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    "# Generador de un perfil NACA de 4 dígitos\n",
    "\n",
    "Asignatura: Vehículos aeroespaciales\n",
    "\n",
    "Departamento: Ciencia y Tecnología de Materiales y Fluidos\n",
    "\n",
    "Centro: Escuela Universitaria Politécnica de Teruel\n",
    "\n",
    "Profesor: Adrián Navas Montilla"
   ]
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       "         var(--colab-secondary-surface-color); padding: 8px 12px;\n",
       "         border-bottom: 1px solid var(--colab-border-color);\"><b>plot_airfoil</b><br/>def plot_airfoil(m, p, t, c, n)</pre><pre class=\"function-repr-contents function-repr-contents-collapsed\" style=\"\"><a class=\"filepath\" style=\"display:none\" href=\"#\">/tmp/ipython-input-537601517.py</a>&lt;no docstring&gt;</pre></div>"
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    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "from ipywidgets import interact, IntSlider, fixed\n",
    "\n",
    "\n",
    "def airfoilNACA(m,p,t,c,n):\n",
    "    m = m / 100\n",
    "    p = p / 10\n",
    "    t = t / 100\n",
    "\n",
    "    # x distribution (cosine spacing)\n",
    "    theta = np.linspace(0, np.pi, n)\n",
    "    x = 0.5 * c * (1 - np.cos(theta))\n",
    "    x_hat = x / c  # normalized x\n",
    "\n",
    "    # Thickness distribution\n",
    "    yt = 5 * t * ( 0.2969 * np.sqrt(x_hat) - 0.1260 * x_hat - 0.3516 * x_hat**2 + 0.2843 * x_hat**3 - 0.1015 * x_hat**4 )\n",
    "\n",
    "    # Camber line and slope\n",
    "    z = np.zeros_like(x)\n",
    "    dzdx = np.zeros_like(x)\n",
    "\n",
    "    for i in range(len(x)):\n",
    "        if x_hat[i] < p and p != 0:\n",
    "            z[i] = (m / p**2) * (2 * p * x_hat[i] - x_hat[i]**2)\n",
    "            dzdx[i] = (2 * m / p**2) * (p - x_hat[i])\n",
    "        elif p != 0:\n",
    "            z[i] = (m / (1 - p)**2) * ((1 - 2 * p) + 2 * p * x_hat[i] - x_hat[i]**2)\n",
    "            dzdx[i] = (2 * m / (1 - p)**2) * (p - x_hat[i])\n",
    "\n",
    "    beta = np.arctan(dzdx)\n",
    "\n",
    "    # Upper and lower airfoil coordinates\n",
    "    xu = x - yt * np.sin(beta)\n",
    "    yu = z + yt * np.cos(beta)\n",
    "    xl = x + yt * np.sin(beta)\n",
    "    yl = z - yt * np.cos(beta)\n",
    "\n",
    "    # Combine and plot\n",
    "    x_total = np.concatenate([xu[::-1], xl[1:]])\n",
    "    y_total = np.concatenate([yu[::-1], yl[1:]])\n",
    "\n",
    "    plt.figure(figsize=(10, 4))\n",
    "    plt.plot(x_total, y_total, 'k-', linewidth=1.5, label=\"Airfoil\")\n",
    "    plt.plot(x, z, 'r--', linewidth=1.2, label=\"Camber line\")\n",
    "    plt.axis('equal')\n",
    "    plt.title(f\"NACA {m*100:.0f}{p*10:.0f}{t*100:.0f}\")\n",
    "    plt.xlabel(\"x/c\")\n",
    "    plt.ylabel(\"y/c\")\n",
    "    plt.grid(True)\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "    return x_total, y_total\n",
    "\n",
    "# Airfoil function\n",
    "def plot_airfoil(m,p,t,c,n):\n",
    "    airfoilNACA(m,p,t,c,n)   # ignoramos el return\n",
    "\n",
    "# Interactive sliders\n",
    "interact(\n",
    "    plot_airfoil,\n",
    "    m=IntSlider(min=0, max=9, step=1, value=2, description=\"m\"),\n",
    "    p=IntSlider(min=0, max=9, step=1, value=4, description=\"p\"),\n",
    "    t=IntSlider(min=10, max=40, step=1, value=12, description=\"t\"),\n",
    "    c=fixed(1.0),  # cuerda\n",
    "    n=fixed(200)   # número de puntos\n",
    ")\n"
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\n",
         "text/plain": "<Figure size 1000x400 with 1 Axes>"
        },
        "metadata": {},
        "output_type": "display_data"
       }
      ]
     }
    },
    "d59d4898fde547d2a729a92a8a6212d8": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "SliderStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "SliderStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": "",
      "handle_color": null
     }
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}