NFPA-EconomicImpactFire-case4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NFPA CBA Example 4 : High Rise Office Building (COM4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notebook initialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import packages\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "This Notebook presents an example application of the prototype methodology for cost-benefit analysis. This case study considers a nine story office building. For background on the model and considered input values, see the background document."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The benefit of the sprayed fire resitance material (SFRM) is evaluated based on the probability of structural failure with the SFRM at increasing levels from one hour to 3 hours levels of protection. The structure is assumed to have no other fire protection measure. "
   ]
  },
  {
   "attachments": {
    "Case%204.png": {
     "image/png": 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3rHSRIn+MAEbsBgv0Ry2SaJGNrjixtHuZNp1sXs3CW1xopYsUTgsisRssWNOdLAqhfWWiLBut1lkL4hciryV13oKAELvBQuiONiwaeGfZ7QTHqjetLka9Eil+3kAiNUs+pnOzqGvmYGwnRBZvWn2Ms+glG4jEbtDYc4doaHlhRSL4w5ocUJkk/oiuq9i97C41AeGoG+jW4xy23757gKdAf6eC9k8F7Z8K2j8VtH8qaP9U0P6poP1TQfungvZPBe2fCto/FbR/Kmj/VND+qaD9U0H7p4L2T+Vy++WfnR/h/Xks3vEeDe1XYRe0v53W9tNmXwiymRzNFpDcotA/uBe7RAHuzDWkadQ96x/1k1qql+rJYW7yihStQLncChlf6qH1jyzcU7WIkwSWxS0e1s1xBB8ajiZfkMulSR+pgdbCuFqTWVQTt5sVtkoPxLGPNOsJ9AbLcbkw6R810Fqoiu6miyCXmOmSFtAljiq7jm6ey9zJ5brkCaSLesgUXlO/WVMbG7n9fLHOphp79gE8mLqLl+qSxh9zGtDBk7l7uFoWDfQYNGEJ2j8VtH8qaP9U0P6p5C06/G1igwaGA3tHNrk4+Sb2+u0Sd85k9J4fSP4spBwUV8Ruz+dsfLXIg9P73Drk6D0/kHr7+YvA/rDAK82tfG2YkTfeyUiLuiJb1Rayi09Om8qKXhKU7GplonCT3vMD4eeL0EPSh0WV9BKbt9CBGERaNCpsTMjLkxjdeBe5dgWXiGYSNnmb6Tw+kvxRQodIp42fPHzYH7fMxSayiSIuR67JAYkl0amyRSHKaaWFdyZJt+g8PpJNw8QgNlrjw+smO68qiS0ZHMftZ1RmXQW+2KAWlWULiCWq7XQcHU3RfvqITRQOSO0XgVYVRGJFLIn99sfQTBUlXrL49qtkwl36Tg+l2v5gDXb9ZqIru9UqEqM+c6tVyDWNibG0+qNsiysH8C5i1KNTtDvcPjgefpA63VUe5N7juJrce7u+2wfH86n259yur/vBxnGjRZd5MncPaP9U0P6poP1TWakstH8qz/Vo1e4v1f7QpafQGyzHYoVpty7w778qXEGzr8e6lZ3w758KnwbtnwraPxW0fypo/1TQ/qmg/VNB+6eC9k8F7Z8K2j8VtH8qaP9U0P6poP1TQfungvZPBe2fCto/FbR/Kmj/VND+qaD9U0H7p4L2TwXtnwraPxW0fypo/1TQ/qmg/VNB+6eC9k8F7Z/Kq+3/tyxa4Ou8237dlwPtnwraPxW0fypo/1TQ/qlYYdl/gR3E4/8gu3B6w8a5k+gwfyuUzBKmJ0m3WL/9vtpAppxTPnFkJ1PjDU7xTS9m51Pt5weg/y09FUjiS7xiMJNYSWADLRqkqwQU7JhvkeVy94z2r7WfdbFxV02JSzSxHl20y+avGjvmW2S53C2jff32UzMVkvQh5OMUW6KJdVkzmygqVahb7xFz6Vegasn+henP1vDRLXycIlul/fLQyRY+cu2w72knyyUKlxPtH2m/oJXbdtp+ZxDb9qqxY75FlksUXqP9q+2PU6RbNCRTjKBdX5Y/xuaSHfMt+Gb2Tcet8R7Ltz8jlj2CnWQP34MsyfrD7d8B7SemFfbGK46g/VvQfgLtnwraPxW0fypo/1TQ/qmg/VNB+6eC9k8F7Z8K2j+VH2j/3H+X9YiJlb04/fMe8oSJhb3cfhXX4jfaT4+p0mLMK+zd9quwGr/RfvzkUzCi/fSP1wejmXvRbKf8n+7naOJR9OfTukaj2XvQTKPR7EPoTjZ8IIT+tIMbZYxN25vroe4PSPxUYUMfuTPVY93vTv1cZWj/BZ4rbGTq3vbr/gRduR+ci5G50f52Vm0/a/czbk52lbbXorbW1YOXbT+pRcbqLWrGja167io7LQpWuQqq8TtJ6uY7dGbKj/PPxGSKBbIhLNl/eEC6GOWihR18JLJR2+CEJWyVm0sB8gmL00lkm4QXsGsMnZny46mj6uCVFnsYucwol258eTZqGzstEjMt7sNXrhNJ2rBw++k52JgvJsilBq87ydiobey2iBzkSx+JdDYxOGnDuu0Pl29/9rC0qBqNqvO3A/VENmob+y0KHr5l/Eiks/FWq0jZz91MZ6b8OGn0dLyzhfaohUUuNSQ9SY6N2sZ+i6hA2uJHQp1NLttK9nM305kpP04a1Sajw4qaWNWJstWk5KGgxEZtg/JV0BvRzTOV1yglDwUVkGcQnZnGFVLSlXtgiwrQ/lPQ/l7Q/lPQ/j7Q/nY+035faPOduko7a1FPZd9pv+4kNN+pq7TT9ut+p7KvtD+rs/lOXaWdtKirsu+03/3ZSi7e2HL6EGf+Q06yd1V25m+gM9Pxca0zrPFyG38OOHEfc9Kirsq+1X5a4xU3mb0jTtzHnCTvquys8AY6M53XubncdsaFkH0udHBzue2Ez7afvuGyxJ8TLoTsc9KirspOcrfQmen4ONfJX8py8VOKJOZDzvyHnGTvquzM30BnpnGFlHTlHtiiArT/FLS/F7T/FLS/D7S/nYXa/9xTdqZ+sv26D6A31YPt1/0mzw3GyMzd7X/qKbsTP1XZ0Lzduc7/+HSHEVkfqWxw0gHJQkXj0dxdaKrBaPIxPDAg4DpoP/hdMP3gd8H0g98F0w9+F0w/+F0w/eB3mT39T/ylMADXKIdP/1r7YCwvTOze8cLePP1cmpwqxSjTTngZgA3lbNi4dIwNHa2drthb7+Ljnawib2ExjxMBKChnI44LC/y9U0xRiot+Z6WNoKCIaXt2RU5KjIoq0yrRycqKCjWRt7CYJ2wuCICccjbiuJCgihMDSfPrJlWuJTZ2d1ZF2X1OcyjxS4G/KER2Ioeb1SQAKpSzEcdFZkcRg+20RElX25RMcajdkrqzdj6z86KORHaWUD2F0xIFAKqUs2HjUp2daOTp9ZHb2ExxbOzubJbO7Lyow+FjCBHz1WsAVChng8eayLQosS06NMZvhDhZ100QszNkZ9Vrx5joVNS8tavImzmdCYAad2cDswW+z/3pp5MYfvBlML7gd8H0g98F0w9+F0w/+F1mTz/+3AzmUQ4f/3U6oXrJ6cTuJajYm6ff5SjFKNNOeBmADeVs2Lh0j81egszeehcf72QVeQuLeZwIQEE5G3FcWODvnWKKUlz0OyttBAUl1LBnV+gcUcq0SnnJyooKNZG3sJgnbC4IgJxyNuK4kKCKEwNJ8+s2VYrPye3urDl4d/bNiaCaU9iIHG5WkwCoUM5GHBeZHUUMttMSJV1tEzLFYXZL6s4mly1h40UdiewsoXoKpyUKAFQpZ8PGpTo70cjT6yOzWCdmlHZ31py8m50XdTh8DCFivnoNgArlbPBYE5kWJbZFh8b4LUaKrhshxoDqhD+rXjvGRKei5q1dRd7M6UwA1Lg7G5gt8H3uTz+dxPCDL4PxBb8Lph/8Lph+8Ltg+sHvUk4//4Xi4R9nz/+su5ehtLf/uTnlYCmQRDPzzmQKABnlbNRmqBE+WUlQsbfeRU9rJloZtfIW1ujwMgAbytmI46JCGiCTbGVI8kEJH+zJLEFxZ0kU2TZdYkgMDTjZnwqLeZwIQEE5G3FcWBCN1jRG4ohSWNkQ/Wwx1Zu9XRFdjLYmi91FFMZlIFG17bqVAKhQzkYcFzc7vFUcfk1+QeeyQOw2t+6sxWd2XtQR0dTOzunsDG38iQsANcrZiONCwmZ2ZMDiot58i2x1I7O7s2bn3ey8qMPhYwgR3UqLswFQoZwNHRf9TpqGJ6m0JHuUo0l30V1gZlf8WTvg5bQKIhZ2FXkzZxEEQE45GzQ2OjlM1KKVNrYSqqeNMA+LsjPOruRnnVtE1rIjZFfd2b1J5XwDoOTubGC2wPe5Pb38PRizD74M5hf8Lph+8Ltg+sHvgukHvwumH/wumH7wu2D6we+C6Qe/C6Yf/C6YfvC7YPrB74LpB78Lph/8Lph+8Ltg+sHvgukHvwumH/wua07/3n81hv+aDIxk/DTxf/EYUPUWe8f30/beEfwij0y/Svdpn34A2nl0+oPIJFHsFQd7oqhCjM8tKjlRpMylAlvVCUDO+KmQmdMBVINY2U14h2AxXt0zVORc1YU9KQCALeNnYzOQumVTGBTFyT5GpbohLIpYfCyrJiXzLTjTl9C6wWXGtyy9BpV4y16OV0TexKhUNySrwrq6xBLwJ+4QDt4+O4Ov1bsE4/vl3oG8EdZlNcQcyESTY7RuBDuIXI6CxIoWUN02Va4jOT7GJ4ueyt9ql779/iH46Bxh/Nv4a9OvqH6X/gxz+GrdsxjdLZ69xdDSGrh1aAG+Wvcs0K0amP7fAN2qgen/DdCtGjOmKL9lqOBGCYPqfufxZzR5w/QCluToxQSfoHoTh3lVIFRpvclhVVI1Bxzmbb3pfbSaeUy+/aIcvRZ13Xtz53mZu2NxeO5qzpv3vsOLt6oy+faL0jD9YSecmDucJ+3ZsSySiaqPTVIK3HLk02QMi5ZLF/Go2fbcLSaTaZX5YVMtREWLlc3B3onMvfuqHL0VfqMB09KW2apKbs2dMSZg6WWLnkpkTiyrBlftMubZ0smqnTYL4c3sTvRyEgnvclg505h791U5eivi0gB6f0Ky8W6yCLlGm5F8MSbADt7TylZF9JIDV0oTYFF1yRhgLRDtuinRUpl+xZnDZuGBjarUrW8y9ebLIm+yjrpky+JMoT06WMg1pwdMzm0+rhZR56huf5xF1Ysjud25TeTN3Elk3KmN2auMGHSN0qu8f8cvcGH6s5cn6KnMsY3KzIKFZCYfFj0+pMqd6adDjGjRXnGrxA4Vt7Ke8uFqcA5BRHZwmHO9xft3/AL2rmqYK73PJLHCciA5yGOYzXn1VIpxQWllKNLFbTl0DuPOPaywnbNkfqX2nPfv+AXuTdGE17dh2ek/GX5M/0pg+l+Gysb0L8JXp+iz0z8JdKsGpv83QLdqYPp/A3SrykfHCNPfBrpVJYzRBzuD4W8E7apD4/+t3nyv4vmgX7vwOI3n37//qjQarRtcBi17m3///qkEZoPpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zpg+t8G078OmP63wfSvA6b/bTD964DpfxtM/zr82ekPQwZa0d79DH94+lUAV8H0/xkw/c1g+v8MmP5mMP1/Bkx/M5j+PwOmvxlM/58B09/M9Zbp/zP2o/8P2bdyN55Zd/pbnr4SiulvZtMy+T+Ar70GsfWM/oWz2xDTD4821tQW/SLpYTclyivJrZWHxvQ3U0y/3xy7jqFs01+7XVtRzz7BfVyHNyU6T6J8aEx/M23Tb9+CeA+C7M4XIYsgcSpUojQ2yclne2ZXg0CyeC/TFPwi7ik2JVYfs3xoTH8zxfQLqibyN5Bvsouy8RRSGWUyLyITmU67l00xk2zXaAp+EXu+wKZEfSdbq+4RTH8z9e/9JTZutU12UTYewl7cTpTJvIiBibruXjYl367REvsm7iFUsjbUH6+wYvqbOZj+rLvqqG6yi7LxKCmgjDKZl7Buddu9HIN4M881moJfxD3FpkT/fFEsHxrT38z+9Nv3X0HlfOMYQuS0xoAYwpItWZQGJDstqrMz2QWx06qbKhdpCn4Rewr3lIpTkqd8aEx/Mwcty9tbdnsZ2ipb9jkudTjGlMGY/mb+wPQ3Vvbt57CYSjCmv5nL0/9n+PZjHVSP6W/m91r2R7+oMf03wPT/GTD9zWD6/wyY/mYw/X8GTH8zmP4/A6a/GUz/nwHT3wym/8+A6W8G0/9nwPQ3g+n/M2D6m8H0/xkw/c1g+v8MmP5mMP1/Bkx/M5j+v4D+DxIzagLHaLcItfwEf/J7v77HgBrAGdqvH+vY3/zJR98khv86P9mxP/pz/y++yk5+sWN/9U+9GP5mfrBjf3X6w7tUAVzl9zq2xPTz/2zDN9CKp6PlfAGteEXm17Z+j4xlKl2mkFMWr3R2YUs3p8b8etGyYSzwJlX8DJNLRsvGMbeqD77IwNSq0bKBTC0q9OSLr3Lmu0TLRjJ7+lX6FnOnX6VvgekvWPhVHlaG6SeaKsH0Fxy1JPjUeaFvl1s7JnDiq2y7NTWRYFFMp4wPJKSI1Zha01FLgku9F/p2ubVjAie+yqZb++AxT+5pagKmv+Bk+rW/GhSCGVaYqNcECkib2m3P/WaV3Wy07qAxM2i7dQrmByPNCerQTe22536zym42Wi+iZxZjak1HLWFXWnRNu5dKpwqy7QcW/kDNtmHiq2y8dQjXA3Yuns/s0VoEFv5AzXbCxJYdMLWmo5akDrMUI92R+GajcRvFWzQGNoGyuQBKubWVxPu+z41byxE7F8+rkDmJTaBsLoA6tLWdc6PuF5ha01FL1BU2lmLk5oikMOM2KnMSm0DZouI0tdWZ+Crv3JrP2Ll4XgXeojGwCZQtKk5T2zUmtuyAqTUdtcRcIYYl1d0Jb9h65dDmqJdrfr+pUkfPzaDp1hqaPVE8X22Bl2t+v6lyjaa6X2NqTUctia4YFIQ83htEcn7xqV4EZn7vs79pirYalmMCbbemB4oHRHLnxad6EZj5ve9Si7ZYzrWYWtOaLTlnYt1o2Ugw/TfA9DeD6S/Aq2wGLRsJpv8GmP5mMP0FeJXNoGUj+fD0h9Pb86I/3uiJr7Lz1tN6NrFlB0ytqasl+4cfb/TEV9l363k9m9iyA6bW1NOScNaOR0HfoV+T4qNFuk13gvt03ZofPXWBhSBt16T4aJHu0nv+GabW1NUSO6wrb+UaFdFy610mvsq+W8/r2cSWHTC1pq6W5IdFKddcCbsh+j06j/fQd+v8tCjlmithN0S/Rd/pp5haU1dL7DC9FkLk7Zorce9D7zaDvlvbaeoXIfJ2zZW4d6E3W4ypNXW1JHt5upVrrjihh4mvsu/W83o2sWUHTK2pqyV2OOyMyGmtOAg1Rv0Oncd76Lu1naYGECKnteIg1Bj1G/SdfoqpNa3ZknMm1o2WjQTTfwNMfzOY/gK8ymbQspFg+m+A6W8G01+AV9kMWjaSuTV9812GqueVjZYNZPr0f+9dzi0aLRvI5KI++C5nl4yWjWN6VdSZD73NFapFy0axQF38Mr+DVj0VLeUraNXrsUhl2qbV0WqXQEtaHa12Rf73v/8HUPonLhvrDGIAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Case%204.png](attachment:Case%204.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## I. Input\n",
    "User input in this area.  \n",
    "Note: All monetary values in 2022 USD.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### I.1 Building characteristics\n",
    "The building design is based on a FEMA/SAC project for the Boston area post Northridge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "S_area = 18810 # [m2] Floor area of structure\n",
    "Construction_Cost = 1674.43 # [USD/m2] Construction cost; evaluated through (RSMeans, 2022)\n",
    "Demol_cost = 59.82 # [USD/m2] Demolition cost; evaluated through (RSMeans, 2022)\n",
    "Disposal_cost = 0.145 # [USD/m2] Disposal cost; evaluated through (RSMeans, 2022)\n",
    "\n",
    "SFRM_time = np.array([1,2,3, 1,2,3]) #These ratings are the times in hours that the SFRM is expected to protect the structural members from the fire\n",
    "# note: duplicate ratings are used as two different fire load models are explored within the case study"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### I.2 Discount rate and obsolescence rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = 0.03 # [1/year] continuous discount rate; 3% based on (Fischer, 2014)\n",
    "o = 0    # [1/year] obsolescence rate; 0% - building obsolescence neglected"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### I.3 Cost of fire protection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### I.3.a Investment cost fire protection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "c_ins_unitcost= np.array([13.66, 23.76, 40.99, 13.66, 23.76, 40.99]) # [USD/m2] SFRM unit installation cost, evaluated through (RSMeans, 2022). The duplicate cost values are used as two different fire load models are explored in the case study.  \n",
    "c_ins = c_ins_unitcost[0:]*S_area # [USD] Total installation cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### I.3.b Maintenance cost fire protection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "m= 0*c_ins  # [USD per year] annual maintenance cost; 0% of SFRM installation cost assuming that no maintenance of the sprayed material is required."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### I.4 Benefit of fire protection \n",
    "Benefit evaluation as reduction in cost of fire losses, assessed through flowchart listed in the Introduction.  \n",
    "See background document for discussion."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### I.4.a Fire frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## fire frequency\n",
    "lambda_fi= 0.00423 # [1/year] fire frequency per dwelling (ignition frequency + unsuccesful immediate suppression by occupants); based on (Manes and Rush, 2019) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.4.b SFRM reliability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pfsfrm = np.array([0.97,0.79,0.64,0.73,0.15,0.08]) # [-] probability of failure in case of fire for different SFRM ratings. \n",
    "# These values are obtained from simulations (see report).\n",
    "# The first 3 are using the NFPA fuel distribution model and the next 3 are using the Eurocode model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### I.4.c Fire-induced losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "## valuation of risk to life\n",
    "VSL = 5.657*10**6 # [2022 USD] Value of Statistical Life (VSL); 5.657*10**6 based on (ISO 2394:2015) \n",
    "xi_in = (0.047 * VSL) # [2022 USD] valuation of average injury risk; 0.047*VSL based on (Zhuang et al., 2017)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "## [fatalities/fire]\n",
    "Nf_civilian = 0.9/1000 # [fatality/fire] probability of civilian fatalities; 9 fatalities per 1000 residential fires based on (NFPA 2022)\n",
    "Nf_firefighter_on_ground = 6.9/1e5 # [fatality/fire] probability of firefighter fireground fatality; 6.9/1e5 based on (NFPA, 2022)\n",
    "Nf_firefighter_response = 6.3/1e5 # [fatality/fire] probability of firefighter response fatality; 6.3/1e5 based on (NFPA, 2022)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "## [injuries/fire]\n",
    "Nin_civilian = 1.4/100 # [injury/fire] civilian injuries; 1.4 injuries per 100 reported fires based on (NFPA, 2022)\n",
    "Nin_firefighter_on_ground = 1.62/100 # [injury/fire] firefighter fireground injuries; 1.62 injuries per 100 reported fires based on (NFPA, 2022)\n",
    "Nin_firefighter_response = 0.37/100 # [injury/fire] firefighter response injuries; 0.37 injuries per 100 reported fires based on (NFPA, 2022)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "## property loss\n",
    "S_loss_0 = 18810 # [m2] average damage area in case of structural failure/inability of the SFRM to prevent failure\n",
    "S_loss_s = 83.5 # [m2] average damage area in case of fire containment, assuming the fire does not spread beyond a single compartment\n",
    "eps_loss_content = 2.0 # [-] property loss multiplication factor; eps_loss = ((building loss + content loss) / building loss); 2.0 based on (FEMA, 2015)\n",
    "eps_loss_indirect = 1.25 # [-] total property loss multiplication factor accounting for indirect costs; "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## II. Design fire risk evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### II.1 Calculation of fire scenario parameters\n",
    "Input parameter calculation from raw input data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "## fire protection success probability\n",
    "psfrm = 1-pfsfrm # [-] success probability as complement of failure probability "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Unit replacement cost\n",
    "Replace_cost = Construction_Cost + Demol_cost + Disposal_cost # [USD/m2] replacement cost as sum of demolition, disposal and reconstruction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### II.2 Scenario consequence evaluation\n",
    "Evaluation of consequences for identified scenarios (event tree)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### II.2.a Scenario \"building failure\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Fatalities and injuries\n",
    "# fatality rate\n",
    "Nf_0 = Nf_civilian + Nf_firefighter_on_ground + Nf_firefighter_response # [fatality/fire] total fatality rate without SFRM assuming a 5% increased risk to firefighters due to building failure\n",
    "# injury rate\n",
    "Nin_0 = Nin_civilian + Nin_firefighter_on_ground + Nin_firefighter_response  # [injury/fire] total injury rate without SFRM assuming a 10% increased risk to firefighters due to building failure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Valuation of fatalities and injuries\n",
    "# fatality valuation\n",
    "Df_0=Nf_0*VSL # [USD/fire] valuation expected life loss\n",
    "# injury valuation\n",
    "Din_0=Nin_0*xi_in # [USD/fire] valuation expected injuries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Material loss\n",
    "xi_d_0= S_loss_0 * Replace_cost * eps_loss_content * eps_loss_indirect # [USD] property loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Total loss valuation\n",
    "D0=Df_0+Din_0+xi_d_0 # expected value fire-induced loss, scenario \"no SFRM\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### II.2.b Scenario \"building remains standing\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Fatalities and injuries\n",
    "# fatality rate\n",
    "# no fire-induced fatalities in case of the SFRM successfully preventing building failure; \n",
    "# only fire fighter response fatalities considered\n",
    "Nf_s = Nf_civilian + Nf_firefighter_on_ground + Nf_firefighter_response # [fatalities/fire] total fatality rate in building with SFRM\n",
    "\n",
    "# injury rate and valuation\n",
    "# reduction in civilian injuries in case of the SFRM successfully preventing building failure from fire\n",
    "\n",
    "\n",
    "Nin_s = Nin_civilian + Nin_firefighter_on_ground + Nin_firefighter_response # [injury/fire] total injury rate in case of fire suppresion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Valuation of fatalities and injuries\n",
    "# fatality valuation\n",
    "Df_s=Nf_s*VSL # [USD/fire] valuation expected life loss\n",
    "# injury valuation\n",
    "Din_s=Nin_s*xi_in # [USD/fire] valuation expected injuries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "### Material loss\n",
    "xi_d_s= S_loss_s * Replace_cost * eps_loss_content * eps_loss_indirect # [USD/fire] property loss given fire in case of SFRM preventing building collapse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Total loss valuation\n",
    "Dsup=Df_s+Din_s+xi_d_s # [USD/fire] expected value fire-induced loss, scenario \"no building collapse due to SFRM\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## III. PNV calculation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### III.1 Total safety system cost *C+A*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### III.1.a Investment cost, *C<sub>I</sub>*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "C_I=c_ins # PNV investment cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### III.1.b Maintenance cost, *C<sub>M</sub>*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "C_M=m/g # PNV of maintenace cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### III.1.c Obsolescence cost, *C<sub>A</sub>*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "C_A=C_I*o/g # PNV of obsolescence cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### III.1.d Total safety system cost *C+A*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "net_C=C_I+C_M+C_A # total PNV investment cost (investment cost and maintenance cost)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### III.2 Net benefit *B-D*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### III.2.a Fire-induced losses reference design, *B*\n",
    "Reference design without SFRM protection. Single scenario in event tree: scenario \"failure of building without SFRM due to fire\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Expected loss reference design\n",
    "Dref=D0 # [USD/fire]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "## PNV reference design\n",
    "B=Dref*lambda_fi/g # [USD] PNV fire-induced losses reference design"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### III.2.b Fire-induced losses trial design, *D*\n",
    "The trial design considers the additional protection to the building system by adding SFRM.  \n",
    "The SFRM has a reliability psfrm.  \n",
    "The overall design performance is a combination of the scenario \"building failure\" (with probability pfsfrm) and the scenario \"building remains standing\" (with probability psfrm)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Expected loss design with SFRM protection\n",
    "Dsp=(pfsfrm)*D0+psfrm*Dsup # [USD/fire]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "## PNV reference design\n",
    "D=Dsp*lambda_fi/g # [USD] PNV expected risk to life reference design"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### III.2.c PNV net benefit, *B-D*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "netB=B-D # [USD] PNV net benefit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IV. Cost-Benefit evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The PNV for SFRM fire protection is, \n",
      "\t1-hour prescribed rating: 86,522 [USD] (NFPA model); \n",
      "\t2-hour prescribed rating: 1,957,343 [USD] (NFPA model); \n",
      "\t3-hour prescribed rating: 3,350,582 [USD] (NFPA model); \n",
      "\t1-hour prescribed rating: 2,834,258 [USD] (Eurocode model); \n",
      "\t2-hour prescribed rating: 9,284,639 [USD] (Eurocode model); \n",
      "\t3-hour prescribed rating: 9,761,966 [USD] (Eurocode model); \n"
     ]
    }
   ],
   "source": [
    "BCR=netB/net_C # [-] benefit cost ratio\n",
    "Z=netB-net_C # [USD] PNV of proposed safety measure\n",
    "print(\"\\nThe PNV for SFRM fire protection is, \")\n",
    "for j,Zj in enumerate(Z):\n",
    "    if j<3: print(\"\\t{0:,.0f}-hour prescribed rating: {1:,.0f} [USD] (NFPA model); \".format(SFRM_time[j],Zj))\n",
    "    else: print(\"\\t{0:,.0f}-hour prescribed rating: {1:,.0f} [USD] (Eurocode model); \".format(SFRM_time[j],Zj))\n",
    "      "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example 1 - Parameter study and visualizations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Visualization of cost distribution design alternatives"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Design alternatives- With and without SFRM\n",
    "\n",
    "## Investment costs\n",
    "Investment_sfrm=C_I+C_M+C_A  # [USD] array of PNV investment costs for case with SFRM (investment, maintenance, obsolescence)\n",
    "Investment_nosfrm=np.array([0,0,0]) # [USD] array of PNV investment costs for case without SFRM (investment, maintenance, obsolescence)\n",
    "\n",
    "### Two scenarios (Building failure prevented by SFRM and building failure even with SFRM)\n",
    "## Scenario failure not prevented by SFRM\n",
    "# valuation of risk to life\n",
    "Df_0=Nf_0*VSL # [USD/fire] valuation expected life loss\n",
    "Din_0=Nin_0*xi_in # [USD/fire] valuation expected injuries\n",
    "\n",
    "# valuation of material losses\n",
    "xd_direct_0= S_loss_0 * Replace_cost # [USD] direct property loss related to the building itself\n",
    "xd_contents_0 = xd_direct_0*(eps_loss_content-1) # [USD] direct property loss related to the contents\n",
    "xd_indirect_0 = xd_direct_0*eps_loss_content *eps_loss_indirect # indirect losses\n",
    "\n",
    "# Array of costs and PNV evaluation\n",
    "Costs_0 = np.array([xd_direct_0,xd_contents_0,xd_indirect_0,Df_0,Din_0])\n",
    "Costs_0 = Costs_0 * lambda_fi/g\n",
    "\n",
    "## Scenario failure prevented by SFRM\n",
    "# valuation of risk to life\n",
    "Df_s=Nf_s*VSL # [USD/fire] valuation expected life loss\n",
    "Din_s=Nin_s*xi_in # [USD/fire] valuation expected injuries\n",
    "\n",
    "# valuation of material losses\n",
    "xd_direct_s= S_loss_s * Replace_cost # [USD] direct property loss related to the building itself\n",
    "xd_contents_s = xd_direct_s*(eps_loss_content-1) # [USD] direct property loss related to the contents\n",
    "xd_indirect_s = xd_direct_s*eps_loss_content*eps_loss_indirect # indirect losses\n",
    "\n",
    "# Array of costs and PNV evaluation\n",
    "Costs_s = np.array([xd_direct_s,xd_contents_s,xd_indirect_s,Df_s,Din_s])\n",
    "Costs_s = Costs_s*lambda_fi/g\n",
    "\n",
    "### Costs per design\n",
    "## Design A, no SFRM in building members, \n",
    "psfrm_0 = 0 # No SFRM present\n",
    "Costs_no_sfrm = ((1-psfrm_0) * Costs_0) + (psfrm_0 * Costs_s)\n",
    "TotalCost_no_sfrm=np.append(Costs_no_sfrm,Investment_nosfrm)\n",
    "\n",
    "\n",
    "\n",
    "## Design B, with SFRM in building members\n",
    "\n",
    "for j in np.arange(len(psfrm[0:3])):\n",
    "\n",
    "    Costs_sfrm = ((1-psfrm[j]) * Costs_0) + (psfrm[j] * Costs_s)\n",
    "    \n",
    "    TotalCost_sfrm=np.append(Costs_sfrm,Investment_sfrm[j])\n",
    "\n",
    "    ### Visualization of cost distribution per design\n",
    "    fig, ax = plt.subplots()\n",
    "    labels=['no SFRM','SFRM']\n",
    "    categories=['direct loss building','direct loss contents','indirect loss','fatalities','injuries','investment']\n",
    "    bar_width = 0.35\n",
    "    opacity = 0.8\n",
    "\n",
    "    cumCost=np.array([0,0])\n",
    "    for i, cat in enumerate(categories):\n",
    "        ax.bar(labels,[TotalCost_no_sfrm[i],TotalCost_sfrm[i]],bar_width,bottom=cumCost,label=cat)\n",
    "        cumCost=cumCost+np.array([TotalCost_no_sfrm[i],TotalCost_sfrm[i]])\n",
    "\n",
    "    #ax.set_ylim((0,8000))\n",
    "    ax.set_ylabel('PNV costs [USD]')\n",
    "    plt.title('PNV cost of design ' +str(j+1)+ '-hour fire rating (NFPA model)')\n",
    "    handles, labels = ax.get_legend_handles_labels()\n",
    "    ax.legend(handles[::-1], labels[::-1])\n",
    "    ax.legend(labels,fontsize=16)\n",
    "    fig.set_size_inches(10,8)\n",
    "    \n",
    "    \n",
    "    \n",
    "for j in np.arange(len(psfrm[3:])):\n",
    "\n",
    "    Costs_sfrm = (1-psfrm[j+3]) * Costs_0 + psfrm[j+3] * Costs_s\n",
    "    \n",
    "    TotalCost_sfrm=np.append(Costs_sfrm,Investment_sfrm[j])\n",
    "\n",
    "    ### Visualization of cost distribution per design\n",
    "    fig, ax = plt.subplots()\n",
    "    labels=['no SFRM','SFRM']\n",
    "    categories=['direct loss building','direct loss contents','indirect loss','fatalities','injuries','investment']\n",
    "    bar_width = 0.35\n",
    "    opacity = 0.8\n",
    "\n",
    "    cumCost=np.array([0,0])\n",
    "    for i, cat in enumerate(categories):\n",
    "        ax.bar(labels,[TotalCost_no_sfrm[i],TotalCost_sfrm[i]],bar_width,bottom=cumCost,label=cat)\n",
    "        cumCost=cumCost+np.array([TotalCost_no_sfrm[i],TotalCost_sfrm[i]])\n",
    "\n",
    "    #ax.set_ylim((0,8000))\n",
    "    ax.set_ylabel('PNV costs [USD]')\n",
    "    plt.title('PNV cost of design ' +str(j+1)+ '-hour fire rating (Eurocode model)')\n",
    "    handles, labels = ax.get_legend_handles_labels()\n",
    "    ax.legend(handles[::-1], labels[::-1])\n",
    "    ax.legend(labels,fontsize=16)\n",
    "    fig.set_size_inches(10,8)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Parameter study with damage area in the absence of structural failure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Function definition PNV Z, to allow parameter study psfrm and S_loss_s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Function combining above model assumption for parameter study\n",
    "\n",
    "def Zvalue(psfrm,S_loss_s):  \n",
    "    ## II. Design fire risk evaluation ##\n",
    "    #####################################    \n",
    "    ## II.2.b Scenario \"successful sprinkler suppression\"\n",
    "    ### Material loss\n",
    "    xi_d_s= S_loss_s * Replace_cost * eps_loss_content * eps_loss_indirect # [USD/fire] property loss given fire in case of succesful sprinkler suppression\n",
    "    ### Total loss valuation\n",
    "    Dsup=Df_s+Din_s+xi_d_s # [USD/fire] expected value fire-induced loss, scenario \"successful prevention of collapse due to SFRM\"\n",
    "    \n",
    "    ## III. PNV calculation ##\n",
    "    ##########################  \n",
    "    ## III.2.b Fire-induced losses trial design, D\n",
    "    ## Expected loss design with sprinkler protection\n",
    "    Dsp=(1-psfrm)*D0+psfrm*Dsup # [USD/fire]\n",
    "    ## PNV reference design\n",
    "    D=Dsp*lambda_fi/g # [USD] PNV expected risk to life reference design\n",
    "    \n",
    "    ## III.2.c PNV net benefit, B-D\n",
    "    netB=B-D # [USD] PNV net benefit\n",
    "    \n",
    "    ## IV. Cost-Benefit evaluation ##\n",
    "    #################################\n",
    "    #for i in np.arange(len(netB)):\n",
    "    Z=netB-net_C # [USD] PNV of proposed safety measure\n",
    "    BCR_var = netB/net_C\n",
    "    \n",
    "    return Z, BCR_var\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Example of usage function Zvalue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The PNV for SFRM fire protection is, \n",
      "\t1-hour prescribed rating: PNV 86,522 [USD] and BCR 1.34 (NFPA model); \n",
      "\t2-hour prescribed rating: PNV 1,957,343 [USD] and BCR 5.38 (NFPA model); \n",
      "\t3-hour prescribed rating: PNV 3,350,582 [USD] and BCR 5.35 (NFPA model); \n",
      "\t1-hour prescribed rating: PNV 2,834,258 [USD] and BCR 12.03 (Eurocode model); \n",
      "\t2-hour prescribed rating: PNV 9,284,639 [USD] and BCR 21.77 (Eurocode model); \n",
      "\t3-hour prescribed rating: PNV 9,761,966 [USD] and BCR 13.66 (Eurocode model); \n"
     ]
    }
   ],
   "source": [
    "# Example application of function Zvalue - verification base values\n",
    "\n",
    "# input values\n",
    "psfrm = psfrm # [-] probability of no structural failure due to presence of SFRM\n",
    "\n",
    "# CBA \n",
    "out=Zvalue(psfrm,S_loss_s) # [USD] PNV of proposed safety measure\n",
    "Z = out[0]; BCR_var = out[1]\n",
    "\n",
    "print(\"\\nThe PNV for SFRM fire protection is, \")\n",
    "for j,Zj in enumerate(Z):\n",
    "    if j<3: print(\"\\t{0:,.0f}-hour prescribed rating: PNV {1:,.0f} [USD] and BCR {2:.2f} (NFPA model); \".format(SFRM_time[j],Zj,BCR[j]))\n",
    "    else: print(\"\\t{0:,.0f}-hour prescribed rating: PNV {1:,.0f} [USD] and BCR {2:.2f} (Eurocode model); \".format(SFRM_time[j],Zj,BCR[j]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Parameter study and visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[    0.    940.5  1881.   2821.5  3762.   4702.5  5643.   6583.5  7524.\n",
      "  8464.5  9405.  10345.5 11286.  12226.5 13167.  14107.5 15048.  15988.5\n",
      " 16929.  17869.5 18810. ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams.update({'font.size': 15})\n",
    "\n",
    "psfrm = psfrm\n",
    "Dam_rate=np.array(range(0,105,5))\n",
    "Dam_area = (Dam_rate/100)*S_area # [m2] floor area damaged\n",
    "print(Dam_area)\n",
    "\n",
    "Zvalues=np.zeros((len(psfrm),len(Dam_area)))\n",
    "\n",
    "for i,area in enumerate(Dam_area):\n",
    "    out = Zvalue(psfrm,area)\n",
    "    Zvalues[:,i] = out[0]\n",
    "\n",
    "# Plot the data\n",
    "fig,ax = plt.subplots(1,1)\n",
    "\n",
    "color = (['r','r','r', 'g', 'g', 'g'])\n",
    "linestyle = (['solid','dashed','dashdot','solid','dashed','dashdot','solid','dashed','dashdot'])\n",
    "\n",
    "legends = []\n",
    "for j,ps in enumerate(psfrm):\n",
    "    ax.plot(Dam_rate,Zvalues[j,:]/1e3,linestyle=linestyle[j],color=color[j])\n",
    "    if j<3: legends.append(str(j+1)+'-hour fire rating (NFPA model) $P_{f}$ = '+str(round(1-ps,2)))\n",
    "    else: legends.append(str(j-2)+'-hour fire rating (Eurocode model) $P_{f}$ = '+str(round(1-ps,2)))\n",
    "\n",
    "ax.plot([0,100],[0,0],linestyle='solid',color='k',linewidth=3.0)\n",
    "ax.text(10,0.15,'Z = 0')\n",
    "ax.set_xlim([0,100])\n",
    "\n",
    "ax.set_xlabel('Damage area as percentage of total floor area [%]') \n",
    "ax.set_ylabel('Present net value, $Z$ [$10^3 $ USD]')\n",
    "ax.legend(legends,fontsize=12)\n",
    "\n",
    "fig.set_size_inches(12,8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}