Karel van de PlasscheThese are the options available to QLKNN fortran. The options are given as a derived data type found in src/core/qlknn_types.f90. All options are also exposed to MATLAB, where they are given by a struct.
| option | default | description |
|---|---|---|
| apply_victor_rule | false | Apply the 'Victor' rotation model in postprocessing |
| use_ion_diffusivity_networks | false | True: Return D_i if use_effective_diffusivity = false
|
False: Return D_e if use_effective_diffusivity = false
|
||
| use_effective_diffusivity | true | Return \Gamma_{e}, not separarate Ds and Vs |
| calc_heat_transport | true | Return q_i and q_e for all modes (not implemented yet) |
| calc_part_transport | true | Return \Gamma_{e,eff}, Ds, and Vs for all modes |
| use_ETG | true | Return q_{e,ETG}
|
| use_ITG | true | Return q_{e,ITG}, q_{i,ITG}, \Gamma_{e,ITG}, D_{i,ITG}, D_{e,ITG}
|
| use_TEM | true | Return q_{e,TEM}, q_{i,TEM}, \Gamma_{e,TEM}, D_{i,TEM}, D_{e,TEM}
|
| constrain_inputs | true | Constrain inputs at QLKNN ingestion to set ranges |
| min_input, max_input, margin_input | per net | min, max and margin of QLKNN input clipping |
| constrain_outputs | true | Constrain outputs after QLKNN calculation, but before merging modes together |
| min_output, max_output, margin_output | per net | min, max and margin of QLKNN output clipping |
The following debug options are also available, but should not be touched in general. Additionally, the verbosity input is passed from any implementing interface where QLKNN verbosity = interface verbosity - 1
| option | default | description |
|---|---|---|
| apply_stability_clipping | true | Clip all transport if leading flux is <=0
|
| merge_modes | true | Merge modes together. (e.g. q_{e} = q_{e, ETG} + q_{e, ITG} + q_{e, TEM}) |
| force_evaluate_all | false | Override all flags, and evaluate and return all fluxes |
Flags can be combined in an and-like fashion. For example use_ITG = false use_effective_diffusivity = false and rest default will return q_{e,ETG}, q_{e,TEM}, q_{i,TEM}, \Gamma_{e,TEM}, D_{e,TEM}
QLKNN-10D IO
The call signature of QLKNN-10D is as follows
evaluate_QLKNN_10D(input, nets, qlknn_out, verbosityin, optsin, qlknn_normsin, dqlknn_out_dinput)| argument | description | shape | optional |
|---|---|---|---|
| input | Input array to NNs | 11xnrho | no |
| nets | The networks to be evaluated, see type net_collection in src/qlknn_types.f90
|
- | no |
| qlknn_out | output array of the evaluated networks | nrho x nout | no |
| verbosityin | verbosity of debug messages | - | yes, default = 0 |
| optsin | Options (described above) to QLKNN | - | yes, defaults as above |
| qlknn_normsin | normalizations needed for victor rule | - | yes, mandatory if use_victor_rule = true
|
| dqlknn_out_dinput | Jacobian of QLKNN with respect to input vector | nout x nrho x 10 | yes |
nout is the amount of networks if merge_modes = false. The columns are (1)q_{e,ETG}, (2)q_{e,ITG}, (3)q_{e,TEM}, (4)q_{i,ITG}, (5)q_{i,TEM}, (6)\Gamma_{e,ITG}, (7)\Gamma_{e,TEM}, (8)D_{e,ITG}, (9)D_{e,TEM}, (10)V_{t,e,ITG}, (11)V_{t,e,TEM}, (12)V_{c,e,ITG}, (13)V_{c,e,TEM}, (14)D_{i,ITG}, (15)D_{i,TEM}, (16)V_{t,i,ITG}, (17)V_{t,i,TEM}, (18)V_{c,i,ITG}, (19)V_{c,i,TEM}, (20)\gamma_0
if merge_modes = true nout = 10, namely (1)q_{e}, (2)q_{e,ETG}, (3)q_{i}, (4)\Gamma_{e}, (5)D_{e}, (6)V_{t,e}, (7)V_{c,e}, (8)D_{i}, (9)V_{t,i}, (10)V_{c,i}
RAPTOR NOTE: As of legacy (sorry!) in RAPTOR it is: if merge_modes = true nout = 7, namely (1)q_{e}, (2)q_{i}, (3)\Gamma_{e}, (4)D_{e}, (5)V_{e}, (6)D_{i}, (7)V_{i}
Input is not hard-coded, but currently:
(1)Z_{eff}, (2)RLT_i, (3)RLT_e, (4)RLn, (5)q, (6)\hat{s}, (7)x, (8)T_i/T_e, (9)\log{\nu^*}, (10)\gamma_{ExB}, (11)T_e, where T_e is only needed if use_victor_rule = true
All in-out quantities are in GyroBohm and/or QuaLiKiz convenient units when applicable.
Conversion from QLKNN to TCI interface
The QLKNN outputs fluxes in QuaLiKiz GB units. The inputs are QuaLiKiz convenient units.
| variable | definition | calculation | TCI field |
|---|---|---|---|
A_{ns} |
Normalized logarithmic density gradient | -\frac{R_0}{n_{s, FSA}} * \frac{dn_{s, FSA}}{dr_{minor}} |
- |
A_{ts} |
Normalized logarithmic temperature gradient | -\frac{R_0}{T_s} \frac{dT_s}{dr_{minor}} |
- |
n_{s,LFS} |
Density in [m**-3] on LFS midplane | - |
ni_LFS/ne_LFS
|
n_{s,FSA} |
Density in [m**-3] Flux Surface Avaraged | - |
ni/ne
|
T_e |
temperature in [J] | - | Te |
q_s |
Heat transport SI | (n_{s,LFS} * T_s * \chi_{GB})/a_{ref} * q_{s,NN} |
heat_fluxes |
\Gamma_e |
Particle transport SI | (n_{s,LFS} * \chi_{GB})/a_{ref} * \Gamma_{e,NN} |
particle_fluxes |
\chi_{s, eff} |
Effective heat diffusivity | q_s / (n_{s,FSA} * A_{ts} * \frac{T_s}{R_0}) |
chieff |
V_{s, t, eff} |
Effective heat pinch | q_s / (n_{s,FSA} T_s) |
- |
D_{s, eff} |
Effective diffusivity | \Gamma_{FSA} / (A_{ns} \frac{n_{s, FSA}}{R_0}) |
deff |
V_{s, p, eff} |
Effective particle pinch | \Gamma_{FSA} / n_{s, FSA} |
- |
Note that QuaLiKiz R_0 == R_{0,TCI}, and we don't have heavy impurity 2D effects, so $\Gamma_{FSA} == \Gamma_{asym} == \Gamma$. $aref=Rmin_in(1)$.
Now there are multiple options to get the \chi, V_t, D and V terms for the transport equation solver (TCI chi, Vt, d and Vp respectively)
1. effective flux
If heat_fluxes * A_{ts} > 0 and |A_{ts}| >=0.1:
chi = \chi_{s, eff}
Vt = 0
else (as RAPTOR doesn't have Vt, this is never true in RAPTOR)
chi = 0
Vt = V_{s, t, eff}
Similar for the particle fluxes, if particle_fluxes * A_{ns} > 0 and |A_{ns}| >=0.1:
D = D_{s, eff}
Vp = 0
else (as RAPTOR doesn't have Vt, this is never true in RAPTOR)
D = 0
Vp = V_{s, p, eff}
- Using the electron D's/V's
Transport in transport codes
In general it depends on the transport equation being solved which transport coefficients QLKNN has to provide. In jetto this is for all ions and electrons:
TRANSPORT%chi
TRANSPORT%Vt
TRANSPORT%d
TRANSPORT%Vp
TRANSPORT%chimom