{ "cells": [ { "cell_type": "markdown", "id": "ad441e7b", "metadata": {}, "source": [ "# Overriding a Mechanism in MusicBox\n", "\n", "Each MusicBox instance can only work with one mechanism at a time. To change the chemical system, you can load a new mechanism using the `load_mechanism()` method, which will replace the existing one. This tutorial demonstrates how to switch from one mechanism to a completely different chemical system." ] }, { "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 to set up the mechanism for overriding." ] }, { "cell_type": "code", "execution_count": 1, "id": "f0cb3f6f", "metadata": {}, "outputs": [], "source": [ "from acom_music_box import MusicBox\n", "import musica.mechanism_configuration as mc\n", "import matplotlib.pyplot as plt\n", "\n", "# Create species and phase for the reactions\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", "\n", "# Create the Arrhenius reactions\n", "reaction1 = mc.Arrhenius(name=\"X->Y\", A=4.0e-3, C=50, reactants=[species[\"X\"]], products=[species[\"Y\"]], gas_phase=gas)\n", "reaction2 = mc.Arrhenius(name=\"Y->Z\", A=4.0e-3, C=50, reactants=[species[\"Y\"]], products=[species[\"Z\"]], gas_phase=gas)\n", "rxns = {\"X->Y\": reaction1, \"Y->Z\": reaction2}\n", "\n", "# Create the mechanism that is defined by the species, phases, and reactions\n", "mechanism = mc.Mechanism(\n", " name=\"tutorial_mechanism\", \n", " species=list(species.values()), \n", " phases=[gas], \n", " reactions=list(rxns.values()))\n", "\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. Overriding with a New Mechanism\n", "\n", "Now we'll completely replace the mechanism with a different chemical reactions. Instead of the Arrhenius reactions system, we'll create quantum tunneling reactions.\n", "\n", "This demonstrates how to override a mechanism by:\n", "- Using different species (G and H instead of X, Y, Z)\n", "- Using quantum tunneling reactions\n", "\n", "Here's the code to define and load the new mechanism:" ] }, { "cell_type": "code", "execution_count": 2, "id": "6c840133", "metadata": {}, "outputs": [], "source": [ "# Create new species and phase\n", "G = mc.Species(name=\"G\")\n", "H = mc.Species(name=\"H\")\n", "species = {\"G\": G, \"H\": H}\n", "\n", "gas = mc.Phase(name=\"gas\", species=list(species.values()))\n", "\n", "# Create the reactions and overwrite the variables\n", "reaction1 = mc.Tunneling(name=\"G->H\", A=2.0e-3, B=2, C=50, reactants=[species[\"G\"]], products=[species[\"H\"]], gas_phase=gas)\n", "reaction2 = 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\": reaction1, \"H->G\": reaction2}\n", "\n", "\n", "# Create the new mechanism with the newly defiend reactions\n", "mechanism = mc.Mechanism(\n", " name=\"new_mechanism\", \n", " species=list(species.values()), \n", " phases=[gas], \n", " reactions=list(rxns.values())\n", ")\n", "\n", "# Override the previous mechanism by loading the new one\n", "box_model.load_mechanism(mechanism)" ] }, { "cell_type": "markdown", "id": "62878d04", "metadata": {}, "source": [ "## 3. Running and Visualizing the New Box Model\n", "\n", "Now we can run the simulation with our new reversible mechanism. Notice that we're using the species names \"G\" and \"H\" instead of \"X\", \"Y\", and \"Z\" from the previous mechanism.\n", "\n", "The rest of this code is adapted from the Basic Workflow Tutorial. For detailed explanations of each step, refer to that tutorial:" ] }, { "cell_type": "code", "execution_count": 3, "id": "c2f1f497", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ " " ] }, { "data": { "text/html": [ "
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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.set_condition(\n", " time=0,\n", " temperature=298.15, # Units: Kelvin (K)\n", " pressure=101325.0, # Units: Pascals (Pa)\n", " concentrations={ # Units: mol/m^3\n", " \"G\": 2.5,\n", " \"H\": 5.0,\n", " }\n", ")\n", "\n", "# Set the box model conditions at the defined time\n", "box_model.set_condition(\n", " time=100.0, # Units: Seconds (s)\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": "musica", "language": "python", "name": "musica" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.14.2" } }, "nbformat": 4, "nbformat_minor": 5 }