Skip to main content

SLiM project and its supporting scripts

Project description

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

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

GUI: 000GUI_SLiM_mode_finder.py

script: 00SLiM_mode_finder.py

  1. 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

  1. 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

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

  2. 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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

SLiM_phys-0.1.2.tar.gz (65.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

SLiM_phys-0.1.2-py3-none-any.whl (71.9 kB view details)

Uploaded Python 3

File details

Details for the file SLiM_phys-0.1.2.tar.gz.

File metadata

  • Download URL: SLiM_phys-0.1.2.tar.gz
  • Upload date:
  • Size: 65.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for SLiM_phys-0.1.2.tar.gz
Algorithm Hash digest
SHA256 04d36899a6afcfb4a2dfeb7262b152ff55e616f09ad46f7e33e3fac1ffbd4451
MD5 03c16414d8ccc637239470bfd0c4aabe
BLAKE2b-256 d5069912f63d314673407f9bf4a6db5b99bc98dc0b45250de89cdc357220fdc4

See more details on using hashes here.

File details

Details for the file SLiM_phys-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: SLiM_phys-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 71.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for SLiM_phys-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 ee92089faefdd5da70920abdc293783181e64aa79048ba6cccf8b70a48398115
MD5 ada99c65061c09c91c112c2c1abefaef
BLAKE2b-256 7cfb661d8908374032942cce7150abec4e15bab379d62212b8e86945c217d3ad

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page