diff --git a/Introduction to Bamboo.ipynb b/Introduction to Bamboo.ipynb index c1d5dc7..1eacc48 100644 --- a/Introduction to Bamboo.ipynb +++ b/Introduction to Bamboo.ipynb @@ -479,7 +479,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] diff --git a/cusfbamboo/engine.py b/cusfbamboo/engine.py index 1ffa21d..20f2c6b 100644 --- a/cusfbamboo/engine.py +++ b/cusfbamboo/engine.py @@ -1180,7 +1180,7 @@ def steady_heating_analysis(self, num_grid = 1000, counterflow = True, iter_star results["info"]["T_exhaust"] = "Exhaust temperature at each position (K). T_exhaust[i] is the value at x[i]. " results["info"]["dQ_dx"] = "Heat transfer rate per unit axial length (W/m). dQ_dx[i] is the value at x[i]." results["info"]["dQ_dLc"] = "Heat transfer rate per unit length along the cooling channel (W/m) - equal to dQ/dx for 'vertical' channels but not for 'spiral' channels. dQ_dx[i] is the value at x[i]." - results["info"]["dQ_dA"] = "Heat transfer rate per unit chamber area (W/m2). dQ_dA[i] is the value at x[i]." + results["info"]["dQ_dA"] = "Heat transfer rate per unit chamber area at the innermost wall (W/m2). dQ_dA[i] is the value at x[i]." results["info"]["Rdx"] = "Local thermal resistances at each position (K m/W), in the order coolant convection (index 0) --> exhaust convection. R_dx[i] a list of resistances at the value at x[i]" results["info"]["rho_coolant"] = "Density of coolant (kg/m3). rho_coolant[i] is the value at x[i]." results["info"]["p_coolant"] = "Static pressure of coolant (Pa). p_coolant[i] is the value at x[i]." @@ -1239,7 +1239,9 @@ def steady_heating_analysis(self, num_grid = 1000, counterflow = True, iter_star poisson = self.walls[j].material.poisson t_w = self.walls[j].thickness(x) - results["sigma_t_thermal"][i][j] = E * alpha * results["dQ_dA"][i] * t_w / (2 * (1 - poisson) * k) + corrected_dQ_dA = results["dQ_dA"][i] * self.geometry.r(x = results["x"][i]) / (D/2) # Need to get the actual dQ/dA at the local wall radius (the local radius increases as you move out for each wall) + + results["sigma_t_thermal"][i][j] = E * alpha * corrected_dQ_dA * t_w / (2 * (1 - poisson) * k) # Pressure stress from Heister [9] D += t_w / 2 # Average diameter diff --git a/examples/Cantera Example.ipynb b/examples/Cantera Example.ipynb index 24f984b..58c15a5 100644 --- a/examples/Cantera Example.ipynb +++ b/examples/Cantera Example.ipynb @@ -142,13 +142,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1073: RuntimeWarning: divide by zero encountered in true_divide\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1215: RuntimeWarning: divide by zero encountered in true_divide\n", " a = -(dx2)/(dx1 * (dx1 + dx2))\n", - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1074: RuntimeWarning: divide by zero encountered in true_divide\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1216: RuntimeWarning: divide by zero encountered in true_divide\n", " b = (dx2 - dx1) / (dx1 * dx2)\n", - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1075: RuntimeWarning: divide by zero encountered in true_divide\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1217: RuntimeWarning: divide by zero encountered in true_divide\n", " c = dx1 / (dx2 * (dx1 + dx2))\n", - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1081: RuntimeWarning: invalid value encountered in add\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1223: RuntimeWarning: invalid value encountered in add\n", " out[tuple(slice1)] = a * f[tuple(slice2)] + b * f[tuple(slice3)] + c * f[tuple(slice4)]\n" ] }, diff --git a/examples/Simple Engine.ipynb b/examples/Simple Engine.ipynb index 8256d0c..6a53f8a 100644 --- a/examples/Simple Engine.ipynb +++ b/examples/Simple Engine.ipynb @@ -82,13 +82,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1073: RuntimeWarning: divide by zero encountered in true_divide\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1215: RuntimeWarning: divide by zero encountered in true_divide\n", " a = -(dx2)/(dx1 * (dx1 + dx2))\n", - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1074: RuntimeWarning: divide by zero encountered in true_divide\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1216: RuntimeWarning: divide by zero encountered in true_divide\n", " b = (dx2 - dx1) / (dx1 * dx2)\n", - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1075: RuntimeWarning: divide by zero encountered in true_divide\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1217: RuntimeWarning: divide by zero encountered in true_divide\n", " c = dx1 / (dx2 * (dx1 + dx2))\n", - "C:\\Users\\Daniel\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:1081: RuntimeWarning: invalid value encountered in add\n", + "C:\\Users\\Daniel\\AppData\\Roaming\\Python\\Python38\\site-packages\\numpy\\lib\\function_base.py:1223: RuntimeWarning: invalid value encountered in add\n", " out[tuple(slice1)] = a * f[tuple(slice2)] + b * f[tuple(slice3)] + c * f[tuple(slice4)]\n" ] }, @@ -176,7 +176,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": { "scrolled": false }, @@ -199,7 +199,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": { "scrolled": false }, diff --git a/setup.py b/setup.py index a34591f..8a787be 100644 --- a/setup.py +++ b/setup.py @@ -14,8 +14,8 @@ name='cusfbamboo', author = 'Daniel Gibbons', author_email = 'daniel.u.gibbons@gmail.com', - version = '0.2.3', - license = ' gpl-3.0', + version = '0.2.4', + license = ' AGPL-3.0', packages = find_packages(), install_requires = ['numpy', 'matplotlib', 'scipy'], description = 'Cooling system modelling for liquid rocket engines', @@ -26,7 +26,7 @@ 'Development Status :: 4 - Beta', 'Intended Audience :: Science/Research', 'Topic :: Scientific/Engineering', - 'License :: OSI Approved :: GNU General Public License v3 (GPLv3)', + 'License :: OSI Approved :: GNU Affero General Public License v3', 'Programming Language :: Python :: 3'], long_description = long_description, long_description_content_type='text/markdown'