chapter6-2-ShockTubeProblem-FDS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 第6章 圧縮性流れの数値計算法その1（システム方程式の数値計算法）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.2 高解像度風上法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "jmax = 101\n",
    "dt = 0.002"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gamma = 1.4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "PI = 1.0\n",
    "RHOI = 1.0\n",
    "UI = 0.0\n",
    "\n",
    "PE = 0.1\n",
    "RHOE = 0.1\n",
    "UE = 0.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "xmin, xmid, xmax = 0.0, 0.5, 1.0\n",
    "x = np.linspace(xmin, xmax, jmax)\n",
    "\n",
    "dx = (xmax - xmin) / (jmax - 1)\n",
    "\n",
    "dtdx = dt / dx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Roeスキームによる計算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def init():\n",
    "    Q = np.zeros([jmax, 3])\n",
    "\n",
    "    Q[x <= xmid, 0] = RHOI\n",
    "    Q[x <= xmid, 1] = RHOI * UI\n",
    "    Q[x <= xmid, 2] = (PI / (gamma - 1.0) + 0.5 * RHOI * UI ** 2)\n",
    "\n",
    "    Q[x > xmid, 0] = RHOE\n",
    "    Q[x > xmid, 1] = RHOE * UE\n",
    "    Q[x > xmid, 2] = (PE / (gamma - 1.0) + 0.5 * RHOE * UE ** 2)\n",
    "\n",
    "    return Q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_CFL(Q):\n",
    "    rho, rhou, e = Q[:, 0], Q[:, 1], Q[:, 2]\n",
    "    \n",
    "    u = rhou / rho\n",
    "    p = (gamma - 1.0) * (e - 0.5 * rho * u ** 2)\n",
    "    \n",
    "    c = np.sqrt(gamma * p / rho)\n",
    "    sp = c + np.abs(u)\n",
    "    return max(sp) * dtdx   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Roe_flux(QL, QR, E):\n",
    "    for j in range(jmax - 1):        \n",
    "        rhoL, uL, pL = QL[    j, 0], QL[    j, 1], QL[    j, 2]\n",
    "        rhoR, uR, pR = QR[j + 1, 0], QR[j + 1, 1], QR[j + 1, 2]\n",
    "        \n",
    "        rhouL = rhoL * uL\n",
    "        rhouR = rhoR * uR\n",
    "\n",
    "        eL = pL / (gamma - 1.0) + 0.5 * rhoL * uL ** 2\n",
    "        eR = pR / (gamma - 1.0) + 0.5 * rhoR * uR ** 2\n",
    "\n",
    "        HL = (eL + pL) / rhoL\n",
    "        HR = (eR + pR) / rhoR\n",
    "        \n",
    "        cL = np.sqrt((gamma - 1.0) * (HL - 0.5 * uL ** 2))\n",
    "        cR = np.sqrt((gamma - 1.0) * (HR - 0.5 * uR ** 2))\n",
    "                \n",
    "        # Roe平均 式(6.38)        \n",
    "        sqrhoL = np.sqrt(rhoL)\n",
    "        sqrhoR = np.sqrt(rhoR)\n",
    "\n",
    "        rhoAVE = sqrhoL * sqrhoR\n",
    "        uAVE = (sqrhoL * uL + sqrhoR * uR) / (sqrhoL + sqrhoR)\n",
    "        HAVE = (sqrhoL * HL + sqrhoR * HR) / (sqrhoL + sqrhoR) \n",
    "        cAVE = np.sqrt((gamma - 1.0)* (HAVE - 0.5 * uAVE ** 2))\n",
    "        eAVE = rhoAVE * (HAVE - cAVE ** 2 / gamma)\n",
    "        \n",
    "        dQ = np.array([rhoR - rhoL, rhoR * uR - rhoL * uL, eR - eL])\n",
    "        \n",
    "        Lambda = np.diag([np.abs(uAVE - cAVE), \n",
    "                                              np.abs(uAVE), \n",
    "                                                          np.abs(uAVE + cAVE)])\n",
    "        \n",
    "        b1 = 0.5 * (gamma - 1.0) * uAVE ** 2 / cAVE ** 2\n",
    "        b2 = (gamma - 1.0) / cAVE ** 2\n",
    "\n",
    "        R = np.array([[               1.0,              1.0,                1.0],\n",
    "                      [       uAVE - cAVE,             uAVE,        uAVE + cAVE],\n",
    "                      [HAVE - uAVE * cAVE, 0.5 * uAVE ** 2, HAVE + uAVE * cAVE]])\n",
    "        \n",
    "        Rinv = np.array([[0.5 * (b1 + uAVE / cAVE), -0.5 * (b2 * uAVE + cAVE), 0.5 * b2],\n",
    "                         [                1.0 - b1,                 b2 * uAVE,      -b2],\n",
    "                         [0.5 * (b1 - uAVE / cAVE), -0.5 * (b2 * uAVE - cAVE), 0.5 * b2]])\n",
    "        \n",
    "        AQ = R @ Lambda @ Rinv @ dQ\n",
    "        \n",
    "        \n",
    "        EL = np.array([rhoL * uL, pL + rhouL * uL, (eL + pL) * uL])\n",
    "        ER = np.array([rhoR * uR, pR + rhouR * uR, (eR + pR) * uR])\n",
    "        \n",
    "        E[j] = 0.5 * (ER + EL - AQ) # 式(6.43)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def minmod(x, y):\n",
    "    sgn = np.sign(x)\n",
    "    return sgn * np.maximum(np.minimum(np.abs(x), sgn * y), 0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def MUSCL(Q, order, kappa):\n",
    "    # 基本変数で内挿する\n",
    "    \n",
    "    rho, rhou, e = Q[:, 0], Q[:, 1], Q[:, 2]\n",
    "    \n",
    "    Q[:, 1] = rhou / rho  # u\n",
    "    Q[:, 2] = (gamma - 1.0) * (e - 0.5 * rho * Q[:, 1] ** 2) # p\n",
    "    \n",
    "    if order == 2 or order == 3:\n",
    "        # 2nd / 3rd order & minmod limitter\n",
    "        dQ = np.zeros([jmax, 3])\n",
    "        for j in range(jmax - 1):\n",
    "            dQ[j] = Q[j+1] - Q[j]\n",
    "        \n",
    "        b = (3.0 - kappa) / (1.0 - kappa) # 式(2.74)\n",
    "        \n",
    "        Dp = np.zeros([jmax, 3])\n",
    "        Dm = np.zeros([jmax, 3])\n",
    "        for j in range(1, jmax - 1):\n",
    "            Dp[j] = minmod(dQ[j]  , b * dQ[j - 1]) # 式(2.73a)\n",
    "            Dm[j] = minmod(dQ[j-1], b * dQ[j])     # 式(2.73b)\n",
    "        Dp[0] = Dp[1]\n",
    "        Dm[0] = Dm[1]\n",
    "        \n",
    "        QL = Q.copy()\n",
    "        QR = Q.copy()\n",
    "        for j in range(1, jmax - 1):\n",
    "            QL[j] += 0.25 * ((1.0 - kappa) * Dp[j] + (1.0 + kappa) * Dm[j]) # 式(2.72a)\n",
    "            QR[j] -= 0.25 * ((1.0 + kappa) * Dp[j] + (1.0 - kappa) * Dm[j]) # 式(2.72b)\n",
    "        \n",
    "    else:\n",
    "        # 1st order\n",
    "        QL = Q.copy()\n",
    "        QR = Q.copy()\n",
    "\n",
    "    return QL, QR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Roe_FDS(Q, order, kappa, nmax, print_interval = 2):\n",
    "    E = np.zeros([jmax, 3])\n",
    "\n",
    "    for n in range(nmax):\n",
    "        if n % print_interval == 0:\n",
    "            print(f'n = {n : 4d} : CFL = {calc_CFL(Q) : .4f}')\n",
    "\n",
    "        Qold = Q.copy()\n",
    "        \n",
    "        coefs = [0.5, 1.0]\n",
    "        for coef in coefs:\n",
    "            QL, QR = MUSCL(Qold, order, kappa)\n",
    "        \n",
    "            Roe_flux(QL, QR, E)\n",
    "            for j in range(1, jmax - 1):\n",
    "                Qold[j] = Q[j] - coef * dtdx * (E[j] - E[j-1])\n",
    "            \n",
    "            Qold[0] = Q[0]\n",
    "            Qold[-1] = Q[-1]\n",
    "    \n",
    "        Q[:] = Qold[:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n =    0 : CFL =  0.2366\n",
      "n =    4 : CFL =  0.4206\n",
      "n =    8 : CFL =  0.4332\n",
      "n =   12 : CFL =  0.4619\n",
      "n =   16 : CFL =  0.4750\n",
      "n =   20 : CFL =  0.4793\n",
      "n =   24 : CFL =  0.4823\n",
      "n =   28 : CFL =  0.4838\n",
      "n =   32 : CFL =  0.4840\n",
      "n =   36 : CFL =  0.4825\n",
      "n =   40 : CFL =  0.4822\n",
      "n =   44 : CFL =  0.4806\n",
      "n =   48 : CFL =  0.4803\n",
      "n =   52 : CFL =  0.4797\n",
      "n =   56 : CFL =  0.4791\n",
      "n =   60 : CFL =  0.4788\n",
      "n =   64 : CFL =  0.4785\n",
      "n =   68 : CFL =  0.4785\n",
      "n =   72 : CFL =  0.4785\n",
      "n =   76 : CFL =  0.4784\n",
      "n =   80 : CFL =  0.4784\n",
      "n =   84 : CFL =  0.4783\n",
      "n =   88 : CFL =  0.4782\n",
      "n =   92 : CFL =  0.4782\n",
      "n =   96 : CFL =  0.4781\n"
     ]
    }
   ],
   "source": [
    "nmax = 100\n",
    "print_interval = 4\n",
    "\n",
    "order = 2\n",
    "\n",
    "# -1  = 2nd order fully upwind, \n",
    "# 0   = 2nd order upwind biased\n",
    "# 1/3 = 3rd order upwind biased\n",
    "kappa = 0\n",
    "\n",
    "Q = init()\n",
    "Roe_FDS(Q, order, kappa, nmax, print_interval)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 厳密解の計算"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 初期化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "Pext = np.zeros([jmax, 3])\n",
    "Qext = np.zeros([jmax, 3])\n",
    "\n",
    "GUESS = 1.0\n",
    "FINC = 0.01\n",
    "itemax1 = 5000\n",
    "itemax2 = 500\n",
    "\n",
    "CI = np.sqrt(gamma * PI / RHOI)\n",
    "CE = np.sqrt(gamma * PE / RHOE)\n",
    "P1P5 = PI / PE\n",
    "\n",
    "GAMI = 1.0 / gamma\n",
    "GAMF = (gamma - 1.0) / (2.0 * gamma)\n",
    "GAMF2 = (gamma + 1.0) / (gamma - 1.0)\n",
    "GAMFI = 1.0 / GAMF\n",
    "\n",
    "for it1 in range(itemax1):\n",
    "    for it2 in range(itemax2):\n",
    "        SQRT1 = (gamma - 1.0) * (CE / CI) * (GUESS - 1.0)\n",
    "        SQRT2 = np.sqrt(2.0 * gamma * (2.0 * gamma + (gamma + 1.0) * (GUESS - 1.0)))\n",
    "        FUN = GUESS * (1.0 - (SQRT1 / SQRT2)) ** (-GAMFI)\n",
    "        DIF = P1P5 - FUN\n",
    "        \n",
    "        if np.abs(DIF) <= 0.000002:\n",
    "            break\n",
    "        \n",
    "        if DIF >= 0.0:\n",
    "            GUESS += FINC\n",
    "        else:\n",
    "            GUESS -= FINC\n",
    "            FINC = 0.5 * FINC\n",
    "    else:\n",
    "        continue\n",
    "    \n",
    "    break\n",
    "\n",
    "P4P5 = GUESS\n",
    "P4 = PE * P4P5\n",
    "P3P1 = P4P5 / P1P5\n",
    "P3 = P3P1 * PI\n",
    "\n",
    "R4R5 = (1.0 + GAMF2 * P4P5) / (GAMF2 + P4P5)\n",
    "RHO4 = RHOE * R4R5\n",
    "U4 = CE * (P4P5 - 1.0) * np.sqrt(2.0 * GAMI / ((gamma + 1.0) * P4P5 + (gamma - 1.0)))\n",
    "C4 = np.sqrt(gamma * P4 / RHO4)\n",
    "\n",
    "R3R1 = P3P1 ** GAMI\n",
    "RHO3 = RHOI * R3R1 \n",
    "U3 = 2.0 * CI / (gamma - 1.0) * (1.0 - P3P1 ** GAMF)\n",
    "C3 = np.sqrt(gamma * P3 / RHO3)\n",
    "CS =  CE * np.sqrt(0.5 * ((gamma - 1.0) * GAMI + (gamma + 1.0) * GAMI * P4 / PE))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 計算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "TOT = 0.0\n",
    "EPST = 1.0e-14\n",
    "for n in range(nmax):\n",
    "    TOT = TOT + dt\n",
    "    rad = dt / dx\n",
    "    \n",
    "    x1 = xmid - CI * TOT\n",
    "    x2 = xmid - (CI - 0.5 * (gamma + 1.0) * U3) * TOT\n",
    "    x3 = xmid + U3 * TOT\n",
    "    x4 = xmid + CS * TOT\n",
    "    \n",
    "    for j in range(jmax):\n",
    "        xx = x[j]\n",
    "        if xx <= x1:\n",
    "            Qext[j, 0] = RHOI\n",
    "            Qext[j, 1] = RHOI * UI\n",
    "            Qext[j, 2] = PI / (gamma - 1.0) + 0.5 * UI * Qext[j, 1]\n",
    "            Pext[j] = PI\n",
    "        elif xx <= x2:\n",
    "            UT = UI + (U3 - UI) / ((x2 - x1) + EPST) * ((xx - x1) + EPST)\n",
    "            RTRI = (1.0 - 0.5 * (gamma - 1.0) * UT / CI) ** (2.0 / (gamma - 1.0))\n",
    "            RT = RHOI * RTRI\n",
    "            PT = RTRI ** gamma * PI\n",
    "            Qext[j, 0] = RT\n",
    "            Qext[j, 1] = RT * UT\n",
    "            Qext[j, 2] = PT / (gamma - 1.0) + 0.5 * UT * Qext[j, 1]\n",
    "            Pext[j] = PT\n",
    "        elif xx <= x3:\n",
    "            Qext[j, 0] = RHO3\n",
    "            Qext[j, 1] = RHO3 * U3\n",
    "            Qext[j, 2] = P3 / (gamma - 1.0) + 0.5 * U3 * Qext[j, 1]\n",
    "            Pext[j] = P3\n",
    "        elif xx <= x4:\n",
    "            Qext[j, 0] = RHO4\n",
    "            Qext[j, 1] = RHO4 * U4\n",
    "            Qext[j, 2] = P4 / (gamma - 1.0) + 0.5 * U4 * Qext[j, 1]\n",
    "            Pext[j] = P4\n",
    "        else:\n",
    "            Qext[j, 0] = RHOE\n",
    "            Qext[j, 1] = RHOE * UE\n",
    "            Qext[j, 2] = PE / (gamma - 1.0) + 0.5 * UE * Qext[j, 1]\n",
    "            Pext[j] = PE            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 結果の可視化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,7), dpi=100) # グラフのサイズ\n",
    "plt.rcParams[\"font.size\"] = 22 # グラフの文字サイズ\n",
    "plt.plot(x, Qext[:,0], color='black', linewidth = 1.0, linestyle = 'dashed', label = 'Analytical')\n",
    "plt.plot(x, Q[:,0], color='red', linewidth = 1.5, label = 'Numerical')\n",
    "plt.grid(color='black', linestyle='dotted', linewidth=0.5)\n",
    "plt.xlabel('x')\n",
    "plt.ylabel(r'$\\rho$')\n",
    "#plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,7), dpi=100) # グラフのサイズ\n",
    "plt.rcParams[\"font.size\"] = 22 # グラフの文字サイズ\n",
    "plt.plot(x, Qext[:,1]/Qext[:,0], color='black', linewidth = 1.0, linestyle = 'dashed', label = 'Analitical')\n",
    "plt.plot(x, Q[:,1]/Q[:,0], color='red', linewidth = 1.5, label = 'Numerical')\n",
    "plt.grid(color='black', linestyle='dotted', linewidth=0.5)\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('u')\n",
    "#plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,7), dpi=100) # グラフのサイズ\n",
    "plt.rcParams[\"font.size\"] = 22 # グラフの文字サイズ\n",
    "yext = (gamma - 1.0) * (Qext[:,2] - 0.5 * Qext[:,1] ** 2 / Qext[:,0])\n",
    "y = (gamma - 1.0) * (Q[:,2] - 0.5 * Q[:,1] ** 2 / Q[:,0])\n",
    "plt.plot(x, yext, color='black', linewidth = 1.0, linestyle = 'dashed',label = 'Analytical')\n",
    "plt.plot(x, y, color='red', linewidth = 1.5,  label = 'Numerical')\n",
    "plt.grid(color='black', linestyle='dotted', linewidth=0.5)\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('p')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}