FUSE Introductory Tutorial
Download this tutorial from the FuseExamples repository
NOTE: Julia is a Just In Time (JIT) programming language. The first time something is executed it will take longer because of the compilation process. Subsequent calls the the same code will be blazingly fast.
Import the necessary packages
using Plots # for plotting
using FUSE # this will also import IMAS in the current namespaceStarting from a use-case
FUSE comes with some predefined use-cases, some of which are used for regression testing. Note that some use cases are for non-nuclear experiments and certain Actors like Blankets or BalanceOfPlant will not perform any actions.
FUSE.test_casesARC ini, act = FUSE.case_parameters(:ARC)
CAT ini, act = FUSE.case_parameters(:CAT)
D3D ini, act = FUSE.case_parameters(:D3D; scenario=:default)
D3D_Hmode ini, act = FUSE.case_parameters(:D3D; scenario_sources=true, scenario=:H_mode)
D3D_Lmode ini, act = FUSE.case_parameters(:D3D; scenario_sources=false, scenario=:L_mode)
DTT ini, act = FUSE.case_parameters(:DTT)
EXCITE ini, act = FUSE.case_parameters(:EXCITE)
FPP ini, act = FUSE.case_parameters(:FPP)
ITER_ods ini, act = FUSE.case_parameters(:ITER; init_from=:ods)
ITER_scalars ini, act = FUSE.case_parameters(:ITER; init_from=:scalars)
JET_HDB5 ini, act = FUSE.case_parameters(:HDB5; case=500, tokamak=:JET)
KDEMO ini, act = FUSE.case_parameters(:KDEMO)
KDEMO_compact ini, act = FUSE.case_parameters(:KDEMO_compact)
MANTA ini, act = FUSE.case_parameters(:MANTA)
SPARC ini, act = FUSE.case_parameters(:SPARC; init_from=:ods)
Get initial parameters (ini) and actions (act) for a given use-case
ini, act = FUSE.case_parameters(:KDEMO);Modifying ini parameters.
ini.equilibrium.B0 = 7.8
ini.equilibrium.R0 = 6.5;Modifying act parameters.
act.ActorCoreTransport.model = :FluxMatcher;Initialize the data dictionary (dd) using the 0D parameters.
NOTE: init() does not return a self-consistent solution, just a plausible starting point to initialize our simulations!
dd = FUSE.init(ini, act);actors: Equilibrium
actors: TEQUILA
actors: HCD
actors: SimpleEC
actors: SimpleIC
actors: SimpleLH
actors: SimpleNB
actors: SimplePellet
actors: Current
actors: SteadyStateCurrent
actors: CXbuild
actors: PassiveStructuresUsing checkpoints to save and restore states (we'll use this later)
empty!(FUSE.checkpoint)
@checkin :init dd ini actExploring the data dictionary
- FUSE stores data following the IMAS data schema.
- The root of the data structure is
dd, which stands for "Data Dictionary". - More details are available in the documentation.
Display part of the equilibrium data in dd
dd.equilibrium.time_slice[2].boundaryboundary
├─ elongation ➡ 1.99926
├─ elongation_lower ➡ Function
├─ elongation_upper ➡ Function
├─ geometric_axis
│ ├─ r ➡ 6.49971 [m]
│ └─ z ➡ -0.00101717 [m]
├─ minor_radius ➡ 2.00728 [m]
├─ outline
│ ├─ r ➡ 241-element Vector{Float64} [m]
│ │ min:4.51 avg:6.28 max:8.52
│ └─ z ➡ 241-element Vector{Float64} [m]
│ min:-4.08 avg:-0.03 max:3.93
├─ ovality ➡ 0.00308297
├─ squareness ➡ -0.00753311
├─ squareness_lower_inner ➡ Function
├─ squareness_lower_outer ➡ Function
├─ squareness_upper_inner ➡ Function
├─ squareness_upper_outer ➡ Function
├─ strike_point
│ ├─ 1
│ │ ├─ r ➡ 5.44008 [m]
│ │ └─ z ➡ -5.01853 [m]
│ └─ 2
│ ├─ r ➡ 4.24377 [m]
│ └─ z ➡ -4.48402 [m]
├─ tilt ➡ -0.00645963
├─ triangularity ➡ 0.585259
├─ triangularity_lower ➡ Function
├─ triangularity_upper ➡ Function
├─ twist ➡ 0.00262375
└─ x_point
├─ 1
│ ├─ r ➡ 5.10505 [m]
│ └─ z ➡ -4.08783 [m]
└─ 2
├─ r ➡ 4.88353 [m]
└─ z ➡ 4.34169 [m]
this can be done up to a certain depth with print_tree
print_tree(dd.equilibrium.time_slice[2].boundary; maxdepth=1)boundary
├─ elongation ➡ 1.99926
├─ elongation_lower ➡ Function
├─ elongation_upper ➡ Function
├─ geometric_axis
│ ⋮
│
├─ minor_radius ➡ 2.00728 [m]
├─ outline
│ ⋮
│
├─ ovality ➡ 0.00308297
├─ squareness ➡ -0.00753311
├─ squareness_lower_inner ➡ Function
├─ squareness_lower_outer ➡ Function
├─ squareness_upper_inner ➡ Function
├─ squareness_upper_outer ➡ Function
├─ strike_point
│ ⋮
│
├─ tilt ➡ -0.00645963
├─ triangularity ➡ 0.585259
├─ triangularity_lower ➡ Function
├─ triangularity_upper ➡ Function
├─ twist ➡ 0.00262375
└─ x_point
⋮Plotting data from dd
FUSE provides Plots.jl recipes for visualizing data from dd, this means different plots are shown by calling the same plot() function on different items in the data structure. Learn more about Plots.jl here
For example plotting the equilibrium...
plot(dd.equilibrium)
...or the core profiles
plot(dd.core_profiles)
Whant to know what arguments can be passed? use help_plot() function
help_plot(dd.equilibrium; core_profiles_overlay=true, psi_levels_in=21, psi_levels_out=5, show_secondary_separatrix=true, coordinate=:psi_norm)
These plots can be composed by calling plot!() instead of plot()
plot(dd.equilibrium; color=:gray, cx=true)
plot!(dd.build; equilibrium=false, pf_active=false)
plot!(dd.pf_active)
Plotting an array...
plot(dd.core_profiles.profiles_1d[1].pressure_thermal)
...is different from plotting a field from the IDS (which plots the quantity against its coordinate and with units)
plot(dd.core_profiles.profiles_1d[1], :pressure_thermal)
Customizing plot attributes:
plot(dd.core_profiles.profiles_1d[1], :pressure_thermal; label="", linewidth=2, color=:red, labelfontsize=25)
Working with time series
The IMAS data structure supports time-dependent data, and IMAS.jl provides ways to handle time data efficiently.
Each dd has a global_time attribute, and actors operate at such time
dd.global_time0.0Here we see that equilibrium has mulitiple time_slices
dd.equilibrium.time2-element Vector{Float64}:
-Inf
0.0Accessing time-dependent arrays of structures, via integer index
eqt = dd.equilibrium.time_slice[2]
eqt.time0.0At a given time, by passing the time as a floating point number (in seconds)
eqt = dd.equilibrium.time_slice[0.0]
eqt.time0.0At the global time, leaving the square brackets empty
eqt = dd.equilibrium.time_slice[]
eqt.time0.0Using the @ddtime macro to access and modify time-dependent arrays at dd.global_time:
dd.equilibrium.vacuum_toroidal_field.b02-element Vector{Float64}:
7.80034989842101
7.80034989842101Accessing data at dd.global_time
my_b0 = @ddtime(dd.equilibrium.vacuum_toroidal_field.b0)7.80034989842101Writin data at dd.global_time
@ddtime(dd.equilibrium.vacuum_toroidal_field.b0 = my_b0 + 1)
dd.equilibrium.vacuum_toroidal_field.b02-element Vector{Float64}:
7.80034989842101
8.800349898421011Expressions in dd
Some fields in the data dictionary are expressions (ie. Functions). For example dd.core_profiles.profiles_1d[].pressure is dynamically calculated as the product of thermal densities and temperature with addition of fast ions contributions
print_tree(dd.core_profiles.profiles_1d[1]; maxdepth=1)1
├─ conductivity_parallel ➡ Function [ohm^-1.m^-1]
├─ electrons
│ ⋮
│
├─ grid
│ ⋮
│
├─ ion
│ ⋮
│
├─ j_bootstrap ➡ 101-element Vector{Float64} [A/m^2]
│ min:8.02e+03 avg:1.71e+05 max:4.68e+05
├─ j_non_inductive ➡ 101-element Vector{Float64} [A/m^2]
│ min:8.02e+03 avg:8.9e+05 max:5.23e+06
├─ j_ohmic ➡ 101-element Vector{Float64} [A/m^2]
│ min:378 avg:3.59e+05 max:1.15e+06
├─ j_tor ➡ 101-element Vector{Float64} [A/m^2]
│ min:7e+03 avg:1.27e+06 max:6.52e+06
├─ j_total ➡ 101-element Vector{Float64} [A/m^2]
│ min:8.4e+03 avg:1.25e+06 max:6.35e+06
├─ pressure ➡ Function [Pa]
├─ pressure_ion_total ➡ Function [Pa]
├─ pressure_parallel ➡ Function [Pa]
├─ pressure_perpendicular ➡ Function [Pa]
├─ pressure_thermal ➡ Function [Pa]
├─ rotation_frequency_tor_sonic ➡ 101-element Vector{Float64} [s^-1]
│ all:0
├─ t_i_average ➡ Function [eV]
├─ time ➡ 0 [s]
└─ zeff ➡ 101-element Vector{Float64}
all:2accessing a dynamic expression, automatically evaluates it (in the pressure example, we get an array with data)
dd.core_profiles.profiles_1d[1].electrons.pressure101-element Vector{Float64}:
404069.7674418606
402676.39614741056
401188.69386268617
399538.217176196
397724.14560254384
395750.4731921339
393622.078210206
391343.9022614207
388920.7411999893
386357.19999876065
⋮
42719.87665551564
40586.07330511076
37459.269373948504
32406.321396106454
24688.808073507695
14967.908148062737
6626.039795948137
1990.951110677052
218.31440777766358In addition to evaluating expressions by accessing them, expressions in the tree can be evaluated using IMAS.freeze()
print_tree(IMAS.freeze(dd.core_profiles.profiles_1d[1]); maxdepth=1)profiles_1d
├─ conductivity_parallel ➡ 101-element Vector{Float64} [ohm^-1.m^-1]
│ min:2.88e+06 avg:4.1e+09 max:1.36e+10
├─ electrons
│ ⋮
│
├─ grid
│ ⋮
│
├─ ion
│ ⋮
│
├─ j_bootstrap ➡ 101-element Vector{Float64} [A/m^2]
│ min:8.02e+03 avg:1.71e+05 max:4.68e+05
├─ j_non_inductive ➡ 101-element Vector{Float64} [A/m^2]
│ min:8.02e+03 avg:8.9e+05 max:5.23e+06
├─ j_ohmic ➡ 101-element Vector{Float64} [A/m^2]
│ min:378 avg:3.59e+05 max:1.15e+06
├─ j_tor ➡ 101-element Vector{Float64} [A/m^2]
│ min:7e+03 avg:1.27e+06 max:6.52e+06
├─ j_total ➡ 101-element Vector{Float64} [A/m^2]
│ min:8.4e+03 avg:1.25e+06 max:6.35e+06
├─ pressure ➡ 101-element Vector{Float64} [Pa]
│ min:413 avg:4.6e+05 max:9.45e+05
├─ pressure_ion_total ➡ 101-element Vector{Float64} [Pa]
│ min:195 avg:1.86e+05 max:3.6e+05
├─ pressure_parallel ➡ 101-element Vector{Float64} [Pa]
│ min:138 avg:1.53e+05 max:3.15e+05
├─ pressure_perpendicular ➡ 101-element Vector{Float64} [Pa]
│ min:138 avg:1.53e+05 max:3.15e+05
├─ pressure_thermal ➡ 101-element Vector{Float64} [Pa]
│ min:413 avg:3.95e+05 max:7.65e+05
├─ rotation_frequency_tor_sonic ➡ 101-element Vector{Float64} [s^-1]
│ all:0
├─ t_i_average ➡ 101-element Vector{Float64} [eV]
│ min:80 avg:1.48e+04 max:2.64e+04
├─ time ➡ 0 [s]
└─ zeff ➡ 101-element Vector{Float64}
all:2Whole facility design
Here we restore the :init checkpoint that we had previously stored. Resetting any changes to dd, ini, and act that we did in the meantime.
@checkout :init dd ini actActors in FUSE can be executed by passing two arguments to them: dd and act. Internally, actors can call other actors, creating workflows. For example, the ActorWholeFacility can be used to to get a self-consistent stationary whole facility design. The actors: print statements with their nested output tell us what actors are calling other actors.
FUSE.ActorWholeFacility(dd, act);
nothing #hideLike before we can checkpoint results for later use
@checkin :awf dd ini actRunning a custom workflow
Let's now run a series of actors similar to what ActorWholeFacility does and play around with plotting to get a sense of what each individual actor does.
Let's start again from after the initialization stage
@checkout :init dd ini actLet's start by positioning the PF coils, so that we stand a chance to reproduce the desired plasma shape. This will be important to ensure the stability of the ActorStationaryPlasma that we are going to run next.
actor = FUSE.ActorPFdesign(dd, act);actors: PFdesignThe ActorStationaryPlasma iterates between plasma transport, pedestal, equilibrium and sources to return a self-consistent plasma solution
peq = plot(dd.equilibrium; label="before")
pcp = plot(dd.core_profiles; color=:gray, label="before")
FUSE.ActorStationaryPlasma(dd, act);
nothing #hidewe can compare equilibrium before and after the self-consistency loop
plot!(peq, dd.equilibrium; label="after")
we can compare core_profiles before and after the self-consistency loop
plot!(pcp, dd.core_profiles; label="after")
here are the sources
plot(dd.core_sources)
and the flux-matched transport
plot(dd.core_transport)
HFS sizing actor changes the thickness of the OH and TF layers on the high field side to satisfy current and stresses constraints
plot(dd.build)
FUSE.ActorHFSsizing(dd, act);
plot!(dd.build; cx=false)The stresses on the center stack are stored in the solid_mechanics IDS
plot(dd.solid_mechanics.center_stack.stress)LFS sizing actors change location of the outer TF leg to meet ripple requirements
plot(dd.build)
FUSE.ActorLFSsizing(dd, act);
plot!(dd.build; cx=false)
A custom show() method is defined to print the summary of dd.build.layer
dd.build.layer24×10 DataFrame
Row │ group details type ΔR R_start R_end material area volume shape
│ String String String Float64 Float64 Float64 String Float64 Float64 String
─────┼───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ in 1.68288 0.0 1.68288 steel 22.2098 107.051
2 │ in oh 1.02879 1.68288 2.71167 nb3sn 7.70459 87.1544
3 │ hfs tf 0.511494 2.71167 3.22317 nb3sn_kdemo 45.381 919.044 convex hull
4 │ hfs gap tf vacuum vessel 0.0960705 3.22317 3.31924 vacuum 14.6305 779.057 double ellipse
5 │ hfs vacuum outer vessel 0.0960705 3.31924 3.41531 steel 3.13352 127.129 negative offset
6 │ hfs gap water 0.144106 3.41531 3.55941 water 4.59152 186.415 negative offset
7 │ hfs vacuum inner vessel 0.0960705 3.55941 3.65548 steel 2.9885 121.424 negative offset
8 │ hfs gap high temp shield vacuum vess… 0.00960705 3.65548 3.66509 vacuum 0.295659 12.0169 negative offset
9 │ hfs high temp shield 0.192141 3.66509 3.85723 steel 5.79137 235.545 negative offset
10 │ hfs blanket 0.365068 3.85723 4.2223 lithium_lead 22.6154 1015.17 negative offset
11 │ hfs first wall 0.0192141 4.2223 4.24151 tungsten 0.81387 29.4331 offset
12 │ lhfs plasma 4.55071 4.24151 8.79222 plasma 34.7526 1360.62
13 │ lfs first wall 0.0192141 8.79222 8.81144 tungsten 0.812886 29.402 offset
14 │ lfs blanket 1.15285 8.81144 9.96429 lithium_lead 22.6164 1015.2 negative offset
15 │ lfs high temp shield 0.192141 9.96429 10.1564 steel 5.79137 235.545 negative offset
16 │ lfs gap high temp shield vacuum vess… 0.111204 10.1564 10.2676 vacuum 0.295659 12.0169 negative offset
17 │ lfs vacuum inner vessel 0.0960705 10.2676 10.3637 steel 2.9885 121.424 negative offset
18 │ lfs gap water 0.144106 10.3637 10.5078 water 4.59152 186.415 negative offset
19 │ lfs vacuum outer vessel 0.0960705 10.5078 10.6039 steel 3.13352 127.129 negative offset
20 │ lfs gap tf vacuum vessel 0.757997 10.6039 11.3619 vacuum 14.6305 779.057 double ellipse
21 │ lfs tf 0.511494 11.3619 11.8734 nb3sn_kdemo 45.381 919.044 convex hull
22 │ out 1.92141 11.8734 13.7948 vacuum 114.339 6591.64
23 │ out cryostat 0.0960705 13.7948 13.8908 steel 4.64448 294.895 silo
24 │ out 0.960705 13.8908 14.8516 vacuum 48.4753 3201.35ActorHFSsizing and ActorLFSsizing only change the layer's thicknesses, so we then need to trigger a build of the 2D cross-sections after them:
FUSE.ActorCXbuild(dd, act);
plot(dd.build)
Generate passive structures information (for now the vacuum vessel)
FUSE.ActorPassiveStructures(dd, act)
plot(dd.pf_passive)
We can now give the PF coils their final position given the new build
actor = FUSE.ActorPFdesign(dd, act);
plot(actor)
With information about both pfactive and pfpassive we can now evaluate vertical stability
FUSE.ActorVerticalStability(dd, act)
IMAS.freeze(dd.mhd_linear)mhd_linear
├─ time ➡ [0] [s]
└─ time_slice
└─ 1
├─ time ➡ 0 [s]
└─ toroidal_mode
├─ 1
│ ├─ growthrate ➡ 0.11825 [Hz]
│ ├─ n_tor ➡ 0
│ └─ perturbation_type
│ ├─ description ➡ "Vertical stability margin, > 0.15 for stability (N.B., not in Hz)"
│ └─ name ➡ "m_s"
└─ 2
├─ growthrate ➡ 10.444 [Hz]
├─ n_tor ➡ 0
└─ perturbation_type
├─ description ➡ "Normalized vertical growth rate, < 10 for stability (N.B., not in Hz)"
└─ name ➡ "γτ"
The ActorNeutronics calculates the heat flux on the first wall
FUSE.ActorNeutronics(dd, act);
p = plot(; layout=2, size=(900, 350))
plot!(p, dd.neutronics.time_slice[].wall_loading, subplot=1)
plot!(p, FUSE.define_neutrons(dd, 100000)[1], dd.equilibrium.time_slice[]; subplot=1, colorbar_entry=false)
plot!(p, dd.neutronics.time_slice[].wall_loading; cx=false, subplot=2, ylabel="")
The ActorBlanket will change the thickess of the first wall, breeder, shield, and Li6 enrichment to achieve target TBR
FUSE.ActorBlanket(dd, act);
print_tree(IMAS.freeze(dd.blanket); maxdepth=5)actors: Blanket
actors: CXbuild
blanket
├─ module
│ └─ 1
│ ├─ layer
│ │ ├─ 1
│ │ │ ├─ material ➡ "tungsten"
│ │ │ ├─ midplane_thickness ➡ 0.195005 [m]
│ │ │ └─ name ➡ "lfs first wall"
│ │ ├─ 2
│ │ │ ├─ material ➡ "lithium-lead: Li6/7=100.000"
│ │ │ ├─ midplane_thickness ➡ 1.15285 [m]
│ │ │ └─ name ➡ "lfs blanket"
│ │ └─ 3
│ │ ├─ material ➡ "steel"
│ │ ├─ midplane_thickness ➡ 1.49218 [m]
│ │ └─ name ➡ "lfs high temp shield"
│ ├─ name ➡ "blanket"
│ └─ time_slice
│ └─ 1
│ ├─ peak_escape_flux ➡ 952109 [W/m^2]
│ ├─ peak_wall_flux ➡ 2.56731e+06 [W/m^2]
│ ├─ power_incident_neutrons ➡ 2.76935e+08 [W]
│ ├─ power_incident_radiated ➡ 0 [W]
│ ├─ power_thermal_extracted ➡ 3.32322e+08 [W]
│ ├─ power_thermal_neutrons ➡ 3.32322e+08 [W]
│ ├─ power_thermal_radiated ➡ 0 [W]
│ ├─ time ➡ 0 [s]
│ └─ tritium_breeding_ratio ➡ 1.19785
├─ time ➡ [0] [s]
└─ tritium_breeding_ratio ➡ [1.14117]The ActorDivertors actor calculates the divertors heat flux
FUSE.ActorDivertors(dd, act);
print_tree(IMAS.freeze(dd.divertors); maxdepth=4)actors: Divertors
divertors
├─ divertor
│ └─ 1
│ ├─ power_conducted
│ │ ├─ data ➡ [1.27961e+08] [W]
│ │ └─ time ➡ [0] [s]
│ ├─ power_convected
│ │ ├─ data ➡ [0] [W]
│ │ └─ time ➡ [0] [s]
│ ├─ power_incident
│ │ ├─ data ➡ [2.1999e+07] [W]
│ │ └─ time ➡ [0] [s]
│ ├─ power_thermal_extracted
│ │ ├─ data ➡ [2.1999e+07] [W]
│ │ └─ time ➡ [0] [s]
│ └─ target
│ ├─ 1
│ │ ⋮
│ │
│ └─ 2
│ ⋮
│
└─ time ➡ [0] [s]The ActorBalanceOfPlant calculates the optimal cooling flow rates for the heat sources (breeder, divertor, and wall) and get an efficiency for the electricity conversion cycle
actor = FUSE.ActorBalanceOfPlant(dd, act);actors: BalanceOfPlant
actors: ThermalPlant
actors: PowerNeedsplot(actor)
ActorCosting will break down the capital and operational costs
FUSE.ActorCosting(dd, act)
plot(dd.costing)
Let's checkpoint our results
@checkin :manual dd ini actSaving and loading data
tutorial_temp_dir = tempdir()
filename = joinpath(tutorial_temp_dir, "$(ini.general.casename).json")"/tmp/K-DEMO.json"When saving data to be shared outside of FUSE, one can set freeze=true so that all expressions in the dd are evaluated and saved to file.
IMAS.imas2json(dd, filename; freeze=false, strict=false);Load from JSON
dd1 = IMAS.json2imas(filename);Comparing two IDSs
We can introduce a change in the dd1 and spot it with the diff function
dd1.equilibrium.time_slice[1].time = -100.0
IMAS.diff(dd.equilibrium, dd1.equilibrium)Dict{String, String} with 1 entry:
"time_slice[1].time" => "value: -Inf -- -100.0"Summary
Snapshot of dd in 0D quantities (evaluated at dd.global_time)
FUSE.extract(dd)GEOMETRY EQUILIBRIUM TEMPERATURES
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
R0 → 6.5 [m] B0 → 7.8 [T] Te0 → 17.6 [keV]
a → 2.01 [m] ip → 13.1 [MA] Ti0 → 17.1 [keV]
1/ϵ → 3.24 q95 → 7.29 <Te> → 9.85 [keV]
κ → 2 <Bpol> → 0.827 [T] <Ti> → 8.85 [keV]
δ → 0.585 βpol_MHD → 0.943 Te0/<Te> → 1.79
ζ → -0.00753 βtor_MHD → 0.0102 Ti0/<Ti> → 1.93
Volume → 969 [m³] βn_MHD → 1.23
Surface → 780 [m²]
DENSITIES PRESSURES TRANSPORT
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
ne0 → 8.53e+19 [m⁻³] P0 → 0.51 [MPa] τe → 2.04 [s]
ne_ped → 6.93e+19 [m⁻³] <P> → 0.25 [MPa] τe_exp → 2.71 [s]
ne_line → 8.43e+19 [m⁻³] P0/<P> → 2.03 H98y2 → 0.91
<ne> → 8.07e+19 [m⁻³] βn → 1.21 H98y2_exp → 0.994
ne0/<ne> → 1.06 βn_th → 1.15 Hds03 → 0.64
fGW → 0.813 Hds03_exp → 0.728
zeff_ped → 2 τα_thermalization → 0.816 [s]
<zeff> → 2 τα_slowing_down → 0.973 [s]
impurities → DT Ne20 He4
SOURCES EXHAUST CURRENTS
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
Pec → 50 [MW] Psol → 128 [MW] ip_bs_aux_ohm → 13.3 [MA]
rho0_ec → 0.5 [MW] PLH → 72.3 [MW] ip_ni → 7.63 [MA]
Pnbi → NaN [MW] Bpol_omp → 1.52 [T] ip_bs → 3.15 [MA]
Enbi1 → NaN [MeV] λq → 0.737 [mm] ip_aux → 4.48 [MA]
Pic → 50 [MW] qpol → 3.24e+03 [MW/m²] ip_ohm → 5.64 [MA]
Plh → NaN [MW] qpar → 1.31e+04 [MW/m²] ejima → 0.4
Paux_tot → 100 [MW] P/R0 → 19.7 [MW/m] flattop → NaN [Hours]
Pα → 72.7 [MW] PB/R0 → 154 [MW T/m]
Pohm → NaN [MW] PBp/R0 → 16.3 [MW T/m]
Pheat → NaN [MW] PBϵ/R0q95 → 6.51 [MW T/m]
Prad_tot → -42.5 [MW] neutrons_peak → 0.466 [MW/m²]
BOP BUILD COSTING
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
Pfusion → 363 [MW] PF_material → nb3sn capital_cost → 6.48 [$B]
Qfusion → 3.63 TF_material → nb3sn_kdemo levelized_CoE → Inf [$/kWh]
thermal_cycle_type → rankine OH_material → nb3sn TF_of_total → 12.8 [%]
thermal_efficiency_plant → 36.5 [%] TF_max_b → NaN [T] BOP_of_total → 5.5 [%]
thermal_efficiency_cycle → NaN [%] OH_max_b → NaN [T] blanket_of_total → 19.8 [%]
power_electric_generated → 145 [MW] TF_j_margin → NaN cryostat_of_total → 2.5 [%]
Pelectric_net → -0.337 [MW] OH_j_margin → NaN
Qplant → 0.998 TF_stress_margin → NaN
TBR → 1.14 OH_stress_margin → NaN
Extract + plots saved to PDF (or printed to screen it filename is omitted)
filename = joinpath(tutorial_temp_dir, "$(ini.general.casename).pdf")
FUSE.digest(dd)#, filename)GEOMETRY EQUILIBRIUM TEMPERATURES
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
R0 → 6.5 [m] B0 → 7.8 [T] Te0 → 17.6 [keV]
a → 2.01 [m] ip → 13.1 [MA] Ti0 → 17.1 [keV]
1/ϵ → 3.24 q95 → 7.29 <Te> → 9.85 [keV]
κ → 2 <Bpol> → 0.827 [T] <Ti> → 8.85 [keV]
δ → 0.585 βpol_MHD → 0.943 Te0/<Te> → 1.79
ζ → -0.00753 βtor_MHD → 0.0102 Ti0/<Ti> → 1.93
Volume → 969 [m³] βn_MHD → 1.23
Surface → 780 [m²]
DENSITIES PRESSURES TRANSPORT
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
ne0 → 8.53e+19 [m⁻³] P0 → 0.51 [MPa] τe → 2.04 [s]
ne_ped → 6.93e+19 [m⁻³] <P> → 0.25 [MPa] τe_exp → 2.71 [s]
ne_line → 8.43e+19 [m⁻³] P0/<P> → 2.03 H98y2 → 0.91
<ne> → 8.07e+19 [m⁻³] βn → 1.21 H98y2_exp → 0.994
ne0/<ne> → 1.06 βn_th → 1.15 Hds03 → 0.64
fGW → 0.813 Hds03_exp → 0.728
zeff_ped → 2 τα_thermalization → 0.816 [s]
<zeff> → 2 τα_slowing_down → 0.973 [s]
impurities → DT Ne20 He4
SOURCES EXHAUST CURRENTS
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
Pec → 50 [MW] Psol → 128 [MW] ip_bs_aux_ohm → 13.3 [MA]
rho0_ec → 0.5 [MW] PLH → 72.3 [MW] ip_ni → 7.63 [MA]
Pnbi → NaN [MW] Bpol_omp → 1.52 [T] ip_bs → 3.15 [MA]
Enbi1 → NaN [MeV] λq → 0.737 [mm] ip_aux → 4.48 [MA]
Pic → 50 [MW] qpol → 3.24e+03 [MW/m²] ip_ohm → 5.64 [MA]
Plh → NaN [MW] qpar → 1.31e+04 [MW/m²] ejima → 0.4
Paux_tot → 100 [MW] P/R0 → 19.7 [MW/m] flattop → NaN [Hours]
Pα → 72.7 [MW] PB/R0 → 154 [MW T/m]
Pohm → NaN [MW] PBp/R0 → 16.3 [MW T/m]
Pheat → NaN [MW] PBϵ/R0q95 → 6.51 [MW T/m]
Prad_tot → -42.5 [MW] neutrons_peak → 0.466 [MW/m²]
BOP BUILD COSTING
─────────────────────────────────── ─────────────────────────────────── ───────────────────────────────────
Pfusion → 363 [MW] PF_material → nb3sn capital_cost → 6.48 [$B]
Qfusion → 3.63 TF_material → nb3sn_kdemo levelized_CoE → Inf [$/kWh]
thermal_cycle_type → rankine OH_material → nb3sn TF_of_total → 12.8 [%]
thermal_efficiency_plant → 36.5 [%] TF_max_b → NaN [T] BOP_of_total → 5.5 [%]
thermal_efficiency_cycle → NaN [%] OH_max_b → NaN [T] blanket_of_total → 19.8 [%]
power_electric_generated → 145 [MW] TF_j_margin → NaN cryostat_of_total → 2.5 [%]
Pelectric_net → -0.337 [MW] OH_j_margin → NaN
Qplant → 0.998 TF_stress_margin → NaN
TBR → 1.14 OH_stress_margin → NaN
@ time = 0.0 [s]
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