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   "source": [
    "# Tutorial - Axial pile capacity calculation according to API RP2 GEO with groundhog\n",
    "\n",
    "At the request of users, a routine for axial capacity is developed within groundhog.\n",
    "\n",
    "The pile capacity class ``AxCapCalculation`` develops a workflow in which the unit skin friction methods and unit end bearing methods are introduced into a ``SoilProfile`` object.\n",
    "\n",
    "A check is then performed to assess whether the necessary soil parameters are defined in the ``SoilProfile``. If all necessary parameters are available, a calculation grid is defined and the unit skin friction and unit end bearing calculations are calculated. This notebook outlines the different components of the calculation for the API RP2 GEO Main Text method."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77957da6",
   "metadata": {},
   "source": [
    "## Library imports\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "8c22a2ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "1bc9aa18",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.io as pio\n",
    "pio.templates.default = 'plotly_white'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "048eba65",
   "metadata": {},
   "outputs": [],
   "source": [
    "from groundhog.general.soilprofile import SoilProfile\n",
    "from groundhog.general.plotting import LogPlot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc9955d2",
   "metadata": {},
   "source": [
    "## Preparing a ``groundhog`` ``SoilProfile`` object for axial capacity analysis\n",
    "\n",
    "### Definition of methods and soil parameters in ``SoilProfile``\n",
    "\n",
    "For each layer in the ``SoilProfile``, the unit skin friction and unit end bearing need to be set. Each methods has associated required parameters. The presence of these parameters can be checked before starting the calculation.\n",
    "\n",
    "First, a basic soil profile with three layers is defined:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "e0d6d987",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Depth from [m]</th>\n",
       "      <th>Depth to [m]</th>\n",
       "      <th>Soil type</th>\n",
       "      <th>Total unit weight [kN/m3]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>Sand</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>40</td>\n",
       "      <td>Clay</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Depth from [m]  Depth to [m] Soil type  Total unit weight [kN/m3]\n",
       "0               0            10      Sand                         20\n",
       "1              10            40      Clay                         18"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "sp = SoilProfile({\n",
    "    'Depth from [m]': [0, 10],\n",
    "    'Depth to [m]': [10, 40],\n",
    "    'Soil type': ['Sand', 'Clay'],\n",
    "    'Total unit weight [kN/m3]': [20, 18]\n",
    "})\n",
    "sp"
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    "Next, the calculation methods for unit skin friction and unit end bearing are specified in the columns ``Unit skin friction`` and ``Unit end bearing``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "56f8d1ba",
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   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Depth from [m]</th>\n",
       "      <th>Depth to [m]</th>\n",
       "      <th>Soil type</th>\n",
       "      <th>Total unit weight [kN/m3]</th>\n",
       "      <th>Unit skin friction</th>\n",
       "      <th>Unit end bearing</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>Sand</td>\n",
       "      <td>20</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>40</td>\n",
       "      <td>Clay</td>\n",
       "      <td>18</td>\n",
       "      <td>API RP2 GEO Clay</td>\n",
       "      <td>API RP2 GEO Clay</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   Depth from [m]  Depth to [m] Soil type  Total unit weight [kN/m3]  \\\n",
       "0               0            10      Sand                         20   \n",
       "1              10            40      Clay                         18   \n",
       "\n",
       "  Unit skin friction  Unit end bearing  \n",
       "0   API RP2 GEO Sand  API RP2 GEO Sand  \n",
       "1   API RP2 GEO Clay  API RP2 GEO Clay  "
      ]
     },
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     "metadata": {},
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   "source": [
    "sp['Unit skin friction'] = ['API RP2 GEO Sand', 'API RP2 GEO Clay']\n",
    "sp['Unit end bearing'] = ['API RP2 GEO Sand', 'API RP2 GEO Clay']\n",
    "sp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "097b4d06",
   "metadata": {},
   "source": [
    "### Overburden calculation\n",
    "\n",
    "As several method require the vertical effective stress as an input, the stresses can be calculated using the ``calculate_overburden`` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "e28b4306",
   "metadata": {},
   "outputs": [],
   "source": [
    "sp.calculate_overburden()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1dd1c453",
   "metadata": {},
   "source": [
    "The vertical effective stress profile can be plotted:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "59a5e900",
   "metadata": {},
   "outputs": [
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          "colorway": [
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           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
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          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "white",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "#C8D4E3"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "white",
          "polar": {
           "angularaxis": {
            "gridcolor": "#EBF0F8",
            "linecolor": "#EBF0F8",
            "ticks": ""
           },
           "bgcolor": "white",
           "radialaxis": {
            "gridcolor": "#EBF0F8",
            "linecolor": "#EBF0F8",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "#EBF0F8",
           "linecolor": "#EBF0F8",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "#EBF0F8",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "#EBF0F8",
           "linecolor": "#EBF0F8",
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           },
           "zerolinecolor": "#EBF0F8",
           "zerolinewidth": 2
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        },
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         "side": "top",
         "tickvals": [],
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         "range": [
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         ],
         "side": "top",
         "title": {
          "text": "$ \\sigma_{v0}^{\\prime} \\ \\text{[kPa]} $"
         },
         "type": "linear"
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
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         ],
         "range": [
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         "title": {
          "text": "$ z \\ \\text{[m]} $"
         }
        },
        "yaxis2": {
         "anchor": "x2",
         "domain": [
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         ],
         "matches": "y",
         "showticklabels": false
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stress_plot = LogPlot(sp, no_panels=1, fillcolordict={'SAND': 'yellow', 'CLAY': 'brown'})\n",
    "stress_plot.add_trace(\n",
    "    x=sp.soilparameter_series('Vertical effective stress [kPa]')[1],\n",
    "    z=sp.soilparameter_series('Vertical effective stress [kPa]')[0],\n",
    "    name=r'$ \\sigma_{v0}^{\\prime} $', showlegend=False, panel_no=1)\n",
    "stress_plot.set_xaxis(title=r'$ \\sigma_{v0}^{\\prime} \\ \\text{[kPa]} $', panel_no=1)\n",
    "stress_plot.set_zaxis(title=r'$ z \\ \\text{[m]} $', range=(20, 0))\n",
    "stress_plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc6f0ac8",
   "metadata": {},
   "source": [
    "## Axial pile capacity calculation setup\n",
    "\n",
    "### Creating the calculation object\n",
    "\n",
    "An axial capacity calculation can be set up based on the soil profile. The ``AxcapCalculation`` class contains the necessary functionality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "3326adcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from groundhog.deepfoundations.axialcapacity.axcap import AxCapCalculation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "b40f0fc8",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc = AxCapCalculation(sp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0508cbf5",
   "metadata": {},
   "source": [
    "### Checking of presence of require soil parameters\n",
    "\n",
    "The presence of the required input to unit skin friction and unit end bearing calculations can be checked. Note that both numerical and string soil parameters need to be checked:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "e31ea761",
   "metadata": {},
   "outputs": [],
   "source": [
    "from groundhog.general.parameter_mapping import SOIL_PARAMETER_MAPPING, reverse_dict\n",
    "from groundhog.deepfoundations.axialcapacity.skinfriction import SKINFRICTION_PARAMETERS, SKINFRICTION_METHODS\n",
    "from groundhog.deepfoundations.axialcapacity.endbearing import ENDBEARING_PARAMETERS, ENDBEARING_METHODS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f3ba2e0",
   "metadata": {},
   "source": [
    "``groundhog`` has a standard mapping for soil parameters, which defines the mapping from column headers in a Pandas dataframe to ``groundhog`` function variables. Column headers must conform to this naming."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "39c6262c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'qc [MPa]': 'qc',\n",
       " 'fs [MPa]': 'fs',\n",
       " 'u2 [MPa]': 'u2',\n",
       " 'qt [MPa]': 'qt',\n",
       " 'ft [MPa]': 'ft',\n",
       " 'qnet [MPa]': 'qnet',\n",
       " 'Vertical total stress [kPa]': 'sigma_vo',\n",
       " 'Vertical effective stress [kPa]': 'sigma_vo_eff',\n",
       " 'Effective pressure [kPa]': 'p_eff',\n",
       " 'Effective unit weight [kN/m3]': 'gamma_eff',\n",
       " 'Total unit weight [kN/m3]': 'gamma_tot',\n",
       " 'Unit weight [kN/m3]': 'gamma',\n",
       " 'Ic [-]': 'ic',\n",
       " 'Dr [-]': 'relative_density',\n",
       " 'Gmax [kPa]': 'gmax',\n",
       " 'G [kPa]': 'shearmodulus',\n",
       " 'Qt [-]': 'Qt',\n",
       " 'Bq [-]': 'Bq',\n",
       " 'Fr [%]': 'Fr',\n",
       " 'Rf [%]': 'Rf',\n",
       " 'K0 [-]': 'k0',\n",
       " 'Vs [m/s]': 'Vs',\n",
       " 'gamma [kN/m3]': 'gamma',\n",
       " 'OCR [-]': 'ocr',\n",
       " 'PI [%]': 'pi',\n",
       " 'z [m]': 'depth',\n",
       " 'Embedded length [m]': 'embedded_length',\n",
       " 'Effective friction angle [deg]': 'phi_eff',\n",
       " 'Friction angle [deg]': 'phi',\n",
       " 'Critical state friction angle [deg]': 'phi_cs',\n",
       " 'Cohesion [kPa]': 'cohesion',\n",
       " 'Minor principal stress [kPa]': 'sigma_3',\n",
       " 'Major principal stress [kPa]': 'sigma_1',\n",
       " 'Interface friction angle [deg]': 'interface_friction_angle',\n",
       " 'Undrained shear strength [kPa]': 'undrained_shear_strength',\n",
       " 'API soil description': 'api_soildescription',\n",
       " 'API relative density description': 'api_relativedensity',\n",
       " 'Limiting unit skin friction [kPa]': 'fs_lim',\n",
       " 'Limiting unit end bearing [kPa]': 'qb_lim',\n",
       " 'Tension modifier [-]': 'tension_modifier',\n",
       " 'Borehole diameter [mm]': 'borehole_diameter',\n",
       " 'Rod length [m]': 'rod_length',\n",
       " 'Country': 'country',\n",
       " 'Hammer type': 'hammertype',\n",
       " 'Hammer release': 'hammerrelease',\n",
       " 'Sampler type': 'samplertype',\n",
       " 'N [-]': 'N',\n",
       " 'N1_60 [-]': 'N1_60',\n",
       " 'eta H [%]': 'eta_H',\n",
       " 'eta B [-]': 'eta_B',\n",
       " 'eta S [-]': 'eta_S',\n",
       " 'eta R [-]': 'eta_R',\n",
       " 'd50 [mm]': 'd_50',\n",
       " 'N60 [-]': 'N_60',\n",
       " 'Granular': 'granular',\n",
       " 'Void ratio [-]': 'voidratio',\n",
       " 'Dry density [kg/m3]': 'dry_density',\n",
       " 'Bulk density [kg/m3]': 'bulk_density',\n",
       " 'Water density [kg/m3]': 'water_density',\n",
       " 'Density [kg/m3]': 'density',\n",
       " 'Gs [-]': 'specific_gravity',\n",
       " 'S [-]': 'saturation',\n",
       " 'Water content [%]': 'water_content',\n",
       " 'Vertical coefficient of consolidation [m2/yr]': 'cv',\n",
       " 'Horizontal coefficient of consolidation [m2/yr]': 'ch'}"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SOIL_PARAMETER_MAPPING"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ba53be4",
   "metadata": {},
   "source": [
    "The necessary parameters for skin friction calculation can be printed. In v0.9.0, only the API RP2 GEO methods are defined with their associated parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "2801771b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'API RP2 GEO Sand': ['api_relativedensity',\n",
       "  'api_soildescription',\n",
       "  'sigma_vo_eff'],\n",
       " 'API RP2 GEO Clay': ['undrained_shear_strength', 'sigma_vo_eff'],\n",
       " 'Alm and Hamre Sand': ['qt',\n",
       "  'sigma_vo_eff',\n",
       "  'interface_friction_angle',\n",
       "  'depth',\n",
       "  'embedded_length'],\n",
       " 'Alm and Hamre Clay': ['depth',\n",
       "  'embedded_length',\n",
       "  'qt',\n",
       "  'fs',\n",
       "  'sigma_vo_eff']}"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SKINFRICTION_PARAMETERS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f11246b",
   "metadata": {},
   "source": [
    "With the method ``check_methods``, the presence of the parameters can be checked. At this point, the parameters are not yet defined so the method will return a message that the required parameters are not found."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "ace9bbf9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skin friction method API RP2 GEO Sand: Required parameter API relative density description not found\n",
      "Skin friction method API RP2 GEO Sand: Required parameter API soil description not found\n",
      "Skin friction method API RP2 GEO Clay: Required parameter Undrained shear strength [kPa] not found\n",
      "End bearing method API RP2 GEO Sand: Required parameter API relative density description not found\n",
      "End bearing method API RP2 GEO Sand: Required parameter API soil description not found\n",
      "End bearing method API RP2 GEO Clay: Required parameter Undrained shear strength [kPa] not found\n"
     ]
    }
   ],
   "source": [
    "calc.check_methods()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75566c90",
   "metadata": {},
   "source": [
    "The required soil parameters can be defined. Example parameters are defined below. The documentation of the unit skin friction and unit end bearing methods can be checked in the ``groundhog`` documentation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "e259d473",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.sp['API soil description'] = ['Sand', 'Clay']\n",
    "calc.sp['API relative density description'] = ['Medium dense', '-']\n",
    "calc.sp['Undrained shear strength from [kPa]'] = [np.nan, 150]\n",
    "calc.sp['Undrained shear strength to [kPa]'] = [np.nan, 200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "265982be-942e-4f93-b73c-afd2576bf051",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i, row in calc.sp.iterrows():\n",
    "    if row['API relative density description'] == 'Very loose':\n",
    "        calc.sp.loc[i, 'Dr [pct]'] = 10\n",
    "    elif row['API relative density description'] == 'Loose':\n",
    "        calc.sp.loc[i, 'Dr [pct]'] = 25\n",
    "    elif row['API relative density description'] == 'Medium dense':\n",
    "        calc.sp.loc[i, 'Dr [pct]'] = 50\n",
    "    elif row['API relative density description'] == 'Dense':\n",
    "        calc.sp.loc[i, 'Dr [pct]'] = 75\n",
    "    elif row['API relative density description'] == 'Very dense':\n",
    "        calc.sp.loc[i, 'Dr [pct]'] = 90\n",
    "    else:\n",
    "        calc.sp.loc[i, 'Dr [pct]'] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "115b7810",
   "metadata": {},
   "source": [
    "When re-running the ``check_methods`` no messages are returned. But the attribute ``checked`` is now ``True``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "cb670c65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calc.check_methods()\n",
    "calc.checked"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "480fbcc3",
   "metadata": {},
   "source": [
    "## Gridding for axial capacity calculation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac7531c3",
   "metadata": {},
   "source": [
    "A calculation grid can be created based on the soil profile with a spacing of 1m."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "ea110216",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.create_grid(dz=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f785cb9",
   "metadata": {},
   "source": [
    "The grid has a ``nodes`` and ``elements`` attribute where the former contains the nodal coordinates and the associated parameter values at the nodes. The latter contains the element definition with the parameter values at the center of the element."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "5e7c53b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>z [m]</th>\n",
       "      <th>Soil type</th>\n",
       "      <th>Unit skin friction</th>\n",
       "      <th>Unit end bearing</th>\n",
       "      <th>API soil description</th>\n",
       "      <th>API relative density description</th>\n",
       "      <th>Total unit weight [kN/m3]</th>\n",
       "      <th>Water unit weight [kN/m3]</th>\n",
       "      <th>Effective unit weight [kN/m3]</th>\n",
       "      <th>Hydrostatic pressure [kPa]</th>\n",
       "      <th>Vertical effective stress [kPa]</th>\n",
       "      <th>Vertical total stress [kPa]</th>\n",
       "      <th>Undrained shear strength [kPa]</th>\n",
       "      <th>Dr [pct]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
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       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   z [m] Soil type Unit skin friction  Unit end bearing API soil description  \\\n",
       "0    0.0      Sand   API RP2 GEO Sand  API RP2 GEO Sand                 Sand   \n",
       "1    1.0      Sand   API RP2 GEO Sand  API RP2 GEO Sand                 Sand   \n",
       "2    2.0      Sand   API RP2 GEO Sand  API RP2 GEO Sand                 Sand   \n",
       "3    3.0      Sand   API RP2 GEO Sand  API RP2 GEO Sand                 Sand   \n",
       "4    4.0      Sand   API RP2 GEO Sand  API RP2 GEO Sand                 Sand   \n",
       "\n",
       "  API relative density description  Total unit weight [kN/m3]  \\\n",
       "0                     Medium dense                       20.0   \n",
       "1                     Medium dense                       20.0   \n",
       "2                     Medium dense                       20.0   \n",
       "3                     Medium dense                       20.0   \n",
       "4                     Medium dense                       20.0   \n",
       "\n",
       "   Water unit weight [kN/m3]  Effective unit weight [kN/m3]  \\\n",
       "0                       10.0                           10.0   \n",
       "1                       10.0                           10.0   \n",
       "2                       10.0                           10.0   \n",
       "3                       10.0                           10.0   \n",
       "4                       10.0                           10.0   \n",
       "\n",
       "   Hydrostatic pressure [kPa]  Vertical effective stress [kPa]  \\\n",
       "0                         0.0                              0.0   \n",
       "1                        10.0                             10.0   \n",
       "2                        20.0                             20.0   \n",
       "3                        30.0                             30.0   \n",
       "4                        40.0                             40.0   \n",
       "\n",
       "   Vertical total stress [kPa]  Undrained shear strength [kPa]  Dr [pct]  \n",
       "0                          0.0                             NaN      50.0  \n",
       "1                         20.0                             NaN      50.0  \n",
       "2                         40.0                             NaN      50.0  \n",
       "3                         60.0                             NaN      50.0  \n",
       "4                         80.0                             NaN      50.0  "
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calc.grid.nodes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "5bcaf639",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Depth from [m]</th>\n",
       "      <th>Depth to [m]</th>\n",
       "      <th>z [m]</th>\n",
       "      <th>dz [m]</th>\n",
       "      <th>Total unit weight [kN/m3]</th>\n",
       "      <th>Water unit weight [kN/m3]</th>\n",
       "      <th>Effective unit weight [kN/m3]</th>\n",
       "      <th>Hydrostatic pressure from [kPa]</th>\n",
       "      <th>Hydrostatic pressure to [kPa]</th>\n",
       "      <th>Hydrostatic pressure [kPa]</th>\n",
       "      <th>...</th>\n",
       "      <th>Vertical total stress [kPa]</th>\n",
       "      <th>Undrained shear strength from [kPa]</th>\n",
       "      <th>Undrained shear strength to [kPa]</th>\n",
       "      <th>Undrained shear strength [kPa]</th>\n",
       "      <th>Dr [pct]</th>\n",
       "      <th>Soil type</th>\n",
       "      <th>Unit skin friction</th>\n",
       "      <th>Unit end bearing</th>\n",
       "      <th>API soil description</th>\n",
       "      <th>API relative density description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>...</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>API RP2 GEO Sand</td>\n",
       "      <td>Sand</td>\n",
       "      <td>Medium dense</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
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      "text/plain": [
       "   Depth from [m]  Depth to [m]  z [m]  dz [m]  Total unit weight [kN/m3]  \\\n",
       "0             0.0           1.0    0.5     1.0                       20.0   \n",
       "1             1.0           2.0    1.5     1.0                       20.0   \n",
       "2             2.0           3.0    2.5     1.0                       20.0   \n",
       "3             3.0           4.0    3.5     1.0                       20.0   \n",
       "4             4.0           5.0    4.5     1.0                       20.0   \n",
       "\n",
       "   Water unit weight [kN/m3]  Effective unit weight [kN/m3]  \\\n",
       "0                       10.0                           10.0   \n",
       "1                       10.0                           10.0   \n",
       "2                       10.0                           10.0   \n",
       "3                       10.0                           10.0   \n",
       "4                       10.0                           10.0   \n",
       "\n",
       "   Hydrostatic pressure from [kPa]  Hydrostatic pressure to [kPa]  \\\n",
       "0                              0.0                           10.0   \n",
       "1                             10.0                           20.0   \n",
       "2                             20.0                           30.0   \n",
       "3                             30.0                           40.0   \n",
       "4                             40.0                           50.0   \n",
       "\n",
       "   Hydrostatic pressure [kPa]  ...  Vertical total stress [kPa]  \\\n",
       "0                         5.0  ...                         10.0   \n",
       "1                        15.0  ...                         30.0   \n",
       "2                        25.0  ...                         50.0   \n",
       "3                        35.0  ...                         70.0   \n",
       "4                        45.0  ...                         90.0   \n",
       "\n",
       "   Undrained shear strength from [kPa]  Undrained shear strength to [kPa]  \\\n",
       "0                                  NaN                                NaN   \n",
       "1                                  NaN                                NaN   \n",
       "2                                  NaN                                NaN   \n",
       "3                                  NaN                                NaN   \n",
       "4                                  NaN                                NaN   \n",
       "\n",
       "   Undrained shear strength [kPa]  Dr [pct]  Soil type  Unit skin friction  \\\n",
       "0                             NaN      50.0       Sand    API RP2 GEO Sand   \n",
       "1                             NaN      50.0       Sand    API RP2 GEO Sand   \n",
       "2                             NaN      50.0       Sand    API RP2 GEO Sand   \n",
       "3                             NaN      50.0       Sand    API RP2 GEO Sand   \n",
       "4                             NaN      50.0       Sand    API RP2 GEO Sand   \n",
       "\n",
       "   Unit end bearing  API soil description  API relative density description  \n",
       "0  API RP2 GEO Sand                  Sand                      Medium dense  \n",
       "1  API RP2 GEO Sand                  Sand                      Medium dense  \n",
       "2  API RP2 GEO Sand                  Sand                      Medium dense  \n",
       "3  API RP2 GEO Sand                  Sand                      Medium dense  \n",
       "4  API RP2 GEO Sand                  Sand                      Medium dense  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calc.grid.elements.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e7769e3",
   "metadata": {},
   "source": [
    "The parameters in the grid can be prepared for plotting by applying the ``soilparameter_series`` with the name of the parameter under consideration. The x- and z-values can be defined based on the parameter name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "3d29f620",
   "metadata": {},
   "outputs": [],
   "source": [
    "su_z, su_x = calc.grid.soilparameter_series('Undrained shear strength [kPa]')\n",
    "Dr_z, Dr_x = calc.grid.soilparameter_series('Dr [pct]')\n",
    "sigmav_z, sigmav_x = calc.grid.soilparameter_series('Vertical effective stress [kPa]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "29f7e0f0",
   "metadata": {},
   "outputs": [
    {
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         "matches": "y",
         "showticklabels": false
        },
        "yaxis3": {
         "anchor": "x3",
         "domain": [
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         ],
         "matches": "y",
         "showticklabels": false
        }
       }
      },
      "image/png": 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   "source": [
    "parameter_plot = LogPlot(calc.sp, no_panels=2, fillcolordict={'SAND': 'blanchedalmond', 'CLAY': 'wheat'})\n",
    "\n",
    "parameter_plot.add_trace(x=su_x, z=su_z, showlegend=False, mode='lines',name='Su', panel_no=1)\n",
    "parameter_plot.add_trace(x=sigmav_x, z=sigmav_z, showlegend=True, mode='lines',name='With linear', panel_no=2)\n",
    "\n",
    "parameter_plot.set_xaxis(title=r'$ \\sigma_{vo}^{\\prime} \\ \\text{[kPa]} $', panel_no=2, range=(0, sigmav_x.max()))\n",
    "parameter_plot.set_xaxis(title=r'$ S_u \\ \\text{[kPa]} $', panel_no=1, range=(0, 400))\n",
    "parameter_plot.set_zaxis(title=r'$ z \\ \\text{[m]}$')\n",
    "parameter_plot.show()"
   ]
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   "cell_type": "markdown",
   "id": "549b94d4",
   "metadata": {},
   "source": [
    "## Calculation of unit skin friction and unit end bearing\n",
    "\n",
    "Unit skin friction and unit end bearing can be calculated by running the functions for the selected methods at each element.\n",
    "\n",
    "Note that the unit skin friction distribution may be depth-dependent, so at this stage, the pile penetration will need to be introduced.\n",
    "\n",
    "### Setting the pile penetration\n",
    "\n",
    "The pile penetration can be set with the ``set_pilepenetration`` method. In this example, a pile penetration of 18m is selected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "b8432b63",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.set_pilepenetration(30)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d55c0d0",
   "metadata": {},
   "source": [
    "### Calculation of unit skin friction\n",
    "\n",
    "For the calculation of unit skin friction, the equation for the selected method is applied for each element."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "21003bed",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.calculate_unitskinfriction()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a42597b",
   "metadata": {},
   "source": [
    "### Calculation of unit end bearing\n",
    "\n",
    "Similarly, the unit end bearing can be calculated:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "1bed3419",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.calculate_unitendbearing()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdfe66ed",
   "metadata": {},
   "source": [
    "### Unit skin friction and unit end bearing visualisation\n",
    "\n",
    "The unit skin friction and unit end bearing profile can be visualised with the ``groundhog`` ``LogPlot``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "66a87954",
   "metadata": {},
   "outputs": [
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           "#FECB52"
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          "font": {
           "color": "#2a3f5f"
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          "geo": {
           "bgcolor": "white",
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           "landcolor": "white",
           "showlakes": true,
           "showland": true,
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          "hoverlabel": {
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           },
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            "linecolor": "#EBF0F8",
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          },
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            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "#EBF0F8",
           "linecolor": "#EBF0F8",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "#EBF0F8",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "#EBF0F8",
           "linecolor": "#EBF0F8",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "#EBF0F8",
           "zerolinewidth": 2
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         }
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
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         ],
         "side": "top",
         "tickvals": [],
         "title": {},
         "type": "linear"
        },
        "xaxis2": {
         "anchor": "y",
         "domain": [
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         "range": [
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         "side": "top",
         "title": {
          "text": "$ f_s \\ \\text{[kPa]} $"
         },
         "type": "linear"
        },
        "xaxis3": {
         "anchor": "y",
         "domain": [
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         "side": "top",
         "title": {
          "text": "$ q_b \\ \\text{[kPa]} $"
         },
         "type": "linear"
        },
        "yaxis": {
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         "domain": [
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         ],
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         "title": {
          "text": "$ z \\ \\text{[m]}$"
         },
         "type": "linear"
        },
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         ],
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Xzw46QbOn3xLp87+YJ+d7WPuu7j9fmpMONcHbObpVVWirzTfStj/aLH1RmX5X4feY6Nat8R+rmr+iJnhbb1vfe1in6NZi5Zkvn3LfKqFm+FHna63evbRW79X0vXW+raE/+ZHWWK1H+tXhbf0sCX4mt/W172+4bnwPiDMhYBQg1BgBGZ48geDVInddc4Y2+N7a6YsLwsR1dzysO68+I3kXG/MVfblgkfYbfaZOO2a4dh78Q8179wMdPPY8zXzk2qYrufjau9NviTp65D4xX137ne6Sa+9JvxR93GH764G//b0p1OCzYk12G35y+vNEzhz3m/SrjK686QEdNnwP/XCLjdg///+VNMHnUASvEpn5yhsKnmPHjNpXhw3fPR39Ovrza+VQc/eDT2rmq3N18ZlHND3hg7ennjR2mO79y9P68Q83TQev4E8QvQbtcaReePR6Plg4z2+PfA/LE85p2Keff6X7//q0eq/RS6+98Y4efepfOnb0fvrVPjunX9na1u8q/B7jtACtTNNaqAneDt7W956f7H0M6xTdcrSYubVQEwSX4B89gg+Yf/yZF9P/YHTPdWfr0aeeb/NnSRBq2vo50xhKY3pInAYBkwChxsTH4CQK7HnIaTr35FHa8ptX1Dw07Vn97Yl/tvgX3CRed9TXFLxnd8SxF2q7bfqn/yIZ/An+Ujn4l0frtSdvToeK4E/w4Z/rr9tHIw/aLepLSsT8L732ln57xpX6w+TfqaK8XH99/Dm9PHuezhx3iDp16tThfYJFCp5Th/9mr6YPoL7rwSf15D9e0oWnj8FH0jmX3aYFXy/WBaeNVvAXs6NOu1z777GDfrHzth3eZ+VQE3zI+90PPZl+xVHjn+B70FUTjk3/JTb4bJpRw1Z87/nvR5/p5wef1OIVf4n4plFAF8H3+GQtVvC9M/jMuOCtf5l+V+H3mOjWrbVQE7x9ta3vPXv93+lt/k7JOvmuU2uhpvkZghs+BPH+/FMOVWmnTm3+LJn/xddtfq3x7wa+V85sCEQjQKgJ4cot3kJgteOhR552uXbdcWD6rgrBn6tv+bM+//JrnXXcIe14Ve176traOh11+u/V91u9ddbxhzS9zSmVSqn/jiP02F0Xq++3e6cvMniZ6cF779z0l/L2vfLozx7sj8m3/HmVEwV3wPr7n67o8D4BTPCcCt4jHnzuSvAniJ/3Pvy0brviVHykdIy5+sLjtPkm66V9grdbPjjtWU256IQO77NyqAk+Cyr4cNtH/zgp/X2o8S9Nj99zqR57eqbefv8jBXelC/4Ebxs566KbNfXOi6L/RlCkZ+B7fLIWNvhcjeADbZ/585Xp76tt/a7C7zHRrVtroSaIZ21972GdoluLlWfOFmqC44PPDPrFTj/WRuuv0+bPkuBVN239nOmz1urxPSDOhIBRgFCTAyC3tswBKUGH/O2J53XrPY/qhktOTL8lYd9Dz9CEU0enP0m+I/4J3qpy0rkr3tp0/imj1bm0U/p/B68WKS3tpOAT9YNP0D9x7DC9OGuuRh03STMemqyePbp2RK4Wb30KAPBZER7uuP8x3XTZyem3Ph0//mr133i99Ev48VH6TkU/3ur7GvObPbV8eb1Ou2CKeq/eS6cd86sO77NyqKmrW669Rpyuo0bsk/7A9+BDPIOXs983Zbz+8+Fn2vfQM9P/O/g8guAX7Q3XW1vHjTmgQ34v8nrQPEe9JMPP89Y7H2itNXqpV89uqqmt06kTpqTfxhe8IiDT7yr8HhPeOtcRrYWaTN97WKdcZe3HrRxqgt83Zs15WwP6b5gO+8GHDv/66PPTr0jr+6012vxZkunnjP0qmQGB+AQINTlYc2vLHJASdEjwL4jnXX67Hpo2I/2vtcEHUx4/5oCmV5Ek6FJjuZTgX7APGHP2KucKPoPm8N/smb597snnXadnZ76uqsoKnXPiiPStvDvqn+D90M+//EbT7bnxUTrOBJ/jE3zYa/CcGrLdAE0644j0XzjwkYI7u5xy/nXpW3QHfwb075eOw8FL6Tu6z7Cx52rc6P21zYBNmr6lBK8qOOfSWxX8JTb4AM/gg4T7rbfiM8WCPfb7G+5Lvy0z+NDqS84aq+7dqjrqtyOXx93R96ALYp6TBD9PgrcTB6/QXFZTl/4Ho+BnbLeulcr0uwq/x+QJnsOw4G3gW+86Rq88doPKyjo3jWjrew/rlAOq0yFX3Hi/Onfu3HTXpyC4BPE+eLVT8BwKfkcN7q7YeFfSTD9LMn3N6XKZBoHIBQg1WYi5tWXkezCyEwT/etWppKTFD+LITlYEEwdv7auqLO+wQSvbEuIjBW+hq29ItfrBrvhIwV8AglepBR/GvfIffFZ9hi1aXN1qhGloSGlZTU36l3L++AmwB/0sw8wU/B4Z7PUe3bqmvz+s/CfT7yr8HhNG2n5spu89rJPdN98Zgn8gqq9vaDPat/WzJDhfpq/lez2MQyAuAUJNFmlubRnXVuQ8CCCAAAIIIIAAAggggAACCCBAqMmyB7Ld2nL+1zWJ30W9e5Yn/hqjusAvvq5RKqrJmRcBBBBAoKAEqio6q6q8tKCu2etil9bUa8my5V7TMQ8CCCCAQIELdOS/IxbC0hFqsqxStltb/t9vd9HWP/g0sWv9/Cvf1m2/fzSx1xflhX2xsEapVipNl89nq8eMS1S75mZaOOj4KC+BuRFAAAEEEiTQUUPN0tp6LVnqG2m2+6BOi1LSs98pU/eSBC0yl4IAAgggkJMAoSYnpnY7iFCThT7brS0n3/wDHTni1XZbwGwnvuLGATpm1EvZDivKrzeGmjV6lqvF75AfvyY9dqHUZ3Np6ClF+dhzeVA1dQ2qratX96pVP08jl/HFfkzt8gYtq6lXj674tLbWy+tTWry0Tr26dSn2rZDX4ws+y2fhkjqt1h2f1gAbUtKCRTVavUfHfcVnXhsrz0GNoaayvFRdK/73Aap5TpcetsmcxVrYIL25aTf1WPWjVyxTd6ixwSudGlIpt3XpUHgRP9jgVfP8RTZi5Dymr66pV/AvsUF45w8CxSxAqMlhdTPd2pJQkwNgOx1CqMkMT6jJ7EOoyexDqMnsQ6jJ7EOoifcHI6EmXu8wZyPUhNGK91hCTbzeuZ6NUJOrFMcVugChJocVzHRrS0JNDoDtdAihhlBj2XqEGkKNZf8Qagg1lv3jPZZQ4y3qNx+hxs/SeyZCjbeoz3yEGh9HZkm+AKEmxBq1dmtLQk0IwJgPJdQQaixbjlBDqLHsH0INocayf7zHEmq8Rf3mI9T4WXrPRKjxFvWZj1Dj48gsyRcg1BjX6GcH7qu1+ywxzhLd8A8+7arH7rw/uhMkeOasoSbfax92g1RWme/oxIzjrU+Zl4JQQ6ixPFkJNYQay/7xHhtFqNl4zmItavC+0mjmm7dpN3VN6OfoEGqiWXOPWQk1Hor+cxBq/E2ZMZkChBrjunDXJyNghMMJNZlxCTWEGsvTj8+oyaxHqCHUWJ5f3mOjCDWNHybsfa1RzEeoiUK1+Ock1CRzjQk1yVwXrspfgFBjNOWtT0bACIe3GWryPeedh0p1SyVeUZOvYEGN4xU1mZeLUEOosTyh+TBhi174sVGEmvBXEf+IDecs1pIGiVATv30xnJFQk8xVJNQkc124Kn8BQo3RlFBjBIxwOKEmMy6vqMnsQ6gh1Fi+PfGKmsx6hBrL7go/llDDW5/C7xpGEGqSuQcINclcl/yuaqmkVyTV5ji8QtLAHI8t/MMINcY1JNQYASMcTqgh1Fi2F6GGUGPZP4QaQo1l/3iPJdQQarz3VEeYj1CTzFUm1CRzXfK7qoWSdpL0Qo7Dh0n6Y47Htn5YKpXSwkXV6tq1Qp1LS01zrTz4s/kL9NSzL+nAvYa4zEuoMTISaoyAEQ4n1BBqLNuLUEOosewfQg2hxrJ/vMcSagg13nuqI8xHqEnmKhNqkrku+V1VvKHmprv+pmtufSh9qdVLl2m/3X+q8SeMyO/SWxn12pvv6oTxV2vqnRe5zEmoMTJy1ycjYITDIws1+VzzoMOkfj/NZ2RkY3jrU2ZaQg2hxvLkI9QQaiz7x3tsRw01G81ZrMUFcmeqtzfrpsoS75VnPosAocaiF91YQk10tvHPHF+oefv9j7TnIafpL7ddoPW+20eLFlfrs/lfaYPvre32sAk1bpQ+E3HXJx/HKGZJVqgZLfXbIYqHmfechBpCTd6bRxIfJpxZj1BDqLE8v7zHdtRQ0/hhwt6eUcxHqIlC1TYnocbmF9VoQk1Usu0xb3yh5p8vztGJ516j6ff/XqWlnVo82A8/ma9zL7tVL86ap+7dKnX4r/fUAXvumD7muLMna+sfbKLb75umz7/4Wnv+bJCOOXRf9ezeVbW1dbromrv050efTY/bdceBevyZF3lFTXtspdbOyVufkrISq16He6jJ56HOmCL9e7o0iFCTD197juEVNZn1CTWEGsvzkw8TtuiFH9tRQ014qfhHbDB7sZamJEJN/PbZzkioySbUPl8n1LSPezRnjS/UBG912mXYidpi0w107Oj9tOF632l6SEuql+n5l+ZomwHf1+y33tPIcRP14tTrVVHeRcOPOl8ffTpfZ447ROt+51s65fzrNXzfodrjZ4N0271T9YcHHk+/faqkU4nGX3KL6usbCDXRbJbwsxJqwpvFNYJQk1maV9Rk9iHUEGos36t4RU1mPUKNZXeFH0uoCW8W1whCTVzS4c9DqAlvFscIQk0cynGdI75QEzyiTz7/UlfccL8enPqshmw3QGeMO0Rr9e7V9GDr6pbriwULtf/os3TVhGO15aYbpEPNNgM20TGj9k0fF7yy5o1572vCqaP166MnaPttNteYX++R/loQbYJ4w2fUxLV/spyHUJOQhWjlMgg1hBrL7iTUEGos+4dQQ6ix7B/vsYQab1G/+Qg1fpbeMxFqvEV95iPU+DgmY5Z4Q03jY/74sy913uW36csFi3Tn1WfotTfe0fV3PKxXZv9bG/f7rp57YbZuv/J0bbX5hulQ838H/lw7D/5hevhD057V9Bmv6NKzj0y/Que0Y4brp9tumf7av15+U2dMupFQk4zNJRFqkrISq14HoYZQY9mdhBpCjWX/EGoINZb94z2WUOMt6jcfocbP0nsmQo23qM98hBofx2TM0j6hJnjs//3oM/384JP0ymM3aJeDT9RBew3RqGG/UEMqpUF7HKnrJh3fFGqCV8wMHrjFKqHmwDHjtdfPt9fBewe3GF8RcSbf/GdCTTI2l8Rdn5KyEgkPNfkw9d1C2vnkfEbmNIa3PmVmItQQanJ6IrVxEKGGUGPZP95jCTXeon7zNYYavxmjm6mjfY4OoSa6vWSZmVBj0Uva2PhCzX8+/FRlZWXqs9bqamhI6bb7puqBv/5dD95yvrbZ7QhdfOYR6Rjz4NR/6HcTb2zxipq2Qs2l192jl16bl351TfABxadfOEXv/ucTQk1Sthl3fUrKShBqwq4EoYZQE3bPND+eDxPOrEeoIdRYnl/eYwk13qJ+8xFq/Cy9ZyLUeIv6zEeo8XFMxizxhZqp02em7+BUVVmh4IOFv7/hujr/lEO18Qbr6NZ7p2rS5DvTX9tysw3UqaRERxyylwb0X/HWp+ah5uFpM/TUjJfTcWbB14vTcz7/8htpzl/tM1RPP/cKoSYZm4u3PiVlHVq7jkS89SkfoI9mSY9PlHhFTT56bmN4RU1mSkINocbyZOPDhC164ccSasKbxTViaU19+qX2XSs6x3XK0OfpqG/PItSE3iqxDCDUxMIc00niCzXBA1peX6+Fi6pVWVGuyoouLR5jTW1d+nbb3btVhX7swV2jyjqXqkuXstBjMw0oSaVSKdcZO9hkfEZNchecUJN5bXhFTWYfQg2hxvLdjVfUZNYj1Fh2V/ixhJrwZnGNINTEJR3+PISa8GZxjCDUxKEc1zmWSnpFUm2OJ6yQNDDHYwv/MEKNcQ0JNUbACIcTagg1lu1FqCHUWPYPoYZQY9k/3mMJNd5pwbsNAAAgAElEQVSifvMRavwsvWci1HiL+sxHqPFxZJbkCxBqjGtEqDECRjicUEOosWwvQg2hxrJ/CDWEGsv+8R5LqPEW9ZuPUONn6T0TocZb1Gc+Qo2PI7MkX4BQY1wj7vpkBIxweMGGmg9flZ6YlL/MsBukssqs43nrU2YiQg2hJuuTKMMBhBpCjWX/eI8l1HiL+s1XSKHG71FHN9M7m3VTRYnP/IQaH0fvWQg13qLMl1QBQo1xZbjrkxEwwuEFG2oaP0w4XxtCTb5yLcYRagg1lo1EqCHUWPaP91hCjbeo33yEGj/LYKaP+ndzm5BQ40bpOhGhxpWTyRIsQKgxLg5vfTICRji8YENNviZ3HirVLZUINfkKEmpCyHHXp8xYhBpCTYinU+SHEmoiJ877BIUQavJ+cDEOXG/2YtWkCDUxkrfbqQg17UbPiWMWINQYwQk1RsAIhxNqMuPy1qfMPryiJrMPoYZQY/n2zV2fLHrhxxJqwpvFNYJQ4yNNqPFxLIRZCDWFsEpco4cAocaoSKgxAkY4nFBDqLFsL0INocayf3hFTWY9Qo1ld4UfS6gJbxbXCEKNjzShxsexEGYh1BTCKuV2jfXLlumrN99UQ11dTgNKu3TRGltumdOxxXAQoca4ioQaI2CEwwk1hBrL9iLUEGos+4dQQ6ix7B/vsYQab1G/+Qg1PpaEGh/HQpiFUFMIq5TbNdYtXqwnRo7Ul7Nn5zRg3d1203YXXZTTsdkOql66TFKJqirL04e+8OpcLa+v14+32jTb0Ni+TqgxUnPXJyNghMM7bKjJx3TQYVK/n+YzsmjHEGoINZbNTagh1Fj2j/dYQo23qN98hBofy76vL/aZKIZZPD/wOIbLTdwpCDWJW5K8LyjuUJNKpXTvw9N17e0P6dPPv0pf93f6rKnbrzxd9zz0lGrr6nTcmAPyfjzeAwk1RlHu+mQEjHA4oSYE7qDRUr8dQgwo/kMJNYQayy4n1BBqLPvHeyyhxlvUbz5CjY9l4ytqfGaLdhZCjc2XUGPzS9LouEPNTXf9TXfc/5guOuMI/WCzfkoppTlz39MWm26gq276E6EmSZvD41p465OHYjRzdLhQE5Ix+DDhTs9NUdl7f5cINavoEWoINSGfUi0OJ9QQaiz7x3ssocZb1G8+Qo2fpfdM3rfnbnzVD6HGtlKEGptfkkbHGWqCtzptvevhunbi8Ro8cPNVGJqHmg8/ma9zL7tVL86ap+7dKnX4r/fUAXvuqAlX/EHr9F1Tv97vZ+nxNbV12n/0Wbr07CPVb7213Wl5RY2RlFBjBIxwOKEmMy6hJrMPoYZQY/n2RKgh1Fj2j/dYQo23qN98hBo/S++ZCDXeoj7zEWp8HJMwS5yh5o1572u/0Wdp1hM3qbS0U8ZQs6R6mZ5/aY62GfB9zX7rPY0cN1EvTr1eM16YrYuvuUt/u2NievzTz72qCVfcoUf/OEklJSXupIQaIymhxggY4XBCDaHGsr0INYQay/4h1BBqLPvHeyyhxlvUbz5CjZ+l90yEGm9Rn/kINT6OSZglzlDz7MzXdcr51+mZP1/Z6kNv7a1PdXXL9cWChelXzVw14VhtuuG6GrTnUbr58pPVf+P1dMqE67XeOn005td7RMJJqDGyEmqMgBEOJ9QQaizbi1BDqLHsH0INocayf7zHEmq8Rf3mI9T4WXrPRKjxFvWZj1Dj45iEWeIMNe9/8Kl2G36yXnj0elVWdFnl4TcPNa+98Y6uv+NhvTL739q433f13Auz0x84vNXmG+qSa+9RfX29jh61r37088P0yB8m6btrrxUJJ6HGyMpdn4yAEQ4n1IQINfmsQ98tpJ1PzmdkQYwh1BBqLBuVUEOosewf77GEGm9Rv/kINX6W3jNFFWq8rzOK+ZL8OTqEmihWvH3mjDPUBLfe3nKnUbry/N9qyHYDMoaaIfuP00F7DdGoYb9QQyqlQXscqesmHZ8ONfPe/UAHjz1P559yqG67d6ruuOr0yPAINUZa7vpkBIxwOKGGUGPZXoQaQo1l/xBqCDWW/eM9llDjLeo3H6HGz9J7JkKNt6jPfIQaH8ckzBJnqAke7633Tk3f3emqCb/VVv03VFlZZwUfHLz2t3s33fVp3GH7a5vdjtDFZx6hwQO30INT/6HfTbyx6RU1wTwHjhmvBQsXa/Svdtd+u/80MkpCjZGWtz4ZASMcTqjJHmpq6+rVvaos3Cp8NEt6fKLEK2rCuRXZ0cvrU1q8tE69uq368tEie6h5PRxCDaEmr40T0SBCTUSwDtMSahwQI5rCO9REdJmu0xbCnakINa5L3q6TxR1qggd73e0P66+PP6e33/8o/dg3WLevHrp1gibf/Kf0XZyOG3NAOuhMmnynqiortOVmG6hTSYmOOGQvDei/YXrMPQ9P1/hLbtGMhyerZ/eukRkSaoy0hBojYITDCTWEGsv24hU1mfUINZl9CDWEGsv3H++xhBpvUb/5CDV+lt4zEWq8RX3mI9T4OCZhlvYINY2Pe+Hi6nSA6da1slWKINrU1tape7eqVb5+y92PatYbb6dvyx3lH0KNUZdQYwSMcDihhlBj2V6EGkKNZf8Qagg1lv3jPZZQ4y3qNx+hxs/SeyZCjbeoz3yEGh/HJMxSv2yZvnrzTTXU1eV0OaVdumiNLbfM6dgoDlq0uFr//egzHfLbC3X9Rcc3vcIminMFcxJqjLKEGiNghMMJNYQay/Yi1BBqLPuHUEOosewf77GEGm9Rv/kINX6W3jMRarxFfeYj1Pg4Mkt4gQuv+qNeeHWuDtxrR+2/+w7hJwg5glATEmzlw7nrkxEwwuGEmohCzYevSk9Myn/lht0glbX+MsP8J/UfSagh1Fh2FaGGUGPZP95jCTXeon7zEWr8LL1n6sihxtsyivmSfGeqKB4vc3Y8AUKNcc2565MRMMLhhJqIQk3jhwnnu3aEmnzlEjWOz6jJvByEGkJNkp6whJokrUbLayHUJHdtCDXJXZvgygg1yV4frs4uQKgxGvLWJyNghMMJNRGFmnzX7M5DpbqlEqEmX8FEjSPUEGosG7IhJS1YVKPVe5RbpmFsjgKEmhyh2uEwQk07oOd4yo4YanKkadfDCuHOVO0KxMmLRoBQY1xKQo0RMMLhhBpCjWV78danzHqEGkKN5flFqLHohR9LqAlvFtcIQk1c0uHPQ6gJbxbHCEJNHMqcIwkChBrjKhBqjIARDifUEGos24tQQ6ix7B/e+pRZj1Bj2V3hxxJqwpvFNYJQE5d0+PMQasKbxTGCUBOHMudIggChxrgKhBojYITDCTWEGsv2ItQQaiz7h1BDqLHsH++xhBpvUb/5CDV+lt4zEWq8RX3mI9T4ODJL8gUINcY14q5PRsAIhxNqEhpq8lnzQYdJ/X6az8i8xxBqCDV5bx5JhBpCjWX/eI8l1HiL+s1HqPGz9J6JUOMt6jNfY6jxmS3aWfjA42h9i312Qo1xhbnrkxEwwuGEmmIKNaOlfjtEuFtWnZpQQ6ixbDhCDaHGsn+8xxJqvEX95iPU+Fl6z0So8Rb1mY9Q4+PILMkXINQY14i3PhkBIxxOqElYqMlnrWdMkf49XRpEqMmHL8oxfJhwZl1CDaEmyudf2LkJNWHF4jueUBOfddgzEWrCisVzfHVNvZRKqaqiczwnzOMsvD0rDzSGrCJAqDFuCkKNETDC4YQaQo1le/GKmsx6hBpCjeX5xYcJW/TCjyXUhDeLawShJi7p8Och1IQ3i2MEoSYOZc6RBAFCjXEVCDVGwAiHE2oINZbtRagh1Fj2D6+oyaxHqLHsrvBjCTXhzeIaQaiJSzr8eQg14c3iGEGoiUOZcyRBgFBjXAVCjREwwuGEGkKNZXsRagg1lv1DqCHUWPaP91hCjbeo33yEGj9L75kINd6iPvMRanwcmSX5AoQa4xpx1ycjYITDCTVFFGry2Sd9t5B2PjmfkekxhBpCTd6bh7s+ZaXjFTVZiVwPINS4crpORqhx5XSdjFDjyuk2WSGFGrcHHdFE3JUqIlinaQk1ISCXVC9T16qKFiO461MIwJgPJdQQagg10T3p+IyazLa8oiazD6EmuudmazMTauL1DnM2Qk0YrXiPJdTE653r2Qg1uUplP45Qk92oPY8g1DTTn/v2fzXurKu0+9BBGnvIXk1f+fjTL3TqBVM0e+57Wr1Xd5181MEast2A9Nd561N7bt/M5ybUFEGoyWd7fTRLenyixCtq8tHLeQyhhlCT82Zp5UBCjUUv/FhCTXizuEYQauKSDn8eQk14szhGFEKoicPBeo7gzlSEGqtitOMJNd/4PvLk85pwxR36Tt+1NHjgFi1CzXFnT1aftdbQuDH7a9acdzTmpEs07a6LtFrP7oSaaPenaXZCDaGGV9SYnkIZBxNqCDWW3UWoseiFH0uoCW8W1whCTVzS4c9DqAlvFscIQo2PMqHGxzHKWQg13+i+9No89V69hx742zPq0qWsKdQsr6/XljuN0vT7L9eaa/RKHz1y3EQN33eohmy/FaEmyt1pnJtQQ6gh1BifRBmGE2oINZbdRaix6IUfS6gJbxbXCEJNXNLhz0OoCW8WxwhCjY8yocbHMcpZCDUr6V4+5b4Woeaz+Qu0437H6vWnblZJSUn66DMm3aRN+q2jX+0zlFAT5e40zk2oIdQQaoxPIkJN3oB8Rk1mOkJN3lsrr4GEmrzYYhlEqImFOa+TEGryYot8EKHGh5hQ4+MY5SyEmiyhZt67H+jgsedp5iPXNh158bV3q7xLmY4euY+461OU29M2d2OoqazorBWJjT/NBYK/SNbXp9SlrFNRwZR+PEvlf7+4qB4TD6Z1gfq+A1QzeFwieVIpqaauXhVdShN5fe19USlJy2rqVVker09Z504qK+14PxEaQ0368Xcuru/57b2XrecPXp2YSqVYFytkBOODIFAV8/eoCB5GZFO+XpvSL99fFtn8TBy9AJ9RE72x5QyEmiyh5ssFizT4l0frtSdvVqdOK365+93EG7X+un008qDdtOugfbRu3SLLGkQ69r2y7np0xgORniOpkzeFmvJSQk0rixT8cljf0KDysnj/ohT1fin95DVCTdTICZm/vs+Wqhl8XEKupuVlNKRSqqltiD1EJBKjlYsKQtay2uWqLO8c6yWXlZV28FBTorJSQk2smy7LyeqWNygIl10IaElalvS1VC9brqqKeL9HJQ4hwwWlQ81/agrpkrnWlQQINcneEoSaLKEm+FeO/juO0GN3Xay+3+6dPnr4Uefr4L131m47DdThWw/VT6o/SuwqP911bV33r2mJvb4oL4y3PmXWralrUG1dvbpXlUW5DAU7d+3yhvS/+Pfoik9ri9iun1HzwcvSkxdL3xkgDTkhkXuMtz5lXhbe+hTvtuWtT/F6hzkbb30KoxXvsbz1KbP3rGUN+vm/q7VFRSc92q8qtsXhrU+xUXOidhYg1GQJNcGXx196q8o6l+rEscP04qy5GnXcJM14aLJ69uhKqGnnDZzp9IQaQo1lexJqMusRajL7EGoINZbvP95jCTXeon7zEWr8LL1nItQQarz3FPMhEEaAULOS1hU33q/OnTu3uD33V18v0snnXadnZ76uqsoKnXPiCO06ZGB6JK+oCbPd4j2WUEOosew4Qg2hxrJ/CDWEGsv+8R5LqPEW9ZuPUONn6T0ToYZQ472nmA+BMAKEmhBaS6qXqaqyvOnuT4SaEHjtcCihhlBj2XaEGkKNZf8Qagg1lv3jPZZQ4y3qNx+hxs/SeyZCDaHGe08xHwJhBAg1YbRaOXa7wcPUsz65H6S1oHMXzfj7XcZHWZjDCTWEGsvOJdQUQKjJdIkDR0gb72zZAqaxhBpCjWkDOQ8m1DiDOk5HqHHEdJ6KUJMZ9LVlDdrl39UtDlq7rEQzN+7qvBItp+MzaiLlZfIECRBqjIvBXZ+MgBEOJ9QQaizbi1BT6KHm/6SNh1q2gGksoYZQY9pAzoMJNc6gjtMRahwxnaci1GQGbfww4eZHEWqcNyHTdWgBQo1x+fmMGiNghMMJNYQay/Yi1CQ41GS6tOdvkeY+Jg0k1Fj2f9RjuetT1MIt5yfUxOsd5myEmjBa8R5LqMnd+8O6lLaeu0SEmtzNOBKBbAKEmmxCWb5OqDECRjicUEOosWwvQg2hxrJ/eEVNZj1CjWV3hR9LqAlvFtcIQk1c0uHPQ6jJ3YxQk7sVRyKQqwChJlepNo4j1BgBIxxOqCHUWLYXoYZQY9k/hBpCjWX/eI8l1HiL+s1HqPGz9J6JUJO7KKEmdyuORCBXAUJNrlKEGqNU/MMJNYQay64j1BBqLPuHUEOosewf77GEGm9Rv/kINX6W3jMRanIXJdTkbsWRCOQqQKjJVaqN47jrkxEwwuGEGkKNZXsRago81LR1+Z3LpYNvsmyNnMYSagg1OW2UmA4i1MQEncdpCDV5oMU0hFCTO3RjqGk+orJEenuzbrlPkuOR3PUpRygOK3gBQo1xCbnrkxEwwuGEGkKNZXsRagg1lv1DqCHUWPaP91hCjbeo33yEGj9L75kINbmLthZqqjpJ/96UUJO7Ikci0FKAUGPcEXxGjREwwuGEGkKNZXsRago01LR12ctrpD+OlHhFjeVp4TaWDxN2o8xpIkJNTkztchChpl3YczopoSYnplUOqm6Q+s1ZLEJNfn6MQqBRgFBj3AuEGiNghMMJNYQay/Yi1BBqLPuHV9Rk1iPUWHZX+LGEmvBmcY0g1MQlHf48hJrwZsEIQk1+boxCYGUBQo1xTxBqjIARDifUEGos24tQQ6ix7B9CDaHGsn+8xxJqvEX95iPU+Fl6z0SoyU+UUJOfG6MQINQ47wFCjTOo43SEGkKNZTsRagg1lv1DqCHUWPaP91hCjbeo33yEGj9L75kINfmJEmryc2MUAoQa5z3AXZ+cQR2nI9QQaizbiVBTZKGmvlb6w4jMD2rwUdJ621q2TdNYQg2hxmUjOU1CqHGCjGAaQk0EqE5TEmryg1zSIG04Z/Eqg9/ZrJsqSvKbs/ko7vpkN2SGwhDgrU/GdeKuT0bACIcTagg1lu1FqCmyUNP4YcKZHhahxvKUCTWWz6gJxWU+mFBjJoxsAkJNZLTmiQk1+RE2vqJm5dEf9fe5AxShJr91YVThCRBqjGvGW5+MgBEOJ9QQaizbi1BTZKEm08N55irp3eckQo3lKRNqLKEmFJf5YEKNmTCyCQg1kdGaJybUmAnTE6w3e7FqUhKhxseTWTqOAKHGuNaEGiNghMMJNYQay/Yi1BBqLPuHtz5l1iPUWHZX+LGEmvBmcY0g1MQlHf48hJrwZq2NINT4ODJLxxMg1BjXnFBjBIxwOKGGUGPZXoQaQo1l/xBqCDWW/eM9llDjLeo3H6HGz9J7JkKNjyihxseRWTqeAKHGuOaEGiNghMMJNYQay/Yi1BBqLPuHUEOosewf77GEGm9Rv/kINX6W3jMRanxECTU+jszS8QQINcY1565PRsAIhxNqCDWW7UWo6UihZrL07oy2H3C/HaRBo0NtJ0INoSbUhon4YEJNxMCG6Qk1BryIhxJqfID7vr7qHaBe3qSrvtU5v1tA8WHCPuvCLMkXINQY14i7PhkBIxxOqCHUWLYXoaYjhZpvPky4rYe84Q7StoQay/Np5bF8Ro2nZva5CDXZjdrrCEJNe8lnPy+hJrtRLkc0vqKm+bGEmlzkOKajCxBqjDuAtz4ZASMcTqgh1Fi2F6GmA4Wath7qvOnSc1MkQo3lqdTqWEKNO2nGCQk18XqHORuhJoxWvMcSavy9B7y5RJ8uT4lQ42/LjMUnQKgxrimhxggY4XBCDaHGsr0INYQaEWosT6GMYwk1kdG2OjGhJl7vMGcj1ITRivdYQo2/N6HG35QZi1eAUGNcW0KNETDC4YQaQo1lexFqCDWEGsszKPNYQk10tq3NTKiJ1zvM2Qg1YbTiPZZQ4+9NqPE3ZcbiFSDUGNeWUGMEjHA4oYZQY9lehBpCDaHG8gwi1ESnF35mQk14s7hGEGrikg5/HkJNeLNsIwg12YT4OgL/EyDUGHcDd30yAkY4nFBDqLFsL0INoUbznpKeu6FtiG9vJv3stFa/zl2fCDWW7z/eYwk13qJ+8xFq/Cy9ZyLUeItKjaGm+cxPblilTco75Xwy7vqUMxUHFrgAoca4gNz1yQgY4XBCDaHGsr0INYSaplfUtEVBqMn7KcZbn/Kmy2sgoSYvtlgGEWpiYc7rJISavNgyDmot1Dy1YZU2JtT4YzNjwQsQaoxLyFufjIARDifUEGos24tQQ6hpU+CT2dK0CRKhJu+nGKEmb7q8BhJq8mKLZRChJhbmvE5CqMmLLedBO86r1tyaBhFqcibjwA4mQKgxLjihxggY4XBCDaHGsr0INYQaQo3lGZR5LKEmOtvWZibUxOsd5myEmjBa8R5LqInWm1ATrS+zF74Aoca4hoQaI2CEwwk1hBrL9iLUEGoINZZnEKEmOr3wMxNqwpvFNYJQE5d0+PMQasKbhRlBqAmjxbEdUYBQY1x1Qo0RMMLhhBpCjWV7EWoINYQayzOIUBOdXviZCTXhzeIaQaiJSzr8eQg14c3CjCDUhNHi2I4oQKgxrjp3fTICRjicUEOosWwvQg2hpu1QM0eadn7bQGtupPpdztTCJXVarXsXyzYs2rG89SnepSXUxOsd5myEmjBa8R5LqInWe4d51XqrpqHFSe5br1KDupZmPDF3fYp2XZg9OQKEGuNacNcnI2CEwwk1hBrL9iLUEGraDjXffJhwWwcQarI+9Qg1WYlcDyDUuHK6TkaoceV0nYxQ48q5ymSNr6hp/oX716vUtoSaaOGZvWAECDXGpeKtT0bACIcTagg1lu1FqCHUhN4/n78lPTJeItRkpSPUZCVyPYBQ48rpOhmhxpXTdTJCjStnxsn2fXepnltSL0JNfOacKfkChBrjGhFqjIARDifUEGos24tQQ6gJvX8INTmTEWpypnI5kFDjwhjJJISaSFhdJiXUuDDmNAmhJicmDupgAoQa44ITaoyAEQ4n1BBqLNuLUEOoCb1/CDU5kxFqcqZyOZBQ48IYySSEmkhYXSYl1Lgw5jQJoSYnJg7qYAKEGuOCE2qMgBEOJ9QQaizbi1BDqAm9fwg1OZMRanKmcjmQUOPCGMkkhJpIWF0mJdS4MOY0CaEmJyYO6mAChBrjgnPXJyNghMMJNYQay/Yi1BBqQu+fz+dJj5zd9rC1fyDtdGLoaYtxAKEm3lUl1MTrHeZshJowWvEeS6iJz3ufd5fqn0vqW5zwxu9WaNcenVe5CO76FN+6cKb2FSDUGP2565MRMMLhhBpCjWV7EWoINaH3T+MratoaSKhpkiHUhN5dpgGEGhNfpIMJNZHymiYn1Jj4Qg1ufEVN80GEmlCEHFyEAoQa46Ly1icjYITDCTWEGsv2ItQQaiz7p74hpYVL6rRa9y7Sh69IT1wkEWoINZZNZRhLqDHgRTyUUBMxsGF6Qo0BzzB01H+W6ZGFy0WoMSAytCgECDXGZSTUGAEjHE6oIdRYthehhlBj2T+Emsx6vKLGsrvCjyXUhDeLawShJi7p8Och1IQ38xhBqPFQZI5iECDUGFeRUGMEjHA4oYZQY9lehBpCjWX/EGoINZb94z2WUOMt6jcfocbP0nsmQo23aG7zEWpyc+Ko4hcg1BjXmFBjBIxwOKGGUGPZXoQaQo1l/xBqCDWW/eM9llDjLeo3H6HGz9J7JkKNt2hu8xFqcnPiqOIXINQY15i7PhkBIxxOqCHUWLYXoYZQY9k/LUPNq9ITk7JPN/RUqU//7McVwRG89SneRSTUxOsd5myEmjBa8R5LqInXu/FsjaGm+dknrV2u4auVpf8v7vrUPuvCWeMXINQYzbnrkxEwwuGEGkKNZXsRagg1lv3T6itqsk1IqMkmxNfzFCDU5AkXwzBCTQzIeZ6CUJMnnHFYq6Gmb7mGr06oMdIyvMAECDXGBeOtT0bACIcTagg1lu1FqCHUWPZPi1CTbaLHLpA+fl0i1GST4ut5ChBq8oSLYRihJgbkPE9BqMkTznHYSR/V6I4v6zSJUOOoylSFIkCoMa4UocYIGOFwQg2hxrK9CDWEGsv+IdRk1uOtT5bdFX4soSa8WVwjCDVxSYc/D6EmvJn3CEKNtyjzFZIAoca4WoQaI2CEwwk1hBrL9iLUEGos+4dQQ6ix7B/vsYQab1G/+Qg1fpbeMxFqvEXDz0eoCW/GiOIRINQY15JQYwSMcDihhlBj2V6EGkKNZf8Qagg1lv3jPZZQ4y3qNx+hxs/SeyZCjbdo+PkINeHNGFE8AoQa41py1ycjYITDCTWEGsv2ItQQaiz7J1youVD6+LXsp+u2lrTPZdmPK4AjeOtTvItEqInXO8zZCDVhtOI9llATr3drZ2sMNc2/dkLvMh3eq1RVFZ3b/wK5AgQiFCDUNMNtaEhp0ZJq9ezetVXyJdXL1LWqosXXuOtThLvTODWhhlBj2UKEGkKNZf+ECzXffJhwthMSarIJ8fU2BAg1yd0ahJrkrg2hpv3XhlDT/mvAFbSfAKFG0vL6el1/+8O6+e5Hm1Zi/AkjtNtOA9P//fGnX+jUC6Zo9tz3tHqv7jr5qIM1ZLsB6a/x1qf227zZzkyoIdRk2yOZvk6oIdRY9k+oUJPtRIs/kx4YJxFqsknxdUJNwe0BQk1yl4xQk6y1ueDTWl35ea14RU2y1oWriU6AUCMpeCXNbfdO1a5DBupba66mqdP/pePOvlovTZui8i5lOu7syeqz1hoaN2Z/zZrzjsacdImm3XWRVuvZnVAT3d40z0yoIdRYNhGhhlBj2T+Emsx6vPXJsrvCj+UVNeHN4hpBqIlLOvx5CDXhzaIcQaiJUpe5kyhAqGllVaqXLtPWux6up+67XKuv1l1b7jRK0++/XGuu0St99MhxEzV836Easv1WhJok7pbGb+kAAB0ZSURBVOpvrolQQ6ixbE9CDaHGsn8INYQay/7xHkuo8Rb1m49Q42fpPROhxlvUNh+hxubH6MITINS0smbTZ7yicy67VU/ee5k+m79AO+53rF5/6maVlJSkjz5j0k3apN86+tU+Qwk1Cd7zhBpCjWV7EmoINZb9Q6gh1Fj2j/dYQo23qN98hBo/S++ZCDXeorb5CDU2P0YXngChZqU1+3LBIu03+kyddsxw7Tz4h5r37gc6eOx5mvnItU1HXnzt3em3RB09ch9x16fkbvrGUFNZ0VkrEht/mgsEf5Gsr0+pS1knYFoRCHyW16dUjk+r+yN460ptXb0qupSyf1oRSKWkGiefkiWfq/Ivx+fkXPvjMVq+7nY5HdueB6UkLaupV2V5vPunrHMnlZV2vJ8IjaEm/fg78z2/Pff+yucOfs6kUinWJUmL8s21VNfUqyrm71EJZEjMJV0yv07XfLW8xfWM7FWq09bskphrLLQLYX8ne8UINc3Wp3ppjUYce6G226a/jhm1b/orQbgZ/Muj9dqTN6tTpxW/3P1u4o1af90+GnnQbuKuT8nd4E2hpryUUNPKMgW/HNY3NKi8LN6/KCV3x7S8snSoWd6gckJE66GmIaXgVUeEmtZ3dEMqpZraBpcQkQ41fz0hp6dO7cDDtXzdbXM6tj0PCkLWstrlqiyP9/aqZWWlHTzUlKislFDTnnt/5XPXLW9QEC67ENCStCzpa6letpxbQCdoVS7+YrmubS3U9C5L0FUW1qVwi/Nkrxeh5pv1qa2t01Gn/159v9VbZx1/SNPbnIJ/5ei/4wg9dtfF6vvt3umjhx91vg7ee+f0XaG461NyNzhvfcq8NjV1DelXRHSv4gdca1K89Snz/glC3+KlderVjX/Jak3K9a1PuXyb/cfV0jvPStuPldZP/itq+DDhXBbV7xje+uRn6T0Tb33yFvWbj7c++Vl6zhS80ummr5Zrwvw6jeldprO+Xe45PXMhkBgBQs03t+c+6dwVb206/5TR6vzNvzZ16tRJpaWdNP7SW1XWuVQnjh2mF2fN1ajjJmnGQ5PVs0dXQk1itvKqF0KoIdRYtiehhlBj2T+Emsx6hBrL7go/llAT3iyuEYSauKTDn4dQE94sjhGEmjiUOUcSBAg1kmbPfU8HjDl7lfUIPoPm8N/sqa++XqSTz7tOz858XVWVFTrnxBHpW3kHf3hFTRK2cevXQKgh1Fh2J6GGUGPZP4QaQo1l/3iPJdR4i/rNR6jxs/SeiVDjLeozH6HGx5FZki9AqAmxRkuql6mqsrzpbVGEmhB47XAooYZQY9l2hBpCjWX/EGoINZb94z2WUOMt6jcfocbP0nsmQo23qM98hBofR2ZJvgChxrhG3PXJCBjhcEINocayvQg1hBrL/ok91DxztfTus9kvec2NpF3Pyn5cxEfw1qeIgVeanlATr3eYsxFqwmjFeyyhJl7vXM8WhJqbv1qu8+fXtRhy0GqddenaFblOw3EIJF6AUGNcIu76ZASMcDihhlBj2V6EGkKNZf/EHmoaP0w420UTarIJFeXXCTXJXVZCTXLXhlCTzLVp/oqa5ld44GqddRmhJpmLxlXlJUCoyYvtf4P4jBojYITDCTWEGsv2ItQQaiz7J/ZQk+1iP39LemS8RKjJJlWUXyfUJHdZCTXJXRtCTTLXJgg1SqWabp1+91fLNe7DZSLUJHO9uKr8BQg1+dulRxJqjIARDifUEGos24tQQ6ix7B9CTWY93vpk2V3hxxJqwpvFNYJQE5d0+PMQasKbxTGCUBOHMudIggChxrgKhBojYITDCTWEGsv2ItQQaiz7h1BDqLHsH++xhBpvUb/5CDV+lt4zEWq8RX3mI9T4ODJL8gUINcY1ItQYASMcTqgh1Fi2F6GGUGPZP4QaQo1l/3iPJdR4i/rNR6jxs/SeiVDjLeozH6HGx5FZki9AqDGuEXd9MgJGOJxQQ6ixbC9CDaHGsn+SF2rmSY+cndtDOuAaqaJHbsfmeRRvfcoTLs9hhJo84WIYRqiJATnPUxBq8oSLeFhboab5aXfqXqrb162M+EqYHoFoBQg1Rl/u+mQEjHA4oYZQY9lehBpCjWX/JC/UfPNhwrk8KEJNLkoFdQyhJrnLRahJ7toQapK5NrmEmp27l+o2Qk0yF5CrylmAUJMzVesH8tYnI2CEwwk1hBrL9iLUEGos+ydxoSaXB3PPEdKyhRKhJhetgjqGUJPc5SLUJHdtCDXJXJuVQ03zq3x8Ub1+8/5SEWqSuXZcVTgBQk04r1WOJtQYASMcTqgh1Fi2F6GGUGPZP4SazHq89cmyu8KPJdSEN4trBKEmLunw5yHUhDeLYwShJg5lzpEEAUKNcRUINUbACIcTagg1lu1FqCHUWPYPoYZQY9k/3mMJNd6ifvMRavwsvWci1HiL+sxHqPFxZJbkCxBqjGtEqDECRjicUEOosWwvQg2hxrJ/CDWEGsv+8R5LqPEW9ZuPUONn6T0TocZb1Gc+Qo2PI7MkX4BQY1wj7vpkBIxwOKGGUGPZXoQaQo1l/xR0qMn2wH96jLTuwGxHZfw6b30y8YUeTKgJTRbbAEJNbNShT0SoCU0Wy4BMoeaxRfU65P2lLa5j66pOenD9qliujZMg4ClAqDFqctcnI2CEwwk1hBrL9iLUEGos+6eoQ81Pjpa+92MLjwg1Jr7Qgwk1ocliG0CoiY069IkINaHJYhmQyytqml8IoSaWZeEkEQgQaoyovPXJCBjhcEINocayvQg1hBrL/inIUJPtAf/9Sum9f0qEmmxSifs6oSZxS9J0QYSa5K4NoSaZa5Mp1DS/4pnVDdrrnWoRapK5jlxVdgFCTXajjEcQaoyAEQ4n1BBqLNuLUEOosewfQk1mPV5RY9ld4ccSasKbxTWCUBOXdPjzEGrCm8UxglAThzLnSIIAoca4CoQaI2CEwwk1hBrL9iLUEGos+4dQQ6ix7B/vsYQab1G/+Qg1fpbeMxFqvEV95iPU+DgyS/IFCDXGNSLUGAEjHE6oIdRYthehhlBj2T+EGkKNZf94jyXUeIv6zUe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   "source": [
    "z_fs, x_fs = calc.output.soilparameter_series('Unit skin friction outside compression [kPa]')\n",
    "z_qb, x_qb = calc.output.soilparameter_series('Unit end bearing plugged [kPa]')\n",
    "\n",
    "fs_qb_plot = LogPlot(calc.output, no_panels=2, fillcolordict={'Sand': 'yellow', 'Clay': 'brown'})\n",
    "\n",
    "fs_qb_plot.add_trace(x=x_fs, z=z_fs, showlegend=False, mode='lines',name='fs comp', panel_no=1)\n",
    "fs_qb_plot.add_trace(x=x_qb, z=z_qb, showlegend=False, mode='lines',name='qb', panel_no=2)\n",
    "\n",
    "fs_qb_plot.set_xaxis(title=r'$ q_b \\ \\text{[kPa]} $', panel_no=2, range=(0, x_qb.max()))\n",
    "fs_qb_plot.set_xaxis(title=r'$ f_s \\ \\text{[kPa]} $', panel_no=1, range=(0, x_fs.max()))\n",
    "fs_qb_plot.set_zaxis(title=r'$ z \\ \\text{[m]}$')\n",
    "fs_qb_plot.show()"
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   "source": [
    "## Integration of unit skin friction and unit end bearing\n",
    "\n",
    "Unit skin friction can be integrated over the annulus of the pile. Four modes are discerned:\n",
    "\n",
    "   - Plugged compression: Outside skin friction and end bearing over the full diameter of the pile\n",
    "   - Plugged tension: Outside skin friction in tension + weight of the pile material and/or internal soil plug\n",
    "   - Coring compression: Outside skin friction + inside skin friction + annular end bearing\n",
    "   - Coring tension: Outside skin friction in tension + inside skin friction in tension\n",
    "   \n",
    "The pile circumference and base cross-sectional area need to be known. Because pile shapes and sizes may differ, the weight of the pile and/or internal soil plug is excluded from the assessment. Calculating this component with a separate calculation is straightforward.\n",
    "\n",
    "In this example, a tubular open-ended pile with 2.48m outer diameter and 50mm wall thickness is taken."
   ]
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    "calc.calculate_pilecapacity(\n",
    "    circumference=np.pi * 2.48, base_area=0.25 * np.pi * 2.48 ** 2,\n",
    "    internal_circumference=np.pi * 2.38, annulus_area=0.25 * np.pi * (2.48 ** 2 - 2.38 ** 2))"
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       "   Depth from [m]  Depth to [m]  z [m]  dz [m]  Total unit weight [kN/m3]  \\\n",
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       "2             2.0           3.0    2.5     1.0                       20.0   \n",
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       "4             4.0           5.0    4.5     1.0                       20.0   \n",
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       "   Water unit weight [kN/m3]  Effective unit weight [kN/m3]  \\\n",
       "0                       10.0                           10.0   \n",
       "1                       10.0                           10.0   \n",
       "2                       10.0                           10.0   \n",
       "3                       10.0                           10.0   \n",
       "4                       10.0                           10.0   \n",
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       "0                              0.0                           10.0   \n",
       "1                             10.0                           20.0   \n",
       "2                             20.0                           30.0   \n",
       "3                             30.0                           40.0   \n",
       "4                             40.0                           50.0   \n",
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       "   Hydrostatic pressure [kPa]  ...  Unit skin friction inside tension [kPa]  \\\n",
       "0                         5.0  ...                                     1.85   \n",
       "1                        15.0  ...                                     5.55   \n",
       "2                        25.0  ...                                     9.25   \n",
       "3                        35.0  ...                                    12.95   \n",
       "4                        45.0  ...                                    16.65   \n",
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       "   Unit end bearing plugged [kPa]  Unit end bearing coring [kPa]  \\\n",
       "0                           100.0                          100.0   \n",
       "1                           300.0                          300.0   \n",
       "2                           500.0                          500.0   \n",
       "3                           700.0                          700.0   \n",
       "4                           900.0                          900.0   \n",
       "\n",
       "   Fs compression outside [kN]  Fs tension outside [kN]  \\\n",
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       "2                   129.722644               129.722644   \n",
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       "4                   360.340677               360.340677   \n",
       "\n",
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       "\n",
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    "### Results for the final penetration\n",
    "\n",
    "As unit skin friction profiles can be penetration-dependent, the plot of unit skin friction $ f_s $ is only valid for the selected final pile penetration.\n",
    "\n",
    "The profiles of unit skin friction $ f_s $, unit end bearing $ q_b $ and integrated shaft resistance in compression and tension over the inside and outside of the pile are plotted as well as the plugged and unplugged (coring) end bearing."
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             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "white",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "#C8D4E3"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "white",
          "polar": {
           "angularaxis": {
            "gridcolor": "#EBF0F8",
            "linecolor": "#EBF0F8",
            "ticks": ""
           },
           "bgcolor": "white",
           "radialaxis": {
            "gridcolor": "#EBF0F8",
            "linecolor": "#EBF0F8",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           },
           "yaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           },
           "zaxis": {
            "backgroundcolor": "white",
            "gridcolor": "#DFE8F3",
            "gridwidth": 2,
            "linecolor": "#EBF0F8",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "#EBF0F8"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           },
           "bgcolor": "white",
           "caxis": {
            "gridcolor": "#DFE8F3",
            "linecolor": "#A2B1C6",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "#EBF0F8",
           "linecolor": "#EBF0F8",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "#EBF0F8",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "#EBF0F8",
           "linecolor": "#EBF0F8",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "#EBF0F8",
           "zerolinewidth": 2
          }
         }
        },
        "title": {},
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          0.042
         ],
         "range": [
          0,
          1
         ],
         "side": "top",
         "tickvals": [],
         "title": {},
         "type": "linear"
        },
        "xaxis2": {
         "anchor": "y",
         "domain": [
          0.082,
          0.2815
         ],
         "range": [
          0,
          108.07404868885037
         ],
         "side": "top",
         "title": {
          "text": "$ f_s \\ \\text{[kPa]} $"
         },
         "type": "linear"
        },
        "xaxis3": {
         "anchor": "y",
         "domain": [
          0.3215,
          0.521
         ],
         "range": [
          0,
          1900
         ],
         "side": "top",
         "title": {
          "text": "$ q_b \\ \\text{[kPa]} $"
         },
         "type": "linear"
        },
        "xaxis4": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0.5609999999999999,
          0.7605
         ],
         "range": [
          -15063.689292371473,
          15063.689292371473
         ],
         "side": "top",
         "title": {
          "text": "$ F_s \\ \\text{[kN]} $"
         },
         "type": "linear"
        },
        "xaxis5": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0.8005,
          1
         ],
         "range": [
          0,
          9177.974441903365
         ],
         "side": "top",
         "title": {
          "text": "$ Q_b \\ \\text{[kN]} $"
         },
         "type": "linear"
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "range": [
          40,
          0
         ],
         "title": {
          "text": "$ z \\ \\text{[m]}$"
         },
         "type": "linear"
        },
        "yaxis2": {
         "anchor": "x2",
         "domain": [
          0,
          1
         ],
         "matches": "y",
         "showticklabels": false
        },
        "yaxis3": {
         "anchor": "x3",
         "domain": [
          0,
          1
         ],
         "matches": "y",
         "showticklabels": false
        },
        "yaxis4": {
         "anchor": "x4",
         "domain": [
          0,
          1
         ],
         "matches": "y",
         "showticklabels": false
        },
        "yaxis5": {
         "anchor": "x5",
         "domain": [
          0,
          1
         ],
         "matches": "y",
         "showticklabels": false
        }
       }
      },
      "image/png": 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   "source": [
    "calc.plot_single_penetration()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b3106bf",
   "metadata": {},
   "source": [
    "Numerical values of the results are available in the ``result`` attribute. These values are valid for the final pile penetration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "e1bd24bf",
   "metadata": {},
   "outputs": [
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       "      <th>Rs compression plugged [kN]</th>\n",
       "      <th>Rb plugged [kN]</th>\n",
       "      <th>Rs compression coring [kN]</th>\n",
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       "      <th>Pile weight [kN]</th>\n",
       "      <th>Soil plug weight [kN]</th>\n",
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       "      <th>Rt tension coring [kN]</th>\n",
       "      <th>Rt tension [kN]</th>\n",
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       "      <td>626.948011</td>\n",
       "      <td>7307.169368</td>\n",
       "      <td>22997.806672</td>\n",
       "      <td>30146.919769</td>\n",
       "      <td>22997.806672</td>\n",
       "      <td>True</td>\n",
       "      <td>15063.689292</td>\n",
       "      <td>29519.971758</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15063.689292</td>\n",
       "      <td>29519.971758</td>\n",
       "      <td>15063.689292</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Rs compression plugged [kN]  Rb plugged [kN]  Rs compression coring [kN]  \\\n",
       "0                 15063.689292      7934.117379                29519.971758   \n",
       "\n",
       "   Rb coring [kN]  Rb internal [kN]  Rt compression plugged [kN]  \\\n",
       "0      626.948011       7307.169368                 22997.806672   \n",
       "\n",
       "   Rt compression coring [kN]  Rt compression [kN]  Plugged compression  \\\n",
       "0                30146.919769         22997.806672                 True   \n",
       "\n",
       "   Rs tension plugged [kN]  Rs tension coring [kN]  Pile weight [kN]  \\\n",
       "0             15063.689292            29519.971758                 0   \n",
       "\n",
       "   Soil plug weight [kN]  Rt tension plugged [kN]  Rt tension coring [kN]  \\\n",
       "0                      0             15063.689292            29519.971758   \n",
       "\n",
       "   Rt tension [kN]  Plugged tension  \n",
       "0     15063.689292             True  "
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.DataFrame.from_dict([calc.result])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "340609be",
   "metadata": {},
   "source": [
    "### Results for all penetrations\n",
    "\n",
    "The calculation of axial pile capacity needs to be repeated for every pile penetration for pile sizing as unit skin friction and unit end bearing can be depth-dependent (e.g. due to friction fatigue)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b5dbf68",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.calculate_capacity_profile(\n",
    "    circumference=np.pi * 2.48, base_area=0.25 * np.pi * 2.48 ** 2,\n",
    "    internal_circumference=np.pi * 2.38, annulus_area=0.25 * np.pi * (2.48 ** 2 - 2.38 ** 2),\n",
    "    pile_weight_permeter=0.25 * np.pi * (2.48 ** 2 - 2.38 ** 2) * 68.5,\n",
    "    soilplug_weight_permeter=0.25 * np.pi * 2.38 ** 2 * 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a22cae7a",
   "metadata": {},
   "source": [
    "The results can be visualised. The leftmost panel shows the shaft resistance in compression and tension for plugged (only outside) and coring (inside and outside) conditions. The coring and plugged base resistance are shown in the middle panel. In the right-most panel, the compression and tension resistance for plugged and coring conditions are shown. Depending on the relative magnitude of internal shaft resistance vs end bearing on the plug, the calculation selects whether plugged (internal shaft resistance > end bearing on soil plug) or coring (internal shaft resistance < end bearing on soil plug) conditions are expected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "71630010",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.plot_all_penetrations()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e019eea9",
   "metadata": {},
   "source": [
    "The results are shown in a dataframe which can be exported to csv or Excel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82bd7eff",
   "metadata": {},
   "outputs": [],
   "source": [
    "calc.capacity_profile.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cb5375d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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