compute_geoparas_from_profile.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "In this example, we want to use ntrfc-methods to define a naca-profile.\n",
    "We are using the naca_airfoil_creator module from ntrfc.turbo.airfoil_generators and d the DomainParameters object.\n",
    "\n",
    "Lets start with importing all the necessary modules"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [],
   "source": [
    "from ntrfc.turbo.airfoil_generators.naca_airfoil_creator import naca\n",
    "import numpy as np\n",
    "import pyvista as pv\n",
    "from ntrfc.cascade_case.domain.geoparas import DomainParameters\n",
    "\n",
    "pv.set_jupyter_backend(\"static\")\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "We now can define 2D points using the naca-function.\n",
    "Afterwards, we can create a PolyData object to parse this to the generate_params_by_pointcloud method to generate all attributes of DomainParas"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/many/miniconda3/envs/NTRfC/lib/python3.10/site-packages/pyvista/core/filters/poly_data.py:2772: PyvistaFutureWarning: The default value of the ``capping`` keyword argument will change in a future version to ``True`` to match the behavior of VTK. We recommend passing the keyword explicitly to prevent future surprises.\n",
      "  warnings.warn(\n",
      "\u001B[0m\u001B[33m2022-12-21 12:45:33.956 ( 156.352s) [        D0EB4180]        vtkRenderer.cxx:1172  WARN| vtkOpenGLRenderer (0x4367190): Resetting view-up since view plane normal is parallel\u001B[0m\n"
     ]
    },
    {
     "data": {
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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pv.set_jupyter_backend(\"static\")\n",
    "xs,ys = naca(\"6510\",256)\n",
    "points = pv.PolyData(np.stack([xs,ys,np.zeros(len(xs))]).T)\n",
    "alpha = 1\n",
    "domainparas = DomainParameters()\n",
    "domainparas.generate_params_by_pointcloud(points,alpha=1)\n",
    "domainparas.plot()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "The domainaras object now has several parameters of the blade-geometry as attributes."
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['stagger_angle', 'sspoly', 'pspoly', 'midspoly', 'xinlet', 'xoutlet', 'pitch', 'blade_yshift', 'beta_in', 'beta_out', 'alpha', 'profile_points', 'leading_edge_index', 'trailing_edge_index'])\n",
      "dict_values([179.98765292832272, PolyData (0x7fbbd7082380)\n",
      "  N Cells:\t260\n",
      "  N Points:\t260\n",
      "  X Bounds:\t0.000e+00, 1.000e+00\n",
      "  Y Bounds:\t-1.776e-02, 2.048e-02\n",
      "  Z Bounds:\t0.000e+00, 0.000e+00\n",
      "  N Arrays:\t0\n",
      ", PolyData (0x7fbbd70822c0)\n",
      "  N Cells:\t253\n",
      "  N Points:\t253\n",
      "  X Bounds:\t-2.935e-04, 9.994e-01\n",
      "  Y Bounds:\t0.000e+00, 1.061e-01\n",
      "  Z Bounds:\t0.000e+00, 0.000e+00\n",
      "  N Arrays:\t0\n",
      ", PolyData (0x7fbbd7082d40)\n",
      "  N Cells:\t1\n",
      "  N Points:\t100\n",
      "  X Bounds:\t0.000e+00, 9.994e-01\n",
      "  Y Bounds:\t0.000e+00, 6.012e-02\n",
      "  Z Bounds:\t0.000e+00, 0.000e+00\n",
      "  N Arrays:\t0\n",
      ", None, None, None, None, 14.932326726746801, 13.456929952586245, 1, PolyData (0x7fbbf7714640)\n",
      "  N Cells:\t511\n",
      "  N Points:\t511\n",
      "  X Bounds:\t-2.935e-04, 1.000e+00\n",
      "  Y Bounds:\t-1.776e-02, 1.061e-01\n",
      "  Z Bounds:\t0.000e+00, 0.000e+00\n",
      "  N Arrays:\t0\n",
      ", 72, 324])\n"
     ]
    }
   ],
   "source": [
    "print(domainparas.__dict__.keys())\n",
    "print(domainparas.__dict__.values())"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}