{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Supercritical water oxidation (SCWO)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import PFAS_SAT_ProcessModels as pspd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_colwidth', 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model document\n",
    "\n",
    "SCWO systems use supercritical water (i.e., water above 373.946 C and 22.064 MPa) to facilitate the oxidation of PFAS or other hazardous substances in aqueous streams. SCWO systems are already in operation in Japan and Korea to manage PCBs and halogenated wastes, and the Chematur Engineering facility in the UK uses SCWO to recover metals from catalysts. Research into the use the SCWO for PFAS destruction is ongoing, and there are several different systems being developed. SCWO produces steam, water, and slurry outputs. The mineralized fluoride remains in the slurry. The destruction of PFAS is modeled using a destruction and removal efficiency (DRE). Any PFAS that is not destroyed or removed remains in the water. There may also be small amounts of PFAS volatilized in the steam and remaining in the slurry. The process model estimates the fraction of incoming water that goes to each stream, and the PFAS remaining in each. \n",
    "\n",
    "<img src=\"../Images/ProcessModels/SCWO.png\" alt=\"Drawing\" style=\"width: 700px;\"/>\n",
    "\n",
    "\n",
    "### Assumptions and Limitations:\n",
    "\n",
    "1.\tIt assumes that the destruction and removal efficiency remains constant for each PFAS.\n",
    "2.\tBy default, the model assumes that all the remaining PFAS is in the water stream. However, this is a user input, and the user can send PFAS to the steam or slurry streams as well. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input Parameters for SCWO model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Dictonary_Name</th>\n",
       "      <th>Parameter Name</th>\n",
       "      <th>Parameter Description</th>\n",
       "      <th>amount</th>\n",
       "      <th>unit</th>\n",
       "      <th>Reference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFOA</td>\n",
       "      <td>DRE of PFOA</td>\n",
       "      <td>0.99260</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFOS</td>\n",
       "      <td>DRE of PFOS</td>\n",
       "      <td>0.99997</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFBA</td>\n",
       "      <td>DRE of PFBA</td>\n",
       "      <td>0.95043</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFPeA</td>\n",
       "      <td>DRE of PFPeA</td>\n",
       "      <td>0.94257</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFHxA</td>\n",
       "      <td>DRE of PFHxA</td>\n",
       "      <td>0.99843</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFHpA</td>\n",
       "      <td>DRE of PFHpA</td>\n",
       "      <td>0.96303</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFNA</td>\n",
       "      <td>DRE of PFNA</td>\n",
       "      <td>0.99260</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFDA</td>\n",
       "      <td>DRE of PFDA</td>\n",
       "      <td>0.99970</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFBS</td>\n",
       "      <td>DRE of PFBS</td>\n",
       "      <td>0.99950</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Total destruction and removal efficiency</td>\n",
       "      <td>DRE</td>\n",
       "      <td>PFHxS</td>\n",
       "      <td>DRE of PFHxS</td>\n",
       "      <td>0.99993</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SCWO parameters</td>\n",
       "      <td>SCWO</td>\n",
       "      <td>frac_water_to_steam</td>\n",
       "      <td>Fraction of incoming water to steam</td>\n",
       "      <td>0.01000</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>SCWO parameters</td>\n",
       "      <td>SCWO</td>\n",
       "      <td>frac_water_to_slurry</td>\n",
       "      <td>Fraction of incoming water to slurry</td>\n",
       "      <td>0.10000</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SCWO parameters</td>\n",
       "      <td>SCWO</td>\n",
       "      <td>frac_PFAS_to_steam</td>\n",
       "      <td>Fraction of destroyed and removed that remains in steam</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SCWO parameters</td>\n",
       "      <td>SCWO</td>\n",
       "      <td>frac_PFAS_to_slurry</td>\n",
       "      <td>Fraction of destroyed and removed that remains in slurry</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Category Dictonary_Name  \\\n",
       "0   Total destruction and removal efficiency  DRE             \n",
       "1   Total destruction and removal efficiency  DRE             \n",
       "2   Total destruction and removal efficiency  DRE             \n",
       "3   Total destruction and removal efficiency  DRE             \n",
       "4   Total destruction and removal efficiency  DRE             \n",
       "5   Total destruction and removal efficiency  DRE             \n",
       "6   Total destruction and removal efficiency  DRE             \n",
       "7   Total destruction and removal efficiency  DRE             \n",
       "8   Total destruction and removal efficiency  DRE             \n",
       "9   Total destruction and removal efficiency  DRE             \n",
       "10  SCWO parameters                           SCWO            \n",
       "11  SCWO parameters                           SCWO            \n",
       "12  SCWO parameters                           SCWO            \n",
       "13  SCWO parameters                           SCWO            \n",
       "\n",
       "          Parameter Name  \\\n",
       "0   PFOA                   \n",
       "1   PFOS                   \n",
       "2   PFBA                   \n",
       "3   PFPeA                  \n",
       "4   PFHxA                  \n",
       "5   PFHpA                  \n",
       "6   PFNA                   \n",
       "7   PFDA                   \n",
       "8   PFBS                   \n",
       "9   PFHxS                  \n",
       "10  frac_water_to_steam    \n",
       "11  frac_water_to_slurry   \n",
       "12  frac_PFAS_to_steam     \n",
       "13  frac_PFAS_to_slurry    \n",
       "\n",
       "                                       Parameter Description   amount  \\\n",
       "0   DRE of PFOA                                               0.99260   \n",
       "1   DRE of PFOS                                               0.99997   \n",
       "2   DRE of PFBA                                               0.95043   \n",
       "3   DRE of PFPeA                                              0.94257   \n",
       "4   DRE of PFHxA                                              0.99843   \n",
       "5   DRE of PFHpA                                              0.96303   \n",
       "6   DRE of PFNA                                               0.99260   \n",
       "7   DRE of PFDA                                               0.99970   \n",
       "8   DRE of PFBS                                               0.99950   \n",
       "9   DRE of PFHxS                                              0.99993   \n",
       "10  Fraction of incoming water to steam                       0.01000   \n",
       "11  Fraction of incoming water to slurry                      0.10000   \n",
       "12  Fraction of destroyed and removed that remains in steam   0.00000   \n",
       "13  Fraction of destroyed and removed that remains in slurry  0.00000   \n",
       "\n",
       "        unit Reference  \n",
       "0   fraction            \n",
       "1   fraction            \n",
       "2   fraction            \n",
       "3   fraction            \n",
       "4   fraction            \n",
       "5   fraction            \n",
       "6   fraction            \n",
       "7   fraction            \n",
       "8   fraction            \n",
       "9   fraction            \n",
       "10  fraction            \n",
       "11  fraction            \n",
       "12  fraction            \n",
       "13  fraction            "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SCWO = pspd.SCWO()\n",
    "SCWO.InputData.Data[['Category','Dictonary_Name','Parameter Name', 'Parameter Description', 'amount', 'unit','Reference']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Incoming Contaminated Water to SCWO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Parameter</th>\n",
       "      <th>Unit</th>\n",
       "      <th>Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mass flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Solids flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Moisture flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Volume flow</td>\n",
       "      <td>L</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Carbon flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>PFOA</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PFOS</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>PFBA</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>PFPeA</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>PFHxA</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PFHpA</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PFNA</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>PFDA</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>PFBS</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PFHxS</td>\n",
       "      <td>μg</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Parameter Unit    Amount\n",
       "0   Mass flow      kg   1000    \n",
       "1   Solids flow    kg   5.0     \n",
       "2   Moisture flow  kg   995.0   \n",
       "3   Volume flow    L    1000.0  \n",
       "4   Carbon flow    kg   2.5     \n",
       "5   PFOA           μg   100000.0\n",
       "6   PFOS           μg   100000.0\n",
       "7   PFBA           μg   100000.0\n",
       "8   PFPeA          μg   100000.0\n",
       "9   PFHxA          μg   100000.0\n",
       "10  PFHpA          μg   100000.0\n",
       "11  PFNA           μg   100000.0\n",
       "12  PFDA           μg   100000.0\n",
       "13  PFBS           μg   100000.0\n",
       "14  PFHxS          μg   100000.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IncominWaste = pspd.IncomFlow()\n",
    "IncominWaste.set_flow('ContaminatedWater', 1000)\n",
    "IncominWaste.calc()\n",
    "ContaminatedWater = IncominWaste.Inc_flow\n",
    "ContaminatedWater.report()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PFAS balance in SCWO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Effluent</th>\n",
       "      <th>Slurry</th>\n",
       "      <th>Steam</th>\n",
       "      <th>Destroyed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PFOA</th>\n",
       "      <td>0.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFOS</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBA</th>\n",
       "      <td>4.96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFPeA</th>\n",
       "      <td>5.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxA</th>\n",
       "      <td>0.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHpA</th>\n",
       "      <td>3.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>96.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFNA</th>\n",
       "      <td>0.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFDA</th>\n",
       "      <td>0.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBS</th>\n",
       "      <td>0.05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxS</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Effluent  Slurry  Steam  Destroyed\n",
       "PFOA   0.74      0.0     0.0    99.26    \n",
       "PFOS   0.00      0.0     0.0    100.00   \n",
       "PFBA   4.96      0.0     0.0    95.04    \n",
       "PFPeA  5.74      0.0     0.0    94.26    \n",
       "PFHxA  0.16      0.0     0.0    99.84    \n",
       "PFHpA  3.70      0.0     0.0    96.30    \n",
       "PFNA   0.74      0.0     0.0    99.26    \n",
       "PFDA   0.03      0.0     0.0    99.97    \n",
       "PFBS   0.05      0.0     0.0    99.95    \n",
       "PFHxS  0.01      0.0     0.0    99.99    "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SCWO.calc(Inc_flow=ContaminatedWater)\n",
    "SCWO.report(normalized=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SCWO.plot_sankey()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SCWO.plot_sankey_report(margin=.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
