Metadata-Version: 2.1
Name: SLiM-phys
Version: 1.0.2
Summary: SLiM project and its supporting scripts
Author: maxtcurie (Max Curie)
Author-email: <maxtcurie@gmail.com>
License: UNKNOWN
Keywords: python,plasma,physics,microtearing modes,reduced model,neural network
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Education
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
License-File: LICENSE


# SLiM

The Slab Like Microtearing mode (SLiM) model



Overview



This software provides a rapid assessment of the slab-like microtearing mode using a global linear dispersion model, which takes 50ms to calculate the growth rate and frequency of a given mode on the personal computer. Potentially uses 10^-7 of the computation resources for discharge study. For detail, one can check on the site (under construction): https://www.drmcurie.com/project-page/Research_Projects/SLiM



SLiM EXE can be found from this link: https://drive.google.com/drive/folders/12e1t6liY5JztwOBOLehPoV8GbfORn_j8?usp=sharing







Executable the program: 



1. Plot the modified the safety factor (q) to see if the rational surfaces are intersected with the q profile. 

 GUI:    000GUI_Plot_q_modification.py

 script: 0Plot_q_modification.py



2. Determine the stabilities of the MTM for different mode numbers 

 GUI:    000GUI_SLiM_mode_finder.py

 script: 00SLiM_mode_finder.py



3. Calculate a list of dispersion relations provided by a csv file

 script: 0MTMDispersion_list_Calc.py

 script(CPU accelerated,beta): 0MTMDispersion_list_Calc_parallel.py





GitHub repo:

https://github.com/maxtcurie/SLiM



APS 2021 invited talk about SLiM model:

https://youtu.be/j2MYfGwlBYY



Playlist for tutorial on running the SLiM model:

https://youtube.com/playlist?list=PLgNi5MiqkBWagsB8yRjRncsz1D4oeedQB



How to use GUI:

    mode finder GUI: https://youtu.be/R_-ldYNvmhU

    plot modified safety factor GUI: https://youtu.be/L01xl_e1bpM





CPU accellerated dispersion calculation:

    With    CPU acceleration: 297.5 sec

    Without CPU acceleration: 481.1 sec



Trained neural network dispersion calculation: 0.05sec





Citation 



This software is based on the following articles and presentations, please the cite those articles in the publications uses such software package: 



1. M.T. Curie, J. L. Larakers, D. R. Hatch, A. O. Nelson, A. Diallo, E. Hassan, W. Guttenfelder, M. Halfmoon, M. Kotschenreuther, R. D. Hazeltine, S. M. Mahajan, R. J. Groebner, J. Chen, C. Perez von Thun, L. Frassinetti, S. Saarelma, C. Giroud, M. M. Tennery (2022) "A survey of pedestal magnetic fluctuations using gyrokinetics and a global reduced model for microtearing stability" Physics of Plasmas (Editor's Pick)

https://doi.org/10.1063/5.0084842



2. M. Curie, J.L. Larakers, D.R. Hatch, A. Diallo, E. Hassan, O. Nelson, W. Guttenfelder, M. Halfmoon, M. Kotschenreuthe, S. M. Mahajan, R. J. Groebner (2021)"Reduced predictive models for Micro-tearing modes in the pedestal" APS DPP

https://doi.org/10.13140/RG.2.2.27713.48482



3. M. Curie (2022) "Simulations and reduced models for Micro-tearing modes in the Tokamak pedestal" Ph.D. Dissertation

https://doi.org/10.13140/RG.2.2.24468.37769



4. J.L. Larakers,  M. Curie, D. R. Hatch, R. D. Hazeltine, and S. M.Mahajan, 2021) "Global Theory of Microtearing Modes in the Tokamak Pedestal" 

https://doi.org/10.1103/PhysRevLett.126.225001





SLiM_obj.py



self.r_sigma

self.R_ref

self.cs_to_kHz

self.omn

self.omn_nominal

self.cs

self.rho_s

self.Lref

self.x

self.shat

self.shat_nominal

self.eta

self.ky

self.ky_nominal=

self.nu

self.zeff

self.beta

self.q

self.q_nominal

self.ome

self.ome_nominal

self.Doppler