Skip to content

Instantly share code, notes, and snippets.

@wtbarnes
Created May 25, 2023 19:34
Show Gist options
  • Save wtbarnes/c6e87519be9b098653af11df16852c2c to your computer and use it in GitHub Desktop.
Save wtbarnes/c6e87519be9b098653af11df16852c2c to your computer and use it in GitHub Desktop.
Notebook showing comparison between HYDRAD and EBTEL initial conditions.
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "markdown",
"id": "7ed94b42-877a-43df-b182-04a4ea2b4fcd",
"metadata": {},
"source": [
"# Investigating Consistency Between Initial Conditions in HYDRAD and EBTEL"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "f5d18411-8f36-46b5-abe5-1df92bb6f516",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import astropy.units as u\n",
"import astropy.table\n",
"from astropy.visualization import quantity_support\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib\n",
"\n",
"from synthesizAR.interfaces.ebtel import run_ebtel, read_xml\n",
"\n",
"import pydrad.configure\n",
"import pydrad.configure.data\n",
"import pydrad.parse\n",
"import pydrad.visualize"
]
},
{
"cell_type": "markdown",
"id": "8bce7422-dac9-4de2-a58e-304f9e868ba7",
"metadata": {},
"source": [
"## Theory"
]
},
{
"cell_type": "markdown",
"id": "aeb6d2a2-7075-46cd-9582-d18d591614a3",
"metadata": {},
"source": [
"The EBTEL energy and density equations, from Klimchuk et al. (2008), are,\n",
"$$\n",
"\\frac{1}{\\gamma-1}\\frac{d}{dt}p = Q - \\frac{R_C}{L}\\left(1 + \\frac{R_{TR}}{R_{C}}\\right)\n",
"$$\n",
"$$\n",
"\\frac{d}{dt}n = -\\frac{c_2(\\gamma - 1)}{2c_3\\gamma Lk_BT}(F_{c0} + R_{TR})\n",
"$$\n",
"where $n$ and $T$ are assumed to be spatially-averaged coronal quantites, $F_{c0}$ is the heat flux at the interface between the corona and TR, $c_2=T/T_a$, $c_1=R_{TR}/R_C$ is the ratio of radiative losses from the transition region and corona, respectively, and $R_C=n^2\\Lambda(T)L$.\n",
"\n",
"In equilibrium, these equations become,\n",
"$$\n",
"Q = \\frac{R_C}{L}(1 + c_1)\n",
"$$\n",
"$$\n",
"R_{TR} = -F_{c0}\n",
"$$\n",
"\n",
"In the case of hydrostatic equilibrium, the energy equation is,\n",
"$$\n",
"Q(s) - n^2(s)\\Lambda(T(s)) - \\frac{d}{ds}F_c = 0\n",
"$$\n",
"Integrating this over the corona and assuming that the heating is uniform across the loop, i.e. $Q(s)=Q$ for all $s$,\n",
"$$\n",
"QL - R_C + F_{c0} = 0 \n",
"$$\n",
"Similarly, integrating the hydrostatic energy equation over the transition region,\n",
"$$\n",
"-R_{TR} - F_{c0} = 0\n",
"$$\n",
"Note that these are the same as the equilibrium EBTEL conditions that we defined above."
]
},
{
"cell_type": "markdown",
"id": "ae89eba2-2b22-42e7-a4b6-6d106c5aaecd",
"metadata": {},
"source": [
"To derive the EBTEL equilibrium temperature, we can take the second energy equation and expand the definition of the thermal conduction term,\n",
"$$\n",
"\\frac{2}{7}\\kappa_0\\frac{T_a^{7/2}}{L} = R_{TR},\n",
"$$\n",
"$$\n",
"\\frac{2\\kappa_0}{7L}\\left(\\frac{T}{c_2}\\right)^{7/2} = c_1R_{C}\n",
"$$\n",
"And then using the first EBTEL equilibrium energy equation,\n",
"$$\n",
"\\frac{2\\kappa_0}{7L}\\left(\\frac{T}{c_2}\\right)^{7/2} = QL\\frac{c_1}{1+c_1}\n",
"$$\n",
"$$\n",
"T_{eq} = c_2\\left(\\frac{7QL^2}{2\\kappa_0}\\frac{c_1}{1+c_1}\\right)^{2/7}\n",
"$$\n",
"To get the equilibrium density, use the first EBTEL equilibrium energy equation,\n",
"$$\n",
"Q = \\frac{R_C}{L}(1 + c_1),\n",
"$$\n",
"$$\n",
"\\frac{Q}{1+c_1} = n_{eq}^2\\Lambda(T_{eq}),\n",
"$$\n",
"$$\n",
"n_{eq} = \\left(\\frac{Q}{\\Lambda(T_{eq})}\\frac{1}{1+c_1}\\right)^{1/2}\n",
"$$"
]
},
{
"cell_type": "markdown",
"id": "25d4f8a2-957e-4a91-99d5-dd06cac31c14",
"metadata": {},
"source": [
"Note that although these expressions are simple, they do not have an exact solution because of the presence of the $c_1$ term which is, in general, temeprature dependent (see Figure 3 of Cargill et al. (2012a)). Either one mst apply some iterative scheme to solve for $T_{eq}$ or assume a constant value for $c_1$ (typically $c_1=2-4$ is not a bad guess). Either way, this introduces additional uncertainty."
]
},
{
"cell_type": "markdown",
"id": "414808a8-dc79-48ed-b531-855f43c8bd45",
"metadata": {},
"source": [
"Overall, for the same $Q$, one should not expect the EBTEL and spatially-averaged HYDRAD equilibria to be exactly the same, though in practice when spatially-averaging the HYDRAD results, the results will be similar. In particular, the operations of solving an ODE and taking a spatial average do not commute. That is, spatially-averaging a system of equations and then solving them is not the same as solving that system of equations and then taking the spatial average. Note that you could use the spatially-averaged hydrostatic equilibrium results as the initial conditions for EBTEL but that these values are not necessarily an equilibrium solution to the EBTEL equations."
]
},
{
"cell_type": "markdown",
"id": "1cf8db80-50c2-443b-bc26-e94759c99c0b",
"metadata": {},
"source": [
"## Numerical Experiments"
]
},
{
"cell_type": "markdown",
"id": "860bf32a-fb5e-481e-9103-3e9b73dbf054",
"metadata": {},
"source": [
"Set up a HYDRAD run"
]
},
{
"cell_type": "code",
"execution_count": 76,
"id": "0c74a5d3-435b-4425-bbab-84dc10c5948c",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING: UnitsWarning: The unit 'erg' has been deprecated in the VOUnit standard. Suggested: cm**2.g.s**-2. [astropy.units.format.utils]\n"
]
}
],
"source": [
"hydrad_config = pydrad.configure.data.get_defaults()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"id": "77d7fc66-68f4-4b06-9113-43d72273ac4b",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"loop_length = 100 * u.Mm\n",
"total_time = 5000 * u.s"
]
},
{
"cell_type": "code",
"execution_count": 96,
"id": "697641d9-02e3-44c6-8bdd-b265862a7f47",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"hydrad_config['general']['loop_length'] = loop_length + 2*hydrad_config['general']['footpoint_height']\n",
"hydrad_config['general']['total_time'] = total_time\n",
"hydrad_config['general']['heat_flux_timestep_limit'] = 1e-5 * u.s\n",
"hydrad_config['general']['write_file_equation_terms'] = False\n",
"hydrad_config['general']['write_file_hydrogen_level_populations'] = False\n",
"hydrad_config['general']['write_file_ion_populations'] = True\n",
"hydrad_config['general']['write_file_physical'] = True\n",
"hydrad_config['general']['write_file_timescales'] = False\n",
"hydrad_config['initial_conditions']['footpoint_density'] = 1e11 * u.cm**(-3)\n",
"hydrad_config['initial_conditions']['footpoint_temperature'] = 1e4 * u.K\n",
"hydrad_config['initial_conditions']['heating_scale_height'] = 1e300 * u.cm\n",
"hydrad_config['radiation']['use_power_law_radiative_losses'] = True\n",
"hydrad_config['grid']['adapt_every_n_time_steps'] = 10\n",
"hydrad_config['grid']['initial_refinement_level'] = 6\n",
"hydrad_config['grid']['maximum_refinement_level'] = 6\n",
"hydrad_config['grid']['refine_on_hydrogen_energy'] = False\n",
"hydrad_config['solver']['cutoff_temperature_fraction'] = 0.2\n",
"hydrad_config['heating']['background']['use_initial_conditions'] = True\n",
"hydrad_config['heating']['electron_heating'] = 1.0\n",
"hydrad_config['heating']['events'] = []"
]
},
{
"cell_type": "code",
"execution_count": 98,
"id": "f478dfd0-4067-4eec-b50c-c1bc5eef9d41",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"conf = pydrad.configure.Configure(hydrad_config)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "146ed664-4eae-45a5-b4fc-64d9d07ca675",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"conf.setup_simulation('hydrad-ebtel-ic-comparison',\n",
" '/Users/wtbarnes/Documents/codes/HYDRAD/',\n",
" overwrite=True)"
]
},
{
"cell_type": "code",
"execution_count": 100,
"id": "cb0e7679-ff31-412a-9cee-526af4fe94ac",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"strand = pydrad.parse.Strand('hydrad-ebtel-ic-comparison/')"
]
},
{
"cell_type": "markdown",
"id": "09db6bf3-7136-4279-a4c4-15ae10e54ab0",
"metadata": {},
"source": [
"Set up an EBTEL run"
]
},
{
"cell_type": "code",
"execution_count": 102,
"id": "f5748803-33d9-4662-88a0-62ee02215fe7",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"ebtel_config = read_xml('/Users/wtbarnes/Documents/codes/ebtelPlusPlus/config/ebtel.example.cfg.xml')\n",
"ebtel_config['total_time'] = total_time.to_value('s')\n",
"ebtel_config['loop_length'] = (loop_length/2).to_value('cm')\n",
"ebtel_config['use_flux_limiting']= True\n",
"ebtel_config['use_adaptive_solver'] = True\n",
"ebtel_config['saturation_limit'] = 1\n",
"ebtel_config['adaptive_solver_error'] = 1e-10\n",
"ebtel_config['heating']['events'] = []\n",
"ebtel_config['heating']['background'] = conf.equilibrium_heating_rate.to_value('erg cm-3 s-1')"
]
},
{
"cell_type": "code",
"execution_count": 103,
"id": "b73f5f84-1471-4f11-8c44-9ebc1d5eddcc",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"simulation = run_ebtel(ebtel_config, '/Users/wtbarnes/Documents/codes/ebtelPlusPlus/')\n",
"time_ebtel = simulation['time'] * u.s\n",
"heat_ebtel = simulation['heat'] * u.Unit('erg cm-3 s-1')\n",
"electron_temperature_ebtel = simulation['electron_temperature'] * u.K\n",
"density_ebtel = simulation['density'] * u.Unit('cm-3')"
]
},
{
"cell_type": "markdown",
"id": "ae624cab-27ad-47e1-b8f5-d1553b8b090e",
"metadata": {},
"source": [
"## Comparing Initial Conditions\n",
"\n",
"To compare the initial conditions, we need to average over the appropriate portion of the HYDRAD spatial domain. Recall that, in this formalism, the corona is defined energetically, such that thermal conduction is always a sink in the corona and a source in the transition region. That is, because the term $-dF_c/ds$ shows up in our energy equation, we want only positions where $dF_c/ds>0$. In the case of a semi-circular loop with monotonically increasing $T(s)$ from footpoint to apex, this is just the region between the minimum and maximum of the conduction term which is output by HYDRAD."
]
},
{
"cell_type": "code",
"execution_count": 210,
"id": "1e73c325-2354-476d-bfd5-3585ae02c241",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"initial_strand = strand.initial_conditions\n",
"s_lower = initial_strand.coordinate[np.argmin(initial_strand.electron_conduction)]\n",
"s_upper = initial_strand.coordinate[np.argmax(initial_strand.electron_conduction)]"
]
},
{
"cell_type": "code",
"execution_count": 211,
"id": "6d709295-c3a3-43e1-b237-1cfe925d025e",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x28d1ebf70>"
]
},
"execution_count": 211,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"in_corona = np.logical_and(initial_strand.coordinate>=s_lower,\n",
" initial_strand.coordinate<=s_upper)\n",
"with quantity_support():\n",
" plt.plot(initial_strand.coordinate,initial_strand.electron_conduction)\n",
" plt.plot(initial_strand.coordinate[in_corona], initial_strand.electron_conduction[in_corona],\n",
" lw=3, ls='--', label='corona')\n",
"plt.plot(s_lower, np.min(initial_strand.electron_conduction),\n",
" marker='o', ls='', label='coronal lower bound')\n",
"plt.plot(s_upper, np.max(initial_strand.electron_conduction),\n",
" marker='o', ls='', label='coronal upper bound')\n",
"plt.title('Thermal Conduction')\n",
"plt.legend()"
]
},
{
"cell_type": "markdown",
"id": "2f7bdcb6-8dae-45c6-9fcd-b3f5eb3241a6",
"metadata": {},
"source": [
"Now, let's average over this spatial domain and compare with the inital EBTEL values."
]
},
{
"cell_type": "code",
"execution_count": 212,
"id": "17f93bbf-e858-4f08-873f-3187a6deeb88",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'EBTEL / HYDRAD density ratio = 0.9556857768422369')"
]
},
"execution_count": 212,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 2000x800 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(20,8))\n",
"plt.subplot(121)\n",
"with quantity_support():\n",
" plt.plot(initial_strand.coordinate, initial_strand.electron_temperature)\n",
" plt.plot(initial_strand.coordinate[in_corona], initial_strand.electron_temperature[in_corona], lw=3, color='C3', label='corona')\n",
"hydrad_temp_average = initial_strand.spatial_average('electron_temperature', bounds=(s_lower, s_upper))\n",
"plt.axhline(y=hydrad_temp_average.to_value('K'), color='C1', label='HYDRAD average')\n",
"plt.axhline(y=electron_temperature_ebtel[0].to_value('K'), color='C2', label='EBTEL')\n",
"plt.legend()\n",
"plt.title(f'EBTEL / HYDRAD temperature ratio = {electron_temperature_ebtel[0] / hydrad_temp_average}')\n",
"plt.subplot(122)\n",
"with quantity_support():\n",
" plt.plot(initial_strand.coordinate, initial_strand.electron_density)\n",
" plt.plot(initial_strand.coordinate[in_corona], initial_strand.electron_density[in_corona], lw=3, color='C3', label='corona')\n",
"hydrad_density_average = initial_strand.spatial_average('electron_density', bounds=(s_lower, s_upper))\n",
"plt.axhline(y=hydrad_density_average.to_value('cm-3'), color='C1')\n",
"plt.axhline(y=density_ebtel[0].to_value('cm-3'), color='C2', ls='--')\n",
"plt.yscale('log')\n",
"plt.ylim(3e8,1e9)\n",
"plt.title(f'EBTEL / HYDRAD density ratio = {density_ebtel[0] / hydrad_density_average}')"
]
},
{
"cell_type": "markdown",
"id": "ad174346-d177-474f-9d53-8e2f8b87be1b",
"metadata": {},
"source": [
"In general, it is more important to get the initial density close as the initial temperature is quickly washed out by the heating and subsequent cooling by thermal conduction. However, to have more a balance in agreement between the two quantities (i.e. make the density agreement \"worse\" but the temperature agreement better), you can always fiddle with the background heating a bit. Unless you're interested in closely comparing the solutions of the two models though and benchmarking one against the other, this is not as important, particularly in the case of multiple heating and cooling cycles."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f1bb4f4d-4814-4235-a830-f9d43bfa3f23",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:mocksipipeline]",
"language": "python",
"name": "conda-env-mocksipipeline-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment