{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "66b27885-ccc3-4a13-8b04-afa36a02f13c",
   "metadata": {},
   "source": [
    "A heat exchanger example\n",
    "========================\n",
    "within carbatpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9bdcebe4-1e2d-4820-8fd3-353c764890ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import carbatpy as cb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5df7915a-2bc9-4a5f-aaa3-8c246857a4e3",
   "metadata": {},
   "source": [
    "Select two fluid (mixtures) and further conditions. H_DOT is the wanted heatflow rate ($\\dot Q = $1 kW) here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0dbb11ff-ba47-4556-ad7d-4c0f8ac9e2ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "FLUID = \"Propane * Pentane\"  # working fluid\n",
    "FLS = \"Methanol\"  # \"Water\"  # secondary fluid\n",
    "comp = [.50, 0.5]\n",
    "flm = cb.fprop.FluidModel(FLUID)\n",
    "myFluid = cb.fprop.Fluid(flm, comp)\n",
    "\n",
    "secFlm = cb.fprop.FluidModel(FLS)\n",
    "secFluid = cb.fprop.Fluid(secFlm, [1.])\n",
    "D_TEMP_MIN = 5.0\n",
    "\n",
    "# Condenser, working fluid fixes all, secondary output enthalpy can be varied:\n",
    "SEC_TEMP_IN = 300.0  # K\n",
    "SEC_TEMP_OUT_MAX = 370.0\n",
    "SEC_PRES_IN = 5e5  # Pa\n",
    "H_DOT = 1e3  # W"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1aa628ee-50ff-4845-adf2-9ae8bbfd0ca1",
   "metadata": {},
   "source": [
    "Now set the wanted states, determine the enthalpies (alwas the value state[2] below), needed as input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5c3392b8-f82d-43e7-aed4-a4c5ac179e22",
   "metadata": {},
   "outputs": [],
   "source": [
    "state_sec_out = secFluid.set_state([SEC_TEMP_OUT_MAX, SEC_PRES_IN], \"TP\")\n",
    "\n",
    "state_sec_in = secFluid.set_state(\n",
    "    [SEC_TEMP_IN, SEC_PRES_IN], \"TP\")  # this is the entering state\n",
    "\n",
    "# working fluid\n",
    "\n",
    "TEMP_SAT_VAP = SEC_TEMP_OUT_MAX + D_TEMP_MIN\n",
    "state_in = myFluid.set_state(\n",
    "    [TEMP_SAT_VAP, 1.], \"TQ\")  # find minimum pressure\n",
    "\n",
    "WF_TEMP_IN = TEMP_SAT_VAP + D_TEMP_MIN\n",
    "WF_TEMP_OUT = SEC_TEMP_IN + D_TEMP_MIN\n",
    "state_out = myFluid.set_state([WF_TEMP_OUT, state_in[1]], \"TP\")\n",
    "\n",
    "state_in = myFluid.set_state([myFluid.properties.pressure,\n",
    "                              WF_TEMP_IN],\n",
    "                             \"PT\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "955b0ce9-4ea7-4f67-98f7-4d067d99bf51",
   "metadata": {},
   "source": [
    "Now we create an instance of the heat exchanger here: hex0. The input are the two Fluid-instances with the correct input states. The enthalpies of the wanted output states (one will be varied later to meet the minimum approach temperature). The pressures will be deduced from the actual values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f8b7025a-80d2-4eb4-a5e4-4b7d7bd0daed",
   "metadata": {},
   "outputs": [],
   "source": [
    "hex0 = cb.hex_th.StaticHeatExchanger([myFluid, secFluid], H_DOT, state_out[2],\n",
    "                           state_sec_out[2],\n",
    "                           d_temp_separation_min=D_TEMP_MIN)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "035b8cf5-d193-48fa-b054-811641ce5986",
   "metadata": {},
   "source": [
    "It is called find_pinch, but it actually just varies the fluid mass flow rate ratio, until the minimum approach temperature(d_temp_separation_min) is reached, if it is possible for the given inlet, wanted outlet values. If not a warning is given."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b75f1eb1-1440-4d63-9fee-5601d337b572",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Min T-distance 4.999, Mean T-distance 13.816\n",
      "Min T-distance 4.9990002898326225, Mean T-distance 13.816388378792048\n",
      "cond 4.999999996768054 7.880529723560983 4.9990002898326225 22.9172499170362\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e7a76ec550>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 6000x4200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hex0.find_pinch()\n",
    "if hex0.warning > 0:\n",
    "    print(hex0.warning_message)\n",
    "\n",
    "# now plotting can directly be done in pinch_calc 2024-05-24\n",
    "fig_act, ax_act = plt.subplots(1)\n",
    "PLOT_INFO = {\"fig\": fig_act, \"ax\": ax_act, \"what\": [2, 0], \"col\": [\"r:\", \"ko\"],\n",
    "             \"label\": [\"work,c\", \"sec,c\"], \"x-shift\": [0, 0]}\n",
    "hex0.plot_info=PLOT_INFO\n",
    "hex0.pinch_calc(verbose=True)\n",
    "ax_act.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "90ae03b1-581c-402d-93c2-1cf9dd059614",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 All o.k.\n"
     ]
    }
   ],
   "source": [
    "print(hex0.warning, hex0.warning_message)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9ade21f-bd60-4f2f-b942-6171c74af144",
   "metadata": {},
   "source": [
    "You can plot a second heat exchanger into the same plot by passing the figure information. But first we need a new instance of an heat exchanger, now an evaporator called hex1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8c2bfba0-3d64-4a42-adb2-9087e9ac2975",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "state in (T,p,h,v,s,q,u): [2.77000000e+02 1.04510486e+05 2.37193722e+05 2.21710771e-01\n",
      " 1.11102909e+03 5.28596305e-01 2.14022622e+05]\n"
     ]
    }
   ],
   "source": [
    "#  Evaporator: ----------------------------\n",
    "\n",
    "SEC_TEMP_IN = 300.0 # K\n",
    "SEC_TEMP_OUT = 285\n",
    "SEC_PRES_IN = 15e5\n",
    "H_DOT = 1e3  # heat flow rate\n",
    "extra = 2  # some additional temperature difference between both fluids at the entrance of the working fluid\n",
    "# D_TEMP_SUPER = 5.\n",
    "D_TEMP_MIN = 6.0  # Minimum approach temperature, allowed\n",
    "\n",
    "state_sec_out = secFluid.set_state([SEC_TEMP_OUT, SEC_PRES_IN], \"TP\")\n",
    "state_out = myFluid.set_state([SEC_TEMP_IN-D_TEMP_MIN - extra, 1.0], \"TQ\")\n",
    "\n",
    "# the inlet states must be the last set_state before the hex is constructed, because it is further used by the heat exchanger:\n",
    "state_sec_in = secFluid.set_state([SEC_TEMP_IN, SEC_PRES_IN], \"TP\")\n",
    "state_in = myFluid.set_state(\n",
    "    [SEC_TEMP_OUT-D_TEMP_MIN - extra, state_out[1]], \"TP\")\n",
    "\n",
    "print(\"state in (T,p,h,v,s,q,u):\", state_in)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eec82178-d37f-4c31-8c23-8b6e56eb40ac",
   "metadata": {},
   "source": [
    "The new states are set, now we can do the calculations again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1aaf624f-664d-422c-ac05-6cdc715795b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Min T-distance 5.999, Mean T-distance -6.650\n",
      "Min T-distance 5.9990002875455275, Mean T-distance -6.65042055546035\n",
      "evap -8.000000001512547 -7.619450263333988 -5.9990002875455275 -8.000000001512547\n"
     ]
    }
   ],
   "source": [
    "hex1 = cb.hex_th.StaticHeatExchanger([myFluid, secFluid], H_DOT, state_out[2],\n",
    "                           state_sec_out[2],\n",
    "                           d_temp_separation_min=D_TEMP_MIN)\n",
    "# ms1, d_tempall1, w1, s1 = hex1.pinch_calc()\n",
    "\n",
    "factor_out = hex1.find_pinch()\n",
    "if hex1.warning > 2:\n",
    "    print(\"Second heat exchanger:\", hex1.warning_message, hex1.dt_min)\n",
    "else:\n",
    "\n",
    "    # plotting in the same figure\n",
    "    PLOT_INFO = {\"fig\": fig_act, \"ax\": ax_act, \"what\": [2, 0], \"col\": [\"k:\", \"bo\"],\n",
    "                 \"label\": [\"work,e\", \"sec,e\"], \"x-shift\": [0, 0]}\n",
    "    hex1.plot_info=PLOT_INFO\n",
    "    hex1.pinch_calc(verbose=True)\n",
    "    ax_act.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9be33cb0-48d9-4749-a2c1-80b057be4edf",
   "metadata": {},
   "source": [
    "By the way, the mean temperature difference between both curves is evaluated. If you have an idea of the mean heat transfer coefficient U, you can calculate the needed heat exchanger area:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c61bd44c-e3a8-4d0d-9d1f-c8f18c934f3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated HEX area: 0.301 m^2\n"
     ]
    }
   ],
   "source": [
    "u_heat_transfer = 500 # W/ (m2 K)\n",
    "area_needed = H_DOT/ np.abs(hex1.dt_mean) /u_heat_transfer\n",
    "print(f\"Estimated HEX area: {area_needed:.3f} m^2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2f0cead8-6445-4f4d-98b9-815323964e46",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 6000x4200 with 1 Axes>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig_act"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9845730b-04b9-4446-b857-7d862d35f62f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}