FESTIM: overview of hydrogen transport simulation capabilities

Remi Delaporte-Mathurin and FESTIM contributors

User inputs

Material properties
Trap properties
Geometry
Boundary conditions
Initial conditions
...

T

FESTIM

Outputs

H concentration fields $c(x,t)$
Temperature field $T(x,t)$

surface fluxes
inventories
average concentration
...

Heat transfer model

Hydrogen transport model(s)

Delaporte-Mathurin et al, 2024. International Journal of Hydrogen Energy 10.1016/j.ijhydene.2024.03.184

📈5 years of development

📑14+ publications

🗣️130+ citations

🧑‍💻23+ contributors

🏛️27+ institutions using the code

🧑‍💻80+ Slack members

⭐~100 stars on GitHub

🧑‍💻4 user workshops

FESTIM in numbers

✅100% open-source

Source code: github.com/festim-dev/FESTIM

Tutorials: github.com/festim-dev/FESTIM -workshop

Documentation: festim.readthedocs.io

FESTIM is verified & validated

Validated against TDS, permeation experiments...
Verified against analytical solutions in many different problems
New V&V online book

festim-vv-report.readthedocs.io

19 V&V cases in total (more to come)

Remi Delaporte-Mathurin and Jair Santana, FESTIM V&V Book, 2024, https://dspace.mit.edu/handle/1721.1/156690.

FESTIM from mesoscale to reactor scale

Gas driven permeation

J_\mathrm{left} = K_d \ P - K_r \ c^2

J_\mathrm{left} = K_d \ P - K_r \ c^2

J_\mathrm{right} = - K_r \ c^2

J_\mathrm{right} = - K_r \ c^2

Surface limited regime

Bulk limited regime

Transition to bulk limited as the permeation number $W$ increases

High H pressure

Low H pressure

Permeation flux

$c = K_H \ P_\mathrm{up}$

$c = 0$

Permeation through the crucible wall

FLiBe

2D permeation through molten salts

\mathrm{flux} = 2 \pi \ \int_0^R r \ D \nabla c \ \cdot \mathbf{n} \ dr

\mathrm{flux} = 2 \pi \ \int_0^R r \ D \nabla c \ \cdot \mathbf{n} \ dr

HYPERION permeation rig

Permeation barriers

No barrier

with barrier

Permeation barrier

Substrate

High H pressure

Low H pressure

Permeation flux

Ongoing tritium permeation barriers development project at MIT

Conservation of chemical potential

\frac{c^-}{K_S^-} = \frac{c^+}{K_S^+}

\frac{c^-}{K_S^-} = \frac{c^+}{K_S^+}

TDS analysis: neutron damage

James Dark et al 2024 Nucl. Fusion 64 086026

\frac{d n}{dt} = \Phi \ K \ (1 - \frac{n}{n_\mathrm{max}}) - A \ n

\frac{d n}{dt} = \Phi \ K \ (1 - \frac{n}{n_\mathrm{max}}) - A \ n

New proposed model for neutron-induced trap creation
Parameterised on TDS data (self-damaged W)

TDS analysis: neutron damage

James Dark et al 2024 Nucl. Fusion 64 086026

Model was used to simulate inventory evolution in PFCs
Neglecting neutron traps could potentially underestimate inventories by several orders of magnitude after 1 FPY
Need similar studies for structural materials!

TDS analysis: codeposits

Patino et al. Nuclear Materials and Energy 41 (2024) 101808

Simulation of W codeposited layers
Influence of partial pressure
10 different traps!

Kinetic surface model

Kulagin et al (2024) arXiv, arXiv:2411.16474

Kinetic surface model

V&V available at
github.com/KulaginVladimir/FESTIM-SurfaceKinetics-Validation

Kulagin et al (2024) arXiv, arXiv:2411.16474

D in damaged W (S. Markelj JNM 2016)
Comparison with NRA profiles

Kinetic surface model

V&V available at
github.com/KulaginVladimir/FESTIM-SurfaceKinetics-Validation

Kulagin et al (2024) arXiv, arXiv:2411.16474

H in oxidised W (A. Dunand et al 2022 Nucl. Fusion)
Comparison with TDS spectra

Kinetic surface model

V&V available at
github.com/KulaginVladimir/FESTIM-SurfaceKinetics-Validation

Kulagin et al (2024) arXiv, arXiv:2411.16474

H in Ti (Hirooka et al 1981 JNM)
Validation at 5 temperatures

H content (H/Ti)

Component scale modelling & multiphysics

Influence of ELMs on retention

Kulagin, V., & Gasparyan, Y. Numerical Simulation of deuterium retention in tungsten under ELM-like conditions. J. Nucl. Mater.

1D model of a ITER monoblock
Transient heat transfer simulation
Varying surface heat flux

Metal Foil Pumps for DIR

H is implanted in the first $10 \ \mathrm{nm}$
Super-permeation regime is attained at high recombination energy (upstream surface)
Source code

Benedikt & Day, (2017) Fusion Engineering and Design

Retention studies

Delaporte-Mathurin et al 2024 International Journal of Hydrogen Energy 63 786–802
Delaporte-Mathurin et al 2024 Nucl. Fusion 64 026003

ITER plasma facing components
Transient estimation of tritium retention

Retention (T/m3)

Detritiation studies

Delaporte-Mathurin et al 2024 Nucl. Fusion 64 026003

Breeding Blanket modelling

DEMO WCLL
Complex 3D geometry
Coupled to fluid dynamics
Tritium generation in the LiPb volume (computed from neutronics)

James Dark et al 2021 Nucl. Fusion 61 116076

Tritium extraction system

Dunnell and Delaporte-Mathurin, MIT NSE Beyond Oppenheimer (2024) 10.13140/RG.2.2.13923.16164

Permeation Against Vacuum
Complex 3D geometry
Coupled with fluid dynamics
Tritium extraction from permeable membranes

MIT tritium breeding experiment

Velocity

Temperature

Tritium concentration

For more details on experiment: Delaporte-Mathurin et al, Advancing Tritium Self-Sufficiency in Fusion Power Plants: Insights from the BABY Experiment (under review in Nucl. Fusion)

① neutrons are generated

② tritium is created from nuclear reactions

③ tritium is transported in the salt

④ tritium is released into the gas phase

⑤ tritium is collected and counted

BABY breeding experiment

Towards FESTIM2

Rewrite of FESTIM with FEniCSx
Improved performances
New physics and features

Spherical cavity trapping

see Zibrov and Schmid, NME, 2024

for complete description

Implementation in FESTIM of the spherical cavity trapping model developed by Zibrov and Schmid
Custom trapping equations
Smooth implementation in FESTIM

Anisotropy

Anisotropic materials can be simulated with very few modifications
Composites
Anisotropic microstructures

D = \begin{bmatrix} D_{xx} & 0\\ 0 & D_{yy} \end{bmatrix}

D = \begin{bmatrix} D_{xx} & 0\\ 0 & D_{yy} \end{bmatrix}

\mathrm{H} + [\ \ \ ]_\mathrm{trap} \ \substack{p \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k} \ [\mathrm{H}]_\mathrm{trap}

\mathrm{H} + [\ \ \ ]_\mathrm{trap} \ \substack{p \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k} \ [\mathrm{H}]_\mathrm{trap}

\mathrm{D} + [\ \ \ ]_\mathrm{trap} \ \substack{p \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k} \ [\mathrm{D}]_\mathrm{trap}

\mathrm{D} + [\ \ \ ]_\mathrm{trap} \ \substack{p \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k} \ [\mathrm{D}]_\mathrm{trap}

\mathrm{D} + [\mathrm{H}]_\mathrm{trap} \ \substack{k_\mathrm{swap} \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1.2em] k_\mathrm{swap}} \ [\mathrm{D}]_\mathrm{trap} + \mathrm{H}

\mathrm{D} + [\mathrm{H}]_\mathrm{trap} \ \substack{k_\mathrm{swap} \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1.2em] k_\mathrm{swap}} \ [\mathrm{D}]_\mathrm{trap} + \mathrm{H}

same underlying equations!

Can be represented by festim.Reaction

Isotope swapping

Trapping reactions

Swapping reaction

Isotope swapping

my_model.species = [
    mobile_H,
    mobile_D,
    trapped_H,
    trapped_D,
]

my_model.reactions = [
    F.Reaction(
        k_0=k_0,
        E_k=0.39,
        p_0=1e13,
        E_p=1.2,
        reactant1=mobile_H,
        reactant2=empty_trap,
        product=trapped_H,
        volume=my_subdomain,
    ),
    F.Reaction(
        k_0=k_0,
        E_k=0.39,
        p_0=1e13,
        E_p=1.2,
        reactant1=mobile_D,
        reactant2=empty_trap,
        product=trapped_D,
        volume=my_subdomain,
    ),
    F.Reaction(
        k_0=k_0,
        E_k=0.1,
        p_0=k_0,
        E_p=0.1,
        reactant1=mobile_H,
        reactant2=trapped_D,
        product=[mobile_D, trapped_H],
        volume=my_subdomain,
    ),
]

Usual trapping reactions

Swapping reaction

4 species are defined

Multi-isotope transport and multi-level trapping

2 isotopes, 1 trap (2 levels)
7 different species
6 reactions

\mathrm{H} + [\ \ \ ] \ \substack{p_1 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_1} \ [\mathrm{H}_1\mathrm{D}_0]

\mathrm{H} + [\ \ \ ] \ \substack{p_1 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_1} \ [\mathrm{H}_1\mathrm{D}_0]

\mathrm{H} + [\mathrm{H}_1\mathrm{D}_0] \ \substack{p_2 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_2} \ [\mathrm{H}_2\mathrm{D}_0]

\mathrm{H} + [\mathrm{H}_1\mathrm{D}_0] \ \substack{p_2 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_2} \ [\mathrm{H}_2\mathrm{D}_0]

\mathrm{D} + [\ \ \ ] \ \substack{p_3 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_3} \ [\mathrm{H}_0\mathrm{D}_1]

\mathrm{D} + [\ \ \ ] \ \substack{p_3 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_3} \ [\mathrm{H}_0\mathrm{D}_1]

\mathrm{D} + [\mathrm{H}_0\mathrm{D}_1] \ \substack{p_4 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_4} \ [\mathrm{H}_0\mathrm{D}_2]

\mathrm{D} + [\mathrm{H}_0\mathrm{D}_1] \ \substack{p_4 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_4} \ [\mathrm{H}_0\mathrm{D}_2]

\mathrm{H} + [\mathrm{H}_0\mathrm{D}_1] \ \substack{p_5 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_5} \ [\mathrm{H}_1\mathrm{D}_1]

\mathrm{H} + [\mathrm{H}_0\mathrm{D}_1] \ \substack{p_5 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_5} \ [\mathrm{H}_1\mathrm{D}_1]

\mathrm{D} + [\mathrm{H}_1\mathrm{D}_0] \ \substack{p_6 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_6} \ [\mathrm{H}_1\mathrm{D}_1]

\mathrm{D} + [\mathrm{H}_1\mathrm{D}_0] \ \substack{p_6 \\[-1em] \longleftarrow\\[-1em] \longrightarrow \\[-1em] k_6} \ [\mathrm{H}_1\mathrm{D}_1]

✅Mixed domain can streamline multiphysics coupling

❌Some methods do not work for dissimilar materials (Henry vs Sieverts)

FESTIM 2 is much faster

3-30x

faster

HISP project: coupling FESTIM to plasma codes

RISP pulse

ITER FW divided in 60 bins

Data from DINA

Goal: find the best strategy for minimising ITER T inventory

HISP project: coupling FESTIM to plasma codes

10 DT FP pulses

ICWC + RISP

GDC

Simulation time:
~ 60 s per bin (~ hour full reactor)

HISP project: coupling FESTIM to plasma codes

Multi isotopes
Parametrisation for W, B, SS
Testing different scenarios for detritiation in ITER
Flexible enough to be reactor-and plasma code-agnostic
Open-source development
github.com/kaelyndunnell/hisp

Take aways

🚀FESTIM is extremely versatile, from simple to complex cases, from small scale to large scale.

🔓FESTIM is accessible to everyone. FESTIM2 is already usable now and will soon be released as alpha

🫵We - the festim developers - want to work with you - potential users - to have it benefit your work.