOOSE Version: git commit 52562be492 on 2021-04-09\n",
"LibMesh Version: 27141d18f3137f77e33cdb3d565fd38ebfbfc46f\n",
"PETSc Version: 3.15.0\n",
"SLEPc Version: 3.14.2\n",
"Current Time: Mon Apr 19 12:58:37 2021\n",
"Executable Timestamp: Sat Apr 17 21:27:24 2021\n",
"\n",
"Parallelism:\n",
" Num Processors: 1\n",
" Num Threads: 1\n",
"\n",
"Mesh: \n",
" Parallel Type: replicated\n",
" Mesh Dimension: 2\n",
" Spatial Dimension: 2\n",
" Nodes: \n",
" Total: 231\n",
" Local: 231\n",
" Elems: \n",
" Total: 200\n",
" Local: 200\n",
" Num Subdomains: 1\n",
" Num Partitions: 1\n",
"\n",
"Nonlinear System:\n",
" Num DOFs: 231\n",
" Num Local DOFs: 231\n",
" Variables: \"u\" \n",
" Finite Element Types: \"LAGRANGE\" \n",
" Approximation Orders: \"FIRST\" \n",
"\n",
"Auxiliary System:\n",
" Num DOFs: 800\n",
" Num Local DOFs: 800\n",
" Variables: \"diffFluxU\" { \"diffFluxU_x\" \"diffFluxU_y\" } \n",
" Finite Element Types: \"MONOMIAL_VEC\" \"MONOMIAL\" \n",
" Approximation Orders: \"CONSTANT\" \"CONSTANT\" \n",
"\n",
"Execution Information:\n",
" Executioner: Steady\n",
" Solver Mode: NEWTON\n",
" PETSc Preconditioner: lu \n",
" MOOSE Preconditioner: FDP\n",
"\n",
" 0 Nonlinear |R| = \u001b[32m8.869428e-01\u001b[39m\n",
" 0 Linear |R| = \u001b[32m8.869428e-01\u001b[39m\n",
" 1 Linear |R| = \u001b[32m3.889309e-15\u001b[39m\n",
" 1 Nonlinear |R| = \u001b[32m2.705192e-10\u001b[39m\n",
"\u001b[32m Solve Converged!\u001b[39m\n",
"The .pvtu extension should be used when writing VTK files in libMesh.WARNING! There are options you set that were not used!\n",
"WARNING! could be spelling mistake, etc!\n",
"There is one unused database option. It is:\n",
"Option left: name:-i value: engy5310p1/input.hit\n"
]
}
],
"source": [
"'''Run Engy5310P1 MOOSE App'''\n",
"\n",
"!engy5310p1/engy5310p1-opt -i engy5310p1/input.hit"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"cell_style": "center"
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"'''Show 2D solution'''\n",
"\n",
"import pyvista as pv\n",
"poisson = pv.read('out_000_0.vtu')\n",
"cpos = poisson.plot(scalars='u', stitle='Concentration [g/cc]', cmap='plasma', window_size=[800,600], notebook=True)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"cell_style": "split"
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"'''Show 2D solution'''\n",
"\n",
"import pyvista as pv\n",
"poisson = pv.read('out_000_0.vtu')\n",
"cpos = poisson.plot(scalars='diffFluxU_x', stitle='Diffusion Flux X [g/(cm^2 s)]', cmap='plasma', notebook=True) "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"cell_style": "split"
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"'''Show 2D y flux solution'''\n",
"\n",
"import pyvista as pv\n",
"poisson = pv.read('out_000_0.vtu')\n",
"cpos = poisson.plot(scalars='diffFluxU_y', stitle='Diffusion Flux Y [g/(cm^2 s)]', cmap='plasma', notebook=True)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"code_folding": [
2
]
},
"outputs": [
{
"data": {
"image/png": 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RunVr/vzzT6vOiY+PB7C6R9IWJUuWBEhRxXrRokWMGjWK5557jokTJ+Lv75/u+a6urnZXyR10Mrlq1Spee+01IiIiWLZsWa49lvmNFvNQ4UOHDtG0aVPatWuXJuGtUaMGlSpV4sKFC5kmvOah2cmr+ie/TsmSJdNcIyv3Sk61N6vq1KlDTExMmqJ7rq6uvPnmm0DK5N2c0L/99ttMmDCBd999lylTpjB16tTE4fKge/5v3LiRWCQtta5du/LDDz9w4sQJOnTowPbt2+nfvz8zZszI9t+D27dv4+/vT7NmzejduzePPfYYs2fPtmoUx9ChQ6latarVj7V48eIME/QtW7YA0LlzZxwcHFK8kVm0aFFatmxJZGSkxUr3tWvXxtHRMdujT4QQIj+SZdaEEAVG2bJlWb58Oe3bt+fSpUtMmjQpVx7nu+++IzY2ljFjxuDj45Nmv6Uq7tk1a9YsYmJimDZtWmLPVXIuLi6JVdTNwsLCSEhIoHLlyjnalqeffprq1asTExPDrl27ErdfunSJTz/9FDc3N/7444/EIcipPf744zbN389rn3zyCT169ODxxx8nIiIiy9d58cUXeeyxxyzOh/fw8GDAgAEAbN++HSBx1MEnn3xCmTJlEo91dHTk66+/xsnJie+//z7Txz116hR37tzh6aefpmzZsonbCxUqxMyZMy2ek5V7Jafam1UxMTG4urqm+H0oXLgwCxcupEGDBkDKHvRGjRpx+/ZtevXqxd9//8358+dZtWpViu+R2fbt2ylbtiw1atRIsb1ly5asWrWKK1eu0LlzZ0JDQxkzZgwuLi5MnjzZYjsXLVqEUorXX3/dque1Y8cOihQpwty5cwkJCUlR5yEj1apVw8HBwep44403MrzehQsX2LhxI9WqVUvTgz9+/HiKFi3KkiVLLFa6N48AMCf5QgghkkgPuhAiXzIvo+Xo6MhDDz1EvXr1aNWqFW5ubuzdu5eXX345cR3qnObv78/gwYOZM2cOhw4dYt26dZw9e5bSpUvTrFkz7t69m7iGcE45ffo0ffv2ZeHChZw4cYINGzZw5swZXFxcqFy5Mq1btyYkJCTFGwb37t1j7969tG7dmp9++okzZ84QHx/Pb7/9lu5STaklX66sSJEi1K1bl65duwIwevToxOHAZl988QXOzs6MGzeO/fv3s3PnTvbv309ERAQeHh60adMGb2/vxGWYckt6y6wB/PrrrxkWCgsMDLS4bJetHnnkEYYOHUpQUBA7duxIHO5brVo1unXrRuHChfn1119ZtWoVALt37+bLL79k5MiRHD9+nFWrVnHv3j26du1KgwYN+O+///jqq68yfdy4uDhmzJjB2LFjOXToEGvXrsXZ2ZlOnTpx7do1i7UTsnKv5FR7s2rjxo00b96cbdu2sXbtWooWLUrHjh05evQo165do3Dhwil69hs1asT69esTl4MDqFmzJufOnUtz7dWrV9OzZ08ef/xxZs+eDUDDhg35/fffuXPnDp06dUqsXbF69Wr8/Pzo0aMHrVq1SlzP3Mw8yiQuLs6q57Vz507efPNNihUrxvvvv59hsbrcNnjwYHbt2sU333xDx44d8ff355FHHqFDhw6cPn063aUpO3fuTFxcXIY99EIIUZAZXkpeQkJCIqcitfv376uQkBC1f/9+NW/ePPX4448rBweHNOdltMxaRssNZXRMixYt1KpVq1RwcLCKjo5WV69eVX/99Zd67rnnrH6MLVu2KKWU1Y9Zv359tWjRInXx4kV1//59dfPmTXXs2DE1Z84c1b59+zTH16hRQ/32228qNDRUxcfHK6WsWybMktjYWHXt2jX166+/qsceeyzD8+vUqaNmzpypjh07pu7cuaOio6PVtWvX1J9//qn69u2b7rJ26bUjq/eHJcmfv1JJy6xlFrYus1apUiU1ePBgtWbNGnXq1KkU34c//vhDvfzyyxbv1RdeeEH9999/Kjw8XEVFRanjx4+r0aNHKzc3N5vuz5EjR6pz586p6OhodenSJfXll18qd3d3i8usZXavZPQ4OdXe9H4f0gs3Nzc1ffp0dfXqVXXv3j3l5+enBg4cqEqUKKHi4+PTLMN36tQpNWjQoBTb1q1bp6ZNm5bm2i4uLiooKEjt2bMn8XsTFBSkbt26pRo0aJDm+I4dOyqllNq9e3eafQcPHlR37txRDz30kFXPq1WrVkoppfbu3Wv1fZ+bUalSJbVw4UJ17do1FR0drS5evKimT5+uSpYsafH44sWLq8jISLV27VrD2y4hISFhp2F4AyQkJCQkJCQkDAt3d3cVFxenWrRokWL75cuX033D5aOPPlJKKdWoUaMsP26JEiVUXFyc+vLLL60+Z926dSouLk41a9bM8O9bVmLIkCFKKaVatWpleFskJCQk7DQMb4CEhISEhISEhGHRokULFRcXpwoXLpy4rVSpUkoppR5++GGL57i5uamLFy+q3377LcuP++STT6qoqCjl4eFh1fG9e/dWSin1zTffGP49y0oUKlRIXb16Vf3yyy+Gt0VCQkLCXkPmoAshhBCiQHv44Yc5e/ZsioJmjRs3JiYmhpMnT1o8Jzo6mldffZX27dtTuHBhi8XQMvP777/j7u6e4TFeXl689NJL1KhRg9dee43jx48zYsQImx/LHlStWpV58+axePFio5sihBB2ywGdqQshhBBCCDszYMAA5s2bR1hYGJs3b04sLCiEECJ/kgRdCCGEEEIIIYSwAwV2iHt8fDxRUVFGN8MiNzc3oqOjjW6GKCDkfhN5Re41kZfkfhN5Se43kVfs+V5zd3fHycnJ6GY88Apsgh4VFUXRokWNboZFfn5++Pr6Gt0MUUDI/SbyitxrIi/J/SbyktxvIq/Y870WERFhdBPyBUejGyCEEEIIIYQQQghJ0IUQQgghhBBCCLsgCboQQgghhBBCCGEHJEEXQgghhBBCCCHsgCToQgghhBBCCCGEHZAEXQghhBBCCCGEsAOSoAshhBBCCCGEyBODBsGFCxAVBfv3Q6tWGR9fvz5s3QqRkXDlCowZk3J/mzawcyeEhupj/P3hgw9yrfm5zm4S9MHAEeCOKXYBT2RyTn1gKxAJXAHGZHi0EEIIIYQQQgij9OoFM2bApEnQuDHs2gV//QVeXpaPL1YMNm+G4GDw9YV334Xhw2HYsKRjIiJg5kydqNetCxMnwvjx+o2AB5HdJOhXgJFAE6AZ8C/wK9AgneOLAZuBYMAXeBcYDgxL5/gHRUNPaOTQjvoeRrckLU9P/e6Vhx22TQghhBBCCGHfhg2DxYthwQI4dUon3EFB6SfTL78MhQvD66/DiROwZg18+WXKBP3gQVixAk6ehIsX4eefYeNGaN06L55RzrObBP03YANwHjgLfALcBR5N5/iXgcLA68AJYA3wJQ9+gv7zOHBqdI/ln4G7u33F+PF6CMrYsUZ/l4QQQgghhBAPEhcXaNoUNm1KuX3TJvjf/yyf8+ij8N9/cP9+0raNG6FiRaha1fI5jRrp623blhOtznvORjfAEkfgeaAoeqi7JY8C/wHJflZsBCYCVYGLude8XJEQCQ7uSV/XGwiRA41rT0YGD9YRHa3f0UpIMLpFQgghhBBCCCM5Ozvj5+eX+PW8efOYP39+4tdlyoCzsx6unlxwMDz2mOVrenrqeeepjzfvu3gxaXtgIJQtqx9j/HiYOzcbT8ZAdpWg1wd2A4WACOAZ4Hg6x3qih8UnF5xs30UL5wwYMICBA3XW6+7unuIGMtrJPWeoqT7A9dHrOlGPgYRTToQ6PUVMiUqGts3R8R4lSuzA3f0Cjo5xKOWAg4PCzQ2io4ty924T7t71JTzcl/v3qwMOhrZX2MbHx8eufhdE/iX3mshLcr+JvCT3m8gr9nyvxcXF4evrm+lxSqX82sEh7bbMjre0vXVrKFoUWrTQw+ADAuCnn6xouB1S9hIuoGqAagpqEqgQUPXSOXYjqAWptlXWPyf1iBWPFRERYfjzTR3HZqMS4lAJkfpj/Leoa6Aet4O2zZ6NiotDRUbqjwsXonr1Qs2dizp7FqWUjqAg1M8/o/r2RVWpYny7JTIPPz8/w9sgUTBC7jWJvAy53yTyMuR+k8irsOd7LbP8ysUFFRuL6tkz5fZZs1Bbt1o+54cfUL//nnJbs2Y676haNf3H+vhj1Llzxn9PshJ2MwcdIBY9B/0AMBo4DLyfzrHX0T3lyZUzfUw1auKBUbIcHJ8D57dM4vgcCPWAm+i5+TPRIwuMUq4czJmj35GaMweKF4eVK+HNN6FWLahSBfr2hX/+gfbt4fvv9ZCT8+dh3jx44QU95EQIIYQQQghR8MTGwoED0KlTyu2dOulq7pbs3q17xt3cUh5/9WrK4e2pOTqmPOdBY/i7BOnFP6B+TGffW6DugHJLtm0UqCtWXtsee9DNkfydMTdQ09AjA06AamQH7bMmfHxQQ4ag1q5FhYUl9bAfPYqaNg315JOo4sWNb6eEfb8TK5G/Qu41ibwMud8k8jLkfpPIq7Dne82a/KpXL1R0NKpfP1SdOqjp01F376IqV9b7J01C/f130vHFi+sRusuWoerVQz3zDOrOHdSwYUnHDBmC6tYNVbOmjr599TFffGH89ySLYXgDFKC+ANUKVBVQ9dFD3ONBdTHtnwTq72THFwcVBGoZehj8M+iEfVgO3kBGhaVfvE6groKKBjUclKMdtNPacHTUQ1FGjkRt2qSHySulh7js3o2aOBHVvj3Kzc34thbEsOc/9BL5K+Rek8jLkPtNIi9D7jeJvAp7vtesza8GDUIFBKDu30ft349q3Tpp36JFel/y4+vXR23bhoqKQl27hho7NuX+995DHT+OiohA3b6NOnBAP4aDg/HfkyyG4Q3QPwxQF0HdBxUMajOozqn2B6Q6pz6obaCi0HO1x+bCDWREpPeLVwrUKnRv+hZQXnbQ1qyEmxuqbVvUZ5+hdu7UibpS+pfu779Ro0ahmjdHOTkZ39aCEPb8h14if4XcaxJ5GXK/SeRlyP0mkVdhz/eaPedXD1LYTRX3N7Kw/zjQNhfaYq9uAT2BPug56UeBQcByA9uUFdHRel3Cbdv0mupFi0KbNtCxo45Jk/Rxd+7oY/75R8eJE8a2WwghhBBCCCFyk10ViRPWWQw0Ak4Cy4CfgBIGtie7IiLgzz/hgw+gUSNdTK5XL1i+HOrWhRkz4PhxuH4dli6Ffv2gWrWU1/D0hK1bwcPDiGcghBBCCCGEENlnNz3owjYXgDbAKGAc0Ap4DdhuZKNySGgo/PKLDoDKlaFDh6Qe9t699faAAN2z/u+/uppjq1a6R/7tt41ruxBCCCGEEEJklfSgP8DigYlASyAG2AJ8AbgY2ahccPkyLF4Mr74KFSroXvUhQ+DwYd2bvnQpvPEGODnB4MGgFERGGt1qIYQQQgghhLCNJOj5wD6gMbAA+AjYA9QxtEW5y98fvv0Wnn0WKlWCv/6CmJik/YGB0Lmzce0TQgghhBBCiKyQBD2fuAe8CTwNeAEHgcGGtihvXLsGFy/q3vOoKEhIgHLlYMsW+O47mZMuhBBCCCGEeHBIgp7P/AY0ALYC3wJ/APk9Ry1XDubMgRYtdFK+eTPMnq2Hv587B2PGQOHCRrdSCCGEEEIIITImCXo+FAw8AbwNtAeOAU8Z2qLc1bOnnpN+9Kj+2L07vPeenqu+cSN89hmcPasTdke544UQQgghhBB2StKVfGw20AQIBNYB84AihrYob507p5P3li31MPgFC3RhuS5djG6ZEEIIIYQQQqQlCXo+dwpoAUwG+gGHgOaGtijv7dqlk/SePcHdXReV27xZr7kuhBBCCCGEEPZCEvQCIBa9Xnp7wBXYCYwBnIxslAFWr9bD3t99VyfnBw7ADz+Al5fRLRNCCCGEEEIISdALlO3Aw8AK4DPT19UNbVHei42Fb76BGjXg//4PevWCM2fgiy+geHGjWyeEEEIIIYQoyCRBL2DuAK8ALwF1gcNAHwPbY5TwcBg1Cry9YeVKGDECzp+Hd94BFxejWyeEEEIIIYQoiCRBL6CWAQ2BA8Ai4BeglKEtMkZgILz+OjRtqgvIzZwJJ07Ac88Z3TIhhBBCCCFEQSMJegEWCHQERqCXYTsGPGZoi4xz+DB06gRdu8L9+7BqFezcCY8+anTLhBBCCCGEEAWFJOgFXALwFfAIcBvYDEwF3Axsk5E2bNAF5Pr1g6pVdQX4VaugZk2jWyaEEEIIIYTI7yRBF4Cei94UmAm8D+xHD4EviBISYOFCqFULxoyBzp3h5Ek9/L1MGaNbJ4QQQgghhMivJEEXie4D7wFdgdLAPmAY4GBkowwUGQkTJ+re8wULYNAgOHcORo6EQoWMbp0QQgghhBAiv5EEXaSxAd17/hcwBT3svSLgCWwFPAxrmTFu3IDBg6FBA9i6FSZP1kuzvfYaOBTUdy+EEEIIIYQQOU4SdGFRKPAM0A89P/0YsBhoBYw1rlmGOnUKevSAtm0hKAh++AEOHICOHY1umRBCCCGEECI/kARdZGgh4AyUBB4HnIDBgAIiDWyXkbZvhxYt4MUX4aGH4O+/4c8/oX59o1smhBBCCCGEeJBJgi4yVQ1YCsSYvk4Atpi2F1RKwYoVUKcODBsGjzyil2pbsAAqVDC6dUIIIYQQQogHkSToIlPXgTvo3vNodNG49sAXQAkD22UPYmJg2jRdSG7aNHjlFTh7Fj77DIoW1cd4euq56x4FbfK+EEIIIYQQwiaSoAurlAPmAM2BucAp4FXgONDFwHbZi7AwGD5c96ivW6eXZzt3Dt56C8aNg1atYGxBnbwvhBBCCCGEsIok6MIqPYEhwFFgEOADtABuo6u9f4/0pgNcvAgvvQS+vnrN9O++00m6k5OuBK+UXr5NCCGEEEIIIVKTBF1k2QGgKTAJeB3dm/64oS2yH/v3Q6VKemh7QoLeFhcHv/wC1Qry5H0hhBBCCCFEuiRBF9kSA3yM7k2/g15DfQFQ3MhG2Ynr18HfX/eax8bqXvQnn4R27YxumRBCCCGEEMIeSYIucsR+dG/6F0AfdG96ZyMbZCfKlYM5c6BZM1i+HKKi9Md166TauxBCCCGEECIlSdBFjokGRgOPAneBjcA8oJiRjTJYz54wZAgcParnppctC++/D489BidPQv/+RrdQCCGEEEIIYS8kQRc5zg9oAkwG+qJ70zsZ2iL7kZAA06dDgwZw4ADMnw///APVqxvdMiGEEEIIIYTRJEEXuSIaGAX8D7gHbEIvz1aQe9OTu3ABOnbUPehNm8KxY7pn3VF+I4UQQgghhCiw7CYd+AjYhy40dgP4DaiXyTlVAGUhpJK4/dgHNAb+D+gHHAMeM7RF9uX776FuXfj7b5g6FXbtgnqZ3fhCCCGEEEKIfMluEvR2wGx0j2sHIA74GyhpxbmPA57J4t/caaLIomhgJNASiAI2A3OAokY2yo5cuwZPPw0vvqiHuh88CGPHgouL0S0TQgghhBBC5CW7SdC7AIuBE+g5y68CZdFJXWZuAsHJIjZ3miiyaS+6N/0rYAD659zR0BbZlxUrwMdHr5U+fryeo96smdGtEkIIIYQQQuQVu0nQUysGOAFhVhy7Bp2Y7wCey81GiWy7D4xAv/FyHz1KYjbSm2528ya88opeL71kSdizB776CtzdjW6ZEEIIIYQQIrc5oKdt250VQC2gGZCQzjGlgdeBnegh8U8BH5u2/Wzh+AEDBjBw4EAAmjRpwsGDB3O41TnDx8cHf39/o5uR6xzu36finDl4LF1KjKcnF8eM4a6vr9HNshtOThFUrPgN5cqt4f79Sly69Al37zbN8ccpKPebMJ7cayIvyf0m8pLcbyKv2PO95uPjQ9Gi0u2WEyzVWTM0poC6CqpaFs79FtQRK46LiIgw/HmmF35+foa3IS/jf6BOg1Kmn18RO2iTPUW7dqizZ1FKob77DlW8eM5ev6DdbxLGhdxrEnkZcr9J5GXI/SaRV2HP95o951cPUtjdEPepQG90obiALJy/F93zLh4cu4BG6J/9W+hK7+0MbI+92boVGjbUQ90HDIATJ+CJJ4xulRBCCCGEECKn2VWCPh14CZ2cn87iNRoBQTnUHpF3ooAPgDbo6QpbgFlAESMbZUeiomDECHj0UQgLgz/+gJ9+gjJljG6ZEEIIIYQQIqfYTYI+C3gD3XseBniYInmCNgldVMzsNdPxdQBvdIL3NvBNHrRX5I6dwMPANGAQcBRoa2iL7IufHzRtCuPGwfPPw8mT8MILRrdKCCGEEEIIkRPsJkF/GyiOXsP8erL4MNkx5YEaqc77BNgP+AEvAn3RPfHiwRUFDEMn5vHAVmAmUNjANtmT2Fj47DNo0gQuXIDly2HdOqhQweiWCSGEEEIIIbLDbhJ0h3RifLJj3gCqJft6CVAPvURXCcAXy9XbxYNpB7o3fTr6DZyj6CHwQjtxAv73Pxg2DB57TPem9+9vdKuEEEIIIYRI36BBupMpKgr274dWrTI+vn59XZMpMhKuXIExY1Luf+YZ2LgRbtyA8HC9THH37rnW/FxnNwm6EJZEAe+TVDRuGzAD6U03S0iAadN0EbmDB2H+fPjnH6he3eiWCSGEEEIIkVKvXjBjBkyaBI0bw65d8Ndf4OVl+fhixWDzZggOBl9fePddGD5cd1CZtW0L//4L3brpa/75J6xdm3nib88MLyVvRNjzMgD2vHyCkVEY1Az0cmxnQbW2gzbZUzg4oAYMQN2+jbp3D/X++yhHx8zPk/tNIq9C7jWJvAy53yTyMuR+k8irsOd7zZr8as8e1Lx5KbedOYOaNMny8W+9hbpzB1WoUNK2jz9GXbmS8ePs3Yv6+mvjvydZCelBFw+MSOA99Nx0B/Tc9Ono3nRP09cexjTNLiile9Dr1dO96FOn6ncl69UzumVCCCGEEKKgc3HRxY43bUq5fdMmPW3Tkkcfhf/+g/v3k7Zt3AgVK0LVquk/VrFieuWjB5Ek6OKBsx1oCHyLTtiPALOBVsBYA9tlL65ehaeegt699VD3gwdh7Fj9R1EIIYQQQojc4OzsjJ+fX2IMGDAgxf4yZcDZWQ9XTy44GDw9LV/T09Py8eZ9lgweDJUqwY8/ZuFJ2AFnoxsgRFZEAu8CA4GapgAYbIooZJ768uXw9996ns/48dCzJ/Ttq4txCCGEEEIIkZPi4uLw9fXN9DilUn7t4JB2W2bHW9oO8Oyz8NVX8OKLcPlypk2xS9KDLh5oVYEVQKzpawXsJu1yfAVVaCi8/LKuZFmypK5q+X//B+7uRrdMCCGEEEIUJKGhEBeXtue7XLm0veRm169bPh7SnvPss7rX/LXXYP36nGmzESRBFw+068At9I0cbdr2KLAeSGcqS4H0++96LvqCBbry5ZEjuuKlpyfUrj0Qj4I8eV8IIYQQQuS62Fg4cAA6dUq5vVMnXTfJkt27oXVrcHNLefzVq3DxYtK255+Hn36CPn1g9eqcbnnekgRdPPDKAXOA5ui56PvQxeJ2Aj8CFYxrml0JD4e33oL27cHRUa8nuXkzFC16mLEyeV8IIYQQQuSyqVN1Et2vH9SpA9OnQ4UKMGeO3j9pkp6iabZ0qV7/fPFi3dn0zDPw0Uf6OmYvvAA//6y3b98OHh46SpbMwyeWwwwvJW9EyDJr+TsKg5oAKgrUXVCjQLnZQbvsJSIjUUqljchI49smkX9D/rZJ5GXI/SaRlyH3m0RehT3fa9bmV4MGoQICUPfvo/bvR7VunbRv0SK9L/nx9eujtm1DRUWhrl1DjR2bcv+WLZZf127ZYvz3JCshReJEvhQJjAEWAl8Dk4B+wDDgNwPbZS+qV4evv9Zzdczz0YODoVcvY9slhBBCCCHyt+++02HJG2+k3Xb8uJ6amZ727XOmXfZChriLfC0AeA54DLgPrAM2AnWMbJQduH5dD3l3dYWEBFcSEqBECb1++tdf67UjhRBCCCGEEHlLEnRRIPwDNEIvzeYLHAWmAiUMbJPRypXT8338/Rfx3Xd6vs/ChfD++3DqlF6eQgghhBBC2Acp7lswSIIuCow44BvAGz30/T3gDNCfgvmL0LMnDBkCUVHeDBmil2J780149FG4dg2WLYN//4W6dY1uqRBCCCGEGDNGivsWBAUxLxEFXCjwFtAUOA3MR1d+l2XZtH374JFHdMX3hx+Gw4f12ulFixrdMiGEEEKIgicyEpSCwYPBwUExeLD+OjLS6JaJ3CAJuiiwDgNtgBdJWpbtJ2RZNoCEBJg7F7y99bIWw4frYe8vvGB0y4QQQggh8j8XF2jTBiZOhDNndEJudu+eXvO7WjXj2idyjyToosBbAdQGJqALyp0GRgFuRjbKTty8CQMHQosWurDc8uW6kJyPj9EtE0IIIYTIX2rWhLffhnXr9Guwbdtg5Ehd2NfPT3egJCS4UqiQ3hYcbHSLRW6QBF0I9LJsYwEfYBN6WbYTwFNGNsqO7N0LzZvDoEHQqBEcOQJffinD3oUQQgghsqpECb3k7Zw5cOECnD0Ls2bp+j8//gg9ekDp0ronPTBQL03m77+IOXOQQnH5mKyDLkQyF9G96B2AGehl2TahC8qdMq5ZdiEhQf8DWbUKvvgCRoyAl16CDz6AlSuNbp0QQgghhH1zcgJfX+jcGR5/XNf8cXLSveH//KNr/mzapJP11Hr21B/9/HRxX5F/SYIuhAX/opdlGwR8hl6WbRYwHrhjXLPsQmgoDBgACxbA7NmwYoUeBj9kiJ6nLoQQQgghtCpVdELeuTN07AglS+pOj3374PPPdUK+dy/ExRndUmGNS5dsP0cp6NYNTpyw7nhJ0IVIRzw6KV+Onp/+HvAy8DF6mbYE45pmF/bu1e8CDxwIkybB0aMwdSpMmKCLlwghhBBCFDRFikD79klJee3aentgIKxeDRs36t7ysDBj2ymyplIl+PNPCAmx7nhHR3jlFXB1tf4xJEEXIhOh6J70ucBM9LJsbwHvArsMbJc9SD7sffJkXcjk5Zfh/ff1NiGEEEKI/MzBARo31kPWO3eG//1PJ2P37sHWrXq04caNcPq00S0VOeWzz3TRPms4OcGrr9p2fSkSJ4SVDpO0LFs5ZFm25EJDoX9/ePRR/Y7iL7/oIVvmd42FEEIIIfKLChXg9ddh6VK4cQMOHNCjCYsX16MJO3SAUqXgySdh5kxJzvOTMWP0aAhrxcfrc65etf4cSdCFsNEKoA6yLJsle/ZAs2Z6iZBmzfSw9y++0MO9hBBCCCHsnaen7vlOXiW9UCHdO/7113DsmE62Fi+Gdu3gjz/06EEPD2jaFEaNgi1bICbGoCcgctWkSXrpYVvPuXHD+uMlQRciC9Jblu1pIxtlJxIS9HCu2rXhp5/go4/A3z+p+qgQQgghhL0aMwZatYIZM/RKNRs36vniGzfqDoigIPjwQ2jYUPek9+mT1JMuChYHBz2EPbnOnWHYML0scXaoghgRERGGtyG98PPzM7wNErZFB1DHQClQG0H52EGbrI3cvt8efRR18CBKKdSmTajatY1/zhLGhPxtk8jLkPtNIi9D7rcHPyIj9WuV1BEfj5oyBdW5M8rd3fh22vO9Zs/5VW7E8uWoH35I+vrNN/X9Eh+Pun8f1bFj1q4rPehC5ADzsmzvAL7oZdmmASUAT2Ar4JHOufnd7t1Jw959ffWw90mToHBho1smhBBCiILMwUH3ln/zDdy9q7cppT9GR+uq6xUq6J70TZsgKsq4tgr706KFruhuNny4Xoa4RAlYswY+/jhr15UEXYgcYl6WzRtYgK7yfhZYCrRCD4kvqMzD3r294eef9fwsf3947jmjWyaEEEKIguaRR3Qxt8uX4b//oF8/2L5dD2NPSNCJuLMzBAfrEMKScuWSir/VqAHVqsGsWRARAYsWQYMGWbtupsusjcnadRMtAbKwnrsQDyzzsmxvAGWB9qbtg00RBRTUzuOQEOjbV7+7+O23eim2TZvgnXfgzBmjWyeEEEKI/KpJE3jhBejVC6pW1T3kGzbAiBGwfr1Oqlat0svHzpsHAwfqgnFCpCc8HEqX1p+3a6dXNTp2TH8dH6+LC2ZFpgn6p+jB8A5ZuLgCdiAJuiiYqgJfAz1JqvB+F/075QoU5OKeu3bpYe9vvQUTJ+o/Zl9/DZ9/DpGRRrdOCCGEEPlBgwZJSXmtWhAbC5s3w9ixsG6dTrCSS17QdsiQvG2rePDs2qWLIcfFwdChKYe716wJV65k7bpWDXF/H6hmYzQla0m9EPnFdSAc/S5YFJCArv4+BbgADKXg9qSDfmfx2291tfelS2H0aD3s/Zln9H5Ly5wIIYQQQmSkTh0YNw5OntR1b0aOhIAAPYzd0xO6dYMff0ybnAthqxEj9Hr3v/2me8s//TRp3wsv6DpMWZFpDzroIbuXbbxwhI3HfwQ8C9QGooE96LWlT2RyXn30vN/mwC1gLnp9aiHsQTlgDjAPGIguGPcdMBpdRO5jYAb6Hr5tTBMNd+MGvPFG0rD3NWv0kLObN3XhlrFjdYE5IYQQQghLatTQCdELL+jlzxISYNs2vVTa6tV66LEQOe3cOd3RVKoU3LqVct9779m+XnpyGZZ5bw6qVNbKw6vmoIpaefwGUH1A1QNVH9QaUEGgSmZwTjHTMStM5z0LKhzUMCsez56XAbDn5RMkci5agFqHXpotHNRkUB4GtMOe7jcnJ1RMjOVlTiIjjW+fRPbCnu41ifwfcr9J5GXI/Zb3UaUKavhw1P79Sa8V/vsPNWQIytPT+PblVtjzvWbP+dWDFJkOcd+H7pm2VYLpXGt70rsAi9E95seBV9EFtlpmcM7L6CHCr5vOWwN8CQzLQnuFyGt7gKeBhsB64EPgIro3vYpxzTJUfDxUrqzf7Y6L09uU0gXk2rQxtm1CCCGEMFbFinqu7+7dcPEi/N//6dcLw4aBlxe0bq2raGen51KIrHB01Pdi48Y5cK3sXyJ3FAOcgLAMjnkU+A+4n2zbRqAiukCXEA+CY+g3m2qjVz0YAJxDv2FVx7hmGeb6dT3s3cEB7pt+uatX1/+MFy7URV6EEEIIUTB4eOipbtu366Jb06aBq6ueW16tml6Letq0rBfkEiKnOORQATYHdFe61QYDzwCd0tm/EViNnnObHSuAWkAzdG98eo91BeiXbJsXer78o+geyuQGDBjAwIEDAWjSpAkHDx7MZitzh4+PD/7+/kY3QxjEJTgYj6VLKbtmDY7R0dxu146gPn2IrFs3Vx7PHu+3GjWGExtbhpCQZyhbdi2urleJjq5CmTJrcXSM5datx7h+/Q2iomoa3VRhA3u810T+JfebyEtyv+UsZ+cwHnpoC6VKbaZYsYM4OCQQGVmDsLBO3LrViejoykY30TD2fK/5+PhQtGhRo5thCEdHiIkBX184dCj717NpTPw+ULMz2P8NqD3ZHHc/BdRVUNUyOW4jqAWptlXWI2LVI5mca89zJOx5bolE3kVpUONB3ULf0xtAtcmFx3mQ7rdy5VBffIEKD9dzzdasQTVtany7JKyLB+lek3jwQ+43ibwMud9sC09P1NatKA+PpG0lS6L69kVt3IiKjdX/5/39UZ9+ivLxMb7N9hL2fK/Zc36V2+HoiIqPRzVunAPXwka10ENy03PCdExWTQV6Ax2AgEyOvY6uip1cOdPH4Gy0QQh7cBMYh56PPgJ4GNgG7ACeMLBdRrpxA0aNgipV9FIW7drB/v163cn//c/o1gkhhBDCGmPG6JVaJk6EV1+F33/XU9y+/15XZP+//4OHHwYfH/3/3k47jIVIlJAA7dvD6dPZv5bNCboLUCiD/YUy2Z+R6cBL6OTcmue2G2gNuCXb1gm4ii62JUR+cBf4CqiGnmJSEfgDOAT0wo4LSeSisDAYP14n6h99BM2awc6d8O+/+o+jEEIIIexPZCQoBYMHg5MT9O8PS5ZA164wfbr+f16zJnz8sV7DXIgHyfbt+h7PLptf258h/fnnAJ2B81loyCzgDXTveRjgYYoiyY6ZBPyd7OulQCS6mFY99Nz4j9C98ELkN/fRa6jXAl5DvzG1AvAH+qLfPCto7t6FL7+EqlV1VdfatXWSvnMnPFFQhxkIIYQQdsbFBZ58Ev76C2Jjk7bHxsKGDVChgi76duCAcW0UIiNVq8Lff8P58zBlCrgl6yHeuzdnH8vmBH0ZOgn/jJQJgTPwqWnf0iw05G2gOPAveui6OT5Mdkx5oEayr8PRbxZUAPYD3wJTkARd5G9xwI/oN6WeRfewf49+Y+xd9NKDBU1kJMyYoau9v/WW/kf/xx/6H/0zz+RcVU0hhBBCWMfRETp0gPnzITgY1q/XS6aeOaOHA0dF6WMuXND7hbBns2fDmjXw/PNQqhT88w+Y6+G55HAvmc0J+jRgO/AxcA29zNl2IAgYg54fOyULDXFIJ8YnO+YN9DDf5I4DbQF3dKL+WRYeW4gHkQLWolc6eBy4AMxAT+8YDZQwrGXGiY6GuXP1Umx9+ug/nGvWwLFj0Lu3Hk4nhBBCiNzTooV+0/zqVZ3EvPCCTs67doXy5eHUKfjuO33cnDl6GTUh7J2Hh07SDx6EN97QdRP++QeKF9fTNnKazZXlnEENB3UIVIQpDoL6wLQvK9fM67DnKoP2XJ1Rwr6jJajf0VXfb4OaBKpcJufk5/vN0RH1wguoY8d0NdgzZ1BvvIFycTG+bQUx8vO9JmF/IfebRF5GQb/fGjZETZqEunBB/7+NikKtWoV67jlUoULGty8/hT3fa/acX2U3jh9Pu+2DD1B+fvr1ZU4+VpbqS8Whi1Y1Boqaogm65zwuKxcUQuSIncCTQCNgAzAS3aM+EyiIK4YmJMCKFdCwoR7qHh4OCxfC2bMwaFDK+UNCCCGEsF7NmvDJJ3DiBBw5AsOH697x116DcuWgZ09YvRru3ze6pUJk35kz8NhjKbdNmQJLl+qVB3Ka4e9IGBH2/A6PPb8zJvFgRS1QC0DFmGIhqNrJ9nuCCm/cWHnYQVvzKrp0Qe3Yod/hv3YN9f77qMKFjW9XQQj52yaRlyH3m0ReRkG53ypWRA0bpnsNldKxdSvqzTdRZcoY376CEPZ8r9lzfpXdcHXVYWlfhQo5+1g296APBjZnsH8jMNDWiwohcsVZoD+6uOJs4AXgJLASPQJmDFD08GHGGtbCvLdhg157tX17OHkSpk6Fixf1+urFixvdOiGEEMK+lCmjC7Bu2wZXruheQ4APPoBKlaBdO13/JTTU0GYKkatiYnRYcu1azj6Ws60n9EFXTE/PGfSST/Oy2CAhRM4LBIYCnwPvoYvIPW/eqRSD0W++RVFwqsBv3arj0Uf1equTJsGIETBzpi5uc+uW0S0UQgghjFGsmJ4a9uKL0KkTODvrN7XHjIHly+HcOaNbKIT9qFQJvLygUKG0+7Zssf16NifotYBFGew/AbxkezuEEHkgBPgE+AG9hnoj9GoJCeie9bcMa5lxdu/Wa7M2bqwT9bFjYdgwXalz6lRZ+kUIIUTBUKgQdOumVz3p1k1/HRAAX32lk/KjR41uoRD2pVo1+PlnaN5cf21e1lcp/blS+s0tW9l8igtg4c2BRIUy2S+EMN5ZYA/QEHBwdsYhLo666GUS9wCL0Qn8baMaaIBDh3RBm7p1YfRoPXTvnXf0+q1ffaWH9QkhhBD5ibOz7iHv3Rt69NA959evw7x5sGwZ7NljdAuFsF8LFkDlyjB0qC6QmN4Q+KywadL6QVB/ZrD/T1BH7WAif2Zhz0UM7Ln4g0T+iVWgZoE6/vPPahZ6ebZh6N9fBSoK1ApQXUE52UF78zpq1kQtWICKiUFFR6PmzkVVq6b3eXrqojgeHsa380EK+dsmkZch95tEXsaDdL85OqLatkXNmYMKDdWF3m7dQs2fj+rQQe83uo0S6Yc932v2nF/lRoSHo559Nueva3MP+jLgC+AzYAIQa9rujB4629n0UQhh33qaPvp5ezMk2fap6AJyfdDTVXoBQcBP6KHxJ/KwjUY6dw7694fPPtNz0/v1g7599XIazs660NzYsfD220a3VAghCh5nZ2fef/996tWrh6NjllYNzlG3b99myZIlRjcjBScnXeAtNBTi48HVFYoU0eHkBErBvn1w755eCs3NDfr00SHsl5H3WkJCAidOnGDatGnExcni2leu5GyveXK2ZvTqX1DxoEJA/Qdqu+nzeFBbQbnYwTsamYU9v8Njz++MSeS/yOh+cwH1NKi16GXaFKj9oIaAKm0Hbc/LKF8eFRubtKxM8oiMNL59D0LI3zaJvAy53/J39OzZUw0dOlS5uLgY3hZA+fj4GN6G1FG5MqppU5SPD6p+ff15kyaoGjVQJUtKT/mDGkbeay4uLur9999XPXv2tLjfnvOr3IhXXkH991/OL9dr81uOcehe8o+AK+ietiboKtEjgMdI6lUXQjzYYoF1wDNABeBddFG5b4BrwGrgKbJQzOIBFBSkK3SuWpXy3dLYWPjzT+jSRfdICCGEyH3t2rXj559/JjZWXnWm1qQJNG0KZcvqrwsX1r3jSsGRI3D+PISFQUKCse0UD57Y2Fh+/vln2rZta3RT7MJPP+nlBy9ehN9+gx9+SBmLF2ftulkaExQHfIVOzouaogkwxbRPCJH/hKIT86bo4nLfAP9DJ/DXgGnoqvD52fXrEBKiE/GoKP3i5vRpvab6X3/B1aswbZp+cSSEECL3FCtWjJs3bxrdDLvg6AgPPQRVq8LDDydVkjZLSNBLhx49qoe6C5EdoaGhFC9ePFvXGDQILlzQr6X279fTBjNSv75eGjcyUg8rHzMm5X5PT11N3d8f4uJg0aJsNc9qr78Oo0bp378mTaB167SRFVYl6JeBmUAHa08QQuRrx4APgUpAN2ArMAg4BBwG3gfKGdS23FauHMyZAy1awHff6QS9fHm9XuyOHfqfzoEDcOKE/qNdubLRLRZCiPzHwcGBhALcBezsrOeX16wJjRpBjRo6SQgP14lPaKg+LiFBJ/Dx8TpxESK7EhIScEj9LpANevWCGTNg0iS9xO2uXbqTw8vL8vHFisHmzXrZW19fePddGD5cL4lr5uam7/nJk2Hv3iw3zWbjx8PatXq0SqVKUL16yqhRI+vXznQc/CxQl9FzzG+CWgKqByh3Oxj7n9Ww5zkSMm9OIi8jp+63kqAGgdqDnqseC+o3UM+BcrWD55lX8dBDqAEDUNu2Jc1R37oV1b8/qkQJ49tnZMjfNom8DLnf8ncsWbLE8DYkj7yYF1yokF5FpE4dPZ+8aVM9t7xSJVSxYimPrV4d5eWFcnfXH6tXN/57JJEzYQ/1DtL7/bMmv9qzBzVvXsptZ86gJk2yfPxbb6Hu3NH3v3nbxx+jrlyxfPz69ahFi/Lm+3D3rl75IKeva1WH+BCgMtACmAs0Q889DQV+BV4HSllzISFEvhUGfIf+O+EDfI2e+rIKXQV+FuBrWOvyzu3beu30tm2hWjX4+GPw8NDbgoPhl1/gqafAxcXolgohhLB3RYvqnrn69aFePahYUW+/elWP1Dp+XA/5vXs35XkXLkBgoB5CHBiovxYitzk7O+Pn55cYAwYMSLHfxUXXR9i0KeV5mzbB//5n+ZqPPgr//adXGjDbuFH/LlStmrPtt9WOHeDjk/PXtWnEuh8wGqhrigmAJ/A9cB34F3gHncwLIQquU8Ao9N+Cx4ENQF9gH3qZthHoonP53cWLegiXjw80a6aHxrdpA+vW6aJz336r//EIIYQQkHY+ee3aemrV/ftw6ZKeR37qlK6Jcv8+eHt7c/DgQcLDw3nnnXcICAigY8eOuda+3Lj+8ePHs1V0LPX3IC9lt+35TVxcHL6+vokxf/78FPvLlNHTM4KDU54XHKznkVvi6Wn5ePM+I733HgwYAC+9BKVK6foPqSMrsjyl/DQwGd1bVhk95zQe3Wt2ATiAfmEuhCi4EoBNwMvoN/MGALeAL9G1Lf4CXgQKGdXAPHTgAAwdqt/xfeIJ/e5vnz567tW5c/Dpp3ouoRBCiILFxSXtfPISJeDOHV1x/fBh/X8iNFSvHJLciBEj2Lp1K8WLF+ebb74xovnZVr9+fbZt25bl8/Pqe2DpzYnstj0n2/IgUSrl1w4Oabdldryl7XnN3x8aNIAlS+DGDf37mTyyukZ6jqyOdA341hQl0Msu9QDqAxtz4gGEEA+8cGCBKWoCr5liGXAHWAH8AOwyHe8JLAdeAIJTX+wBFheni6H89ZcufPLMM/DKK7oi6bhxsGcP/PgjrFgBUqBYCCHyp0KFdE/5Qw9BkSJ6W3S0fpF/+zZERFh3nSpVqrB8+fJcauWDQb4HD47QUP06KHXPd7lyaXvJza5ft3w8pH9OXvnss9x7k8DwQgNGhBSJk5DQYeT95gCqHajFoCLQxeVOg/oY1A+g4kB9awffo7yIChVQH3yAOnxYF5aLiUGtW4d6/vmUhVEe5JC/bRJ5GXK/5e/IbpE4T09dwNPDI2fak7pwl4ODg/roo4/UpUuX1I0bN9SgQYNUTEyMatiwjKpfP6nIW506ui1Z+Tv/zz//qLi4OBUVFaXu3r2ratWqpQICAlTHjh0VoJRSqkaNGonHL1q0SE2YMEEBqnr16urmzZuqcePGClDly5dXISEhqm3bthk+ZkBAgProo4/UiRMn1K1bt9TChQuVm5tb4v6RI0eqc+fOqfDwcHXixAnVo0ePxH0jRoxQV65cUeHh4erUqVOqQ4cOidc0tzmj46z9HmT0vM2P98EHH6gjR46o27dvq+XLlyc+h0qVKqnVq1erGzduqNDQUPXNN98k3m/x8fEqMjJS3b17Vw0fPjxN2+vUqaO2bNmiwsLC1PHjx1X37t2tekxbn/O6devStOXDDz9Uq1atSnHczJkz1bRp06z6uZUvX16tWrVK3bhxQ124cEG98847Wfr9s7ZI3Ny5KbedPp15kTg3t6Rto0bZR5G4XAwb/xhkEn+DWo+u/P608U8u3ZAEXUJCh73cb0VBvY5OypWFiLSDNuZVNGiA+vJL/c9HKdTt26gFC1Dt2qEcHIxvX1bDXu41iYIRcr/l78hugv7tt6i4OP0xJ9qTOkEfN26c2rFjh2rQoLJq2LC4OnJktwoJCVJNmqBq1kSVKYNyds7+427ZskX169cv8WtrE3RA9e/fX508eVK5u7urDRs2qK+++irTxwsICFDHjh1TlSpVUiVLllQ7duxIcc2ePXuq8uXLKwcHB9WrVy8VERGhPD09lbe3t7p8+bIqX768AlSVKlVU9erV07Q5o+Os/R5Yk6Dv3btXlS9fXpUsWVKdPHlSvfnmm8rR0VEdPnxYTZ06VRUuXFi5ubmpli1bWvzept7m7Oyszp49q0aNGqVcXFxU+/btVXh4uPL29s7wMbPynH18fNK0xdPTU0VERKgSJUooQDk5Oang4GDVpEmTTH9uDg4Oav/+/WrMmDHKxcVFVatWTZ0/f1517tzZ5t8/a/KrXr1Q0dGofv30G1TTp+tq6JUr6/2TJqH+/jvp+OLFUUFBqGXLUPXqoZ55Rifsw4alvO7DD+vYtk13cDz8MMrHJ+//NuVE2DzEvTrgDpQ1fX3b9PEh08cQ9MT2J4C3gJ1AVyDS1gcSQhQoEegh7hvR1eCfAFzRf6kcgHvAj+iCcxvRq0jkV8eOwciReh31du30EPhevaBfP12N9+ef9TD4kyeNbqkQQtiHadP0/O3MtG4NTk5JXw8erCM+XleKzsjhw/D++2m3OztDoUIXcXbWc2Nr1CjDhx8O48UXG+Lqepm4ONi8+Q+aNGnD4cN6bXJ7sGDBArp3787evXtRSvHUU09Zdd6sWbO4cuUKAJ9//jnffPMNY8aMAWDVqlWJx61cuZJRo0bRvHlzTpw4gZubG3Xr1iUkJIRLly5ZvHZ8fLxVx2XXzJkzCQoKAmD9+vU0atSI5s2bU6FCBYYPH058fDwAO3futOp6LVq0oGjRokyePBmlFFu2bOH333+nd+/ejB8/Pt3HhJx5ztevX2f79u08//zzLFiwgC5duhAaGsrBgwcTj0nv5+br60vZsmWZMGECoOe3z58/nxdffJFNqcut54CVK6F0afjkEyhfXq9E8MQTcPmy3l++fMr1w8PDoVMnXVh3/34IC4MpU2Dq1JTXPXw45ddPPaWL9VarluNPIdGIEXqVhXffTbtvxgz9mu3rr22/rs1F4tqhk+2vAA+gtCk80AXi7qGXYSsDTAFaAWNtb5cQooC6jl6WzQmIQhea24wuKNcZ+Ak9J30v8CnwCNmodmnnEhLg33+hb1+9VNuLL+oKvh9+qJfXOXhQv1hMPjfL0xO2btXHCyGESGnvXj1v1ZR/ER+vv967N+vXrFwZHB2jqFcPGjaEZ57pyIUL/hw+fIlTp+DIEXByKs2hQ8fsJjk3mz9/Pg0aNOCbb74hxsqKVoGBgYmfX7p0iQoVktZlefXVVzl06BBhYWGEhYVRv359ypQpw/nz5xk6dCiffvopN27cYNmyZZQvXz7Nta09LruuX7+e+HlkZCRFixbFy8uLS5cuJSbntqhQoQKBgYGoZBOSL126REXzunjpPCbk3HP+4YcfeOWVVwB45ZVX+PHHH1PsT+/nVqVKFSpUqJD4MwsLC2P06NF45OILie++04lzoUJ6lZvkb4698UbapPr4cb18rbs7VKig536nZqmCem4m5+a2Hj1qed/hw3p/Vtj8unYaulf8I1L2YIUCI9EFnqah10QeCfwBPJe1tgkhCqhywBz0KhFz0AXmXkMXjvNFJ+ZxwCfAHnTC/jPwCkmje/KbqChdOO7JJ/U/p3fe0RVCp07Va+Bu2KB72j/7DFq1grHyzqgQogB5/31o3z7zaNkS1qzR50RF6Y+rV+vtmZ1r7j0vXFgXqWraVEfJknq7s2lcaokSZbh8OYSrV+HePXBycqJ79+4cO3YMgL179zJlyhQOHTqU7rJgLi4u7Nmzh0KFCtG9e3e+++47m78n9+7do3Dhwolfe6aqtFWkSBGmT5/OggUL+PTTTylpfiKZ8PLySvy8cuXKXLt2LfHz+fPnM2TIEEqXLk3JkiU5fvw4DqaS28uWLaN169ZUqVIFpRRffvmlxetbe1xWn3d6AgMDqVy5Mk7Jh1gkozKoBnbt2jW8vLwSnyvo78fVq1etemxbn7Oltvz66680bNiQevXq8eSTT/Lzzz+n2J/ezy0wMJCAgABKliyZGMWLF6dbt25Wtb0gq1wZzp61vO/CBahSJWvXtXmIe3t04p2eHejl18z+BjrZ+iAGcnZ2pkePHrRr145ixYql+EXLK7dv32bJkiV5/rjCNkop7t69y9atW/n111+Ji4szukn5Rs9knw9J9rkC9ptiAlAK/felK9AFeAnd434A3eP+F3rtdTvrsMi2kBCYNUuHt7dOzD/+GB5PtraledhmVJR+MSmEEEIrVw7mzIF582DgwIzXUnZw0H9DixWDokV1mPO36Gj90dVVH5eQoCuw//vvKQYM+IyqVaty+/Zt/u///o8aNWpw/PhxSpcuTenSpRk3bhwTJkxg+fLlFpcGi42NZf78+cyYMYOyZcvy/PPP2/w8Dx8+zEsvvcTHH39Mp06daNu2Lfv370/cP2PGDA4cOMCAAQOYO3cuc+bM4YUXXsj0um+//Ta///47kZGRjB49mhUrVgA64VdKERISAkCfPn2oX78+oNcqr1ixIjt37uT+/ftERUXh6Ji2n9Da47LzvNOzb98+goKCmDx5MuPGjSM+Pp6mTZuya5deXyY4OJjq1avzzz//pDl379693Lt3jxEjRjBlyhRatmxJ9+7d8fX1zfRxs/KcLbUlOjqaVatWsXTpUvbt25eixxzS/7nt27eP8PBwRowYwcyZM4mJicHHxwd3d3ervm8FWWSkXj7XkkqVkv5GZIVNk9Zvg5qawf5ppmPMX78N6pYdTLZPHekVMRg+fLgaOnSoKlu2rHJ0dDSkbakLjUjYZzg6OqqyZcuqoUOHJlbzfBAjvxRScgDVBF0BfgdJxeZugloG6jVQ5eygnbkVnp6ojRt19XelkuL2bdSvv6LefVcXnzOyyFx+udckHoyQ+y1/R3aLxKUXDg6ookVR5cujatVCNW6cVHG9bl1dyKpkSZSLiz6+cmXzfgfVtGlSoas5c+aoO3fuqNOnT6t33nlHxcXFKXd3d9W+fXs1ceJEBahatWqp2bNnp9sWHx8fFRcXpypUqJDuMRkViWvatKk6fvy4Cg8PV0uWLFFLly5NLAz21FNPqStXrqiSJUsqQBUpUkSdPXtWvfTSSxl+f5JXAw8LC1OLFy9W7u7uifsnTpyobt68qUJCQtSUKVPU1q1bVb9+/VSDBg3U3r17VXh4uLp586Zav359YlG05G3O6DhrvwcZPe/Ujwe6oN+PP/6oAOXl5aXWrl2rQkNDVUhIiJoxY0bicU899ZS6dOmSCgsLUx988EGaa9WtW1dt3bpV3b59O00F+4we09bn7OPjY7EtgGrZsqVSSqk+ffrY9HMrX768Wrp0qQoKClK3bt1Su3fvTlMQz5rfP3suwp0bsWYN6tAhlKtryu2urqiDB/Xrryxe27YTVoGKAvWChX0vmvb9kmzbIlAH7eAbmDrSu4EWL16sXFxcDG2bJOgPVri4uKjFixcb3o6sRn59EVsSVC/036AgkqrB7wc1AdT/QDnZQTtzMmbP1lWJIyP1x40bUfPmoc6eTUrYb9xArVyply3x9s7b9uXXe03CPkPut/wdOZWgOzqiihXTS13Wro1q0iQpIffxQXl5oR56KP2K69Wr62Pq1q2mvLz016mP6dSpkzpz5owC1HvvvaeeffZZBahevXqpt956SwGqYsWKKc4pVaqU2rx5sxo5cuQD3QkgkfORUZ7g5eWl7t27p4oVK5Ziu6UK9NkJSdB1NGyIiohAXbyImjgRNWiQ/njxoq5M37Bh1q5r8xD3YUBz9HzPr4Fzpu01gfLo4k4fmLa5AVWAB2mwtqOjI7GxsUY3QzxAYmNjbR5+JXJfGLDSFA5AI/RQ+K7AKPT89VskFaDbgJ7L/iCzNGxz4EC9z8tLz6Hs0EGHebTktWu6EN2WLfrjxYuGNV8IIXKdo6Mepl6smI7ChfXwdKX0cNXgYIiI0GFNrbALF/RHH59CpBpRnMjHxydx/nmDBg1Yv349AI0bN2b9+vU4OTmxbNky2rRpA4CrqytLlizh/fffx9/fn507dzJ79mzu3buX7ecv8i8HBweGDRvG8uXLuXv3rtHNKRCOHtWvrb7+Wq++4+iop7rs2AHPPZd+AbnM2JygXwYeRheJexJdQRngIrAU+BL9ohcgGuiQtXYJIUSOUcAhU0xCLwv5GElz180z7g6SNHd9D2B7HVdj9Uw2eX/IkJT7AgNhyRIdoJcw6dBB/2Pp1EnPYwedoJsT9i1bwMr6NkIIYZecnNIm5KAT8nv34Pr1pIQ8tyqs+/j4cPz4cQD69++fuH3UqFEA+Pr6pqg9FBMTw5NPPpn4dYsWLXKnYRZ4eXlxMp01POvWrZtmXnNesMc25baMnvPTTz+Nv79/im2FCxcmODiYS5cu0aVLl7xoYoHVogXs2ZP0tZ+frjBfqJAuGBkWBvfvZ+8xbE7QIalCe0bF4kTeatWqFQsWLKBOnTpGN0UIu3cbWGUK0G86mnvXRwIfm45J3rselOx8T2A5OrF/UHvdz5/XMX++/trHJylh79FDL+0GcOaMTtj//Vcv32aq/SOEEHbJ2TmpoFuxYnpZJtDJ9717etTQ3bv68wyKcueoQYMGZbjfz88PPz+/vGlMJgIDAylWrJjRzUjBHtuU2zJ6zj4+Pmm2RUZGZvg9qpbb640VIDt2wI0b8NtvsHYt/PMPxMXppDwoKPPzrZGlBF0YJyAggP79+6epILljxw67Sc7HjRtHzZo1efXVV41uihBWOWKKyUAJUvaum+vmHiapd/0loBUwFng7j9uaW/z9dXz7rR7u2bBhUsL+0kvw1lv6uGPHkobDb9umKxYLIURu8/SE5cvhhRf0MHQzF5eUCXmhQnp7QoLuFb91SyfkkZF5l5ALIfKvihXhmWfg6afh1191pfYNG3Sy/uef+u9NdmU6cfZR9FJGWbnwo0BRG85pDawDrqCHpL6eyfFVsDyz/vGMTsplnsBWwMPANuSl9NaKzAtGLIEn8r87wGqgP1CJpCk9d0wftwNvAU7AYPTfnChDWpp7lIIjR2DaNHjqKShVCh55BD76SL873L+//qd08ybs3w//93/Qtat+gSyEELlhzBho1UrP9XzjDShdGurX128mVqum/05FR8OVK/rNxkOH9PrE16/nbW+5ECJ/Cw7W9X66doWyZXUHhlJ6240bOll/800oXz7rj5Fpgv4fWUt4HzKdm/nqf0mKAseB94BIG857HJ0Ym+NfG87NaWNI6lnLS23btk0xBycgIIAPPviAI0eOcPv2bZYvX46bm1vi/m7dunHo0CHCwsLYuXMnDRo0SNw3cuRIzp07R3h4OCdOnKBHjx6J+15//XV27NjB1KlTuXnzJp9++qlN7czo2o6Ojnz99deEhIRw4cIF3n77bZRSiW8CbNmyhYkTJ7Jjxw4iIyOpXr06ffr04eTJk4SHh3P+/HkGmitiJfueDBs2jODgYK5du0afPn0S95cqVYrffvuNO3fusG/fPiZMmMB///2XuL927dps2rSJmzdvcurUqSytQSoefEfRtTXaAbXRCbq5jKT59V4h4BSwGBgENCZ/DU+Kj4d9++DLL/Va6yVLQuvW8Omn+p3id9/V7xqHhcGuXTBxInTsmDS0FHTvV+3aA/EoKO9eCiGyzctLJ91KweDBej75K6/AwoX6DcHISF1f4+RJOHwYzp3TL54jbXkRKYQQWRQRoUf29O6tk/VnnoGAAP2GYmCgnqs+MgtzwjN9DekAlAa8bLxwKdO5tjAPHwX9QtdaN8m9eaDT0NWfM9Ma3aNmNtgU8eg3KjJyGHg/C23LTK9evejSpQv3799n586d9OnTh7lz59K4cWMWLlxI9+7d2b9/P6+88gq//fYbtWvXJiYmhvPnz9O6dWuuX7/O888/z08//UTNmjW5fv06AI888gjLly+nXLlyuLi42NSmjK49YMAAunbtSqNGjbh37x6//PJLmvNfffVVunbtyunTp3FwcKB27do8+eSTXLhwgTZt2vDXX3/h5+fHoUOHAPD09KREiRJUrFiRTp06sWrVKn799Vdu377Nt99+y7179/D09KRq1aps3LiRS5cuAbrYxubNmxk7dixdu3alYcOGbNq0iRMnTqRbtEPkf2eBE0BLdK+5K/A7uqBcC/SQePPIn0jggGnfXtPH/FJvLSZGz8HasQMmTNBDSv/3v6Qh8SNHwscf6xfWe/bo4fCNGkHRoocZOxbezi/zAoQQOaJYsaTe8AYNkj4+9FDSMQkJukJydDRs2qTfHDRXUBdCCKPFxene8w0bYNAgXUyuRw947TXdwWELq9aGmg4E2BgHSOpdym1r0An6DuC5PHrM1Paa2mCu+hxv+nqvQe0BmDlzJkFBQYSFhbF+/XoaNWoEwIABA5g7dy779u0jISGBJUuWEB0dnVgldNWqVQQFBaGUYuXKlZw9e5bmzZsnXvfatWvMmjWL+Ph47ttYpjCja/fq1YsZM2Zw9epVbt++zeTJk9Ocv3jxYk6ePEl8fDxxcXH8+eefXDD9h96+fTubNm2idevWicfHxsby2WefERcXx19//UVERAS1a9fG0dGR5557jnHjxhEVFYW/vz8//PBD4nlPPvkkFy9eZPHixcTHx3Po0CFWr15Nz+RlskWBVA6Yg07I5wBx6LnrPdAjeKoCLwJz0e+AvosuRnfFFKuAD9Fv6hXO05bnnvv3dRL+ySfQsqXuYe/aFWbO1D3t48frd5UdHBSDB+vesJgYfYyXre/+CiEeWE5OUKcO9Oql39xbt04n2eHhevTNnDm6h9zBAZYu1S9yW7aE77/XfzeionQRuMBA65ZAE0IIo+zZo6cG1qtn+7mZ9qCPz0qLksnNNzcj0Guu70S/SH4KWIHuwfrZwvEDBgxIHALt7u5usWLm7du3U1RHnGdDe8YGBdHr9m3uOzjgqhT/PvQQE6ycgJC8HmOhQoUsVmgEcHFxoUqVKmn2V6lSBWdn58TtLi4uuLm5JX5dpEgRKlasiI+PD/Xq1cPX15f33nsvxXV9fX0JCQnhqaeeok+fPlSoUAHQvckNGjTg7NmzVKhQgdDQ0HTbB1C2bFlKlChh8ZiMrl21alUcHBwSz3N1ddXfGx8f4uPjKVy4MHFxcSmu27p1awYPHpx4rru7O0FBQfj4+FClShXu3LmDt7d34vGxsbHUq1cPV1dXXFxcKFKkSOL14uLicHd3x8fHB19fX1q0aMGdO3cSz3V2dua3336z+LzKly9vNxVYbeXj4/PAtt0oVUhaYhIgo+/e8ZgYCp89S5Hjxyly7Bjdjh/nOdPaZcrJiagaNYho0IB79epxr0ED7leurLuJ8oljx0Lx8vqKhx76D0fHWJRyJCHBBReXaP78Ux8TH1+EqKjqREXVSPaxBnFxWRmLJYQmf9uMpHB2vknhwudwd08eATg6xugjlBP371cmMrIWV67UJCpKR0yMJ4UKOdC8OZj7BmrUGM7Nm2UICXmGsmXX0rt3KAcOlM/wtUhey+i1mxA5yR7utQf5de+DINME/bO8aEUW3QSmJvv6AFAGGIHlBH3+/PnMN60pFBERga9v2hnyS5YsSbO2oLVcgO+AeUoxEPC8fRv/LJQ49vHxSbcNsbGxXLp0Kc3+cuXKERcXl7g99XEhISGUKFECf39//P392bhxI5MmTUpz/cqVKzN+/Hg6duzI7t27SUhI4NChQ1y/fh1/f3+aN29OZGRkht+j5I9ly7UvXbpEQkJC4nnmJN7f35/4+HgiIyO5du1a4n5XV1f279/Pa6+9xrp164iLi2Pt2rXcvHkTf3//NN+T5N+XnTt3EhsbS0REBGfPngV0Am7uTT9w4ABbt26lc+fO6f+gkgkKCqJTp05WHWtv/Pz8LP4uiNxTBp3gPxIfT4szZ2h+5gzlVq8G9DKW+0gaGr8XuGVUQ3PI7NkwcCAkJLiiVAxz50bz8cf6XeX69aF+/XvUr3+M+vWPUbly0nkhIXD8eMo4cQKSvW8mRLrkb1vecHeHunVTDk9v2FDPxzS7dk0XlDx2DI4e1R/9/eOJiTGPu9xk5aOtSvxsyZK+WX69lhsyeu0mRE6yh3stvde9ERERBrTGOKkW1UohIUG/XjlwQI8CunHD+uvmpzpGgH4x+4ZBj5188POQXHwcc++4WVxcnE3nz58/n7Vr1/L333+zb98+ChcuTLt27di+fTtFihRBKUWIabHjPn36UL9+fZvb6OjomKKNSqlMr71y5Uree+89/vjjD+7du8fITKoquLq64ubmRkhICHFxcXTp0oXOnTtz/PjxTNuXkJDAmjVr+PTTT+nfvz+VK1fmtdde4/LlywD8/vvvTJ48mVdeeYXly5cD0KhRIyIiIjh16pTN3w8hkgsF/jAF6D7iOuikvYUpPiGprsVZdMJuTtqPklSoLjV7XKO9XDk9dLVdu0Vs3foynp56ebadO3WkPlYn7UnRp4+eo2p25UraxN3fXwpDCZFd6S1lBnrYebVqaeeJ16qVNOjn3j39+7huXVIifuyYXvFBCCHyGwcH8PbWFdsDAvTfTQ8P/bcyKEh//cQT8P770Latfq1ijXyXoDcCcmiNeLv1119/pfh64sSJ/P3331aff+DAAQYMGMCsWbOoVasWUVFR7Nixg+3bt+Pv78+UKVMSe7iXLFnCztSvoK3w0ksv8dJLLyV+feXKFby8vDK89vz58/H29ubo0aOEh4czc+ZM2rVrR3w6E80iIiJ49913WblyJW5ubqxfv57ffvvN6jYOGTKExYsXc/36dU6fPs2yZcto1qxZ4rU7d+7M1KlTmTp1Ko6Ojhw5coRhw4bZ/L0QIjMK8DfFYtO2IkAzkpL2x4BXTfuigIOkLEBnXsMh+UoS9lKLzVy6wc/PmyGZvHt544aez/5vquU4KldO3uOuY8iQlGseX7ige9iTJ+6nT0Nseu9mmGSUlAhRkJiXMvv8c/jxx5SJeP36SUspJiToiunHjum54uae8QsXZDkzIUTBMXUqTJ8OTZvqlSTMmjSBlSt1DZ4DB3Rhy88/h2eftf7alpYSNySKgHrYFPdAjTF97mXaPwnU38mOfw1Ub1B1QHmD+gBUNKihVjxWRESExe1Lliwx/Pvg4+NjeBvsIbp06aIuXryYZ483efJktXjx4iydaw/3TVbDz8/P8DZIWBdeoHqC+hrUDlCRoJQpEpJ9njwi7aDd5sjpe83REVWrFuqZZ1BjxqBWrEAdP46KjUUppSMmRm9bvhz1ySeoHj30OY6OSdf59ltUXJz+aPT3SCLnQv62pR9ubqiaNVEdOqD69NG/J+bfmdQREoL65x/U9Omovn1RzZqhChc2/jnY2/9do167eXt7q4MHD6rw8HD1zjvvqICAANWxY8dce7zcuP7x48dV27Ztc+x7kJff/+y2PSthD3lCer9/6eVX+TUOH0a98orlfa++ijp6VH/epw8qNNT669pVD3ozYGuyrz8zxWL0sPXyQI1U53yCLtgUD5wB+mJ5/rmwf4UKFaJ9+/Zs2rQJDw8Pxo0bx9q1a3Pt8WrXro2rqyvHjh3D19eXfv360b9//1x7PCGyK9AU5lmYLkBDdC97e6AzUDzZ8bHoXvnv0cvDmeNKHrU3tyUkwNmzOpL/qXB11UPOkve2N2ume8jNoqLAzS1lPb7Bg3VERUHh/FJiXxQ4Dg56iGXlyjq8vJI+N0e5cmnPi4zUvxNOTnqVhf/+08Myjx3L++cgrDdixAi2bt1KkyZNAB7IkX5ZmUqZXOrvQW4JCAigf//+/JNs4nF2256TbRF5z9sbQkMt7wsJgZo19efnz0ORItZf164S9G1kXK839dzyJaYQ+YODgwPjx49nxYoVREVF8ccffzB27Nhce7xixYqxbNkyKlSowI0bN5gyZQrr1q3LtccTIqfFootjHgBmm2IgelULF3RyHgZ0Q795aXaHlAm7OfLL9KCYmKQh7skVLqyLWZmHyjdtqqtEp/6n6ewMly7pwlZXr+qPlj4PD8+75ySEWdGiGSfflSrpN6mSu3sXLl/WceBA0ueBgfrj1at6mObAgfoNKldXPT1EknP7V6VKlcRaOQWVfA+EUS5ehP799drnqQ0cqPcDlCljey0Ow4cHGBEyxF0iJ8Me7pushgwDzT+xCtQsUA1NH1cl21caVBtQg0z7toC6Qcrh8LdA/QdqDqh3QHUA5ZGD7bPHe232bD28/f59VHw8ats21OefoxYvRm3apIfHh4VZHvobEYE6cwa1ZQvq559RX32FGjoU1asXqlUrVLVqqEKFstc+T0/U1q0oDw/jv1cPWtjj/ZbZz9TZGVW5sr5/evdGjRypp16sX486cgR161ba+zA2FhUQgNq+HfXTT6hJk1BvvYXq1g3VoAGqRAnr2rVqFWrWLFTDhvrjqlXGf68yiuz83+3dW3/P4uP1x969s9+e1K/dHBwc1EcffaQuXbqkbty4oQYNGqRiYmJUmTJlcux78M8//6i4uDgVFRWl7t69q2rVqpViCLpSStWoUSPx+EWLFqkJEyYoQFWvXl3dvHlTNW7cWAGqfPnyKiQkJNPh2gEBAeqjjz5SJ06cULdu3VILFy5Ubm5uiftHjhypzp07p8LDw9WJEydUjx49EveNGDFCXblyRYWHh6tTp06pDh06JF4z+bD59I6z9nuQ0fM2P94HH3ygjhw5om7fvq2WL1+e+BwqVaqkVq9erW7cuKFCQ0PVN998k3i/xcfHq8jISHX37l01fPjwNG2vU6eO2rJliwoLC1PHjx9X3bt3t+oxbX3O69atS9OWDz/8UK1atSrFcTNnzlTTpk2z6udWvnx5tWrVKnXjxg114cKFTKcKyBB3HS++qF9DHDmCGjtW/+0dO1Z/HR+PeuEFfdy336JWr7bp2sY/OSNCEnSJnAx7uG+yGvb6IlYib6IsqHag3gY1G9Q2UKGkTNxDTdtnm45rZzrP1seyx3vN2qSkcGFUjRqoNm30P+Rhw1BTpqCWLdNJ/blzqMhIy4n8zZt6HtqGDaiFC1ETJqAGDUI9/bSez1uhAsrJyfLjyvz4rIc93W+urqhy5XT9g19+SXoz6Msv9T20Ywfq8mX9s7Y0B/zgQdSvv6JmzkR9+KF+0ffoo6iKFVPWUyhIkdX/u7176zfXUr/Zlt0kPfVrt3HjxqkdO3aoypUrq+LFi6vdu3eroKCgHP8+bNmyRfXr1y/xa2sTdED1799fnTx5Urm7u6sNGzaor776KtPHCwgIUMeOHVOVKlVSJUuWVDt27EhxzZ49e6ry5csrBwcH1atXLxUREaE8PT2Vt7e3unz5sipfvrwCVJUqVVT16tXTtDmj46z9HliToO/du1eVL19elSxZUp08eVK9+eabytHRUR0+fFhNnTpVFS5cWLm5uamWLVta/N6m3ubs7KzOnj2rRo0apVxcXFT79u1VeHi48vb2zvAxs/KcfXx80rTF09NTRUREqBIlSihAOTk5qeDgYNWkSZNMf24ODg5q//79asyYMcrFxUVVq1ZNnT9/XnXu3Nnm37+ClqAD6rHHUDt3Jr3Rf/++/pvesWPSMW5u+g1Ya6+ZpSHutYB6QDnTVUKA48C5rFzMziQkJODi4kJsZmV/hTBxcXEhISHB6GYIkSUh6NofW1Nt90D/na9v+lgP6A08lOrcE+i//8mHyltat90TqD1wIB7Yz/JvkFRhHsiwwnxkpJ5Ddv58xtd76CGoWBEqVNCR/PMKFfTwek9PPYw+ufh4XUHePIT+iSdSHmOeH3//vp7zFhGhl7SKibH5KecYe65+7+kJtWsPxMMj+21zcIDixaFECf3zLVEi5efWfDSvNpBcmzY6EhJgyxb4+++0Q88DA2X5wJw2aVLaaS1Fiujty5blzGOUKVOGYcOG0bBhw8TlW//44w/atGmTMw+QQxYsWED37t3Zu3cvSimeeuopq86bNWsWV67oaiaff/4533zzDWPGjAFg1aqktepXrlzJqFGjaN68OSdOnMDNzY26desSEhLCpUuXLF47Pj7equOya+bMmQQF6Yld69evp1GjRjRv3pwKFSowfPjwxBWErF3JqEWLFhQtWpTJkyejlGLLli38/vvv9O7dm/Hjx6f7mJAzz/n69ets376d559/ngULFtClSxdCQ0M5ePBg4jHp/dx8fX0pW7YsEyZMAPT89vnz5/Piiy+yadMmm9tS0Pz9tw4HBz2UPdTUy5FcdLRt17Q6Qa8DvAU8j37hBknzxc1tCAZWAnOBB3Wl6BMnTjBkyBB+/vlnQkNDJfES6XJ0dKRMmTK8/PLLnDhxwujmCJGjgk2RarUzKpCUsJvjNVIWp7tO2vntfYCihw/b1fJvueH2bR0Z/UlwdISyZdNP5KtUgTt3oHTptOcWKqQTN7PYWJ2omxP21B8z2pfRsdYkheYlucaOhbft7Ic6ZgwULXqYsWPhgw+yl1wXK5aymKAl9+7pn9nt2/rjrVt6Tdzk2xISoHt3XfugUCH9PV6zBj780P7e4MjPKle2bXtWdOzYEX9//xSJVunSpTlmh5P658+fz/r16xkwYAAxVr7jFxgYmPj5pUuXqFChQuLXr776KsOGDaNq1aoAFC1alDJlynD+/HmGDh3Kp59+Sr169di4cSPDhg1LTFjNrD0uu65fv574eWRkJBUqVMDLy4tLly6lu7xvRipUqEBgYCAqWWZ26dIlKlasmOFjQs495x9++IFBgwaxYMECXnnlFX788ccU+9P7uVWpUoUKFSoQFhaWuN/JyYn//vvPpscv6JTSheFyQqYJenXgS+AZ9Nq7/wG7gfPATXSSXgqoiV6rtz/wDrAGGAkE5Ew788y0adPo0aMHY8aMoXjx4jg4ZFS2LneUL18+x/8QiZynlCI8PJxt27bx66+/Gt0cIfLENVNsTrW9EmkT975A0eQHKcVgYDC6wF0f9P+SC+je+IIiIUEnZMHBkKxzI405c2DAAJ2Eu7jAX3/ptamLFNGFwix9NH9epgxUrZpyn6Ve3IzaGBlpOZnv2FFX+jYz9+7HxcHChTqZtSacnKw/1trja9ZMnkyrxLZlJD4+KYk2fzx/PuXXmX2Mi7Pu+1qlCrRokbSKQHi4JOd57fJl/bthaXtOKVOmDCHJXqk7OTnRvXt3Jk6cCMDevXvZsWMHHTp0YOHChXzzzTdprtG1a1eaN2/O+PHjeeihh1i+fDldunSxqR337t2jcLIlKTw9PRN7UAGKFCnC9OnTWbBgAZ9++imrV69OkaSlx8vLK/HzypUrc+3atcTP58+fT8eOHdm9ezcJCQkcOnQo8bX0smXLWLZsGcWKFWPu3Ll8+eWXvPbaa2mub+1xWX3e6QkMDKRy5co4OTlZTNJV6m7RZK5du4aXlxcODg6Jx1WuXJkzZ85Y1WZbn7Oltvz6669899131KtXjyeffJIRI0ak2J/ezy0wMJCAgAC8vb2tamtB988/+v/K6dPWHe/goHvY33wTzlk53DzTBP0kcAz9QmoNkNmb6oWBnsC7pnPdrWuH3YiLi2PVqlUphujkNT8/Pzp16mTY4wshhK2umGJjsm0OQFPg/4CWgCt6Scz7QBFSLol5F52on7fw8RK6Mn1BU6YMfPcdzJunq8F6esKKFVm/npOT5WTemo/mz4sW1S9KvLz05w4OutcgOlonm08+qZN7ayM+PuP9cXG2HX/sGDRurHtDnZ31mxvHj+uh+IGBlhPse/dy6AdmhXLl9BsvyX+mIm+NHg3z56cc5n7vnt6eU06dOsVnn31G1apVuX37Nv/3f/9HjRo1OH78OKVLl6Z06dKMGzeOCRMmsHz5cosJup+fH2+99RYAo0aN4osvvrC5HYcPH+all17i448/plOnTrRt25b9+/cn7p8xYwYHDhxgwIABzJ07lzlz5vBC8vUo0/H222/z+++/ExkZyejRo1lh+sNUpEgRlFKJb0706dMncRkyb29vKlasyM6dO7l//z5RUVE4WhiaYu1x2Xne6dm3bx9BQUFMnjyZcePGER8fT9OmTdm1axcAwcHBVK9e3eLSZnv37uXevXuMGDGCKVOm0LJlS7p3746vr2+mj5uV52ypLdHR0axatYqlS5eyb9++FD3mkP7Pbd++fYSHhzNixAhmzpxJTEwMPj4+uLu7W/V9K2jatdMjq6zl4GD7OZDJJPWnsjFpPjvn5nbYcxEDeypsI5H/Q+43idyO2aDiQMW7uqo4UN+CKgTKB1Q3UO+Cmg5qPagToKJIWaQuDtQFUJtBzQU1AlRPUI1BlbCD51cQw1z9PjLS/orYmdsWH+9qd22TyLmw9yruc+bMUXfu3FGnT59W77zzjoqLi1Pu7u6qffv2auLEiQpQtWrVUrNnz073mjt27FAVK1ZMU507eWRUJK5p06bq+PHjKjw8XC1ZskQtXbo0sTDYU089pa5cuaJKliypAFWkSBF19uxZ9dJLL2X4PJNXAw8LC1OLFy9W7u7uifsnTpyobt68qUJCQtSUKVPU1q1bVb9+/VSDBg3U3r17VXh4uLp586Zav359YlG05G3O6DhrvwcZPe/Ujwe6oN+PP/6oAOXl5aXWrl2rQkNDVUhIiJoxY0bicU899ZS6dOmSCgsLUx988EGaa9WtW1dt3bpV3b59O00F+4we09bn7OPjY7EtgGrZsqVSSqk+ffrY9HMrX768Wrp0qQoKClK3bt1Su3fvTlMQz5rfP3vOr3Iq4uNRV66gzp+3PuLiUI0bW/8YDqZPCpyIiAiKFi2a+YEG8PPzs+odNyFygtxvIretQs9Lb/fzz2x9+WU80SOt0uMAlAdqmKJ6qo9lUx1/k6Te9tQ98FeBzCqJeALLgRewrwJ29mzVKrh+PWVPcM+Mfqh5yNy2du1+ZuvWl+2qbSLnLFmyxKZhz7nNx8cHf39/i/s6derEt99+i7e3N++99x6BgYGsWbOGXr16UapUKebMmUPFihW5evVqivNWrlyJi4sLY8eOtcv568IYGd1rXl5enDp1Ck9PT+7evZu4PSAggP79+1vs/c+K9H7/7Dm/yikLF2btvHHj9Egua9hcxf154BdbTxJCCFFgmXMjP29vMiiUnkiRNNfdUomaYqRN2qsDvqbHSv6PLRq4SMrE3fz5BXRtlTFAK8j3BexykrXV741gbpufn7fdtU0UTD4+PokJdoMGDVi/fj0AjRs3Zv369Tg5ObFs2bI0Vd79/PyoX7++JOfCKg4ODgwbNozly5enSM5FzurbN/cfw+YEfSlQEpiX820RQgghMnUXOGKK1JyAyljueW9FymrzqZkL2MUATYBAIDzHWi2EKKh8fHw4fvw4AP3790/cPmrUKAB8fX1ZsmRJmvMaN27MRx99lDeNNPHy8uLkyZMW99WtWzfNvOa8YI9tym0ZPeenn346TQ964cKFCQ4O5tKlSzYXExT2x+YEfTEwGygDTLKwvwW6IJB9rfQohBCiIIhHrx4SkM7+0iQl7A+jR4VVRSf2Cj283hW9tjvAHXSifjmdj1fQCb0QQqRn0KBBGe738/PDz88v8WsPDw/mzZvHxo0bE9dRzyuBgYEUs7WaVS6zxzbltoyes4+PT5ptkZGRGX6PqlWrlmNtE7nP5gR9AHo5nAnoJH2Yabs38AXwNHrIoBBCCGFvbprCDz3vvAQwEP1/yxVdWX4OuhfeK9VHX9LOfwc9vz69BD7QtL9AFnsRQmRJcHAwTz/9tNHNEEIYxOYEHWA0upDOFPSLlQj0ercKmAt8llOtE0IIIXJROXRCPg+dqHsCu01hiTt6zffUCbwXUBfogl5CLrkYdLG69JL4y+ieekukgJ0QQghRsGQpQQeYD3QDXkIn5svRhXbSG1YohBBC2Jvkxb2tqScWBZw1RXpKkrb33fyxFVARcEl1zl0sJ+7PAq3Rb3y/aUX7hBBCCPFgszlBd0YX0RmF7j0/CDRCv9jIfyUahBBCCNuEmeJoOvsd0T3j6SXxjQGPVOcMNEUCsBHdI2+OK8k+v5mDz0MIIYQQec/mBP0s+kXESaAf8Ce6yM4S0+fPAPdysIFCCCFEfpJA0jJye9M5pgowA3gcKIQeJh+AXhquDPqNcQ90sp/cfdIm7ak/vw7E5dSTEUIIIQqoRx6BLl2gRQuoUAHc3SE0FE6fhm3b4Ndf4fZt269rc4LuhC4Ut5ikoje/ALeB1cAWoCvyLr4QQgiRVZfQCbwLSQXs/iHlOu3O6J74Suhh8xVTff6I6WOhVNdOQM9nzyiJv0rmb7bL/HhhJKUUTk5OxMfHG90UIQoUJycnlCrYpU9few0+/BDq1YPwcDh6FM6ehagoKFVKJ+6vvgrffgsrV8L48XDxovXXtzlBrwVEW9i+GXgM+APYBdS29cJCCCGESGSpgF1ycehk+kom1ylF2uTd/Hl19LKopSycd4eMk/h30XPqx5LyjQMh8sLFixfp1q0bf/zxhyTpQuQRJycnunXrxkVbss185vBhKFcOlizRifrhw5aPK14cnnwSXn4ZTpyAN97Qybo1bE7QLSXnZvvQxWw22npRIYQQQqRgawG79NwyxbEMjnEHKpB+b7wPUB7LLxoGmyIemErSmwbmuI7utRciJ02fPp2hQ4fy3HPP4eDgYHRzKF++PEFBQUY3QxQARt5rSikuXrzI9OnTDXl8e7BoEcyZA9EZJcXonvWlS3U0bAieqd9lz0CWq7in5xTQMqcvKoQQQohcEwWcN0V6HNHz3huiC8U+ih56HweEApHoNxLcU50XBwSR1AOfOoG/gh7OH5szT0UUEGFhYYwbN87oZiTy8/OjU6dORjdDFAByrxlrxgzbzzl6VIe1Mk3QOwD/2tgI83C7jug5c0IIIYR4sCWgE+0g4Gn08Hbz/Pg1JA1zL4XufTf3wFdKFnXRhe+KWbj+dZISdkuJ/FXT41nDE6g9cCAeyPx4IYQQuaNxYzh0KOevm2mCvgH4Dz1s7S8yH6bmDDwJDEW/u+6WvfYJIYQQws5kND/ePKQ+o86CYqRM3JMn89XQ0+VKWzjvJhkn8VfQa8qPAYoePizz44UQQuSaLVugRw/YujVnr5t6hZY0GqOHp/2Gftf8J3RhmG7oBPx/6IT8fWCF6ZjV6KFujXK2rUIIIYSwAz3Rw9mPmj72zPjwNO4C/ugCs4uACcBb6NcTjdBLyRVGF6ZtD7yKHla/HL3cnAfwFPAZsBDYhF7+NRy9wsxgwEEpBpu+jkZPv6uEFS98hBBC5KpBg+DCBV31fP9+aNUq4+Pr19dJcGQkXLkCY8akPaZNG32tqCg4fx7efDNXmp7C0qXw55/w7LNp97VsCf/9l7XrZtqDfgI9HK0F+h/e00BvkpZYM3NA/2NcA3wH7M9ae4QQQgghiALOmSI9rujideZeeB/0sm810S9wFPr1iSuww3ROLLqn/SJ6OTtzmL8ORObDCyFEbunVS8/jHjwYduzQH//6C+rWhcDAtMcXKwabN8P27eDrC7Vrw+LFcO8eTJ2qj6laVSfKCxfCK6/ohH/2bAgJgTVrcu+5DB4MQUGwfDm88w7MnavfTJg0Cbp1A3//rF3X6iJxe0zhCDRFzyMri/7nFwIcBw6RNnEXQgghhMgNMSQl2Gbl0D3vCa6uqJgYvkdP06uSLKqaPnZED61P3qtunmt/EcsJ/CWsnwsvhBAipWHDdIK9YIH++t13oUsX3as+enTa419+GQoXhtdfh/v39ZJlPj76OuYE/a234No1fS2AU6f0WuQffpi7CTrAhAlw9Sp89x307q17zgMDoW9fvRRbVthcxT0B8DOFEEIIIYQ9Mc+Pb7doEVtffhlP4LQpLHFB975bSuAfQQ/fd011TggZJ/B3MmifJ3qo/gtIATshRMHi4gJNm8LXX6fcvmkT/O9/ls959FE9VPz+/aRtGzfCxIm65/ziRX3Mpk0pz9u4USf1zs4QF5eTzyKlkiXB2xvi46F1a9i1C9q1019nVY4us2auyno3Jy8qhBBCCGEl83x4P29vq9aPj0XPaw9IZ78jehi9pQS+HvAEer58cndIP4EfjK6ALwXshBD5jbOzM35+Sd248+bNY/78+YlflymjE+bgVO9OBgfDY49Zvqanp553nvp4876LF/XHv/9Oe4yLi37M69ez+IQyMXYsvP++fk5TpsC5c3qN9KlT4b33sn7dHEvQJ6ILuCh0ZdVDwEHTx/U59SBCCCGEEHkoAf265iqwK51jypCUtKdO4tsAD1k4Z7ApYoE3gLPAGeB2DrVbCCHyWlxcHL6+vpkep1LNiXZwSLsts+NTb7fmmJz28cd6qP748XDjht52+TKsXQseHno+fFZ673MsQX8bXSH1BLoCa2OgCfAskqALIYQQIv8KNUV6BXJLoOv3jEGvfuOKXiEnCt37/lOqa50xxdlkn59Dr5AjhBAPqtBQnbB6eqbcXq5c2l51s+vXLR8PSeekd0xsLNy8mf12p8fHR1ejT27LFmjfXhet27Ah/ZEBGcmxBP0WsA/9TvN/phBCCCGEKOjuAP+ih9+3RifmrsCPwFD02u/epqhl+vgY0CfVda6QNnE/C1xAKs8LIexfbCwcOACdOsGqVUnbO3WC1astn7N7N3z5Jbi5QXR00vFXr+rh7eZjevRIeV6nTnrZtdycf546OTc7dEhXkt+4MWvXzdZyoL2AOqaLzEEvv5YdrYF16H9ACnjdinPqA1vR7ypfQb87LYQQQghhb8wF7FqYPnqgE+szwO/oavOD0NXlvYAiwMPA88DHwN9AIeA5YAp6hOIpdMJ/FvgTmI4eOt8JPcTelhd6nujXVB5ZfYJCCJGJqVOhTx/o1w/q1IHp06FCBT13G/QSZcnnky9dqtc/X7wY6tWDZ56Bjz5KquAO+txKlWDaNH3Nfv30Y6QuRpeXzp9Pv/BdZrLVg/4+OkF2Rv9jqIYe1v4reu55hI3XK4perm2JKTJTDNgMbAd8gdrAYuAe+p+cEEIIIYS96Jnsc2sK2EUCR02RWkmSetuTf2xFUtFegGj08HhLPe+p6yaNQQrYCSFy18qVULo0fPIJlC8Px4/DE0/oudugt9WokXR8eLjuDf/2W90jHhamC7IlT9AvXtTXmDZNL9dmXnItN5ZY+/VX+PRTOHw482Nv3NA9/4MH6zcZ5s617jGylaA/avpYGz3v3By90e8SX0An6i9Yeb2/TAE60c7My+i5W68D99Hz332AYUiCLoQQQoj8Kww9tXCfhX2epEzczfEE4JbsuLvoZL0R4JRsu7mAnXmOvBBC5KTvvtNhyRtvpN12/Di0bZvxNbdv10u45bbLl2HPHp2g//wz7NgBR4+mXFatfHlo3hy6d4dnn9XD8fv2tf4xcmQOunl90RXJtpVDF4p7OCceIB2Poue6J1sWj43oivJV0UuaCCGEEEIUJNdNsT3VdkegMikT91pAoGm7eTi8QleT34zu9DgMHAFysdaSEEI8EN59Vw/LHzpU96SXKKErxYeH6znyJUvq5d0cHGDfPn3cjz/aVk3eAf132GqfoHvFDwHXbDnRRnfRw79+yOCYjeh55/2SbfMCLqOT9z2pjh8wYAADBw4EoEmTJhw8eDDH2puTfHx88Pf3N7oZooCQ+03kFbnXRF6S+802VT7/nDLr1qGcnHCIiyPG0xOH+HhcQ0ISj4kpV47IWrWI8vYm0tubyFq1iPbyAsdslTTKF+R+E7mtVKm/qFhxNq6uwcTEeHD16mBu3epqdLNS8PHxoWjRokY3I8+4uMCjj8Ijj+h59IUK6arxp07pHn3zsP2sULZEPKg4UwSD2gBqMqgXQHnbeK2M4i6o1zM5ZiOoBam2VdZvUKhHMjk3IiIix9qa0+Hn52d4GyQKTsj9JpFXIfeaRF6G3G+2xSpQs0A1NH1cZdpeBlRHUMNALQF1FFQs+rWWQr9e2wVqNqg30a+/CtvB88nrkPtNIjejd29URARKqaSIiNDbjW5b8rDn/OpBCpuHuFdBr+WZPDqZrgZJBU1a2XrhLLiOnmeVnGlZPNJZSk8IIYQQQqSSXgG7UOAfU5i5AXXR0xgbmT72RlegB73k7lmShsabP+bmyEsh8rNJk6BIkZTbihTR25ctM6ZNIn3u7tCmDdy6BUeOQEyMbefbnKBfMcW6ZNtqoAu2jUQXhitu60WzaDfwJfofhWlZPDoBV5H550IIIYQQuSGapOmOyVUmqWDww+gVdpIXCg4hZcJ+GL1MXC4uUyxEvlC5sm3bhbE2bNAfXV310nDnz+sK9AMGWHd+jhSJOw98BmwC1gDNsnidIkBN0+fmQiYPA7fQBUwmAc2Bx0zHLAXGoSu+T0QXO/kIGJ/FxxdCCCGEEFlz2RS/JdtWHGhIUm97I3QPfSHT/mj0KjyHSZm830l1bU9gOTrhl1GSoqC5fBmqVrW8XdifSpWSlopzcoIGDaCZDQlyjlb12AP8SdYT5GboP8yH0ct6fGb6/DPT/vLo3nqzcHSPeQVgP/AtMIUHd4m13r0hIACaNm1OQID+2l6Y2xYfj921TQghhBD2KRzYgX6NNgDdq14UqAe8BMxA96x3M32+DV1BPgD4FfgUeAb4P5LWaBeioBk9Gu7dS7nt3j29XdifAwf0+uegc6fDh2HBAtuukaOT2oeAumYHk+szC3srYmDPxR/suW0S2Q8pbCORVyH3mkRehtxvD154gHoc1EhQS0GdBJVAUkG65HEflKMdtNkccr9J5Hb07o0KCEAlJDiogAD7fB1ub/lVXkdoKOqvv1CLF6PWrUNVr56169jcgx4A/AKMAjoDpVPtfxg9VF3YJqPiD0az57YJIYQQIn8IRi+h+yW6d70ueuTkBpJqDSWYPrqhp0D+gZ7e+D/ANS8bK0QeW7YMqlWDAwf2Ua2aFIezR9Wrw1dfgb8/xMbCli1w9SqsWwdjbRj+Y/Mc9AtAB+BZdIoPumjcCfSQpZboP67CNvZc/MGe2yaEEEKI/CvAFJ2AKHQSvgT9WrM10AZ4wnRsFLAX+A/Yji4mnGpUsBBC5JrwcPj3Xx1m5cqBr68Oa9mcoHc0fayKXmKtiSnqo3vON5C0zIawnj0Xf7DntgkhhBAifysHzAHmAQPRBeOWmgL0aM5W6GS9NTAaGIOuDn8Inaz/h54LfzMvGy6EyNc++AAOHtRxJ3VlS5MbN+CPP3RYK8tV3C+aYnVWLyBSGD0a5s9POZTcXoo/2HPbhBBCCJG/pbdGu9lN9PK/5iWAiwKPkpSwvw18YNp3gqSE/T/0KFAhhMiK8eOhkGlJikuXkpJ1c4SEZO26ObLMmsg+8zySSZOgShUHLl1SjB5tH/NLkretcmXdc24vbRNCCCGESC4C2GwK0MPifUkaEv8ySaM9A0gaEv8fcCZPWyqEeJA9+ij8+SdcuQLnzuk8afRocHfX+4OCkpL1Awfg99+tu64k6HZk2TIdfn778LVlokIeMLdNCCGEEOJBEgPsNMVk9BrDDUnqYe8CvGY6NpiUCftRkgrTCSFEcnPnws8/w0cfJW0rWxY+/xwefxxWrICHH4a334ZSpcDZysxbEnQhhBBCCFFgJACHTTHTtM2bpIS9NUnD6u+gE3tz0r4fnfAn5wnUHjgQD3SCL4QoGBo1Spmcgx7WPnAg/Pijnn/++ON6u5eX9de1eZk1IYQQQggh8pMzwALgdaA64IVe6m0ZUAX4Ap2o3wa2AJ8Bj6ELJI8Bih4+jA2rKAkh8oGgIKhf3/K+H36AN99M+jow0PrrSoIuhBBCCCFEMlfQyfkg9EpFZYAewGx0Uj4KPcc9AhgMOCjFYPQSxJEGtFcIkfe+/x4+/RQaN067r0wZ8PDI2nVliLsQQgghhBAZsFQpvhvwMVAXcDJtjwBWAB3QQ+Lj8raZQog8NHkyNGwI+/bBqlWwcaOu5l6zJowbpwvDZYUk6EIIIYQQQtjAnIi3RSfoCa6uEBPDDaA30A8IA/5EJ/UbgLsGtVUIkTsSEuDFF+G112DkSOjVC5QCBwc4dQreeitr15Uh7kIIIYQQQmRBOWAO4L9oEd8Bh9DD4Z8G1gKdgZVACDpZfxMob0xThRC5ZMkSqFcPqlWDNm3Ax0fPTT99OmvXkx50IYQQQgghssBc7d3P25shybb/ZgpH4H/ohP1pdDI/B9hL0pD5k3nWWiFEbrp8WUd2SQ+6EEIIIYQQuSAB2AEMRy/lVhcYbdo3CTgBnAW+Ri/vJi/MhRDyd0AIIYQQQog84I9esq0FUAE95P0sMARdVO46sBDd2+5uUBuFEMaSBF0IIYQQQog8FgTMA55Az1t/HtiIXs7tV3Tl+F+BN4CyRjSwAOrdGwICID5ef+zd2+gWiYJI5qALIYQQQghhoAhglSmcgTYkzVt/Gj1Ufhc6YV8HnDOklflb794wfz4UKaK/rlpVfw2wbJlhzRIFkPSgCyGEEEIIYSfigH+B94CqQCPgM6AIeq76WfTc9UnAI4CDEY3MhyZNSkrOzYoU0duFyEuSoAshhBBCCGGnjgDjgSZAFeAd9PD44cAe4Cq6MnxXwC3ZeZ7AVsAjD9v6IKtc2bbtQuQWSdCFEEIIIYR4AFwGZgGPoeelvwz8B7yEXmc9BL3u+svABKAVMNaQlj540lseKyeWzRLCFpKgCyGEEEII8YC5DSwFXkAXmesK/Ixem/0noD/gBAwGFBBpSCsfHKNHw717Kbfdu6e3C5GXJEEXQgghhBDiARYDbAAGARVNn8em2r8CPUxeWPb/7d17nNVlvejxz3C3wS5ECBFXN8VEhchFIsBEqYNFmZU20RZ3iifsGO68HOLiqGynjqaBu7QDudlmNpt9Cm/bl4qWJFskYBxL21xOMYBcHA8qt+E2l+f88WPGGe6XmfV7Zq3P+/X6vtasZ36/NV/gWQ/zXc/ze34lJTBpEqxfD7W1yeOkSW4Qp8xzF3dJkiQpS2wFyklm4faSXJe+jmSm/UqgDHiAZLZ9eyoZxqukxIJc6XMGXZIkScoiXUg2jhsO3E+y63s3kuXutSTXsW8FHgI+izvBSzFxBl2SJEnKIl9r8PX/aPD1/QdjEHAVyWZy3yK5r/oDwIMkhbuk9DiDLkmSJOWQMpLC/cMkBfom4Icku8Q/Bown2WBOUuZZoEuSJEk5aC/JtegXAB8FfgwMAx4nKdaLgbNTy07KTRbokiRJUo77v8APgB7Al4FS4GaS5e+/J1kO3yG17KTcYYGuFq+wEMrLoaYmeSwsTDsjSZKklqmaZAb9S0BPYNrBx1+RXJ/+z8A5aSUn5QALdLVohYUwbx707g2tWiWP8+ZZpEuSJJ2uLSTXpvcjWQb/JHA1yTXsK4HvAO9LLTspO0VXoE8muVfjXpI3/shjHNsLCEeIzzdzjopHcTHk5zduy89P2iVJknT6ArCYZEO5DwPXkdwK6n6SIv5BYFRayUlZJqoC/TJgDsmGFIOApcBTJNfCHMvnga4N4vfNmKPi0rPnybVLkiTp1L1Dch/1c4AhwC+BS4AXgDUk162flVJuUjaIqkD/PvCvwC+A1cD3SK51mXyc894CKhpEVfOlqMhs3Hhy7ZIkSWoapSS/p3cDJpL8Hv6/SG7bthC4GG/XJp2saAr0tsBgYNEh7YuAEcc5dyHJgPCfwFebPjVFbNo0qKxs3FZZmbRLkiSp+e0hmUkfDfQH7gE+Q3LN+gZgFtDn4LGFhbCxHGprkkf3DZIayyO5rCR13UiuYRkNLGnQPpPktg79j3DOB0k+rXuRZMfJLwHTD7Y9fITjJ02axDXXXAPAueeey8svv9xU6TepgoICVq1alXYaLUanTk/Rvft9tGtXwYEDZ7F587W8/fa4tNNqMexvyhT7mjLJ/qZMsr8dLq+qivctWcKHHnuM9y5bRl5tLXum96HDLZto1e7d9a41NR3YsGGav7udoJj7WkFBAR07dmyy12vXDn784+RDnDPOgN/9Dq69FjZvPvZ5l14Ks2bB2WfD3/4G06fDo4+++/1Ro+DGG2HwYOjeHa68Eh58sMnSbhJH2mct49ENQoAw8pD2WyCsOonX+RmEP53Acbt37079z3y0WLFiReo5GLkT9jcjU2FfMzIZ9jcjk2F/O3Z8BMIMCLXlhBAOj5ry9HNsKRFzX2vq+uq++wibNxMuuogwaBDh+ecJZWWEVq2Ofs7w4YSqKsK0aYT+/ZPHqirCsGHvHjNuHOGOOwhf/SqhspIwcWL6f3cNI5ol7ttIZsG7HtLehWT5+on6I8mtICRJkiSlbxPwT0A42ia+bu6rQ7z3vXDVVXDTTfDcc1BWBn//9/CpT8FFFx39vOuvh+efT+7otHp18rh4cdJe56mnkln13/4Wamub+Q9yCqIp0KtINpoYe0j7WJLd3E/UOSQby0mSJEmKx9E28W21Ef6DY99eWfFr06YNK1asqI9Jkyad8msNHpwscV/UYIOyTZtg1SoYcYwNyj796cbnADzzzLHPiU2btBNo6B7gIWA5yXXl3yG51+LPD36/GBgG1H1ocgVJYV8G1ALjge8C/zNzKUuSJEk6AdOmwS/nQZv8d9uqK2HhNLiAZB+qpcCPSAr2kEqWOlXV1dUMHTq0SV6ra1eoroZt2xq3V1Qk3zvWeRWHLL8+3jmxiWYGHeDfgeuBGcArJJ+iXQzUfdjWDTj7kHNmACuBFcA3gG8Ds5s9U0mSJEkno6QErpgE69cnS4vXr0+eX14CvUgm2j4MPA68SjIZF9Vsok7brFkkG48dI84//+jn5+UlxxzLod8/kXNiEl2fv/9gHMk/HPL8lwdDkiRJUvxKSpI41F7gPmAucBkwFXiQ5BZtdwO/ILmdm1q22bPhV7869jEbN8Lw4dCmDXTu3HgWvUsXeOGFo5/7xhuHz5Z36XL4rHrMoppBlyRJkpS7qoFfA58iWUm7HphDsqL2FqBTapmpKbz1FqxZc+zYuxdKS+HAARjbYIOy7t2hoACWHmODspdeanwOJM+PdU5sLNAlSZIkRecp4HxgBPCfwG0khfpPgB4p5qXmt3MnPPAA3HUXXHghnHMOPPQQ/PnPya7udZ57Ltmpvc6cOTBmDEydCh/7WPJ4wQXJzH2d/HwYODCJVq2gZ8/k6x6RdCoLdEmSJEnRegm4BBgA/IbkWvW/AfOBgvTSUjP7x3+EhQthwQJ48UXYvRvGj298a7Szz4Zu3d59/tJL8I1vwMSJSTF/xRVw+eWwfPm7xwwZAq+8ksR73gO33558ffvtGfqDHUd016BLkiRJ0qH+C7iSZKn794GrDz5/jGTn92VpJaZmsX8/fO97SRxNnz6Ht/32t0kczR/+kGwcFytn0CVJkiS1GBtJ7vzUC7iV5M5PLwGLgf+WVlJSE7FAlyRJkrJIYSGUl0NNTfJYWJh2Rs3jLZLr0nsBU4C+JNetvwIUAq1Ty0w6dRbokiRJUpYoLIR586B372QDrN69k+fZWqQDVAL3AmcDE4G2JDvBrwUmAx3SS006aRbokiRJUpYoLk52qW4oP7/xTtfZqgr4JfAJ4EtABcm91TcAPwDel15q0gmzQJeaUa4sMZMkSXHo2fPk2rNRAJ4guT3baGAlUExy7fqdQLejnyqlzgJdaia5uMRMkiSla+PGk2vPdkuALwADSYr27wPlwFygX4p5SUdjgS41k1xeYiZJktIxbRpUVjZuq6xM2nPZn4FvAX8HzDv49Wrg/wBDGhzXlWQ3+LMynJ9UxwJdaiYuMZMkSZlWUgKTJsH69VBbmzxOmpS0C9YD15Hs/F4MXAisAJ49+PVMktu23ZJSfpIFutRMXGImSZLSUFICffpA69bJo8X54f4fSTHeC7iRpDh/DriW5PZs15Jcy74nrQSVsyzQpWbiEjNJkrJb3WawgwcPczPYFmoXcDfQG1gG1B5srwF+B/RJJy3lMAt0qZm4xEySpOzVcDPYvLzgZrAt3EagjGTW/ABJkXQh8G/A8BTzUu6xQJeakUvMJEnKTm4Gm326AD8Hhh58fAXoD7wEPAoMSCsx5ZQ2aScgSZIktTRuBpt9vtbg62sPPr4HmALcTLIT/K+AIpLN5qTm4Ay6JEmSdJLcDDY37AF+CPQF7gK+DqwB7iWZcZeamgW6JEmSdJLcDDa3vANMJbmP+r8Ak4G/AbOA96aYl7KPBbokSZKiVbdTek0NUe2U3nAz2BDy3Aw2R2whKc77A48DM4Byklu1dUgxL2UPC3RJkiRFqeFO6a1aEd1O6XWbwZaWLncz2BzzN2ACcA7JJnJ3AX8FJuEmXzo9FuiSJEmKkjulK3Z/Ar4IjCbZOG4u8F/A5UBeemmpBbNAl3JU3ZLBwYOHRbVkUJKUebEuI3endLUUS4CRJMX6XpL7p5cCn08zKbVIFuhSDmq4ZDAvL0S3ZFCSlDkxLyN3p3S1NE+SLHufQLJ53NPAYuDT6aWkFsYCXcpBLhmUJNWJ+f8Ed0pXSxSAXwMFJPdT/yiwFHgM+ESKeallsECXcpBLBiUp81xGfvIa7pReW4s7patFqQLuJ7k12w9IrlP/E/BLoE+KeSluFuhSDnLJoKRsFev+Gi4jP3V1O6W3bo07patF2gP8COgL3Al8FVgN/DNwVop5KU4W6FIOcsmgpGwU8/4aLiOX9A7JTPrfAQ8A/53kdm13AO9LMS/FxQJdykENlwyGkBfdksFYl4FKSsT6Ho25CHYZuaQ6W0muTS8AHgWmAeuAm4Az0ktLEQm5GLt37049h6PFihUrUs/ByJ2Irb8VFhJ27yaE8G7s3p20p52bcXoRW1+LPQoLCeXlhJqa5DGW90DM79GamsZ51UVNTfq5lZcfObfy8vRzM04/HN+M04lPQXgCQoCwGcI1ENoc5diY+1rM9VULi9QTaBSTIayDsBfCSggjj3P8JyAshrAHwiYIM0/w58TcgWJ+4xnZF7H1N3+Jzb6oKzRra/OiKjQb5mYRfOIR83s05txi/jc1Tj9i+7/UaJnxGQhLSAr1tRC+ASHvkGNi7msx11ctLFJPoD4ug3AAwtUQ+kO4F8IuCD2OcvyZELZCWABhAIRLIeyE8P0T+Fkxd6CY33hG9kVs/S3mGTCIt6CLNbeYi5KYc4u50Iz5PRrzv2ldfrG9R42midj+LzVadlwM4RWSQr0MwriD7V0h7Bw0KJwVQY5HipjrqxYWqSdQH8sgzD2kbS2E4qMc/x0IOyB0aNA2nWQm/Xg/K+YO5CBvZDJi628xFyYx//Ifa24x/3vGnFvMRXDMf28Q94oNI3sjtv9LjZYfeRAKIfyVpFD/A4TfQqjNyws/iyC/I0XM9VULi9QTCEBoC6EKwtcOaf8pyRL2I53zIIT/OKRtCEkn7n2cnxdzB3KQNzIZsfW3WAtNiLswiTW3mAvNmHOL9d8T4n6PNozYxjYju8P+ZjRXtCVZYRyOEHsiyK9hxFxftaTIO/hF6roBW4DRwJIG7TOBCUD/I5zzDLAJuKpBWw9gI/BpYNkhx0+aNIlrrrkGgHPPPZeXX365SXJvagUFBaxatSrtNJQjYuxvnTo9Rffu99GuXQUHDpzF5s3X8vbb49JOi8GDh5GXd/iQGUIepaXLU8joXbHm9slPjqd9+zcOa9+/vyuvvvpEChm9K+bcOnV6il69imndel99W01NBzZsmBbFeyHW92hDMY5tyl72NzWnttu20ePuu3n/4sW0qq6mpn17tl9wAa9PmUJ1585pp1evoKCAjh07pp1GVkj9UwIgdCP5JOjQTeFugbDqKOc8A+EXh7T1PPg65x3n58X8CY+fwhqZDPvbiUfMs5qx5hbzbGvMudXl5/XKpx6ObUYmw/5mNHfcB6EaQk27dqEaolzmHnN91ZIimvugbwOqga6HtHcBKo5yzhtHOZ5jnCNJp2raNKisbNxWWZm0py3W3BreXzmEvKjurxz7vZ9LSqBPH2jdOnmMJS9JUuZ1AX4OrJo/n58DZ6Wcj5pX6p8S1MUyCP/7kLY1HH+TuPYN2n6Am8QZxsmE/e3kIuZZzZhzA/uakdmwvxmZDPubkamIua/FXF+1pGhDRO4BHgKWAy8C3wE+TPJpEUAxMAy46ODzXwNFwL8C/wR8FJgK3JaxjCXlmpKSeGcyY85NkiRJxxdVgf7vwAeBGSSbxr0GXEyy6RsH285ucPxOYCzwM2Al8A5wN0mhL0mSJElSSxJVgQ5w/8E4kn84QttrwPnNl44kSZIkSRkRzSZxkiRJkiTlMgt0SZIkSZIiYIEuSZIkSVIELNAlSZIkSYqABbokSZIkSRHII7khes6pqalh7969aadxRG3atKG6ujrtNJQj7G/KFPuaMsn+pkyyvylTYu5rZ5xxBq1bt047jRYvZwv0mK1YsYKhQ4emnYZyhP1NmWJfUybZ35RJ9jdlin0t+7nEXZIkSZKkCFigS5IkSZIUAQv0CM2dOzftFJRD7G/KFPuaMsn+pkyyvylT7GvZz2vQJUmSJEmKgDPokiRJkiRFwAJdkiRJkqQIWKBLkiRJkhQBC/TITJ48mXXr1rF3715WrlzJyJEj005JWaioqIgQQqPYunVr2mkpC4waNYrHHnuMTZs2EUJg4sSJhx1TVFTE5s2b2bNnD88//zwf//jHU8hU2eB4/W3+/PmHjXUvvfRSStmqJZs6dSrLly9nx44dvPnmmzz++OMMGDDgsOMc33S6TqSvObZlNwv0iFx22WXMmTOH4uJiBg0axNKlS3nqqafo0aNH2qkpC61evZquXbvWxyc/+cm0U1IW6NixI6+99hpTpkxhz549h33/5ptv5oYbbuC6665j6NChvPnmmzz77LN07NgxhWzV0h2vvwE8++yzjca6iy++OMNZKht89rOf5b777mPEiBGMGTOG6upqnnvuOT7wgQ/UH+P4pqZwIn0NHNuyXTDiiGXLloW5c+c2alu7dm0oLi5OPTcju6KoqCi8+uqrqedhZHfs2rUrTJw4sVHbli1bwrRp0+qfd+jQIezcuTNcc801qedrtOw4Un+bP39+eOKJJ1LPzci+yM/PD9XV1eGLX/xifZvjm9EccaS+5tiW3eEMeiTatm3L4MGDWbRoUaP2RYsWMWLEiJSyUjbr27cvmzZtYt26dZSUlNCnT5+0U1KW69OnD926dWs0zu3bt48XXnjBcU7NZuTIkVRUVLBmzRrmzp3Lhz70obRTUhY488wzad26Ne+88w7g+Kbmc2hfq+PYlr0s0CPRuXNn2rRpQ0VFRaP2iooKunbtmlJWylZ//OMfufLKKxk3bhyTJk2ia9euLF26lE6dOqWdmrJY3VjmOKdMefrpp7niiiu48MILueGGGxg2bBi///3vadeuXdqpqYWbM2cOZWVl9df9Or6puRza18CxLdu1STsBNRZCaPQ8Ly/vsDbpdD399NONni9btox169YxceJEfvKTn6SUlXKF45wyZcGCBfVfv/baa5SWlrJhwwa+8IUv8Mgjj6SYmVqyu+++m5EjRzJy5Ehqa2sbfc/xTU3paH3NsS27OYMeiW3btlFdXX3Yp6xdunQ57NNYqalVVlbyl7/8hX79+qWdirLYG2+8AeA4p9Rs3bqVTZs2OdbplN1zzz0UFhYyZswYysvL69sd39TUjtbXjsSxLbtYoEeiqqqK0tJSxo4d26h97NixLF26NKWslCvat29P//79vdWamlV5eTlbt25tNM61b9+eUaNGOc4pIz74wQ/SvXt3xzqdktmzZ/PNb36TMWPGsGbNmkbfc3xTUzpWXzsSx7bsk/pOdUYSl112Wdi/f3+46qqrQv/+/cPs2bPDrl27Qs+ePVPPzciuuOuuu8Lo0aND7969w7Bhw8ITTzwRduzYYV8zTjvy8/PDwIEDw8CBA0NlZWWYOXNmGDhwYOjRo0cAws033xx27NgRvvKVr4QBAwaEkpKSsHnz5tCxY8fUczdaXhyrv+Xn54e77rorDB8+PPTq1Sucf/75YenSpeH111+3vxknHT/96U/Djh07wgUXXBDOOuus+sjPz68/xvHNaIo4Xl9zbMuJSD0Bo0FMnjw5lJeXh3379oWVK1eGUaNGpZ6TkX1R90vD/v37w6ZNm8JvfvObUFBQkHpeRsuP888/PxzJ/Pnz648pKioKW7ZsCXv37g2LFy8OAwYMSD1vo2XGsfpbhw4dwtNPPx0qKirC/v37w/r168P8+fPDRz7ykdTzNlpeHE1RUVGj4xzfjNON4/U1x7bsj7yDX0iSJEmSpBR5DbokSZIkSRGwQJckSZIkKQIW6JIkSZIkRcACXZIkSZKkCFigS5IkSZIUAQt0SZIkSZIiYIEuSZIkSVIELNAlSZIkSYqABbokSRlWVFRECKE+PvOZz6SWy3nnndcol6KiotRykSQp17VJOwFJknLV9ddfz7Zt21izZk1qOfz1r3/lW9/6Fp07d2b27Nmp5SFJkizQJUlKzaOPPsqGDRtSzeGtt97i4YcfplevXhbokiSlzCXukiRJkiRFwAJdkqST1KFDB15//XU2bNhAu3btGn1v3rx5VFdXc/nll5/y67dt25abbrqJsrIyKisr2b59OytWrOC73/1u/TETJ04khMCYMWOYOXMm69evZ8+ePSxbtozzzjsPgNGjR7NkyRJ2797Nli1bmDFjxinnJEmSmp8FuiRJJ2nfvn0UFRXRs2dPrr322vr24uJirr76aq677joWLFhwSq/dtm1bnnnmGe68804qKiq45ZZbmD59OqWlpVx66aWHHf+jH/2ISy65hDlz5nDbbbfRt29fnnnmGb785S+zcOFClixZwo033sjq1auZNWsWEyZMOOU/tyRJan7BMAzDMIyTi1atWoVXX301VFRUhPz8/DBlypQQQggzZ8487rlFRUUhhBB69ep12PduuummEEIId9xxx2Hfy8vLq/964sSJIYQQSktLQ9u2bevbx48fH0IIoaqqKgwZMqS+vW3btmHLli1h6dKlR8ypV69eIYQQioqKUv+7NQzDMIxcDWfQJUk6BbW1tUydOpUuXbrw6KOPcs8993Dvvfcya9as03rdCRMm8Pbbb3P77bcf9r0QwmFt999/P1VVVfXPlyxZAsCyZctYuXJlfXtVVRXLly+nX79+p5WfJElqPhbokiSdoieffJLS0lIuuugiFixYwJQpU077Nfv168fq1avZv3//CR2/bt26Rs+3b98OQHl5+WHHvvPOO3Tu3Pm0c5QkSc3DAl2SpFP09a9/nXPOOQeAXbt2NdnrHmmm/GhqampOql2SJMXLAl2SpFMwduxYHnroIR555BFKSkr49re/Tf/+/U/7ddeuXUtBQcFhu8NLkqTsZ4EuSdJJGjZsGAsXLuTFF19kwoQJzJgxg9raWn74wx+e9ms//PDDdOrUyVuiSZKUg9qknYAkSS1J//79efLJJ1m7di2XXHIJBw4cYN26dTzwwANMnjyZESNGsHTp0lN+/Tlz5jB+/HhmzpzJ0KFDWbRoEfv27WPAgAF87GMfY+zYsU34p5EkSTFxBl2SpBPUo0cPFi1axI4dOxg3blyj685vv/129uzZw5133nlaP6OqqorPfe5zTJ8+nR49elBcXExxcXH9rL0kScpeeST3W5MkSRlSVFTErbfeyqBBg3j99dfZvn17apu6tW7dmve///306NGDsrIybr31Vm677bZUcpEkKdc5gy5JUkrKysrYtm0bw4cPTy2HIUOGsG3bNsrKylLLQZIkJZxBlyQpw/r06UPfvn3rn69YsYKdO3emksuZZ57JsGHD6p+vW7fuiPdQlyRJzc8CXZIkSZKkCLjEXZIkSZKkCFigS5IkSZIUAQt0SZIkSZIiYIEuSZIkSVIELNAlSZIkSYqABbokSZIkSRH4/1UWbQQZZ/c7AAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"'''Show FEM Solution'''\n",
"\n",
"import pandas as pd\n",
"df = pd.read_csv('out-x_x-line_0002.csv')\n",
" \n",
"plot_solution(df, title='Dirichlet BC FEM Solution $u_h(x,y=0)$', basis_functions_type='Linear Lagrange', flux_basis_functions_type='Constant Monomial')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comments:**\n",
"\n",
"1. The *concentration* drops from the entry value to the exit as prescribed by the boundary conditions.\n",
"1. Because of the non-zero source term and BC the profile is curved.\n",
"1. The normal diffusion flux is negative on the left boundary, $(\\flux\\cdot\\normal)|_{\\xpoint = (a,y)} < 0$, \n",
"hence there is *feeding* on the left. On the right boundary $(\\flux\\cdot\\normal)|_{\\xpoint = (a,y)} > 0$ therefore there is *draining* at the right side."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Quadratic Lagrange FEM](#toc)\n",
"\n",
"FEM parameters:\n",
"\n",
"> + Basis Functions: Second Order Lagrange\n",
"> + num. of finite elements in the *x* direction: 20\n",
"> + num. of finite element in the *y* direction: 10"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"code_folding": [
12
]
},
"outputs": [],
"source": [
"'''FEM Solution'''\n",
"\n",
"n_felem_x = 20\n",
"n_felem_y = 10\n",
"\n",
"order = 'second'\n",
"\n",
"n_plot_pts_x = n_felem_x + 1\n",
"n_plot_pts_y = n_felem_y + 1\n",
"\n",
"from engy_5310.toolkit import write_engy5310_p1_2d_input_file\n",
"\n",
"write_engy5310_p1_2d_input_file(x_left=x_left, x_right=x_right, y_bottom=y_bottom, y_top=y_top, \n",
" u_left=u_left, u_right=u_right, u_bottom=u_bottom, u_top=u_top,\n",
" diff_coeff=diff_coeff, source_s=source_s, n_felem_x=n_felem_x, n_felem_y=n_felem_y, \n",
" order=order, \n",
" n_plot_pts_x=n_plot_pts_x, n_plot_pts_y=n_plot_pts_y, \n",
" compute_diffusion_flux=True,\n",
" solver='fdp-newt-full')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"# Engy-5310 Problem: Poisson 2D FEM\r\n",
"# UMass Lowell Nuclear Chemical Engineering\r\n",
"# Prof. Valmor F. de Almeida\r\n",
"# 19Apr21 12:58:39\r\n",
"\r\n",
"# Parameters\r\n",
"xmin = 0.00000e+00\r\n",
"xmax = 2.50000e+01\r\n",
"ymin = -6.25000e+00\r\n",
"ymax = 6.25000e+00\r\n",
"diff_coeff = 1.00000e-01\r\n",
"source_s = 1.00000e-03\r\n",
"u_left = 3.00000e+00\r\n",
"u_right = 0.00000e+00\r\n",
"u_bottom = 0.00000e+00\r\n",
"u_top = 2.00000e+00\r\n",
"\r\n",
"[Problem]\r\n",
" type = FEProblem\r\n",
" coord_type = XYZ\r\n",
"[]\r\n",
"\r\n",
"[Mesh]\r\n",
" [2d]\r\n",
" type = GeneratedMeshGenerator\r\n",
" dim = 2\r\n",
" xmin = ${replace xmin}\r\n",
" xmax = ${replace xmax}\r\n",
" ymin = ${replace ymin}\r\n",
" ymax = ${replace ymax}\r\n",
" nx = 20\r\n",
" ny = 10\r\n",
" elem_type = QUAD9\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Variables]\r\n",
" [u]\r\n",
" order = second\r\n",
" family = lagrange\r\n",
" initial_condition = ${fparse (u_left+u_right+u_bottom+u_top)/4}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[AuxVariables]\r\n",
" [diffFluxU]\r\n",
" order = FIRST\r\n",
" family = MONOMIAL_VEC\r\n",
" []\r\n",
" [diffFluxU_x]\r\n",
" order = FIRST\r\n",
" family = MONOMIAL\r\n",
" []\r\n",
" [diffFluxU_y]\r\n",
" order = FIRST\r\n",
" family = MONOMIAL\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Kernels]\r\n",
" [diffusion-term]\r\n",
" type = DiffusionTerm\r\n",
" variable = u # produced quantity\r\n",
" diffCoeff = ${replace diff_coeff}\r\n",
" []\r\n",
" [source-term]\r\n",
" type = SourceTerm\r\n",
" variable = u # add to produced quantity\r\n",
" sourceS = ${replace source_s}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[AuxKernels]\r\n",
" [diffusion-flux]\r\n",
" execute_on = timestep_end\r\n",
" type = DiffusionFlux # new kernel\r\n",
" field = u\r\n",
" diffCoeff = ${replace diff_coeff}\r\n",
" variable = diffFluxU # produced quantity\r\n",
" []\r\n",
" [diffusion-flux-x]\r\n",
" execute_on = timestep_end\r\n",
" type = VectorVariableComponentAux # provided by MOOSE\r\n",
" variable = diffFluxU_x # produced quantity\r\n",
" component = x\r\n",
" vector_variable = diffFluxU \r\n",
" []\r\n",
" [diffusion-flux-y]\r\n",
" execute_on = timestep_end\r\n",
" type = VectorVariableComponentAux # provided by MOOSE\r\n",
" variable = diffFluxU_y # produced quantity\r\n",
" component = y\r\n",
" vector_variable = diffFluxU \r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[BCs]\r\n",
" [east]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = left\r\n",
" value = ${replace u_left}\r\n",
" []\r\n",
" [west]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = right\r\n",
" value = ${replace u_right}\r\n",
" []\r\n",
" [south]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = bottom\r\n",
" value = ${replace u_bottom}\r\n",
" []\r\n",
" [north]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = top\r\n",
" value = ${replace u_top}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Preconditioning]\r\n",
" active = 'fdp-newt-full'\r\n",
" [fdp-newt-full]\r\n",
" type = FDP\r\n",
" full = true\r\n",
" solve_type = 'NEWTON'\r\n",
" petsc_options_iname = '-pc_type -mat_fd_coloring_err -mat_fd_type'\r\n",
" petsc_options_value = 'lu 9.9999999999999995474811182588626e-07 ds'\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Executioner]\r\n",
" type = Steady\r\n",
"[]\r\n",
"\r\n",
"[VectorPostprocessors]\r\n",
" [x-line]\r\n",
" type = LineValueSampler\r\n",
" execute_on = 'timestep_end final'\r\n",
" variable = 'u diffFluxU_x diffFluxU_y' # output data\r\n",
" start_point = '${replace xmin} ${fparse (ymax+ymin)/2} 0'\r\n",
" end_point = '${replace xmax} ${fparse (ymax+ymin)/2} 0'\r\n",
" num_points = 21\r\n",
" sort_by = id\r\n",
" []\r\n",
" [y-line]\r\n",
" type = LineValueSampler\r\n",
" execute_on = 'timestep_end final'\r\n",
" variable = 'u diffFluxU_x diffFluxU_y' # output data\r\n",
" start_point = '${fparse (xmax+xmin)/2} ${replace ymin} 0'\r\n",
" end_point = '${fparse (xmax+xmin)/2} ${replace ymax} 0'\r\n",
" num_points = 11\r\n",
" sort_by = id\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Outputs]\r\n",
" console = true\r\n",
" [vtk]\r\n",
" type = VTK\r\n",
" execute_on = final\r\n",
" file_base = out\r\n",
" []\r\n",
" [x]\r\n",
" type = CSV\r\n",
" execute_on = 'final'\r\n",
" show = 'x-line'\r\n",
" file_base = out-x\r\n",
" []\r\n",
" [y]\r\n",
" type = CSV\r\n",
" execute_on = 'final'\r\n",
" show = 'y-line'\r\n",
" file_base = out-y\r\n",
" []\r\n",
"[]\r\n"
]
}
],
"source": [
"'''Display MOOSE input file created'''\n",
"\n",
"!cat engy5310p1/input.hit"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"Framework Information:\n",
"MOOSE Version: git commit 52562be492 on 2021-04-09\n",
"LibMesh Version: 27141d18f3137f77e33cdb3d565fd38ebfbfc46f\n",
"PETSc Version: 3.15.0\n",
"SLEPc Version: 3.14.2\n",
"Current Time: Mon Apr 19 12:58:39 2021\n",
"Executable Timestamp: Sat Apr 17 21:27:24 2021\n",
"\n",
"Parallelism:\n",
" Num Processors: 1\n",
" Num Threads: 1\n",
"\n",
"Mesh: \n",
" Parallel Type: replicated\n",
" Mesh Dimension: 2\n",
" Spatial Dimension: 2\n",
" Nodes: \n",
" Total: 861\n",
" Local: 861\n",
" Elems: \n",
" Total: 200\n",
" Local: 200\n",
" Num Subdomains: 1\n",
" Num Partitions: 1\n",
"\n",
"Nonlinear System:\n",
" Num DOFs: 861\n",
" Num Local DOFs: 861\n",
" Variables: \"u\" \n",
" Finite Element Types: \"LAGRANGE\" \n",
" Approximation Orders: \"SECOND\" \n",
"\n",
"Auxiliary System:\n",
" Num DOFs: 2400\n",
" Num Local DOFs: 2400\n",
" Variables: \"diffFluxU\" { \"diffFluxU_x\" \"diffFluxU_y\" } \n",
" Finite Element Types: \"MONOMIAL_VEC\" \"MONOMIAL\" \n",
" Approximation Orders: \"FIRST\" \"FIRST\" \n",
"\n",
"Execution Information:\n",
" Executioner: Steady\n",
" Solver Mode: NEWTON\n",
" PETSc Preconditioner: lu \n",
" MOOSE Preconditioner: FDP\n",
"\n",
" 0 Nonlinear |R| = \u001b[32m1.855831e+00\u001b[39m\n",
" 0 Linear |R| = \u001b[32m1.855831e+00\u001b[39m\n",
" 1 Linear |R| = \u001b[32m1.506345e-14\u001b[39m\n",
" 1 Nonlinear |R| = \u001b[32m1.333172e-09\u001b[39m\n",
"\u001b[32m Solve Converged!\u001b[39m\n",
"The .pvtu extension should be used when writing VTK files in libMesh.WARNING! There are options you set that were not used!\n",
"WARNING! could be spelling mistake, etc!\n",
"There is one unused database option. It is:\n",
"Option left: name:-i value: engy5310p1/input.hit\n"
]
}
],
"source": [
"'''Run Engy5310P1 MOOSE App'''\n",
"\n",
"!engy5310p1/engy5310p1-opt -i engy5310p1/input.hit"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"cell_style": "center"
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"'''Show 2D solution'''\n",
"\n",
"import pyvista as pv\n",
"poisson = pv.read('out_000_0.vtu')\n",
"cpos = poisson.plot(scalars='u', stitle='Concentration [g/cc]', cmap='plasma', window_size=[800,600], notebook=True)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"cell_style": "split"
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"'''Show 2D solution'''\n",
"\n",
"import pyvista as pv\n",
"poisson = pv.read('out_000_0.vtu')\n",
"cpos = poisson.plot(scalars='diffFluxU_x', stitle='Diffusion Flux X [g/(cm^2 s)]', cmap='plasma', notebook=True) "
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"cell_style": "split"
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"'''Show 2D y flux solution'''\n",
"\n",
"import pyvista as pv\n",
"poisson = pv.read('out_000_0.vtu')\n",
"cpos = poisson.plot(scalars='diffFluxU_y', stitle='Diffusion Flux Y [g/(cm^2 s)]', cmap='plasma', notebook=True)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"'''Show FEM Solution'''\n",
"\n",
"import pandas as pd\n",
"df = pd.read_csv('out-x_x-line_0002.csv')\n",
"\n",
"plot_solution(df, title='Dirichlet BC FEM Solution $u_h(x,y=0)$', basis_functions_type='Quadratic Lagrange', flux_basis_functions_type='Linear Monomial')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Energy Postprocessing](#toc)\n",
"\n",
"To compute the [Poisson-Dirichlet energy](#energy) a *Postprocessor* needs to be built. The user-developed class should use the previously computed diffusion flux component. With an eye towards the future use of this application in 2D and 3D, call this new class, `BulkEnergy`."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"code_folding": [
12
]
},
"outputs": [],
"source": [
"'''FEM Solution'''\n",
"\n",
"n_felem_x = 20\n",
"n_felem_y = 10\n",
"\n",
"order = 'second'\n",
"\n",
"n_plot_pts_x = n_felem_x + 1\n",
"n_plot_pts_y = n_felem_y + 1\n",
"\n",
"from engy_5310.toolkit import write_engy5310_p1_2d_input_file\n",
"\n",
"write_engy5310_p1_2d_input_file(x_left=x_left, x_right=x_right, y_bottom=y_bottom, y_top=y_top, \n",
" u_left=u_left, u_right=u_right, u_bottom=u_bottom, u_top=u_top,\n",
" diff_coeff=diff_coeff, source_s=source_s, n_felem_x=n_felem_x, n_felem_y=n_felem_y, \n",
" order=order, \n",
" n_plot_pts_x=n_plot_pts_x, n_plot_pts_y=n_plot_pts_y, \n",
" compute_energy=True,\n",
" solver='fdp-newt-full')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"# Engy-5310 Problem: Poisson 2D FEM\r\n",
"# UMass Lowell Nuclear Chemical Engineering\r\n",
"# Prof. Valmor F. de Almeida\r\n",
"# 19Apr21 12:58:40\r\n",
"\r\n",
"# Parameters\r\n",
"xmin = 0.00000e+00\r\n",
"xmax = 2.50000e+01\r\n",
"ymin = -6.25000e+00\r\n",
"ymax = 6.25000e+00\r\n",
"diff_coeff = 1.00000e-01\r\n",
"source_s = 1.00000e-03\r\n",
"u_left = 3.00000e+00\r\n",
"u_right = 0.00000e+00\r\n",
"u_bottom = 0.00000e+00\r\n",
"u_top = 2.00000e+00\r\n",
"\r\n",
"[Problem]\r\n",
" type = FEProblem\r\n",
" coord_type = XYZ\r\n",
"[]\r\n",
"\r\n",
"[Mesh]\r\n",
" [2d]\r\n",
" type = GeneratedMeshGenerator\r\n",
" dim = 2\r\n",
" xmin = ${replace xmin}\r\n",
" xmax = ${replace xmax}\r\n",
" ymin = ${replace ymin}\r\n",
" ymax = ${replace ymax}\r\n",
" nx = 20\r\n",
" ny = 10\r\n",
" elem_type = QUAD9\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Variables]\r\n",
" [u]\r\n",
" order = second\r\n",
" family = lagrange\r\n",
" initial_condition = ${fparse (u_left+u_right+u_bottom+u_top)/4}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Kernels]\r\n",
" [diffusion-term]\r\n",
" type = DiffusionTerm\r\n",
" variable = u # produced quantity\r\n",
" diffCoeff = ${replace diff_coeff}\r\n",
" []\r\n",
" [source-term]\r\n",
" type = SourceTerm\r\n",
" variable = u # add to produced quantity\r\n",
" sourceS = ${replace source_s}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[BCs]\r\n",
" [east]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = left\r\n",
" value = ${replace u_left}\r\n",
" []\r\n",
" [west]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = right\r\n",
" value = ${replace u_right}\r\n",
" []\r\n",
" [south]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = bottom\r\n",
" value = ${replace u_bottom}\r\n",
" []\r\n",
" [north]\r\n",
" type = DirichletBC\r\n",
" variable = u\r\n",
" boundary = top\r\n",
" value = ${replace u_top}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Preconditioning]\r\n",
" active = 'fdp-newt-full'\r\n",
" [fdp-newt-full]\r\n",
" type = FDP\r\n",
" full = true\r\n",
" solve_type = 'NEWTON'\r\n",
" petsc_options_iname = '-pc_type -mat_fd_coloring_err -mat_fd_type'\r\n",
" petsc_options_value = 'lu 9.9999999999999995474811182588626e-07 ds'\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Executioner]\r\n",
" type = Steady\r\n",
"[]\r\n",
"\r\n",
"[Postprocessors]\r\n",
" [bulk-energy]\r\n",
" type = BulkEnergy\r\n",
" execute_on = 'timestep_end final'\r\n",
" variable = 'u' # bulk energy unknown variable\r\n",
" diffCoeff = ${replace diff_coeff}\r\n",
" sourceS = ${replace source_s}\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[VectorPostprocessors]\r\n",
" [x-line]\r\n",
" type = LineValueSampler\r\n",
" execute_on = 'timestep_end final'\r\n",
" variable = 'u' # output data\r\n",
" start_point = '${replace xmin} ${fparse (ymax+ymin)/2} 0'\r\n",
" end_point = '${replace xmax} ${fparse (ymax+ymin)/2} 0'\r\n",
" num_points = 21\r\n",
" sort_by = id\r\n",
" []\r\n",
" [y-line]\r\n",
" type = LineValueSampler\r\n",
" execute_on = 'timestep_end final'\r\n",
" variable = 'u' # output data\r\n",
" start_point = '${fparse (xmax+xmin)/2} ${replace ymin} 0'\r\n",
" end_point = '${fparse (xmax+xmin)/2} ${replace ymax} 0'\r\n",
" num_points = 11\r\n",
" sort_by = id\r\n",
" []\r\n",
"[]\r\n",
"\r\n",
"[Outputs]\r\n",
" console = true\r\n",
" [vtk]\r\n",
" type = VTK\r\n",
" execute_on = final\r\n",
" file_base = out\r\n",
" []\r\n",
" [x]\r\n",
" type = CSV\r\n",
" execute_on = 'final'\r\n",
" show = 'x-line'\r\n",
" file_base = out-x\r\n",
" []\r\n",
" [y]\r\n",
" type = CSV\r\n",
" execute_on = 'final'\r\n",
" show = 'y-line'\r\n",
" file_base = out-y\r\n",
" []\r\n",
" [console-energy]\r\n",
" type = Console\r\n",
" execute_on = 'final linear nonlinear'\r\n",
" show = 'bulk-energy'\r\n",
" []\r\n",
" [file-energy]\r\n",
" type = CSV\r\n",
" execute_on = 'final'\r\n",
" file_base = 'out_energy'\r\n",
" show = 'bulk-energy'\r\n",
" []\r\n",
"[]\r\n"
]
}
],
"source": [
"'''Display MOOSE input file created'''\n",
"\n",
"!cat engy5310p1/input.hit"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"Framework Information:\n",
"MOOSE Version: git commit 52562be492 on 2021-04-09\n",
"LibMesh Version: 27141d18f3137f77e33cdb3d565fd38ebfbfc46f\n",
"PETSc Version: 3.15.0\n",
"SLEPc Version: 3.14.2\n",
"Current Time: Mon Apr 19 12:58:40 2021\n",
"Executable Timestamp: Sat Apr 17 21:27:24 2021\n",
"\n",
"Parallelism:\n",
" Num Processors: 1\n",
" Num Threads: 1\n",
"\n",
"Mesh: \n",
" Parallel Type: replicated\n",
" Mesh Dimension: 2\n",
" Spatial Dimension: 2\n",
" Nodes: \n",
" Total: 861\n",
" Local: 861\n",
" Elems: \n",
" Total: 200\n",
" Local: 200\n",
" Num Subdomains: 1\n",
" Num Partitions: 1\n",
"\n",
"Nonlinear System:\n",
" Num DOFs: 861\n",
" Num Local DOFs: 861\n",
" Variables: \"u\" \n",
" Finite Element Types: \"LAGRANGE\" \n",
" Approximation Orders: \"SECOND\" \n",
"\n",
"Execution Information:\n",
" Executioner: Steady\n",
" Solver Mode: NEWTON\n",
" PETSc Preconditioner: lu \n",
" MOOSE Preconditioner: FDP\n",
"\n",
"\n",
"Postprocessor Values:\n",
"+----------------+----------------+\n",
"| time | bulk-energy |\n",
"+----------------+----------------+\n",
"| 0.000000e+00 | 0.000000e+00 |\n",
"+----------------+----------------+\n",
"\n",
" 0 Nonlinear |R| = \u001b[32m1.855831e+00\u001b[39m\n",
" 0 Linear |R| = \u001b[32m1.855831e+00\u001b[39m\n",
" 1 Linear |R| = \u001b[32m1.506345e-14\u001b[39m\n",
" 1 Nonlinear |R| = \u001b[32m1.333172e-09\u001b[39m\n",
"\u001b[32m Solve Converged!\u001b[39m\n",
"\n",
"Postprocessor Values:\n",
"+----------------+----------------+\n",
"| time | bulk-energy |\n",
"+----------------+----------------+\n",
"| 0.000000e+00 | 0.000000e+00 |\n",
"| 1.000000e+00 | 1.498531e-01 |\n",
"+----------------+----------------+\n",
"\n",
"The .pvtu extension should be used when writing VTK files in libMesh.\n",
"FINAL:\n",
"\n",
"Postprocessor Values:\n",
"+----------------+----------------+\n",
"| time | bulk-energy |\n",
"+----------------+----------------+\n",
"| 0.000000e+00 | 0.000000e+00 |\n",
"| 1.000000e+00 | 1.498531e-01 |\n",
"| 2.000000e+00 | 1.498531e-01 |\n",
"+----------------+----------------+\n",
"\n",
"WARNING! There are options you set that were not used!\n",
"WARNING! could be spelling mistake, etc!\n",
"There is one unused database option. It is:\n",
"Option left: name:-i value: engy5310p1/input.hit\n"
]
}
],
"source": [
"'''Run Engy5310P1 MOOSE App'''\n",
"\n",
"!engy5310p1/engy5310p1-opt -i engy5310p1/input.hit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Application Tree](#toc)\n",
"\n",
"This tree printout helps the understanding of various pieces of the `MOOSE` application repository created after all the above steps including future implementations in the notebooks following the present one that cover various boundary conditions."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[01;34mengy5310p1\u001b[00m\r\n",
"├── LICENSE\r\n",
"├── Makefile\r\n",
"├── README.md\r\n",
"├── \u001b[01;34m__pycache__\u001b[00m\r\n",
"│ └── chigger.cpython-38.pyc\r\n",
"├── \u001b[01;34mbuild\u001b[00m\r\n",
"│ ├── \u001b[01;34mheader_symlinks\u001b[00m\r\n",
"│ │ ├── \u001b[01;36mBoundaryEnergy.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/postprocessors/BoundaryEnergy.h\r\n",
"│ │ ├── \u001b[01;36mBulkEnergy.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/postprocessors/BulkEnergy.h\r\n",
"│ │ ├── \u001b[01;36mConvectionTerm.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/kernels/ConvectionTerm.h\r\n",
"│ │ ├── \u001b[01;36mDiffusionFlux.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/auxkernels/DiffusionFlux.h\r\n",
"│ │ ├── \u001b[01;36mDiffusionFluxComponent.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/auxkernels/DiffusionFluxComponent.h\r\n",
"│ │ ├── \u001b[01;36mDiffusionTerm.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/kernels/DiffusionTerm.h\r\n",
"│ │ ├── \u001b[01;36mEngy5310P1App.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/base/Engy5310P1App.h\r\n",
"│ │ ├── \u001b[01;36mNormalFluxBC.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/bcs/NormalFluxBC.h\r\n",
"│ │ └── \u001b[01;36mSourceTerm.h\u001b[00m -> /home/dealmeida/OneDrive/uml-courses/engy-5310/2021-01-05-spring/jupynb-repo/notebooks/engy5310p1/include/kernels/SourceTerm.h\r\n",
"│ └── \u001b[01;34munity_src\u001b[00m\r\n",
"│ ├── auxkernels_Unity.C\r\n",
"│ ├── auxkernels_Unity.x86_64-pc-linux-gnu.opt.lo\r\n",
"│ ├── auxkernels_Unity.x86_64-pc-linux-gnu.opt.lo.d\r\n",
"│ ├── bcs_Unity.C\r\n",
"│ ├── bcs_Unity.x86_64-pc-linux-gnu.opt.lo\r\n",
"│ ├── bcs_Unity.x86_64-pc-linux-gnu.opt.lo.d\r\n",
"│ ├── kernels_Unity.C\r\n",
"│ ├── kernels_Unity.x86_64-pc-linux-gnu.opt.lo\r\n",
"│ ├── kernels_Unity.x86_64-pc-linux-gnu.opt.lo.d\r\n",
"│ ├── postprocessors_Unity.C\r\n",
"│ ├── postprocessors_Unity.x86_64-pc-linux-gnu.opt.lo\r\n",
"│ └── postprocessors_Unity.x86_64-pc-linux-gnu.opt.lo.d\r\n",
"├── \u001b[01;32mengy5310p1-opt\u001b[00m\r\n",
"├── \u001b[01;34minclude\u001b[00m\r\n",
"│ ├── \u001b[01;34mauxkernels\u001b[00m\r\n",
"│ │ ├── DiffusionFlux.h\r\n",
"│ │ └── DiffusionFluxComponent.h\r\n",
"│ ├── \u001b[01;34mbase\u001b[00m\r\n",
"│ │ └── Engy5310P1App.h\r\n",
"│ ├── \u001b[01;34mbcs\u001b[00m\r\n",
"│ │ └── NormalFluxBC.h\r\n",
"│ ├── \u001b[01;34mkernels\u001b[00m\r\n",
"│ │ ├── ConvectionTerm.h\r\n",
"│ │ ├── ConvectionTerm.h~\r\n",
"│ │ ├── DiffusionTerm.h\r\n",
"│ │ └── SourceTerm.h\r\n",
"│ └── \u001b[01;34mpostprocessors\u001b[00m\r\n",
"│ ├── BoundaryEnergy.h\r\n",
"│ └── BulkEnergy.h\r\n",
"├── input.hit\r\n",
"├── \u001b[01;34mlib\u001b[00m\r\n",
"│ ├── \u001b[01;32mlibengy5310p1-opt.la\u001b[00m\r\n",
"│ ├── \u001b[01;36mlibengy5310p1-opt.so\u001b[00m -> \u001b[01;32mlibengy5310p1-opt.so.0.0.0\u001b[00m\r\n",
"│ ├── \u001b[01;36mlibengy5310p1-opt.so.0\u001b[00m -> \u001b[01;32mlibengy5310p1-opt.so.0.0.0\u001b[00m\r\n",
"│ └── \u001b[01;32mlibengy5310p1-opt.so.0.0.0\u001b[00m\r\n",
"├── \u001b[01;34msrc\u001b[00m\r\n",
"│ ├── \u001b[01;34mauxkernels\u001b[00m\r\n",
"│ │ ├── DiffusionFlux.C\r\n",
"│ │ └── DiffusionFluxComponent.C\r\n",
"│ ├── \u001b[01;34mbase\u001b[00m\r\n",
"│ │ ├── Engy5310P1App.C\r\n",
"│ │ ├── Engy5310P1App.x86_64-pc-linux-gnu.opt.lo\r\n",
"│ │ └── Engy5310P1App.x86_64-pc-linux-gnu.opt.lo.d\r\n",
"│ ├── \u001b[01;34mbcs\u001b[00m\r\n",
"│ │ ├── NormalFluxBC.C\r\n",
"│ │ └── NormalFluxBC.C~\r\n",
"│ ├── \u001b[01;34mkernels\u001b[00m\r\n",
"│ │ ├── ConvectionTerm.C\r\n",
"│ │ ├── ConvectionTerm.C~\r\n",
"│ │ ├── DiffusionTerm.C\r\n",
"│ │ └── SourceTerm.C\r\n",
"│ ├── main.C\r\n",
"│ ├── main.C~\r\n",
"│ ├── main.x86_64-pc-linux-gnu.opt.lo\r\n",
"│ ├── main.x86_64-pc-linux-gnu.opt.lo.d\r\n",
"│ └── \u001b[01;34mpostprocessors\u001b[00m\r\n",
"│ ├── BoundaryEnergy.C\r\n",
"│ └── BulkEnergy.C\r\n",
"├── \u001b[01;34mtest\u001b[00m\r\n",
"│ └── \u001b[01;34mlib\u001b[00m\r\n",
"│ ├── \u001b[01;32mlibengy5310p1_test-opt.la\u001b[00m\r\n",
"│ ├── \u001b[01;36mlibengy5310p1_test-opt.so\u001b[00m -> \u001b[01;32mlibengy5310p1_test-opt.so.0.0.0\u001b[00m\r\n",
"│ ├── \u001b[01;36mlibengy5310p1_test-opt.so.0\u001b[00m -> \u001b[01;32mlibengy5310p1_test-opt.so.0.0.0\u001b[00m\r\n",
"│ └── \u001b[01;32mlibengy5310p1_test-opt.so.0.0.0\u001b[00m\r\n",
"├── test.i\r\n",
"└── vtkviz.py\r\n",
"\r\n",
"19 directories, 64 files\r\n"
]
}
],
"source": [
"!tree engy5310p1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
},
"latex_envs": {
"LaTeX_envs_menu_present": true,
"autoclose": false,
"autocomplete": true,
"bibliofile": "biblio.bib",
"cite_by": "apalike",
"current_citInitial": 1,
"eqLabelWithNumbers": true,
"eqNumInitial": 1,
"hotkeys": {
"equation": "Ctrl-E",
"itemize": "Ctrl-I"
},
"labels_anchors": false,
"latex_user_defs": false,
"report_style_numbering": false,
"user_envs_cfg": false
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {
"height": "calc(100% - 180px)",
"left": "10px",
"top": "150px",
"width": "220.75px"
},
"toc_section_display": true,
"toc_window_display": false
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"nbformat": 4,
"nbformat_minor": 2
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