ec2-creep.ipynb

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   "id": "martial-canadian",
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   "source": [
    "## Eurocode 2 - creep"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "id": "technological-detective",
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   "source": [
    "%matplotlib inline\n",
    "import math as m\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import ipywidgets as widgets\n",
    "from ipywidgets import HBox, VBox\n",
    "from ipywidgets import interact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dynamic-trademark",
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   "source": [
    "h0 = widgets.FloatSlider(value=200,min=100,max=1000,step=0.025,description='h0 (mm):',readout_format='.0f')\n",
    "t = widgets.FloatLogSlider(value=100000,min=0,max=6,step=0.025,description='t (d):',readout_format='.0f')\n",
    "t0 = widgets.FloatSlider(value=10,min=3,max=60,step=1,description='t0 (d):',readout_format='.0f')\n",
    "rh = widgets.FloatSlider(value=80,min=0,max=100,step=1,description='RH (%):',readout_format='.0f')\n",
    "fck = widgets.FloatSlider(value=20,min=20,max=50,step=5,description='fck (MPa):',readout_format='.0f')\n",
    "fck2 = widgets.Dropdown(\n",
    "    options=[('C20/25', 20.0), ('C25/30', 25.0), ('C30/37', 30.0), ('C35/45', 35.0), ('C40/50', 40.0), ('C45/55', 45.0), ('C50/60', 50.0)],\n",
    "    value=20,\n",
    "    description='Concrete:',\n",
    ")\n",
    "cem = widgets.Dropdown(\n",
    "    options=[('Type R', 1.0), ('Type N', 0.0), ('Type S', -1.0)],\n",
    "    value=0.0,\n",
    "    description='Cement:'\n",
    ")"
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   "id": "bibliographic-sight",
   "metadata": {},
   "source": [
    "### Creep coefficient according to Annex B.1 of Eurocode 2\n",
    "\n",
    "This function calculates the creep coefficient. Input parameters are: \n",
    "* age\n",
    "* relative humidity\n",
    "* time of first load\n",
    "* concrete compressive strength \n",
    "* cement type parameter (-1 for Type S, 0 for Type N and 1 for Type R)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "conscious-addiction",
   "metadata": {
    "hide_input": true
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   "outputs": [],
   "source": [
    "def creep_coef(t=28, h0=100,rh=65, t0=10, fck=20.0, cem=0.0):\n",
    "    fcm = fck+8\n",
    "    alpha1 = (35/fcm)**0.7\n",
    "    alpha2 = (35/fcm)**0.2\n",
    "    alpha3 = min(1.0, (35/fcm)**0.5)\n",
    "    tt0 = t0*((1.0+9.0/(2.0+t0**1.2))**cem)\n",
    "    phi_RH = (1.0-rh/100)/(0.1*(h0**0.33333333))\n",
    "    phi_RH = 1.0+phi_RH if fcm <= 35 else (1.0+phi_RH*alpha1)*alpha2\n",
    "    beta_fcm = 16.8/m.sqrt(fcm)\n",
    "    beta_t0 = 1.0/(0.1+tt0**0.2)\n",
    "    phi_0 = beta_fcm*beta_t0*phi_RH\n",
    "\n",
    "    try:        \n",
    "        betah = min(1500*alpha3, 1.5*(1.0+m.pow(0.012*rh,18))*h0+250*alpha3)\n",
    "        beta_cc = m.pow((t-t0)/(betah+t-t0), 0.3)\n",
    "        phi = beta_cc*phi_0    \n",
    "    except:\n",
    "        beta_cc = 0.0\n",
    "        phi = 0.0\n",
    "\n",
    "    return phi"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adverse-stanley",
   "metadata": {},
   "source": [
    "Interactive formula for calculating creep coefficient, $\\varphi$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "continental-motion",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "interactive(children=(FloatLogSlider(value=100000.0, description='t (d):', max=6.0, readout_format='.0f', step…"
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   ],
   "source": [
    "@interact(h0=h0, t=t, t0=t0, rh=rh, fck=fck, cem=cem)\n",
    "def creepcoef(t=28, h0=100,rh=65, t0=10, fck=20.0, cem=0.0):\n",
    "    creep = creep_coef(t, h0, rh, t0, fck, cem)\n",
    "    #print(\"fhi={:.3f} betha_cc={:.3f} fhi_0={:.3f}\".format(phi, beta_cc, phi_0))\n",
    "    print(\"fhi={:.3f}\".format(creep))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "soviet-departure",
   "metadata": {},
   "source": [
    "Formula for calculating creep coefficiente by editing and changing input data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "pretty-planner",
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     "output_type": "stream",
     "text": [
      "fhi=3.203\n"
     ]
    }
   ],
   "source": [
    "_t = 10000000 # days\n",
    "_h0 = 2*250*250/(4*250) # mm\n",
    "_rh = 65 # %\n",
    "_t0 = 10 # days\n",
    "_fck = 20 # MPa\n",
    "_cem = 0 # R = 1, N = 0, S = -1\n",
    "creepcoef(_t,_h0,_rh,_t0,_fck,_cem)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "improving-insertion",
   "metadata": {},
   "source": [
    "Graphic for displaying evolution of creep with time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "local-satellite",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "interactive(children=(FloatSlider(value=200.0, description='h0 (mm):', max=1000.0, min=100.0, readout_format='…"
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "tt = np.logspace(1.0, 6)\n",
    "vfunc = np.vectorize(creep_coef)\n",
    "@interact(h0=h0, t0=t0, rh=rh, fck=fck, cem=cem)\n",
    "def draw_creep(h0, t0, rh, fck, cem):\n",
    "    creep = vfunc(tt, h0, rh, t0, fck, cem)\n",
    "    print(\"fhi={:.3f}\".format(creep[49]))\n",
    "    plt.xscale(\"log\")\n",
    "    plt.xlabel(\"Time (days)\")\n",
    "    plt.ylabel(\"Creep coefficient\")\n",
    "    plt.plot(tt, creep)"
   ]
  },
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   "execution_count": 17,
   "id": "waiting-science",
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       "125.0"
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    "_h0"
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   "cell_type": "code",
   "execution_count": null,
   "id": "speaking-norwegian",
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