{ "cells": [ { "cell_type": "markdown", "id": "ad441e7b", "metadata": {}, "source": [ "# Overriding a Mechanism in MusicBox\n", "\n", "The MusicBox class only supports one mechanism at a time. If you desire to change the mechanism within the class, you will need to override it from scratch." ] }, { "cell_type": "markdown", "id": "cad0ad50", "metadata": {}, "source": [ "## 1. Creating the Mechanism and Box Model\n", "\n", "This is simply a copy of the first half of the [Basic Workflow Tutorial](1.%20basic_workflow.ipynb) to set up the mechanism for overriding." ] }, { "cell_type": "code", "execution_count": 1, "id": "f0cb3f6f", "metadata": {}, "outputs": [], "source": [ "from acom_music_box import MusicBox, Conditions\n", "import musica.mechanism_configuration as mc\n", "import matplotlib.pyplot as plt\n", "\n", "# Create each of the species that will be simulated\n", "X = mc.Species(name=\"X\")\n", "Y = mc.Species(name=\"Y\")\n", "Z = mc.Species(name=\"Z\")\n", "species = {\"X\": X, \"Y\": Y, \"Z\": Z}\n", "gas = mc.Phase(name=\"gas\", species=list(species.values()))\n", "# Create the reactions that the species undergo in the\n", "arr1 = mc.Arrhenius(name=\"X->Y\", A=4.0e-3, C=50, reactants=[species[\"X\"]], products=[species[\"Y\"]], gas_phase=gas)\n", "arr2 = mc.Arrhenius(name=\"Y->Z\", A=4.0e-3, C=50, reactants=[species[\"Y\"]], products=[species[\"Z\"]], gas_phase=gas)\n", "rxns = {\"X->Y\": arr1, \"Y->Z\": arr2}\n", "# Create the mechanism that is defined by the species, phases, and reactions\n", "mechanism = mc.Mechanism(name=\"tutorial_mechanism\", species=list(species.values()), phases=[gas], reactions=list(rxns.values()))\n", "# Create the box model that contains the mechanism\n", "box_model = MusicBox()\n", "box_model.load_mechanism(mechanism)" ] }, { "cell_type": "markdown", "id": "017f8fa1", "metadata": {}, "source": [ "## 2. Redefining Code\n", "\n", "For the sake of readability, the code from the previous cells will be redefined here to represent the new mechanism.
\n", "Here, a new type of reaction is used, called a quantum tunneling reaction:" ] }, { "cell_type": "code", "execution_count": 2, "id": "6c840133", "metadata": {}, "outputs": [], "source": [ "# Create each of the species that will be simulated\n", "G = mc.Species(name=\"G\")\n", "H = mc.Species(name=\"H\")\n", "species = {\"G\": G, \"H\": H}\n", "gas = mc.Phase(name=\"gas\", species=list(species.values()))\n", "# Create the reactions that the species undergo in the\n", "arr1 = mc.Tunneling(name=\"G->H\", A=2.0e-3, B=2, C=50, reactants=[species[\"G\"]], products=[species[\"H\"]], gas_phase=gas)\n", "arr2 = mc.Tunneling(name=\"H->G\", A=9.0e-3, B=2, C=50, reactants=[species[\"H\"]], products=[species[\"G\"]], gas_phase=gas)\n", "rxns = {\"G->H\": arr1, \"H->G\": arr2}\n", "# Create the mechanism that is defined by the species, phases, and reactions\n", "mechanism = mc.Mechanism(name=\"overriden_mechanism\", species=list(species.values()), phases=[gas], reactions=list(rxns.values()))\n", "# Create the box model that contains the new mechanism\n", "box_model.load_mechanism(mechanism)" ] }, { "cell_type": "markdown", "id": "62878d04", "metadata": {}, "source": [ "## 3. Running and Visualizing the new Box Model\n", "\n", "The rest of this code is an adapted version of the Basic Workflow code to run with the new mechanism. Refer to there for explanations about the code:" ] }, { "cell_type": "code", "execution_count": 3, "id": "c2f1f497", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ " " ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r" ] }, { "data": { "text/html": [ "
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480.0298.15101325.040.8740454.6191652.880835
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6120.0310.00100100.038.8363315.1564092.343591
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9180.0310.00100100.038.8363315.6277191.872281
10200.0310.00100100.038.8363315.7275891.772411
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" ], "text/plain": [ " time.s ENV.temperature.K ENV.pressure.Pa \\\n", "0 0.0 298.15 101325.0 \n", "1 20.0 298.15 101325.0 \n", "2 40.0 298.15 101325.0 \n", "3 60.0 298.15 101325.0 \n", "4 80.0 298.15 101325.0 \n", "5 100.0 298.15 101325.0 \n", "6 120.0 310.00 100100.0 \n", "7 140.0 310.00 100100.0 \n", "8 160.0 310.00 100100.0 \n", "9 180.0 310.00 100100.0 \n", "10 200.0 310.00 100100.0 \n", "\n", " ENV.air number density.mol m-3 CONC.G.mol m-3 CONC.H.mol m-3 \n", "0 40.874045 2.500000 5.000000 \n", "1 40.874045 3.213819 4.286181 \n", "2 40.874045 3.787516 3.712484 \n", "3 40.874045 4.248595 3.251405 \n", "4 40.874045 4.619165 2.880835 \n", "5 40.874045 4.916991 2.583009 \n", "6 38.836331 5.156409 2.343591 \n", "7 38.836331 5.348819 2.151181 \n", "8 38.836331 5.503449 1.996551 \n", "9 38.836331 5.627719 1.872281 \n", "10 38.836331 5.727589 1.772411 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Set the conditions of the box model at time = 0 s\n", "box_model.initial_conditions = Conditions(\n", " temperature=298.15, # Units: Kelvin (K)\n", " pressure=101325.0, # Units: Pascals (Pa)\n", " species_concentrations={ # Units: mol/m^3\n", " \"G\": 2.5,\n", " \"H\": 5.0,\n", " }\n", ")\n", "# Set the box model conditions at the defined time\n", "box_model.add_evolving_condition(\n", " 100.0, # Units: Seconds (s)\n", " Conditions(\n", " temperature=310.0, # Units: Kelvin (K)\n", " pressure=100100.0 # Units: Pascals (Pa)\n", " )\n", ")\n", "# Set the additional configuration options for the box model\n", "box_model.box_model_options.simulation_length = 200 # Units: Seconds (s)\n", "box_model.box_model_options.chem_step_time = 1 # Units: Seconds (s)\n", "box_model.box_model_options.output_step_time = 20 # Units: Seconds (s)\n", "\n", "df = box_model.solve()\n", "display(df)\n", "df.plot(x='time.s', y=['CONC.G.mol m-3', 'CONC.H.mol m-3'], title='Concentration over time', ylabel='Concentration (mol m-3)', xlabel='Time (s)')\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "musicbox", "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": "3.11.12" } }, "nbformat": 4, "nbformat_minor": 5 }