From d1375d494185e7222dc619c00a8eff0faabb1b32 Mon Sep 17 00:00:00 2001 From: dug20 Date: Fri, 30 Apr 2021 18:10:52 +0100 Subject: [PATCH] Updated 'Introduction to Bamboo'. Changed defaults 'h' models. Now uses Bartz (with sigma) for gas side and Sieder-Tate for coolant side. Have modified the Sieder-Tate implementation to avoid a boil-off problem. Has not been checked thoroughly but seems to work as of now. --- Introduction to Bamboo.ipynb | 380 +++++++++++++++--- bamboo/cooling.py | 50 ++- bamboo/main.py | 87 ++-- docs/_autosummary/bamboo.cooling.html | 4 +- .../_autosummary/bamboo.cooling.doctree | Bin 29722 -> 29667 bytes docs/build/doctrees/environment.pickle | Bin 33422 -> 33508 bytes docs/build/doctrees/index.doctree | Bin 599646 -> 599564 bytes docs/index.html | 54 +-- docs/searchindex.js | 2 +- 9 files changed, 441 insertions(+), 136 deletions(-) diff --git a/Introduction to Bamboo.ipynb b/Introduction to Bamboo.ipynb index 62aae1e..9884426 100644 --- a/Introduction to Bamboo.ipynb +++ b/Introduction to Bamboo.ipynb @@ -6,18 +6,23 @@ "source": [ "# Introduction to Bamboo\n", "\n", - "*March 2021*\n", + "*April 2021*\n", "\n", "Bamboo is Python package for modelling the cooling systems of liquid rocket engines. \n", "\n", - "Most of its functionality revolves around the bamboo.main.Engine class. Full documentation is available at https://cuspaceflight.github.io/bamboo/." + "Most of its functionality revolves around the bamboo.main.Engine class. Full documentation is available at https://cuspaceflight.github.io/bamboo/.\n", + "\n", + "### Contents: \n", + "- Simple Engine Example\n", + "- Running a cooling system analysis\n", + "- Running a stress analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## *Simple Engine Example*\n", + "## *Simple Engine Example* \n", "\n", "We will start with an example of creating an Engine. \n", "\n", @@ -32,8 +37,18 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, - "outputs": [], + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Warning: Missing or invalid temperature-strength relationship. Stress results invalid for at least one material.\n" + ] + } + ], "source": [ "import bamboo as bam\n", "import numpy as np\n", @@ -65,7 +80,9 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "perfect_gas = bam.PerfectGas(gamma = gamma, molecular_weight = molecular_weight)\n", @@ -89,15 +106,15 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "scrolled": true + "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "WARNING: Area ratio is outside the range of the Rao inflection angle data, returning 15 deg instead.\n", - "WARNING: Area ratio is outside the range of the Rao exit angle data, returning 14.999 deg instead.\n" + "bamboo.main.rao_theta_n(): Area ratio is outside the range of the Rao inflection angle data, returning 15 deg instead.\n", + "bamboo.main.rao_theta_e(): Area ratio is outside the range of the Rao exit angle data, returning 14.999 deg instead.\n" ] }, { @@ -161,7 +178,9 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "engine = bam.Engine(perfect_gas, chamber, nozzle)" @@ -179,7 +198,9 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stdout", @@ -215,7 +236,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## *Running a cooling system analysis*\n", + "## *Running a cooling system analysis* \n", "\n", "To run a cooling system analysis, we need to specify the following:\n", "- Engine geometry, using **Engine.add_geometry()**.\n", @@ -237,7 +258,9 @@ { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "#We'll set up a very crude exhaust gas model using thermo.\n", @@ -258,11 +281,13 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "metadata": { + "scrolled": false + }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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\n", 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\n", 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" ] @@ -290,10 +315,10 @@ "Ac = np.pi*0.1**2 #Chamber cross-sectional area (m^2) - we'll use a 0.1 m radius.\n", "L_star = 1.5 #Use the idea of L*: L_star = Volume_c/Area_t\n", "chamber_length = L_star*nozzle.At/Ac\n", - "wall_thickness = 2e-3 #Thickness of engine wall (m)\n", + "inner_wall_thickness = 2e-3 #Thickness of engine wall (m)\n", "\n", "'''Add the geometry to the engine and plot it'''\n", - "engine.add_geometry(chamber_length, Ac, wall_thickness)\n", + "engine.add_geometry(chamber_length, Ac, inner_wall_thickness)\n", "engine.plot_geometry()\n", "plt.title(\"Engine geometry - by default the wall thickness is shown to scale\")\n", "\n", @@ -308,7 +333,7 @@ "plt.show()\n", "\n", "#(Add the normal geometry back for later)\n", - "engine.add_geometry(chamber_length, Ac, wall_thickness)" + "engine.add_geometry(chamber_length, Ac, inner_wall_thickness)" ] }, { @@ -321,11 +346,13 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -341,19 +368,19 @@ "#We'll use the 'thermo' module to get transport properties for our coolant.\n", "#As an alternative, you could also use the 'CoolProp' module.\n", "thermo_coolant = thermo.chemical.Chemical('isopropanol')\n", - "coolant_transport = bam.cooling.TransportProperties(model = \"thermo\", thermo_object = thermo_coolant, force_phase = 'l')\n", + "coolant_transport = bam.cooling.TransportProperties(model = \"thermo\", thermo_object = thermo_coolant)\n", "\n", "'''Cooling jacket properties'''\n", "inlet_T = 298.15 #Coolant inlet temperature (K)\n", - "inlet_p0 = 20e5 #Coolant inlet stagnation pressure (bar)\n", + "inlet_p0 = 30e5 #Coolant inlet stagnation pressure (bar)\n", "OF_ratio = 3.5 #Oxidiser/fuel mass ratio\n", "mdot_coolant = mdot/(OF_ratio + 1) #Mass flow rate of coolant\n", - "wall_material = bam.materials.CopperC700\n", + "inner_wall_material = bam.materials.CopperC700\n", "\n", "'''Add a spiral cooling jacket to the engine'''\n", "#See the documentation for a full list of cooling jacket options\n", "#You can also alternatively use vertical channels, or have the cooling jacket on present over a finite range of the engine.\n", - "engine.add_cooling_jacket(wall_material, \n", + "engine.add_cooling_jacket(inner_wall_material, \n", " inlet_T, \n", " inlet_p0, \n", " coolant_transport, \n", @@ -373,17 +400,19 @@ "metadata": {}, "source": [ "### Ablative*\n", - "*note that right now, ablatives are only modelled as thermal insulators" + "*note that right now, ablatives are only modelled as thermal insulators. If a wall material is specified for the ablative, it will override the inner wall material specified for the cooling jacket, in the area where the ablative is applied." ] }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, + "execution_count": 15, + "metadata": { + "scrolled": false + }, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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" ] @@ -414,7 +443,7 @@ "#By default the program will use an ablative along the whole engine,\n", "#and will fill up the gap between the nozzle contour and chamber radius with ablative\n", "engine.add_ablative(ablative_material,\n", - " wall_material, \n", + " inner_wall_material, \n", " regression_rate = 0.0033e-3)\n", "\n", "engine.plot_geometry()\n", @@ -424,7 +453,7 @@ "\n", "#In this example we make the ablative only present in the nozzle, and make it thickest around the middle.\n", "engine.add_ablative(ablative_material,\n", - " wall_material, \n", + " inner_wall_material, \n", " regression_rate = 0.0033e-3,\n", " xs = [engine.geometry.x_chamber_end, engine.geometry.x_max],\n", " ablative_thickness = [0.0, 0.02, 0.0])\n", @@ -434,7 +463,7 @@ "\n", "#(Replace the ablative with the 1st version - this is the one we'll analyse later)\n", "engine.add_ablative(ablative_material,\n", - " wall_material, \n", + " inner_wall_material, \n", " regression_rate = 0.0033e-3)\n" ] }, @@ -449,55 +478,56 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": {}, + "execution_count": 21, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "Wall tempreature was above coolant boiling point when using the Sieder-Tate equation (h_coolant_model = '2') - coolant boiling temperature was used instead of wall temperature.\n", "Exported JSON data to 'heating_output.json'\n", - "Exported JSON data to 'heating_output.json'\n", - "dict_keys(['x', 'T_wall_inner', 'T_wall_outer', 'T_coolant', 'T_gas', 'q_dot', 'h_gas', 'h_coolant', 'p_coolant', 'boil_off_position'])\n" + "\n", + "dict_keys(['x', 'q_dot', 'T_ablative_inner', 'T_wall_inner', 'T_wall_outer', 'T_coolant', 'T_gas', 'h_gas', 'h_coolant', 'R_gas', 'R_ablative', 'R_wall', 'R_coolant', 'p_coolant', 'p0_coolant', 'mu_gas', 'k_gas', 'Pr_gas', 'Pr_coolant', 'mu_coolant', 'k_coolant', 'cp_coolant', 'rho_coolant', 'v_coolant', 'boil_off_position'])\n" ] } ], "source": [ "#Run the heating analysis - see the documentation for details on the various arguments.\n", - "#We'll try using the two different 'h_gas_model' options, so we can compare them.\n", - "data_hgas1 = engine.steady_heating_analysis(h_gas_model = '1')\n", - "data_hgas3 = engine.steady_heating_analysis(h_gas_model = '3')\n", + "cooling_data = engine.steady_heating_analysis()\n", "\n", "#Print of the keys so we can see what data is available\n", - "print(data_hgas1.keys())" + "print(\"\")\n", + "print(cooling_data.keys())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Note that the 'x' position array runs 'in reverse' - it starts with index [0] at the nozzle exit, and moves towards the chamber. The data in all the other arrays corresponds to the x positions given in the 'x' array.\n", - "\n", - "So e.g. `data_hgas1['T_gas'][0]` is the exhaust gas temperature at nozzle exit, and `data_hgas1['T_gas'][-1]` is the exhaust gas temperature in the chamber." + "Plot the results:" ] }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, + "execution_count": 16, + "metadata": { + "scrolled": false + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Final x position = -0.4163781058592353\n", - "Coolant exit temperature with h_gas_model = '1': 396.0721179787813 K\n", - "Coolant exit temperature with h_gas_model = '3': 388.3356288298858 K\n" + "Coolant exit temperature: 440.7072479415034 K\n" ] }, { "data": { - "image/png": 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57PfNb36TV155BXDtBZw5c6bW9RYXF9OuXTscDgdvvPFGveOq0L17d4qKiioLiMPhYMeOHZf0KSkp4fTp04waNYoZM2awdetWv7dnjKkf2wMJMxFh6dKlPPXUU0ydOpXk5GTS0tKYMWMGgwYNYuPGjWRlZSEivPTSS7Rt25YxY8Z4XF5xCMlXffv25c477yQrK4tOnTqRm5tLq1atavT77W9/y8SJE5k9ezbx8fG88sorNQ4lVfXCCy/Qv39/OnXqRM+ePSkuLq7vrwWAxMREFi9ezKRJkzh9+jRlZWU89dRTZGZmVvYpLi5m9OjRlJaWoqr85je/8Wtbxpj6k7oOY4jIVcCj1HygVNTdC5Kbm6v5+fmXLNu5cyfXX399QLcTSdN51KWkpIQWLVpw7tw5Bg0axMyZM+nTp4/f64vE3IPxN/aksTzS1V+xnH9jz11EClS1xn0BvuyBLAM+AlYBzkAHZsJr4sSJfP7555SWljJ+/PgGFQ9jTGzxpYA0U9UfBT0SExbz588PdwjGmCjly0n0d0VkVNAjMcYYE1V8KSDfx1VESkWk2P2q/TIcY4wxjZ4vNxJG1hlRY4wxEcGny3hF5E6gYq6MPJtA0RhjTJ2HsERkKq7DWJ+7X993LzMBtHTpUkSEXbt2AZdOhlhdWloax48fr3V9L7744iWfb7jhhsAEaowxbr7sgYwCslW1HEBE5gFbgMkN3biIjAR+C8QDr6nq1Grt4m4fBZwDJqjqZl/G+mv69OmcPXs2EKsCoHnz5j7NELtgwQJuuukmFi5cyJQpUxq83RdffJEf//jHlZ8rZtA1xphA8XUqk9ZV3te8VdkPIhIP/B64FcgAxolIRrVutwJd3a+JwCv1GOuXQBYPX9dXUlLCxx9/zOzZsyufCQJw5swZxowZQ0ZGBo8//jjl5eU1xt51113k5OSQmZnJzJkzAdf05ufPnyc7O5v7778fgBYtWgDw7W9/mxUrVlSOnzBhAkuWLMHpdPLMM8/Qt29fevXqxR/+8IcG5W2Mafx8KSD/CWwRkbnuvY8C4MU6xviiH7BXVfep6kVgITC6Wp/RwOvq8gnQWkTa+Tg2arz99tuMHDmSbt260aZNGzZv3gzAp59+yq9+9Su2bdvGF198wVtv1XyK8Jw5cygoKCA/P5+XX36ZEydOMHXqVJo2bcrWrVtrzEU1duzYyueHXLx4kdWrVzNq1Chmz55Nq1at2LRpE5s2bWLWrFns378/+MkbY6KWL4+0XQAMwPUM9LeAgaq6sPZRPukAHKryudC9zJc+voyNGgsWLGDs2LGA6wt+wYIFgGuK82uvvZb4+HjGjRvH+vXra4x9+eWXycrKYsCAARw6dIg9e2qfef/WW29lzZo1XLhwgffff59BgwbRtGlTVq5cyeuvv052djb9+/fnxIkTda7LGBPbanukbbqq7hKRirktCt0/24tI+4pzEQ0gHpZVn5jLWx9fxrpWIDIR1+EvUlJSLplaHKBVq1Z+T/bnq9rWf+LECdasWcO2bdsQEZxOJyLCkCFDKC8vrxxbWlqKw+GguLgYVaWkpIRPP/2UDz74gJUrV9KsWTNGjRrF119/XTmm+nYrPt944428/fbbLF68mPvuu4/i4mIcDgfTpk3jlltu8Tl2T5xOZ9B/n/VVWlpa4+8eDCUlJSHZTqSK5fxjNffaTqL/ANcX7688tCkwtIHbLgQ6VvmcChzxsU+iD2NdgarOBGaCazLF6hOe7dy5M+iT/9W2/vnz5/Pggw9ecs5h8ODBbN68mYKCAo4fP06nTp1YtmwZEydOpGXLlogILVq0wOFwcOWVV5KSksKuXbvYtGkTzZo1o2XLliQkJJCcnExCQkKNOB544AFee+018vPzeeONN0hMTOS2225j3rx53H777SQkJLB79246dOhA8+bN65VrJE6mmJycTO/evYO+ncY+oV5dYjn/WM3d6yEsVZ3ofnurqt5c9YXrqqiG2gR0FZHOIpIIjAWWV+uzHHhQXAYAp1X1qI9jo8KCBQsYM2bMJcvuuece5s+fz8CBA5k8eTI9evSgc+fONfqNHDmSsrIyevXqxfPPP8+AAQMq2yZOnEivXr0qT6JXNXz4cNatW8ctt9xCYmIiAI888ggZGRn06dOHHj168Nhjj1FWVhaEjI0xjYUvl/FuAKpP0eppWb2oapmIfA/4ANeluHNUdYeIPO5ufxVYgatY7cV1Ge9DtY1tSDwVmjdvHvDLeGvjabd30qRJTJo0yeuYqs/9eP/99z32mTZtGtOmTav8XFJSUvk+ISGBEydOXNI/Li6OF198scb9I8YY401t50Da4jox3VREevPP8w6XAc0CsXFVXYGrSFRd9mqV9wp819exgeDLPRt1icTDOMYYE2i17YGMACbgOr/w6yrLi4EfexpgjDEmdngtIKo6D5gnIveo6pIQxmSMMSYK1HYI6zuq+icgTUR+UL1dVX/tYZgxxpgYUdshrIqzvy1CEYgxxpjoUtshrD+4f/4sdOEYY4yJFr5M5/6SiFwmIgkislpEjovId0IRXKyIj48nOzu78jV1qv8TCwdq2vYpU6Ywffp0AH7yk5+watWqgKzXGNN4+HIfyHBV/aGIjMF1Z/h9wFrgT0GNLEzatoVjxxq6ln9ewpuSAl9+WXvviokPAyEY07b//Oc/D8h6ysrKaNLEp2eYGWOigC+z8VbMhTEKWKCqXwcxnrBrePEI3PrS0tL46U9/Sp8+fejZs2flw6aKiooYNmwYffr04bHHHqNTp06VD5iqmLa9YmqFe++9l/T0dO6//35ct9VAQUEBgwcPJicnhxEjRnD06NFa45gwYQKLFy+uNaazZ8/y8MMPM3jwYHr37s2yZcsAmDt3Lvfddx933HEHw4cP9/+XYYyJOL4UkHdEZBeQC6wWkauA0uCGFVsqnt1R8aqYbh3gyiuvZPPmzTzxxBOVh5R+9rOfMXToUDZv3syYMWM4ePCgx/Vu2bKFGTNm8Pnnn7Nv3z4+/vhjHA4HTz75JIsXL6agoICHH36YZ599tl7xeorpl7/8JUOHDuXDDz9k7dq1PPPMM5V39G/cuJF58+axZs0af349xpgIVefxBFWdLCLTgDOq6hSRs0TxszciUW2HsO6++24AcnJyKp8Hsn79epYuXQq45sO6/PLLPY7t168fqampAGRnZ3PgwAFat27N9u3bGTZsGOCaPbddu3b1itdTTCtXrmT58uW89NJLxMXFUVpaWlnYhg0bRps2beq1DWNM5KuzgIhIAvAAMMj1hFk+BF6tdZAJmKSkJMB1or1icsOKQ1G+jq06XlXJzMxk48aNAY9pyZIltG/f/pJpXP7617/We0ZfY0x08OUQ1itADvA/7lcf9zITJjfddBOLFi0CXP/nf/LkSZ/Hdu/enaKiosoC4nA42LGj4fNQjhgxgt/97neVxW3Lli0NXqcxJrL5UkD6qup4VV3jfj0E9A12YLGk+jmQyZMn19r/pz/9KStXrqRPnz68//77tGvXzufJGxMTE1m8eDE/+tGPyMrKIjs7OyBXbj3//PM4HA4GDhxIjx49eP755xu8TmNMhFPVWl/AZqBLlc/XApvrGheJr5ycHK3u888/v+RzSooqBO6VklJjkw1WWlqqDodDVVU3bNigWVlZgd+In86cORPuEGqo/jcOlrVr14ZkO5EqlvNv7LkD+erhO9WXi/KfAdaKyD5cU7p3wv1cjsaorns2fBHs6dwPHjzIt771LcrLy0lMTGTWrFlB25Yxxnjjy1VYq0WkK9AdVwHZpaoXgh6Z8apr1652jsEYE3a+XIWVDPwbcBOuZ6F/JCKvqqrdC2KMMTHMl0NYr+N6iNTv3J/HAX/ENaVJo6CquC9RNo2M+njJszGm/nwpIN1VNavK57Ui8lmwAgq15ORkTpw4wRVXXGFFpJFRVU6cOEFycnK4QzGmUfKlgGwRkQGq+gmAiPQHPg5uWKGTmppKYWEhRUVFAVtnaWlpzH5pRVruycnJlXfjG2MCy5cC0h94UEQqJly6BtgpItsAVdVeQYsuBBISEujcuXNA15mXl0fv3r0Dus5oEcu5GxNrfCkgI4MehTHGmKjjy2W8/whFIMYYY6KLL1OZBJyItBGRv4jIHvdPj9PJishIEfm7iOwVkclVlk8RkcMistX9GhW66I0xxkCYCggwGVitql2B1e7PlxCReOD3wK1ABjBORDKqdPmNqma7XytCEbQxxly4cIHjx49z6NAh9u7dy65duygtLWXfvn2cOnUqpi4d9+VGwu8Bb6iq71O+1m00MMT9fh6QB/yoWp9+wF5V3eeOY6F73OcBjMMYYzwqKyvjyJEjHD58mEOHDnHs2DHOnDlDeXk5TZo0ueSy/7S0NBYtWoTT6SQpKanyyZyN/RHOUle1FJFfAGNxTao4B/hAG1hiReSUqrau8vmkql5erc+9wEhVfcT9+QGgv6p+T0SmABOAM0A+8O/eCpyITAQmAqSkpOQsXLiwIaH7pKSkpPLRsrHGco/N3KFx5O90OiktLeX8+fM4HA5ExKc9iqSkJC5c+OcMTxXFpWXLljRr1izq7zG7+eabC1Q1t/ryOgsIgLiyH45rEsVcYBEwW1W/qGXMKqCth6ZngXk+FJD7gBHVCkg/VX1SRFKA47imVnkBaKeqD9eVR25urubn59fVrcEqnkceiyz3IeEOI2yiNf+zZ8+ydetWCgoKKC4uRlVxOp31Wke3bt3YvXt3jeUJCQkA9O7dm4EDB9K6detAhBxyIuKxgPi0f6WqKiJfAl8CZcDlwGIR+Yuq/tDLmFtqCeaYiLRT1aMi0g74ykO3QqBjlc+pwBH3uo9VWdcs4F1f8jDGmAqHDx9m3bp1fPHFF4hI5dM1A8nhcACQn5/P5s2b6dixIzfccANdunSJ+r0S8O0cyCRgPK7/438NeEZVHSISB+wBPBaQOix3r3Oq++cyD302AV1FpDNwGNdhtH9xx9ROVY+6+40BtvsRgzEmBh08eJCVK1fy1VdfVX7BB1t5eTnl5eXs37+fw4cPk5CQQN++fenduzeXXXZZSGIIBl/2QK4E7q5+P4iqlovI7X5udyqwSET+FTiIe2JGEWkPvKaqo1S1zH0C/wMgHpijqhXPXn1JRLJxHcI6ADzmZxzGmBhx/Phx3nvvPQ4fPhyywuHJxYsXuXjxIh999BEfffQR7du3p1+/fqSnp0fdSXdfbiT8SS1tO/3ZqKqeAL7pYfkRYFSVzyuAGpfoquoD/mzXGBN7HA4Ha9asIT8/H6fTGTGX2VacZ6m4wmvZsmWkp6fTu3dv0tLSiIsL110WvouucmeMMfVw6NAhFi1aRGlpaVDOcQTKxYsXAdi+fTu7d+9GRMjMzCQrK4uOHTtG7PkSKyDGmEanvLyctWvX8sknn0R04fCkophs2bKF7du3ExcXR0ZGBj169KBTp04RtWdiBcQY06icO3eOBQsWcOzYsagrHlWpao1iAq5HWvfo0YMuXbpUXiYcLlZAjDGNRlFREfPmzeP8+fOUl5eHO5yAqVpMduzYwZ49e3A6nXTo0IGePXvSrVu3sFzNZQXEGNMoHDx4kDfeeKPyi7Yxq8jx4MGDHD16lA8++IAWLVpw/fXX0717d1JTU4mPjw96HFZAjDFRb+/evSxatCisl+eGS0XOp06d4pNPPqGgoIDy8nI6duzI9ddfz3XXXcfll3uc8LzBrIAYY6JaLBeP6qoe6tq/fz+FhYWsXLmSxMRE7rjjDtLT0wO6vcg5nW+MMfVkxaN2DoeDsrIyzp07x8GDB+seUE9WQIwxUcmKR/hZATHGRB0rHpHBCogxJqpY8YgcVkCMMVHDikdksQJijIkKVjwijxUQY0zEs+IRmayAGGMimhWPyGUFxBgTsax4RDYrIMaYiGTFI/JZATHGRBwrHtHBCogxJqJY8YgeVkCMMRHDikd0sQJijIkIVjyijxUQY0zYWfGITlZAjDFhZcUjeoWlgIhIGxH5i4jscf/0+LgsEZkjIl+JyHZ/xhtjIpsVj+gWrj2QycBqVe0KrHZ/9mQuMLIB440xEWrv3r28+eabVjyiWLgKyGhgnvv9POAuT51UdR3wtb/jjTGRqaJ4lJWVhTsU0wCiqqHfqMgpVW1d5fNJVfV2GCsNeFdVe/g5fiIwESAlJSVn4cKFfsW8ffsFLl5MRKTu31eHDmc5fLi5X9uJdpZ7bOYO/uYvQYkl1Dp0KOHw4RbhDsOr8nLh6qtL6dgx2a/xN998c4Gq5lZf3qTBkXkhIquAth6ang3WNj1R1ZnATIDc3FwdMmSIX+sZujwNbfUP7x3K4yHOCcD0ttN5+szTXtvrGh/N7R5zj6D4gtk+ve00z7lHSHyWf/Dap6d4+Xfv6/pPdXL9bO3lOyYA7T84so8HHgjsQaegFRBVvcVbm4gcE5F2qnpURNoBX9Vz9Q0dX2/a6h+8lup97+ORQqlsb5WQV6Nv1fa6xkdzu6fcIym+YLZ3Ssjx2icS4rP8g9d+Sn7VsPW798S8/v4C0P5v3wnCGQtVDfkL+C9gsvv9ZOClWvqmAdv9HV/1lZOTo/5iCj63r127tkHjo7ndU+6h3H44273lHqrth7s9lvOfPn96g9dfW59AtDcEkK8evlPDdRJ9KjBMRPYAw9yfEZH2IrKiopOILAA2At1FpFBE/rW28cYYY0InaIewaqOqJ4Bvelh+BBhV5fO4+ow3xhgTOnYnujHGGL9YATHGGOMXKyDGGGP8YgXEGGOMX8JyJ3q45Obman5+vl9j02ak8Y/T3m8kjJd4nOq+kbDbdJ7e/bTX9rrGR3O7p9wjKb5gtk/rOs1j7pESn+UfvHZv/+59Hd+pletGQG/fMYFoP/DUAa/br4uIhPZO9MamPr/8vLw8dFzsFOaqLPfYzB1iO/9Yzd0OYRljjPGLFRBjjDF+sQJijDHGL1ZAjDHG+MUKiDHGGL/E1GW8IlIE1PJQj4C5Ejgegu1EIss9dsVy/o09906qelX1hTFVQEJFRPI9XTMdCyz32MwdYjv/WM3dDmEZY4zxixUQY4wxfrECEhwzwx1AGFnusSuW84/J3O0ciDHGGL/YHogxxhi/WAFpIBFpIyJ/EZE97p+X19I3XkS2iMi7oYwxmHzJX0SSReRTEflMRHaIyM/CEWug+Zh7RxFZKyI73bl/PxyxBpqv/+5FZI6IfCUi20MdY6CJyEgR+buI7BWRyR7aRURedrf/TUT6hCPOULIC0nCTgdWq2hVY7f7szfeBnSGJKnR8yf8CMFRVs4BsYKSIDAhdiEHjS+5lwL+r6vXAAOC7IpIRwhiDxdd/93OBkaEKKlhEJB74PXArkAGM8/B3vBXo6n5NBF4JaZBhYAWk4UYD89zv5wF3eeokIqnAbcBroQkrZOrMX11K3B8T3K/GcPLNl9yPqupm9/tiXP8D0SFUAQaRT//uVXUd8HWIYgqmfsBeVd2nqheBhbh+B1WNBl53/3v/BGgtIu1CHWgoWQFpuBRVPQquLwvgai/9ZgA/BMpDFFeo+JS/+/DdVuAr4C+q+tfQhRg0vv7tARCRNKA3EHO5NwIdgENVPhdS838EfOnTqNgDpXwgIquAth6anvVx/O3AV6paICJDAhhaSDQ0fwBVdQLZItIaWCoiPVQ14o+LByJ393paAEuAp1T1TCBiC7ZA5d5IiIdl1feifenTqFgB8YGq3uKtTUSOiUg7VT3q3l39ykO3G4E7RWQUkAxcJiJ/UtXvBCnkgApA/lXXdUpE8nAdF4/4AhKI3EUkAVfxeENV3wpSqAEXyL97I1AIdKzyORU44kefRsUOYTXccmC8+/14YFn1Dqr6H6qaqqppwFhgTbQUDx/Umb+IXOXe80BEmgK3ALtCFWAQ+ZK7ALOBnar66xDGFmx15t7IbAK6ikhnEUnE9d/x8mp9lgMPuq/GGgCcrjjM12ipqr0a8AKuwHUVyh73zzbu5e2BFR76DwHeDXfcocwf6AVsAf6Ga6/jJ+GOO4S534TrMMbfgK3u16hwxx6K3N2fFwBHAQeu/0P/13DH3oCcRwG7gS+AZ93LHgced78XXFdqfQFsA3LDHXOwX3YnujHGGL/YISxjjDF+sQJijDHGL1ZAjDHG+MUKiDHGGL9YATHGGOMXKyDGhIiIPC4iD7rfTxCR9lXaXgvUJIsicpeI/KSeY1bVNpO0MZ7YZbzGhIH7bvynVTU/COveANypqsfrMWY8kKqqvwx0PKbxsj0QE9NEpK/72Q3JItLc/cyOHtX6pInILhGZ5+67WESaudu+6X7Gyzb3sy+S3Munisjn7v7T3cumiMjTInIvkAu8ISJbRaSpiOSJSK673zj3+raLyLQqcZSIyC/F9VyVT0QkxUM+3YALFcVDROaKyCvuZ5LsE5HB7jh3isjcKkOXA+MC+bs1jZ8VEBPTVHUTri/PXwAvAX9Sz5M8dgdmqmov4AzwbyKSjOt5F99W1Z645pZ7QkTaAGOATHf/X1Tb5mIgH7hfVbNV9XxFm/uw1jRgKK5np/QVkbvczc2BT9T1XJV1wKMe4rwR2Fxt2eXu9f0/4B3gN0Am0FNEst0xnQSSROQKr78sY6qxAmIM/BwYhmuv4CUvfQ6p6sfu93/CNUVJd2C/qu52L58HDMJVYEqB10TkbuBcPWLpC+SpapGqlgFvuNcJcBGoeJplAZDmYXw7oKjasnfUdax6G3BMVbepajmwo9o6vsI1FYkxPrECYgy0AVoALXHNluxJ9ZOFiufpu3F/8ffDNQPvXcD/1SMWj+t0c+g/T1o68Tyb9nlq5nDB/bO8yvuKz1XXkeweb4xPrIAYAzOB53H93/40L32uEZGB7vfjgPW4ZhROE5Hr3MsfAD50P/ujlaquAJ7CdSiqumJcBau6vwKDReRK92NUxwEf1iOXncB1dfaqxj1rcFvgQH3HmthlBcTENPdltWWqOh+Yiuucw1APXXcC40Xkb7j2WF5R1VLgIeDPIrIN1//Rv4qrMLzr7vshrnMP1c0FXq04iV6xUF3Tf/8HsBb4DNisqvWZKn0d0NtdEOojB9f5lbJ6jjMxzC7jNaYO7kfRvquqPerqGwlE5Le4znusqueY5aq6OniRmcbG9kCMaXxeBJrVc8x2Kx6mvmwPxBhjjF9sD8QYY4xfrIAYY4zxixUQY4wxfrECYowxxi9WQIwxxvjFCogxxhi//H94d/YnhXzffAAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" ] @@ -546,21 +576,251 @@ ], "source": [ "#Print the final coolant temperatures in each case:\n", - "print(f\"Final x position = {data_hgas1['x'][-1]}\") \n", - "print(f\"Coolant exit temperature with h_gas_model = '1': {data_hgas1['T_coolant'][-1]} K\")\n", - "print(f\"Coolant exit temperature with h_gas_model = '3': {data_hgas3['T_coolant'][-1]} K\")\n", + "print(f\"Final x position = {cooling_data['x'][-1]}\") \n", + "print(f\"Coolant exit temperature: {cooling_data['T_coolant'][-1]} K\")\n", "\n", "#Plot the geometry again so we can compare it\n", "engine.plot_geometry()\n", "\n", "#Use the built in plotting functions to quickly generate some plots\n", - "bam.plot.plot_temperatures(data_hgas1)\n", - "plt.title(\"Using h_gas_model = '1'\")\n", + "bam.plot.plot_temperatures(cooling_data)\n", + "bam.plot.plot_temperatures(cooling_data, show_ablative = True, show_gas = True)\n", "\n", - "bam.plot.plot_temperatures(data_hgas3)\n", - "plt.title(\"Using h_gas_model = '3'\")\n", + "bam.plot.plot_jacket_pressure(cooling_data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## *Running a stress analysis* \n", + "\n", + "As of now, some stress analysis features don't fully work with spiralling cooling channels. So we'll create a new engine that uses 'vertical' cooling channels instead. \n", "\n", - "bam.plot.plot_jacket_pressure(data_hgas1)" + "Additional engine properties need to be specified to run the stress analysis, including:\n", + "- Outer wall thickness and material for the cooling jacket\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Respecify the cooling jacket, but this time with the outer wall specified.\n", + "outer_wall_material = bam.materials.StainlessSteel304\n", + "outer_wall_thickness = 4e-3\n", + "\n", + "engine.add_geometry(chamber_length, Ac, inner_wall_thickness, outer_wall_thickness)\n", + "\n", + "engine.add_cooling_jacket(inner_wall_material, \n", + " inlet_T, \n", + " inlet_p0, \n", + " coolant_transport, \n", + " mdot_coolant, \n", + " configuration = \"vertical\",\n", + " channel_height = 0.001, \n", + " blockage_ratio = 0.5, \n", + " outer_wall = outer_wall_material)\n", + "\n", + "engine.plot_geometry()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#Steady state stress analysis\n", + "steady_stress_data = engine.run_stress_analysis(heating_result = cooling_data, condition = \"steady\")\n", + "\n", + "#Transient stress analysis\n", + "transient_stress_data = engine.run_stress_analysis(heating_result = cooling_data, condition= \"transient\", T_amb = inlet_T)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "dict_keys(['thermal_stress', 'yield_adj', 'deltaT_wall', 'stress_inner_hoop_steady', 'stress_outer_hoop'])\n", + "\n", + "dict_keys(['stress_inner_hoop_transient', 'stress_inner_IE', 'stress_outer_IE'])\n" + ] + } + ], + "source": [ + "#Show what keys are available from the resulting data\n", + "print(\"\")\n", + "print(steady_stress_data.keys())\n", + "print(\"\")\n", + "print(transient_stress_data.keys())" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Graph results - copied from Henry Free's stress_example.py\n", + "xs = cooling_data[\"x\"]\n", + "threshold = 0.5\n", + "\n", + "#If a hoop or inner expansion stress exceeds this proportion of nominal yield stress,\n", + "#then show the nominal yield stress on the plot to make it clear this could be problematic\n", + "fig1, axs1 = plt.subplots(figsize=(12, 7))\n", + "fig2, axs2 = plt.subplots(figsize=(12, 7))\n", + "fig3, axs3 = plt.subplots(figsize=(12, 7))\n", + "\n", + "axs1.plot(xs, steady_stress[\"thermal_stress\"]/1E6, label = \"Thermal stress\")\n", + "axs1.plot(xs, steady_stress[\"yield_adj\"]/1E6, label = \"Temperature compensated yield stress\")\n", + "axs1.set_title(\"Steady state operation: Inner liner\")\n", + "axs1.set_xlabel(\"Axial displacement from throat $(m)$\")\n", + "axs1.set_ylabel(\"Stress $(MPa)$\")\n", + "axs1.set_ylim([0, None])\n", + "axs1.legend(bbox_to_anchor = (0, -0.16), loc = \"lower left\")\n", + "\n", + "axs1_2 = axs1.twinx()\n", + "axs1_2.plot(xs, steady_stress[\"deltaT_wall\"], color = \"red\", label = \"Coolant side to chamber side $\\Delta T$\")\n", + "axs1_2.set_ylabel(\"Temperature difference ($\\Delta K$)\")\n", + "axs1_2.set_ylim([0, None])\n", + "axs1_2.legend(bbox_to_anchor = (0, -0.22), loc = \"lower left\")\n", + "\n", + "fig1.subplots_adjust(bottom = 0.16)\n", + "\n", + "axs2.plot(xs, steady_stress[\"stress_inner_hoop_steady\"]/1E6, label = \"Inner liner, prior to ignition\")\n", + "axs2.plot(xs, transient_stress[\"stress_inner_hoop_transient\"]/1E6, label = \"Inner liner, after ignition\")\n", + "axs2.plot(xs, steady_stress[\"stress_outer_hoop\"]/1E6, label = \"Outer liner\")\n", + "ymax2 = axs2.get_ylim()[1]\n", + "\n", + "if np.max(steady_stress[\"stress_inner_hoop_steady\"]) > threshold*inner_wall_material.sigma_y or \\\n", + " np.max(transient_stress[\"stress_inner_hoop_transient\"]) > threshold*inner_wall_material.sigma_y:\n", + " axs2i = axs2.twinx()\n", + " axs2i.get_yaxis().set_visible(False)\n", + " axs2i.hlines(inner_wall_material.sigma_y/1E6, xs[0], xs[-1], linestyles = \"dashed\", color = \"indianred\",\n", + " label = \"Nominal inner liner yield stress\")\n", + " ymax2 = max((ymax2, 1.1*inner_wall_material.sigma_y/1E6))\n", + " axs2i.set_ylim(0, ymax2)\n", + " axs2i.legend(bbox_to_anchor = (0.7, -0.11), loc = \"lower left\")\n", + "\n", + "if np.max(steady_stress[\"stress_outer_hoop\"]) > threshold*outer_wall_material.sigma_y:\n", + " axs2o = axs2.twinx()\n", + " axs2o.get_yaxis().set_visible(False)\n", + " axs2o.hlines(outer_wall_material.sigma_y/1E6, xs[0], xs[-1], linestyles = \"dashed\", color = \"maroon\",\n", + " label = \"Nominal outer liner yield stress\")\n", + " ymax2 = max((ymax2, 1.1*outer_wall_material.sigma_y/1E6))\n", + " try:\n", + " axs2i.set_ylim(0, ymax2)\n", + " except NameError:\n", + " pass\n", + " axs2o.set_ylim(0, ymax2)\n", + " axs2o.legend(bbox_to_anchor = (0.7, -0.15), loc = \"lower left\")\n", + "\n", + "axs2.set_title(\"Hoop stresses\")\n", + "axs2.set_xlabel(\"Axial displacement from throat $(m)$\")\n", + "axs2.set_ylabel(\"Stress $(MPa)$\")\n", + "axs2.legend(bbox_to_anchor = (0, -0.19), loc = \"lower left\")\n", + "axs2.set_ylim([0, ymax2])\n", + "\n", + "fig2.subplots_adjust(bottom = 0.14)\n", + "\n", + "axs3.plot(xs, np.abs(transient_stress[\"stress_inner_IE\"]/1E6), label = \"Inner liner\")\n", + "axs3.plot(xs, np.abs(transient_stress[\"stress_outer_IE\"]/1E6), label = \"Outer liner\")\n", + "ymax3 = axs3.get_ylim()[1]\n", + "\n", + "if np.max(np.abs(transient_stress[\"stress_inner_IE\"])) > threshold*inner_wall_material.sigma_y:\n", + " axs3i = axs3.twinx()\n", + " axs3i.get_yaxis().set_visible(False)\n", + " axs3i.hlines(inner_wall_material.sigma_y/1E6, xs[0], xs[-1], linestyles = \"dashed\", color = \"indianred\",\n", + " label = \"Nominal inner liner yield stress\")\n", + " ymax3 = max((ymax3, 1.1*inner_wall_material.sigma_y/1E6))\n", + " axs3i.set_ylim(0, ymax3)\n", + " axs3i.legend(bbox_to_anchor = (0.7, -0.11), loc = \"lower left\")\n", + "\n", + "if np.max(np.abs(transient_stress[\"stress_outer_IE\"])) > threshold*outer_wall_material.sigma_y:\n", + " axs3o = axs3.twinx()\n", + " axs3o.get_yaxis().set_visible(False)\n", + " axs3o.hlines(outer_wall_material.sigma_y/1E6, xs[0], xs[-1], linestyles = \"dashed\", color = \"maroon\",\n", + " label = \"Nominal outer liner yield stress\")\n", + " ymax3 = max((ymax3, 1.1*outer_wall_material.sigma_y/1E6))\n", + " try:\n", + " axs3i.set_ylim(0, ymax3)\n", + " except NameError:\n", + " pass\n", + " axs3o.set_ylim(0, ymax3)\n", + " axs3o.legend(bbox_to_anchor = (0.7, -0.15), loc = \"lower left\")\n", + "\n", + "axs3.set_title(\"Absolute stresses due to constrained inner liner expansion\")\n", + "axs3.set_xlabel(\"Axial displacement from throat $(m)$\")\n", + "axs3.set_ylabel(\"Stress $(MPa)$\")\n", + "axs3.legend(bbox_to_anchor = (0, -0.15), loc = \"lower left\")\n", + "axs3.set_ylim([0, ymax3])\n", + "\n", + "fig3.subplots_adjust(bottom = 0.12)\n", + "\n", + "plt.show()" ] }, { diff --git a/bamboo/cooling.py b/bamboo/cooling.py index b2e2dcd..fa60e0f 100644 --- a/bamboo/cooling.py +++ b/bamboo/cooling.py @@ -49,8 +49,10 @@ def black_body(T): return SIGMA*T**4 def h_gas_1(D, M, T, rho, gamma, R, mu, k, Pr): - """Get the convective heat transfer coefficient on the gas side, non-Bartz equation. - Uses Eqn (8-22) on page 312 or RPE 7th edition (Reference [2]) + """Get the convective heat transfer coefficient on the gas side. Uses Eqn (8-22) on page 312 or RPE 7th edition (Reference [2]). I believe this is just a form of the Dittius-Boelter equation. + + Note: + Seems to give much lower wall temperatures than the Bartz equation, and is likely less accurate. h_gas_2 and h_gas_3 are likely more accurate. Args: D (float): Flow diameter (m) @@ -75,9 +77,6 @@ def h_gas_2(D, cp_inf, mu_inf, Pr_inf, rho_inf, v_inf, rho_am, mu_am, mu0): """Bartz equation, using Equation (8-23) from page 312 of RPE 7th edition (Reference [2]). 'am' refers to the gas being at the 'arithmetic mean' of the wall and freestream temperatures. - Note: - Seems to provide questionable results - may have been implemented incorrectly. - Args: D (float): Gas flow diameter (m) cp_inf (float): Specific heat capacity at constant pressure for the gas, in the freestream @@ -233,12 +232,13 @@ def __init__(self, E, sigma_y, poisson, alpha, k, **kwargs): self.perf_therm = (1 - self.poisson) * self.k / (self.alpha * self.E) #Performance coefficient for thermal stress, higher is better def __repr__(self): - return f"""bamboo.cooling.Material Object \nYoung's modulus = {self.E/1e9} GPa -0.2% Yield Stress = {self.sigma_y/1e6} MPa -Poisson's ratio = {self.poisson} -alpha = {self.alpha} strain/K -Thermal conductivity = {self.k} W/m/K -(may also have a specific heat capacity (self.c) and density (self.rho))""" + return f"""bamboo.cooling.Material Object + Young's modulus = {self.E/1e9} GPa + 0.2% Yield Stress = {self.sigma_y/1e6} MPa + Poisson's ratio = {self.poisson} + alpha = {self.alpha} strain/K + Thermal conductivity = {self.k} W/m/K + (may also have a specific heat capacity (self.c) and density (self.rho))""" def relStrength(self, T, ignoreLowTemp = False, ignoreHighTemp = False): """Uses polynomial coefficients to determine the fraction of yield stress @@ -341,7 +341,6 @@ def check_liquid(self, T, p): return True else: return False - def k(self, T, p): """Thermal conductivity @@ -361,7 +360,11 @@ def k(self, T, p): elif self.force_phase == 'g': return self.thermo_object.kg else: - return self.thermo_object.k + #Manually check which phase we're in, and return the right conductivity (otherwise sometimes it seems to return odd results) + if self.thermo_object.phase == 'l': + return self.thermo_object.kl + elif self.thermo_object.phase == 'g': + return self.thermo_object.kg elif self.model == "CoolProp": return PropsSI("CONDUCTIVITY", "T", T, "P", p, self.coolprop_name) @@ -400,6 +403,7 @@ def mu(self, T, p): elif self.model == "custom": return self.custom_mu + def Pr(self, T, p): """Prandtl number @@ -418,7 +422,11 @@ def Pr(self, T, p): elif self.force_phase == 'g': return self.thermo_object.Prg else: - return self.thermo_object.Pr + #Manually check which phase we're in, and return the right property + if self.thermo_object.phase == 'l': + return self.thermo_object.Prl + elif self.thermo_object.phase == 'g': + return self.thermo_object.Prg elif self.model == "CoolProp": return PropsSI("PRANDTL", "T", T, "P", p, self.coolprop_name) @@ -445,7 +453,11 @@ def cp(self, T, p): elif self.force_phase == 'g': return self.thermo_object.Cpg else: - return self.thermo_object.Cp + #Manually check which phase we're in, and return the right property + if self.thermo_object.phase == 'l': + return self.thermo_object.Cpl + elif self.thermo_object.phase == 'g': + return self.thermo_object.Cpg elif self.model == "CoolProp": return PropsSI("CPMASS", "T", T, "P", p, self.coolprop_name) @@ -469,8 +481,12 @@ def rho(self, T, p): elif self.force_phase == 'g': return self.thermo_object.rhog else: - return self.thermo_object.rho - + #Manually check which phase we're in, and return the right property + if self.thermo_object.phase == 'l': + return self.thermo_object.rhol + elif self.thermo_object.phase == 'g': + return self.thermo_object.rhog + elif self.model == "CoolProp": return PropsSI("DMASS", "T", T, "P", p, self.coolprop_name) diff --git a/bamboo/main.py b/bamboo/main.py index cbc5deb..09fa449 100644 --- a/bamboo/main.py +++ b/bamboo/main.py @@ -1417,17 +1417,17 @@ def regen_ablative_thermal_circuit(self, r, h_gas, h_coolant, wall_material, inn return q_dot, R_gas, R_ablative, R_wall, R_coolant, - def steady_heating_analysis(self, number_of_points=1000, h_gas_model = "1", h_coolant_model = "1", to_json = "heating_output.json"): + def steady_heating_analysis(self, number_of_points=1000, h_gas_model = "3", h_coolant_model = "2", to_json = "heating_output.json"): """Steady state heating analysis. Can be used for regenarative cooling, or combined regenerative and ablative cooling. Args: number_of_points (int, optional): Number of discrete points to divide the engine into. Defaults to 1000. - h_gas_model (str, optional): Equation to use for the gas side convective heat transfer coefficients. Options are '1', '2' and '3'. Defaults to "1". - h_coolant_model (str, optional): Equation to use for the coolant side convective heat transfer coefficients. Options are '1', '2' and '3'. Defaults to "1". + h_gas_model (str, optional): Equation to use for the gas side convective heat transfer coefficients. Options are '1', '2' and '3'. Defaults to "3". + h_coolant_model (str, optional): Equation to use for the coolant side convective heat transfer coefficients. Options are '1', '2' and '3'. Defaults to "2". to_json (str or bool, optional): Directory to export a .JSON file to, containing simulation results. If False, no .JSON file is saved. Defaults to 'heating_output.json'. Note: - h_gas_model = '2' seems to provide questionable results (if it works at all) - use it with caution. h_coolant_model = '2' can raise errors if using the 'force_phase' setting with your coolant TransportProperties object. See the functions h_gas_1(), h_gas_2(), h_coolant_1(), etc.. in the documentation for details on each model. + See the bamboo.cooling module for explanations of each h_gas and h_coolant option. Defaults are Bartz (using sigma correlation) for gas side, and Sieder-Tate for coolant side. These are believed to be the most accurate. Returns: dict: Results of the simulation. Contains the following dictionary keys: @@ -1526,18 +1526,34 @@ def steady_heating_analysis(self, number_of_points=1000, h_gas_model = "1", h_co Pr_gas[i]) elif h_gas_model == "2": - #We need the previous wall temperature to use h_gas_3. If we're on the first step, then just use h_gas_1() + #We need the previous wall temperature to use h_gas_2. If we're on the first step, assume wall temperature = freestream temperature. if i == 0: - h_gas[i] = cool.h_gas_1(2*self.y(x), - self.M(x), - T_gas[i], - self.rho(x), - self.perfect_gas.gamma, - self.perfect_gas.R, - mu_gas[i], - k_gas[i], - Pr_gas[i]) - #Use h_gas_2() for all subsequent steps + gamma = self.perfect_gas.gamma + R = self.perfect_gas.R + D = 2*self.y(x) #Flow diameter + + #Freestream properties + p_inf = self.p(x) + T_inf = T_gas[i] + rho_inf = self.rho(x) + M_inf = self.M(x) + v_inf = M_inf * (gamma*R*T_inf)**0.5 #Gas velocity + mu_inf = mu_gas[i] + Pr_inf = Pr_gas[i] + cp_inf = self.perfect_gas.cp + + ##Properties at arithmetic mean of T_wall and T_inf. Assume wall temperature = freestream temperature for the first step. + T_am = T_inf + mu_am = self.exhaust_transport.mu(T = T_am, p = p_inf) + rho_am = p_inf/(R*T_am) #p = rho R T - pressure is roughly uniform across the boundary layer so p_inf ~= p_wall + + #Stagnation properties + p0 = self.chamber_conditions.p0 + T0 = self.chamber_conditions.T0 + mu0 = self.exhaust_transport.mu(T = T0, p = p0) + + h_gas[i] = cool.h_gas_2(D, cp_inf, mu_inf, Pr_inf, rho_inf, v_inf, rho_am, mu_am, mu0) + else: gamma = self.perfect_gas.gamma R = self.perfect_gas.R @@ -1566,16 +1582,18 @@ def steady_heating_analysis(self, number_of_points=1000, h_gas_model = "1", h_co h_gas[i] = cool.h_gas_2(D, cp_inf, mu_inf, Pr_inf, rho_inf, v_inf, rho_am, mu_am, mu0) elif h_gas_model == "3": - #We need the previous wall temperature to use h_gas_3. If we're on the first step, then just use h_gas_1() + #We need the previous wall temperature to use h_gas_3. If we're on the first step, assume wall temperature = freestream temperature. if i == 0: - h_gas[i] = cool.h_gas_1(2*self.y(x), - self.M(x), - T_gas[i], - self.rho(x), - self.perfect_gas.gamma, - self.perfect_gas.R, - mu_gas[i], - k_gas[i], + h_gas[i] = cool.h_gas_3(self.c_star, + self.nozzle.At, + self.A(x), + self.chamber_conditions.p0, + self.chamber_conditions.T0, + self.M(x), + T_gas[i], + mu_gas[i], + self.perfect_gas.cp, + self.perfect_gas.gamma, Pr_gas[i]) #Use h_gas_3() for all subsequent steps @@ -1636,22 +1654,33 @@ def steady_heating_analysis(self, number_of_points=1000, h_gas_model = "1", h_co rho_coolant[i]) elif h_coolant_model == "2": - #Use '3' for the first step (model '2' relies on the wall temperature, which hasn't yet been calculated for the first step). + #This model requires the cooling channel wall temperature, which hasn't been calculated in the first step. + #Assume the wall temperature = coolant temperature for the first step. if i == 0: - h_coolant[i] = cool.h_coolant_3(rho_coolant[i], + h_coolant[i] = cool.h_coolant_2(rho_coolant[i], v_coolant[i], self.cooling_jacket.D(x=x, y=self.y(x=x, up_to = "wall in")), mu_coolant[i], + self.cooling_jacket.coolant_transport.mu(T = T_coolant[i], p = p_coolant[i]), Pr_coolant[i], k_coolant[i]) - #Use model '2' for every other step. else: + #If the wall temperature is above the boiling temperature of the fluid, cap the wall temperature used in Sieder-Tate to the boiling temperature of the liquid. + #Currently doesn't do anything for CoolProp models. + if self.cooling_jacket.coolant_transport.model == "thermo": + self.cooling_jacket.coolant_transport.thermo_object.calculate(P = p_coolant[i]) + + if self.cooling_jacket.coolant_transport.thermo_object.Tb < T_wall_outer[i-1]: + liquid_wall_temp = self.cooling_jacket.coolant_transport.thermo_object.Tb - 0.001 #Make it a bit smaller just to avoid thermo using the gas phase. + else: + liquid_wall_temp = T_wall_outer[i-1] + h_coolant[i] = cool.h_coolant_2(rho_coolant[i], v_coolant[i], self.cooling_jacket.D(x=x, y=self.y(x=x, up_to = "wall in")), mu_coolant[i], - self.cooling_jacket.coolant_transport.mu(T = T_wall_outer[i-1], p = p_coolant[i]), + self.cooling_jacket.coolant_transport.mu(T = liquid_wall_temp, p = p_coolant[i]), Pr_coolant[i], k_coolant[i]) @@ -1707,7 +1736,7 @@ def steady_heating_analysis(self, number_of_points=1000, h_gas_model = "1", h_co #Not sure if the Sieder-Tate equation is valid with your coolant above the boiling temperature at the wall. if h_coolant_model == '2' and self.cooling_jacket.coolant_transport.check_liquid(T = np.amax(T_wall_outer[i]), p = p_coolant[-1]) == False: - print("Coolant temperature at the wall was above its boiling point when using the Sieder-Tate equation (h_coolant_model = '2') - results should be used with caution.") + print("Wall tempreature was above coolant boiling point when using the Sieder-Tate equation (h_coolant_model = '2') - coolant boiling temperature was used instead of wall temperature.") #Dictionary containing results output_dict = {"x" : list(discretised_x), diff --git a/docs/_autosummary/bamboo.cooling.html b/docs/_autosummary/bamboo.cooling.html index d908464..186ff69 100644 --- a/docs/_autosummary/bamboo.cooling.html +++ b/docs/_autosummary/bamboo.cooling.html @@ -199,7 +199,7 @@

Dittus-Boelter equation for convective heat transfer coefficient.

h_gas_1(D, M, T, rho, gamma, R, mu, k, Pr)

-

Get the convective heat transfer coefficient on the gas side, non-Bartz equation.

+

Get the convective heat transfer coefficient on the gas side.

h_gas_2(D, cp_inf, mu_inf, Pr_inf, rho_inf, …)

Bartz equation, using Equation (8-23) from page 312 of RPE 7th edition (Reference [2]).

@@ -219,7 +219,7 @@

Ablative(ablative_material, wall_material[, …])

Container for refractory or ablative properties.

-

CoolingJacket(geometry, inner_wall, …[, …])

+

CoolingJacket(geometry, inner_wall, inlet_T, …)

Container for cooling jacket information - e.g.

Material(E, sigma_y, poisson, alpha, k, **kwargs)

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zK|DFf$nodASA>B4Db5y5937f|J876{I5abJ4q)Wz&^X?yz<9)=v7B?N907IJPD7OD yj81y8y`68V)FX0SeCHAL18vRR>+G&AUw%q@=`V<^NM}5v?$G09lXacl@Baa9Zg1WI diff --git a/docs/index.html b/docs/index.html index ae16846..f071c4a 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1072,7 +1072,7 @@

Welcome to Bamboo’s documentation!
-add_geometry(chamber_length, chamber_area, inner_wall_thickness, outer_wall_thickness, style='auto')
+add_geometry(chamber_length, chamber_area, inner_wall_thickness, style='auto', **kwargs)

Specify extra geometry parameters. Required for running cooling system analyses.

Parameters
@@ -1082,21 +1082,22 @@

Welcome to Bamboo’s documentation!Keyword Arguments +

outer_wall_thickness (float or array) – Thickness of the outer liner wall (m). Can be constant (float), or variable (array).

+

-add_cooling_jacket(inner_wall, outer_wall, inlet_T, inlet_p0, coolant_transport, mdot_coolant, xs=[- 1000, 1000], configuration='spiral', **kwargs)
+add_cooling_jacket(inner_wall, inlet_T, inlet_p0, coolant_transport, mdot_coolant, xs=[- 1000, 1000], configuration='spiral', **kwargs)

Container for cooling jacket information - e.g. for regenerative cooling.

Parameters
@@ -1340,21 +1341,21 @@

Welcome to Bamboo’s documentation!
-steady_heating_analysis(number_of_points=1000, h_gas_model='1', h_coolant_model='1', to_json='heating_output.json')
+steady_heating_analysis(number_of_points=1000, h_gas_model='3', h_coolant_model='2', to_json='heating_output.json')

Steady state heating analysis. Can be used for regenarative cooling, or combined regenerative and ablative cooling.

Parameters
  • number_of_points (int, optional) – Number of discrete points to divide the engine into. Defaults to 1000.

  • -
  • h_gas_model (str, optional) – Equation to use for the gas side convective heat transfer coefficients. Options are ‘1’, ‘2’ and ‘3’. Defaults to “1”.

  • -
  • h_coolant_model (str, optional) – Equation to use for the coolant side convective heat transfer coefficients. Options are ‘1’, ‘2’ and ‘3’. Defaults to “1”.

  • +
  • h_gas_model (str, optional) – Equation to use for the gas side convective heat transfer coefficients. Options are ‘1’, ‘2’ and ‘3’. Defaults to “3”.

  • +
  • h_coolant_model (str, optional) – Equation to use for the coolant side convective heat transfer coefficients. Options are ‘1’, ‘2’ and ‘3’. Defaults to “2”.

  • to_json (str or bool, optional) – Directory to export a .JSON file to, containing simulation results. If False, no .JSON file is saved. Defaults to ‘heating_output.json’.

Note

-

h_gas_model = ‘2’ seems to provide questionable results (if it works at all) - use it with caution. h_coolant_model = ‘2’ can raise errors if using the ‘force_phase’ setting with your coolant TransportProperties object. See the functions h_gas_1(), h_gas_2(), h_coolant_1(), etc.. in the documentation for details on each model.

+

See the bamboo.cooling module for explanations of each h_gas and h_coolant option. Defaults are Bartz (using sigma correlation) for gas side, and Sieder-Tate for coolant side. These are believed to be the most accurate.

Returns
@@ -1425,16 +1426,16 @@

Welcome to Bamboo’s documentation!Returns

-
Results of the stress simulation. Contains the following dictionary keys (all are arrays):

For a steady state analysis: -- “thermal_stress : Stress induced in the inner liner due to temperature difference, chamber to coolant side, for each x value (Pa). -- “tadjusted_yield : Yield stress of the inner wall material, corrected for the chamber side temperature (worst case) (Pa). -- “deltaT_wall” : Inner liner temperature difference, chamber side - coolant side (K). -- “stress_inner_hoop_steady” : Hoop stress of inner liner due to coolant static pressure in jacket after ignition (Pa). -- “stress_outer_hoop” : Hoop stress of outer liner due to coolant static pressure (same before and after ignition) (Pa). -For a transient analysis: -- “stress_inner_hoop_transient” : Hoop stress of inner liner due to coolant static pressure in jacket prior to ignition (0 chamber pressure) (Pa). -- “stress_inner_IE” : Stress induced in inner liner as it is heated but constrained by cold outer liner (Pa). -- “stress_outer_IE : Stress induced in outer liner by expanding inner liner (Pa).

+
Results of the stress simulation. Contains the following dictionary keys (all are arrays):
    +
  • ”thermal_stress : (steady only) Stress induced in the inner liner due to temperature difference, chamber to coolant side, for each x value (Pa).

  • +
  • ”tadjusted_yield : (steady only) Yield stress of the inner wall material, corrected for the chamber side temperature (worst case) (Pa).

  • +
  • ”deltaT_wall” : (steady only) Inner liner temperature difference, chamber side - coolant side (K).

  • +
  • ”stress_inner_hoop_steady” : (steady only) Hoop stress of inner liner due to coolant static pressure in jacket after ignition (Pa).

  • +
  • ”stress_outer_hoop” : (steady only) Hoop stress of outer liner due to coolant static pressure (same before and after ignition) (Pa).

  • +
  • ”stress_inner_hoop_transient” : (transient only) Hoop stress of inner liner due to coolant static pressure in jacket prior to ignition (0 chamber pressure) (Pa).

  • +
  • ”stress_inner_IE” : (transient only) Stress induced in inner liner as it is heated but constrained by cold outer liner (Pa).

  • +
  • ”stress_outer_IE : (transient only) Stress induced in outer liner by expanding inner liner (Pa).

  • +

@@ -1492,8 +1493,11 @@

Welcome to Bamboo’s documentation!
bamboo.cooling.h_gas_1(D, M, T, rho, gamma, R, mu, k, Pr)
-

Get the convective heat transfer coefficient on the gas side, non-Bartz equation. -Uses Eqn (8-22) on page 312 or RPE 7th edition (Reference [2])

+

Get the convective heat transfer coefficient on the gas side. Uses Eqn (8-22) on page 312 or RPE 7th edition (Reference [2]). I believe this is just a form of the Dittius-Boelter equation.

+
+

Note

+

Seems to give much lower wall temperatures than the Bartz equation, and is likely less accurate. h_gas_2 and h_gas_3 are likely more accurate.

+
Parameters
    @@ -1522,10 +1526,6 @@

    Welcome to Bamboo’s documentation!bamboo.cooling.h_gas_2(D, cp_inf, mu_inf, Pr_inf, rho_inf, v_inf, rho_am, mu_am, mu0)

    Bartz equation, using Equation (8-23) from page 312 of RPE 7th edition (Reference [2]). ‘am’ refers to the gas being at the ‘arithmetic mean’ of the wall and freestream temperatures.

    -
    -

    Note

    -

    Seems to provide questionable results - may have been implemented incorrectly.

    -
    Parameters
      @@ -1960,14 +1960,13 @@

      Welcome to Bamboo’s documentation!
      -class bamboo.cooling.CoolingJacket(geometry, inner_wall, outer_wall, inlet_T, inlet_p0, coolant_transport, mdot_coolant, xs=[- 1000, 1000], configuration='spiral', has_ablative=False, **kwargs)
      +class bamboo.cooling.CoolingJacket(geometry, inner_wall, inlet_T, inlet_p0, coolant_transport, mdot_coolant, xs=[- 1000, 1000], configuration='spiral', has_ablative=False, **kwargs)

      Bases: object

      Container for cooling jacket information - e.g. for regenerative cooling.

      Parameters
      • inner_wall (Material) – Wall material on the inner side of the cooling jacket.

      • -
      • outer_wall (Material) – Wall material for the outer liner.

      • inlet_T (float) – Inlet coolant temperature (K)

      • inlet_p0 (float) – Inlet coolant stagnation pressure (Pa)

      • coolant_transport (TransportProperties) – Container for the coolant transport properties.

      • @@ -1984,6 +1983,7 @@

        Welcome to Bamboo’s documentation!Material) – Wall material for the outer liner.

      diff --git a/docs/searchindex.js b/docs/searchindex.js index 00be16c..79b51f9 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ 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