diff --git a/TP Physique Equation de la chaleur/TP Physique Equation de la chaleur.ipynb b/TP Physique Equation de la chaleur/TP Physique Equation de la chaleur.ipynb index abf5afa..b64b33e 100644 --- a/TP Physique Equation de la chaleur/TP Physique Equation de la chaleur.ipynb +++ b/TP Physique Equation de la chaleur/TP Physique Equation de la chaleur.ipynb @@ -98,8 +98,11 @@ ] }, { - "metadata": {}, "cell_type": "code", + "execution_count": null, + "id": "d480d6e691bf7fbf", + "metadata": {}, + "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", @@ -151,14 +154,12 @@ "plt.title(\"Distribution de température\")\n", "plt.grid()\n", "plt.show()" - ], - "id": "d480d6e691bf7fbf", - "outputs": [], - "execution_count": null + ] }, { - "metadata": {}, "cell_type": "markdown", + "id": "24aae10ae7862f9c", + "metadata": {}, "source": [ "## Exercice 3\n", "$$\n", @@ -170,9 +171,192 @@ "$$\n", "\\frac{T^{n+1}_{i} - T^n_{i}}{\\Delta t} = D \\frac{T^{n}_{i-1} - 2T^n_{i} + T^{n}_{i+1}}{\\Delta x^2}\n", "$$\n", + "### Question 2: Donner l'expression de $T^{n+1}_{i} pour i \\in [1, N]$.\n", + "$$\n", + "(T^{n+1}_{i})_{i \\in [1, N]} = \\Delta t\n", + "$$\n", + "Conditions au bord:\n", + "$$\n", + "T(x = 0) = T(x = 1) = 0\n", + "$$\n", + "### Question 3: Comment adapter cette expression lorsque $i = 0$ et $i = N$?\n", + "$$\n", + "\\begin{cases}\n", + "i = 0 (condition \\space de \\space gauche) \\\\\n", + "i = N (condition \\space de \\space droite)\n", + "\\end{cases}\n", + "$$\n", + "\n", + "$$\n", + "T^{n+1}_{i} = T^n_{i} + \\frac{\\Delta t D}{\\Delta x^2} (T^{n}_{i-1} - 2T^n_{i} + T^{n}_{i+1}) = \\frac{\\Delta t D}{\\Delta x^2} T^{n}_{i-1} + (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) T^n_{i} + \\frac{\\Delta t D}{\\Delta x^2} T^{n}_{i+1}\n", + "$$\n", + "\n", + "$$\n", + "\\forall n T-1 = T_{n + 1} = 0\n", + "$$\n", + "\n", + "$$\n", + "i = 0 => T^{n+1}_{0} = (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) T^n_{0} + \\frac{\\Delta t D}{\\Delta x^2} T^{n}_{1}\n", + "$$\n", + "\n", + "$$\n", + "i = N => T^{n+1}_{N} = \\frac{\\Delta t D}{\\Delta x^2} T^n_{N-1} + (1 - 2\\frac{\\Delta t}{\\Delta x^2}) T^n_{N}\n", + "$$\n", + "Système linéaire:\n", + "$$\n", + "\\begin{cases}\n", + "(1 - 2\\frac{\\Delta t D}{\\Delta x^2}) T^n_{0} + \\frac{\\Delta t D}{\\Delta x^2} T^{n}_{1} \\\\\n", + "\\frac{\\Delta t D}{\\Delta x^2} T^n_{0} + (1 - 2\\frac{\\Delta t}{\\Delta x^2}) T^n_{1} + \\frac{\\Delta t D}{\\Delta x^2} T^{n}_{2} \\\\\n", + "\\vdots \\\\\n", + "\\frac{\\Delta t D}{\\Delta x^2} T^n_{i-1} + (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) T^n_{i} + \\frac{\\Delta t D}{\\Delta x^2} T^{n}_{i+1} \\\\\n", + "\\vdots \\\\\n", + "\\frac{\\Delta t D}{\\Delta x^2} T^n_{N-1} + (1 - 2\\frac{\\Delta t}{\\Delta x^2}) T^n_{N} + \\frac{\\Delta t D}{\\Delta x^2} T^{n}_{N+1} \\\\\n", + "\\end{cases}\n", + "$$\n", + "### Question 4: Mettre l'itération précédente sous la forme matricielle $T^{n+1} = M T^n + b$ avec $M$ une matrice de taille $N * N$ et $b$ un vecteur de taille $N$. On précisera les termes non nuls de $M$ et $b$.\n", + "Matrice du système (simplifiée pour $N = 6$, normalement $N$ indéfini)\n", + "$$\n", + "\\begin{bmatrix}\n", + "(1 - 2\\frac{\\Delta t D}{\\Delta x^2}) & \\frac{\\Delta t D}{\\Delta x^2} & 0 & 0 & 0 & 0 & 0\\\\\n", + "\\frac{\\Delta t D}{\\Delta x^2} & (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) & \\frac{\\Delta t D}{\\Delta x^2} & 0 & 0 & 0 & 0\\\\\n", + "0 & \\frac{\\Delta t D}{\\Delta x^2} & (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) & \\frac{\\Delta t D}{\\Delta x^2} & 0 & 0 & 0\\\\\n", + "0 & 0 & \\frac{\\Delta t D}{\\Delta x^2} & (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) & \\frac{\\Delta t D}{\\Delta x^2} & 0 & 0\\\\\n", + "0 & 0 & 0 & \\frac{\\Delta t D}{\\Delta x^2} & (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) & \\frac{\\Delta t D}{\\Delta x^2} & 0\\\\\n", + "0 & 0 & 0 & 0 & \\frac{\\Delta t D}{\\Delta x^2} & (1 - 2\\frac{\\Delta t D}{\\Delta x^2}) & \\frac{\\Delta t D}{\\Delta x^2}\\\\\n", + "0 & 0 & 0 & 0 & 0 & \\frac{\\Delta t D}{\\Delta x^2} & (1 - 2\\frac{\\Delta t D}{\\Delta x^2})\\\\\n", + "\\end{bmatrix}\n", + "\\begin{bmatrix}\n", + "T0\\\\\n", + "T1\\\\\n", + "T2\\\\\n", + "T3\\\\\n", + "T4\\\\\n", + "T5\\\\\n", + "T6\n", + "\\end{bmatrix}\n", + "=\n", + "\\begin{bmatrix}\n", + "0 \\\\\n", + "0 \\\\\n", + "0 \\\\\n", + "0 \\\\\n", + "0 \\\\\n", + "0 \\\\\n", + "0 \\\\\n", + "\\end{bmatrix}\n", + "$$\n", + "### Question 5: Générer plusieurs profils de température pour la condition initiale $T_{0}(x) = \\sin(\\pi x)$. Attention, la méthode dans ce cas n'est stable que si $\\Delta t < \\frac{\\Delta x^2}{D}$\n", + "\n" + ] + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-04-01T09:21:58.111941Z", + "start_time": "2025-04-01T09:21:58.029753Z" + } + }, + "cell_type": "code", + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Constantes et paramètres\n", + "N = 100\n", + "delta_t = 0.0005\n", + "delta_x2 = 1/N\n", + "D = 1\n", + "T0 = 0\n", + "T1 = 0\n", + "\n", + "if delta_t < (delta_x2 / 2 * D):\n", + "\n", + " M = np.zeros((N + 1, N + 1))\n", + "\n", + " # Remplissage de la matrice M\n", + " for i in range(N + 1):\n", + " if i == 0:\n", + " M[i, i] = (1 - 2 * delta_t * D / delta_x2)\n", + " M[i, i + 1] = delta_t * D / delta_x2\n", + " elif i == N:\n", + " M[i, i - 1] = delta_t * D / delta_x2\n", + " M[i, i] = (1 - 2 * delta_t * D / delta_x2)\n", + " else:\n", + " M[i, i - 1] = delta_t * D / delta_x2\n", + " M[i, i] = (1 - 2 * delta_t * D / delta_x2)\n", + " M[i, i + 1] = delta_t * D / delta_x2\n", + "\n", + " # Affichage de la matrice M\n", + " print(f\"Matrice M: {M}\")\n", + "\n", + " # Vecteur spatial pour tracer\n", + " x = np.linspace(0, 1, N+1)\n", + "\n", + " # Condition initiale T₀(x) = sin(πx)\n", + " T = np.sin(np.pi * x)\n", + " T[0] = T0\n", + " T[N] = T1\n", + "\n", + " # Temps de simulation\n", + " temps_final = 0.1\n", + " nb_iterations = int(temps_final / delta_t)\n", + "\n", + " # Sauvegarder quelques profils à différents temps\n", + " profils = [T.copy()]\n", + " temps_sauvegarde = [0, 0.01, 0.02, 0.05, 0.1]\n", + " indices_sauvegarde = [int(t/delta_t) for t in temps_sauvegarde[1:]]\n", + "\n", + " # Simulation de l'évolution temporelle\n", + " for n in range(nb_iterations):\n", + " T = M @ T\n", + " if n+1 in indices_sauvegarde:\n", + " profils.append(T.copy())\n", + "\n", + " # Tracer les profils de température\n", + " plt.figure(figsize=(10, 6))\n", + " for i, t in enumerate(temps_sauvegarde):\n", + " if i < len(profils):\n", + " plt.plot(x, profils[i], label=f't = {t}s')\n", + "\n", + " plt.xlabel('Position x')\n", + " plt.ylabel('Température T')\n", + " plt.title('Évolution de la température au cours du temps')\n", + " plt.legend()\n", + " plt.grid(True)\n", + " plt.show()\n", + "else:\n", + " print(\"Constante incorrect\")\n", + " print(f\"delta_t = {delta_t}\")\n", + " print(f\"(delta_x2 / 2 * D) = {(delta_x2 / 2 * D)}\")\n", "\n" ], - "id": "24aae10ae7862f9c" + "id": "5dd0262dc1cb55b", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Matrice M: [[0.9 0.05 0. ... 0. 0. 0. ]\n", + " [0.05 0.9 0.05 ... 0. 0. 0. ]\n", + " [0. 0.05 0.9 ... 0. 0. 0. ]\n", + " ...\n", + " [0. 0. 0. ... 0.9 0.05 0. ]\n", + " [0. 0. 0. ... 0.05 0.9 0.05]\n", + " [0. 0. 0. ... 0. 0.05 0.9 ]]\n" + ] + }, + { + "data": { + "text/plain": [ + "
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" 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