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4 results for “Vlasov-Poisson 1D-1V”
1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments for Strong Antenna Emission Amplitudes
<p>This dataset contains the outputs of numerical simulations performed to assess the impact of strong antenna emission amplitudes on the diagnostic performance of mutual impedance experiments. In the case of small emission amplitudes, the plasma response to the emission is linear. In the case of large emission amplitude, instead, non-linear wave-wave and wave-particle interactions are triggered. Using the outputs contained in this dataset, we investigated how such wave-wave and wave-particle interactions perturb mutual impedance experiments.</p> <p>Numerical model:<br> The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson system of equations. The scheme used to solve the model is the one developed by Mangeney, et al. (2002). <em>A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics</em>, (doi: <a href="https://doi.org/10.1006/jcph.2002.7071">https://doi.org/10.1006/jcph.2002.7071</a>). The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010),<em> Vlasov-Poisson simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind, Journal of Geophysical Research (Space Physics), 115, 6106 </em> <em>(</em>doi: <a href="https://doi.org/10.1029/2009JA014969">https://doi.org/10.1029/2009JA014969</a> <em>)</em> <em>.</em></p>
1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments in the presence of small-scale and large-scale plasma inhomogeneities - PART 3
<p>PART 1 IS FOUND AT <strong>https://doi.org/10.5281/zenodo.8118023</strong></p> <p>PART 2 IS FOUND AT <strong> https://doi.org/10.5281/zenodo.8119090</strong></p> <p> </p> <p>=====================================================================================================<br> Author : L. Bucciantini<br> Date : 05/07/2023<br> Laboratory : CNRS-LPC2E, Orléans (France)<br> =====================================================================================================</p> <p>Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will<br> find in it.</p> <p>In case you need help with using the dataset, or if you are interested in mutual impedance experiments,<br> do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu)</p> <p>=====================================================================================================<br> Topic:<br> This dataset contains the outputs of numerical simulations performed to assess<br> the impact of plasma inhomogeneities on the diagnostic performance<br> of mutual impedance experiments.</p> <p><br> Numerical model:<br> The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson<br> system of equations. The scheme used to solve the model is the one developed<br> by Mangeney et al. (2002), A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071).<br> The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson<br> simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind,<br> Journal of Geophysical Research (Space Physics), 115, 6106 (2010)<br> -----------------------------------------------------------------------------------------------------<br> What is inside the dataset:</p> <p>The dataset is composed of 7 different mutual impedance measurements, each corresponding to one<br> directory (see below). The measurements (i.e. directory) correspond to small-scale plasma inhomogeneities at different<br> positions with respect to the mutual impedance antennas, or to a large-scale plasma inhomogeneity.</p> <p>Each directory contains a number of folders. Each folder corresponds to the emission of a signal at<br> different frequency.<br> -----------------------------------------------------------------------------------------------------<br> List of directories:</p> <p>(Note : each directory corresponds to one mutual impedance measurement)</p> <p>L : These outputs correspond to one mutual impedance measurement in<br> small antenna emission amplitude, which corresponds to a linear<br> plasma response to the emission.</p> <p>s_xx : Each of these outputs corresponds to one mutual impedance measurement in correspondance of<br> a small-scale plasma inhomogeneity at xx Debye lengths of distance from the emitting antenna<br> </p> <p>-----------------------------------------------------------------------------------------------------<br> List of folders inside the directories:</p> <p>Folders begin with the name "000" and have increasing index. Inside the same directory, each folder<br> represents a different simulation used to build the same mutual impedance measurement.</p> <p>------------------------------------------------------------------------------------------------------<br> List of files inside the folders:</p> <p>density_e.npz : electron density inside the box, in function of time (tempo)</p> <p>density_p.npz : ion density inside the box, in function of time (tempo)</p> <p>E.npz : electric field in the box, in function of time (tempo)</p> <p>qrho.npz : electric potential in the box, in function of time (tempo)</p> <p>qrho_imposed.npz : electric charge imposed at the emitting antennas, in function of time (tempo)</p> <p>tempo.npz : time-vector for density, electric field, electric potential and charge vectors</p> <p>TEST_Luca.dat : parameters describing the characteristics of the simulated plasma box</p> <p><br> [<br> Note : the previous files can be opened as follows</p> <p>import numpy as np</p> <p>vector_file_name = np.load('file_name.npz') # Use these for the .npz files<br> characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1)</p> <p>]</p> <p><br> -------------------------------------------------------------------------------------------------------<br> Characteristics of the simulated plasma box (TEST_Luca.dat)</p> <p>nx : amount of spatial grid points</p> <p>xl : physical size of the spatial box, expressed in Debye length</p> <p>tt_w : time resolution for ion and electron density, electric field, electric potential and charge</p> <p>rap_m : ion-to-electron mass ratio</p> <p>R_p : ion-to-electron temperature ratio</p> <p>dt : time step used to evolve in time the numerical simulation</p> <p>emission : emission frequency</p> <p>power : amplitude of the electric charge imposed at the emitting antennas</p> <p><br> (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional<br> functionalities of the model. For the use of this dataset, they can be discarded.)</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments in the presence of small-scale and large-scale plasma inhomogeneities - PART 1
<p>=====================================================================================================<br> Author : L. Bucciantini<br> Date : 05/07/2023<br> Laboratory : CNRS-LPC2E, Orléans (France)<br> =====================================================================================================</p> <p>Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will<br> find in it.</p> <p>In case you need help with using the dataset, or if you are interested in mutual impedance experiments,<br> do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu)</p> <p>=====================================================================================================<br> Topic:<br> This dataset contains the outputs of numerical simulations performed to assess<br> the impact of plasma inhomogeneities on the diagnostic performance<br> of mutual impedance experiments.</p> <p><br> Numerical model:<br> The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson<br> system of equations. The scheme used to solve the model is the one developed<br> by Mangeney et al. (2002), A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071).<br> The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson<br> simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind,<br> Journal of Geophysical Research (Space Physics), 115, 6106 (2010)<br> -----------------------------------------------------------------------------------------------------<br> What is inside the dataset:</p> <p>The dataset is composed of 7 different mutual impedance measurements, each corresponding to one<br> directory (see below). The measurements (i.e. directory) correspond to small-scale plasma inhomogeneities at different<br> positions with respect to the mutual impedance antennas, or to a large-scale plasma inhomogeneity.</p> <p>Each directory contains a number of folders. Each folder corresponds to the emission of a signal at<br> different frequency.<br> -----------------------------------------------------------------------------------------------------<br> List of directories:</p> <p>(Note : each directory corresponds to one mutual impedance measurement)</p> <p>L : These outputs correspond to one mutual impedance measurement in<br> small antenna emission amplitude, which corresponds to a linear<br> plasma response to the emission.</p> <p>s_xx : Each of these outputs corresponds to one mutual impedance measurement in correspondance of<br> a small-scale plasma inhomogeneity at xx Debye lengths of distance from the emitting antenna<br> </p> <p>-----------------------------------------------------------------------------------------------------<br> List of folders inside the directories:</p> <p>Folders begin with the name "000" and have increasing index. Inside the same directory, each folder<br> represents a different simulation used to build the same mutual impedance measurement.</p> <p>------------------------------------------------------------------------------------------------------<br> List of files inside the folders:</p> <p>density_e.npz : electron density inside the box, in function of time (tempo)</p> <p>density_p.npz : ion density inside the box, in function of time (tempo)</p> <p>E.npz : electric field in the box, in function of time (tempo)</p> <p>qrho.npz : electric potential in the box, in function of time (tempo)</p> <p>qrho_imposed.npz : electric charge imposed at the emitting antennas, in function of time (tempo)</p> <p>tempo.npz : time-vector for density, electric field, electric potential and charge vectors</p> <p>TEST_Luca.dat : parameters describing the characteristics of the simulated plasma box</p> <p><br> [<br> Note : the previous files can be opened as follows</p> <p>import numpy as np</p> <p>vector_file_name = np.load('file_name.npz') # Use these for the .npz files<br> characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1)</p> <p>]</p> <p><br> -------------------------------------------------------------------------------------------------------<br> Characteristics of the simulated plasma box (TEST_Luca.dat)</p> <p>nx : amount of spatial grid points</p> <p>xl : physical size of the spatial box, expressed in Debye length</p> <p>tt_w : time resolution for ion and electron density, electric field, electric potential and charge</p> <p>rap_m : ion-to-electron mass ratio</p> <p>R_p : ion-to-electron temperature ratio</p> <p>dt : time step used to evolve in time the numerical simulation</p> <p>emission : emission frequency</p> <p>power : amplitude of the electric charge imposed at the emitting antennas</p> <p><br> (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional<br> functionalities of the model. For the use of this dataset, they can be discarded.)</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments in the presence of small-scale and large-scale plasma inhomogeneities - PART 2
<p>PART 1 IS FOUND AT <strong>https://doi.org/10.5281/zenodo.8118023</strong></p> <p> </p> <p> </p> <p>=====================================================================================================<br> Author : L. Bucciantini<br> Date : 05/07/2023<br> Laboratory : CNRS-LPC2E, Orléans (France)<br> =====================================================================================================</p> <p>Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will<br> find in it.</p> <p>In case you need help with using the dataset, or if you are interested in mutual impedance experiments,<br> do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu)</p> <p>=====================================================================================================<br> Topic:<br> This dataset contains the outputs of numerical simulations performed to assess<br> the impact of plasma inhomogeneities on the diagnostic performance<br> of mutual impedance experiments.</p> <p><br> Numerical model:<br> The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson<br> system of equations. The scheme used to solve the model is the one developed<br> by Mangeney et al. (2002), A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071).<br> The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson<br> simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind,<br> Journal of Geophysical Research (Space Physics), 115, 6106 (2010)<br> -----------------------------------------------------------------------------------------------------<br> What is inside the dataset:</p> <p>The dataset is composed of 7 different mutual impedance measurements, each corresponding to one<br> directory (see below). The measurements (i.e. directory) correspond to small-scale plasma inhomogeneities at different<br> positions with respect to the mutual impedance antennas, or to a large-scale plasma inhomogeneity.</p> <p>Each directory contains a number of folders. Each folder corresponds to the emission of a signal at<br> different frequency.<br> -----------------------------------------------------------------------------------------------------<br> List of directories:</p> <p>(Note : each directory corresponds to one mutual impedance measurement)</p> <p>L : These outputs correspond to one mutual impedance measurement in<br> small antenna emission amplitude, which corresponds to a linear<br> plasma response to the emission.</p> <p>s_xx : Each of these outputs corresponds to one mutual impedance measurement in correspondance of<br> a small-scale plasma inhomogeneity at xx Debye lengths of distance from the emitting antenna<br> </p> <p>-----------------------------------------------------------------------------------------------------<br> List of folders inside the directories:</p> <p>Folders begin with the name "000" and have increasing index. Inside the same directory, each folder<br> represents a different simulation used to build the same mutual impedance measurement.</p> <p>------------------------------------------------------------------------------------------------------<br> List of files inside the folders:</p> <p>density_e.npz : electron density inside the box, in function of time (tempo)</p> <p>density_p.npz : ion density inside the box, in function of time (tempo)</p> <p>E.npz : electric field in the box, in function of time (tempo)</p> <p>qrho.npz : electric potential in the box, in function of time (tempo)</p> <p>qrho_imposed.npz : electric charge imposed at the emitting antennas, in function of time (tempo)</p> <p>tempo.npz : time-vector for density, electric field, electric potential and charge vectors</p> <p>TEST_Luca.dat : parameters describing the characteristics of the simulated plasma box</p> <p><br> [<br> Note : the previous files can be opened as follows</p> <p>import numpy as np</p> <p>vector_file_name = np.load('file_name.npz') # Use these for the .npz files<br> characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1)</p> <p>]</p> <p><br> -------------------------------------------------------------------------------------------------------<br> Characteristics of the simulated plasma box (TEST_Luca.dat)</p> <p>nx : amount of spatial grid points</p> <p>xl : physical size of the spatial box, expressed in Debye length</p> <p>tt_w : time resolution for ion and electron density, electric field, electric potential and charge</p> <p>rap_m : ion-to-electron mass ratio</p> <p>R_p : ion-to-electron temperature ratio</p> <p>dt : time step used to evolve in time the numerical simulation</p> <p>emission : emission frequency</p> <p>power : amplitude of the electric charge imposed at the emitting antennas</p> <p><br> (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional<br> functionalities of the model. For the use of this dataset, they can be discarded.)</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
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