taueNN

Contacts: Joseph McClenaghan, Tim Slendebroek

Short Description

This module predicts the energy confinement time based on 0D tokamak parameters

Keywords

neural, taue, prediction

Long Description

This modules mocks up approximate equilibrium and sources based on global parameters. Then the global confinement time is predicted by predicting the pedestal with EPED, and the core temperature scale length with TGLF or TGLF-NN.

Typical workflows

This module is used to:

• Input 0D profiles, or input.gacode file

• Run tauenn for predicted confinement

Supported devices

• This module depends on neural nets of TGLF and EPED which have been trained

primarily on conventional tokamaks

Classes

• omfit_classes.omfit_gapy.OMFITinputgacode()

Contributors

List of contributors sorted by number of lines authored:

850 Joseph McClenaghan
 15 Tim Slendebroek
  2 Orso Meneghini

Submodules

None

Users

List of usernames sorted by number of module imports: N/A