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15 results for “magnetohydrodynamics”
Data for paper "Magnetohydrodynamic Equilibrium Reconstruction with Consistent Uncertainties"
<p>Data and scripts for the conference paper "Magnetohydrodynamic Equilibrium Reconstruction with Consistent Uncertainties" for the 42nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering.</p> <p><strong>Abstract</strong>: We report on progress towards a probabilistic framework for consistent uncertainty quantification and propagation in analysis and numerical modeling of physics in magnetically confined plasmas in the stellarator configuration. A frequent starting point in this process is the calculation of a magnetohydrodynamic equilibrium from plasma profiles. Profiles and therefore the equilibrium are typically reconstructed from experimental data. What sets equilibrium reconstruction apart from usual inverse problems is that profiles are given as functions over a magnetic flux derived from the magnetic field, rather than spatial coordinates. This makes it a fixed-point problem that is traditionally left inconsistent or solved iteratively in a least-squares sense[1–3]. The aim here is towards a straightforward and transparent process to quantify and propagate uncertainties and their correlations for function-valued fields and profiles in this setting. We propose a framework that utilizes a low dimensional prior distribution of equilibria, constructed with principal component analysis. A surrogate of the forward model[4] is trained to enable faster sampling.</p> <p><strong>Funding</strong>: The present contribution is supported by the Helmholtz Association of German Research Centers under the joint research school HIDSS-0006 'Munich School for Data Science - MUDS'. This work has been carried out within the framework of the EUROfusion Consortium, funded by the European Union via the Euratom Research and Training Programme (Grant Agreement No 101052200 - EUROfusion). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them.</p>
Binary data file needed for the Shen et al. (2011) equation of state implemented in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** this file is downloaded automatically from this repository on running Phantom **</p> <p>Contains information needed to load the <a href="http://adsabs.harvard.edu/abs/2011PhRvC..83c5802S">Shen, Horowitz & Teige (2011)</a> equation of state for nuclear matter in Phantom simulations</p> <p>The data file is a binary data file that enables a fast read of the information listed in the ascii tables given in the supplementary material of the Shen et al paper. The original ascii data files can be found here:</p> <p><a href="https://journals.aps.org/prc/supplemental/10.1103/PhysRevC.83.035802">https://journals.aps.org/prc/supplemental/10.1103/PhysRevC.83.035802</a></p> <p>For information on how to read this file, see the Phantom source code (<a href="https://github.com/danieljprice/phantom/blob/master/src/main/eos_shen.f90">eos_shen.f90</a>)</p>
Turbulence pattern files used for star cluster formation in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** these files are automatically downloaded by Phantom on running the code **</p> <p>The files here are sample cubes containing turbulent driving patterns for the velocity field (vx, vy and vz) used to initiate star cluster formation simulations in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code</p> <p>These can be used to set up initial conditions for a set of simulations similar to those shown in <a href="http://adsabs.harvard.edu/abs/2003MNRAS.339..577B">Bate, Bonnell & Bromm (2003)</a>. The files here are not the original driving patterns used in the BBB03 simulations, but have the same structure, and give a default driving pattern that can be used without having to re-generate the files. A similar set of files was used for the simulations published in <a href="https://ui.adsabs.harvard.edu/abs/2017MNRAS.465..105L">Liptai et al. (2017)</a>.</p> <p>The files were generated with a piece of code written by Volker Bromm, which was originally part of Matthew Bate's sphNG simulation code.</p> <p>For details of how to read these files, see the Phantom source code (<a href="https://github.com/danieljprice/phantom/blob/master/src/setup/velfield_fromcubes.f90">src/setup/velfield_fromcubes.f90</a>)</p>
Data files for the tabulated MESA equation of state in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<div> <div> <div> <p>** These tables are automatically downloaded from this repository when running phantom **<br><br>This tabulated equation of state in PHANTOM is adapted from the logPgas − Temperature equation of state tables provided with the open source package Modules for Experiments in Stellar Astrophysics MESA (Paxton et al. 2011). Details of the data, originally compiled from blends of equations of state from Saumon, Chabrier, & van Horn (1995) (SCVH), Timmes & Swesty (2000), Rogers & Nayfonov (2002, also the 2005 update), Potekhin & Chabrier (2010) and for an ideal gas, are outlined by Paxton et al. (2011).</p> <p>Code to read these tables is available as part of phantom (<a href="https://github.com/danieljprice/phantom/blob/master/src/main/eos_mesa_microphysics.f90">src/main/eos_mesa.f90</a>). The original version of these tables and the module to read them was contributed by Tom Constantino from the MUSIC code (<a href="https://ui.adsabs.harvard.edu/abs/2017A&A...600A...7Ga">Goffrey et al. 2017</a>), and the phantom implementation described in <a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. (2018)</a>.The current tables were created by Tom Reichardt for the paper Reichardt et al. (2020):<br><br><a href="https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.5333R/abstract">https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.5333R/abstract</a></p> </div> </div> </div> <p>Figure 1 in Reichardt et al. (2020) shows the pressure, temperature, Gamma and P/Pideal shown as a function of internal energy and density from these tables</p>
Datasets for ``Chiral magnetohydrodynamics with zero total chirality''
<pre>This directory contains an index.html file with links to the run directories and idl plotting routines with secondary data for the other figures for the paper "Chiral Magnetohydrodynamics with Zero Total Chirality" by A. Brandenburg, K. Kamada, K. Mukaida, K. Schmitz, and J. Schober. If anything turns out to be incomplete, please email brandenb@nordita.org.</pre>
Data file needed for star cluster setup in Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** this file is automatically downloaded by Phantom when running the starcluster setup **</p> <p>This is a small ascii file containing positions and velocities of stars utilised in the "starcluster" configuration in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code (<a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. 2018</a>). It is used to set up a collection of N-body particles.</p> <p>The star cluster setup (and the data file) were written by Yann Bernard as part of his PhD thesis at<strong> </strong>Université Grenoble Alpes. The datafile is published here so it can be used in the automated code testing via github actions. </p> <p>The columns are mass, position (x,y,z) and velocity (vx,vy,vz) for all of the stars in the simulation</p>
Binary data file used for analysis_common_envelope unit testing in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** this file is automatically downloaded as part of the Phantom github actions tests **</p> <p>This is an example snapshot from a Phantom simulation of a common envelope interaction, taken from the paper by <a href="https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.3181G">González-Bolívar et al. (2022)</a>. It is posted here primarily in order to perform unit and regression testing on the <a href="https://github.com/danieljprice/phantom/blob/master/src/utils/analysis_common_envelope.f90">analysis_common_envelope</a> module in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code (<a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. 2018</a>).</p>
The data for "Periodic Coronal Rain Driven by Self-consistent Heating Process in a Radiative Magnetohydrodynamic Simulation"
<p>The volumetric heating rate along the coronal loop at all time steps in the work is provided as 'appendix_heating.h5'. The Python script for reading and plotting the data is provided as 'read_appendix_heating.py'. Note that the python module 'h5py' is necessary to read .h5 file.</p>
Data file needed for implementation of the Helmholtz equation of state in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** this file is downloaded automatically on running Phantom **<br><br>This is a datafile containing information needed to utilise the Helmholtz equation of state (<a href="http://adsabs.harvard.edu/abs/2000ApJS..126..501T">Timmes & Swesty 2000</a>) implemented in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code (<a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. 2018</a>). </p> <p>Primarily used to model degenerate matter in white dwarfs</p> <p>For information about how to read the file and its contents, refer to the relevant module in the phantom source code (<a href="https://github.com/danieljprice/phantom/blob/master/src/main/eos_helmholtz.f90">eos_helmholtz.f90</a>)</p>
Influence of magnetohydrodynamics configuration on aerothermodynamics during Martian reentry
<p>This paper investigates the role of magnetohydrodynamics (MHD) on the aerothermodynamics (ATD) of a representative entry vehicle while flying into the Martian atmosphere. By strategically placing a flight-ready superconducting magnet at varied positions in the Schiaparelli reentry capsule of the ExoMars mission, we discern its impact on essential flow properties. The primary consequence of MHD during atmospheric entry is the generation of the Lorentz force, which increases the shock standoff distance resulting in a reduction of the heat flux on the spacecraft by pushing high-energy plasma particles away. Through different magnet configurations, three distinct cases are formed to comprehensively understand the effects and implications of each setup. The study is performed using the COOLFluiD MHD for EnTries, an in-house ATD solver. For case 1, the magnet's placement behind the ExoMars forebody at the stagnation point reduces the heat flux. In case 2, the magnet's relocation to the shoulder region explores its potential to mitigate communication blackouts by influencing the wake region's flow. However, this positioning also induces shock bending, leading to variations in post-shock species mass fractions and heat flux spikes in the post-shock region. Case 3, involving an additional magnet where the shock bends in case 1, showcases a consistent increase in shock standoff distance across the forebody, providing a longer relaxation zone for species equilibration. Our findings highlight that while the strength of the applied magnetic field is crucial, the magnet's size is equally pivotal in determining ATD behavior. Case 3 emerges as the most promising configuration, consistently reducing heat flux across the forebody and maintaining it in the afterbody. This study underscores the potential of multi-magnet configurations as next-generation MHD heat shields for Martian atmospheric entry, emphasizing the criticality of magnet placement and configuration in enabling future MHD-enhanced deep space exploration missions.</p>
Datasets for ``Magnetohydrodynamics predicts heavy-tailed distributions of axion-photon conversion''
<p>This directory contains an index.html file with links to the run<br> directories and idl plotting routines with secondary data for the other<br> figures for the paper "Magnetohydrodynamics predicts heavy-tailed<br> distributions of axion-photon conversion" by P. Carenza, R. Sharma,<br> M. C. D. Marsh, A. Brandenburg, & E. Mueller. If anything turns out to<br> be incomplete, please email brandenb@nordita.org.</p> <p>We provide details of the simulations of small-scale dynamo used for<br> the paper and provide also 3D snapshots of the magnetic fields for the<br> kinetic stage (bb8.dat) and the saturated stage (bb10.dat).</p> <p>Here, we also provide data files containing the probability of conversion<br> of photon to axion for MHD realization of the magnetic field. These<br> probabilities have been calculated using Eqs. (4) and (6) of our paper<br> and the data files bb8.dat and bb10.dat provided in the previous upload.<br> In data files relevant for Figs. 2, 5, and 6, the first and second<br> columns are the x and y coordinates, the third and fourth column<br> gives the probability of conversion for the linearly polarised light<br> in the y and x direction, respectively, and the fifth column gives the<br> probability for the unpolarised light. Additionally, we have data files,<br> "power_mag_bb8.dat" and "power_mag_bb10.dat," which contain data for<br> the magnetic field power spectra for the kinetic and saturated cases.</p> <p>Content:<br> ALP_MHD.zip (115.4 MB)<br> zip file with all run directories.</p> <p>bb10.dat (1.6 GB)<br> Run S, magnetic field as a single array, bb(512,512,512,3),</p> <p>bb10gau.dat (1.6 GB)<br> Gaussian magnetic field for Run S (same spectrum as bb10.dat)</p> <p>bb8.dat (1.6 GB)<br> Run K, magnetic field as a single array, bb(512,512,512,3),</p> <p>bb8gau.dat (1.6 GB)<br> Gaussian magnetic field for Run K (same spectrum as bb8.dat)</p> <p>D512_Pm20a2_bb8_versus_z.mpg (4.2 MB)<br> Anination of different z cross-sections for Run K</p> <p>D512_Pm20a2_versus_t.mpg (50.3 MB)<br> Anination of time evolution for Run S</p> <p>D512_Pm20a2_versus_z.mpg (5.8 MB)<br> Anination of different z cross-sections for Run S</p> <p>D512_Pm20a_gaussian9_versus_z.mpg (14.3 MB)<br> Anination of different z cross-sections for Gaussian version of Run K</p> <p>D512_Pm20a_gaussian_bb10_versus_z.mpg (9.5 MB)<br> Anination of different z cross-sections for Gaussian version of Run S</p> <p>D512_Pm20a_versus_t.mpg (19.3 MB)<br> Anination of time evolution for Run K</p> <p>rr10.dat (1.1 GB)<br> Density for Run S, rr(512,512,512).</p> <p>rr8.dat (1.1 GB)<br> Density for Run K, rr(512,512,512).</p> <p><br> Analysis files for figures (34.5 MB each)</p> <p>fig2a_bb8.dat<br> fig2b_bb8.dat<br> fig2c_bb8.dat</p> <p>fig2d_bb10.dat<br> fig2e_bb10.dat<br> fig2f_bb10.dat</p> <p>fig5a_bb8.dat<br> fig5b_bb10.dat</p> <p>fig6a_mask.dat<br> fig6b_clip.dat</p> <p>power_mag_bb8.dat (6 kB)<br> power_mag_bb10.dat (6 kB)</p>
Initial conditions for galaxy merger setup in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** these files are downloaded automatically by Phantom when running the code **</p> <p>The two files here contain initial conditions (particle positions, velocities etc) for the sample galaxy merger simulation shown in Figure 55 of the Phantom code paper (<a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. 2018</a>). They were created by James Wurster as part of a code comparison with the Hydra code described in section 6.4 of the paper.</p> <p>The files were originally created for use in <a href="http://adsabs.harvard.edu/abs/2013MNRAS.431..539W">Wurster & Thacker (2013)</a></p> <p>For details of how to read these files, see the Phantom source code (<a href="https://github.com/danieljprice/phantom/blob/master/src/setup/setup_galaxies.f90">setup_galaxies.f90</a>)</p>
Coupling the Rice Convection Model-Equilibrium to the Lyon– Fedder–Mobarry Global Magnetohydrodynamic Model
<p>Self-consistent inner-magnetosphere model is driven by inputs from the Lyon-Fedder- Mobarry global magnetohydrodynamic model.</p> <p>The expanded inner magnotospheric modeling region captures high-resolution bursty bulk flows in the plasma sheet.</p> <p>Realistic bursty bulk flows induced aurora patterns are simulated.</p> <p>This includes data and visualization methods that reproduce the figures in the manuscript. Please refer to README for details.</p> <p>Submitted to JGR for review. </p>
Data file for turbulence driving pattern in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** this file is automatically downloaded by phantom on running the code **</p> <p>This is the default driving pattern file used in the "turbdrive" setup of the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code, which was originally written for the set of simulations shown in <a href="http://adsabs.harvard.edu/abs/2010MNRAS.406.1659P">Price & Federrath (2010)</a>. The driving pattern file was originally created by Christoph Federrath.</p> <p>For details and references on the Ornstein-Uhlenbeck stochastic turbulent driving algorithm itself, see section 2.5 of the Phantom code paper (<a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. 2018</a>).</p> <p>The same pattern file has been used in several subsequent studies, including <a href="http://adsabs.harvard.edu/abs/2016MNRAS.461.1260T">Tricco, Price & Federrath (2016)</a> and <a href="http://adsabs.harvard.edu/abs/2017MNRAS.471L..52T">Tricco, Price & Laibe (2017)</a>.</p> <p>For details on how to read this file see the Phantom source code (<a href="https://github.com/danieljprice/phantom/blob/master/src/main/forcing.F90">src/main/forcing.f90</a>)</p>
Influence of magnetohydrodynamics configuration on aerothermodynamics during Martian reentry
<p>This paper investigates the role of magnetohydrodynamics (MHD) on the aerothermodynamics (ATD) of a representative entry vehicle while flying into the Martian atmosphere. By strategically placing a flight-ready superconducting magnet at varied positions in the Schiaparelli reentry capsule of the ExoMars mission, we discern its impact on essential flow properties. The primary consequence of MHD during atmospheric entry is the generation of the Lorentz force, which increases the shock standoff distance resulting in a reduction of the heat flux on the spacecraft by pushing high-energy plasma particles away. Through different magnet configurations, three distinct cases are formed to comprehensively understand the effects and implications of each setup. The study is performed using the COOLFluiD MHD for EnTries, an in-house ATD solver. For case 1, the magnet's placement behind the ExoMars forebody at the stagnation point reduces the heat flux. In case 2, the magnet's relocation to the shoulder region explores its potential to mitigate communication blackouts by influencing the wake region's flow. However, this positioning also induces shock bending, leading to variations in post-shock species mass fractions and heat flux spikes in the post-shock region. Case 3, involving an additional magnet where the shock bends in case 1, showcases a consistent increase in shock standoff distance across the forebody, providing a longer relaxation zone for species equilibration. Our findings highlight that while the strength of the applied magnetic field is crucial, the magnet's size is equally pivotal in determining ATD behavior. Case 3 emerges as the most promising configuration, consistently reducing heat flux across the forebody and maintaining it in the afterbody. This study underscores the potential of multi-magnet configurations as next-generation MHD heat shields for Martian atmospheric entry, emphasizing the criticality of magnet placement and configuration in enabling future MHD-enhanced deep space exploration missions.</p>
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