ctf4science/ctf4nuclear-msfr

CTF4Nuclear — Molten Salt Fast Reactor (MSFR) benchmark

A spatio-temporal benchmark for reduced-order and surrogate modelling of Molten Salt Fast Reactor (MSFR) multiphysics simulations. The dataset consists of snapshot matrices from coupled neutronics + thermal-hydraulics simulations on a 2D axial-symmetric slice of the EVOL MSFR geometry, discretised on a 3 880-node mesh. Each snapshot is a state vector of length 19 400 = 5 fields × 3 880 nodes, with the fields concatenated in the order

[qPrompt, qDecay, T, Ux, Uz]   # prompt power, decay power, temperature, two velocity components

Snapshots are saved every Δt = 0.05 s of simulated physical time.

This dataset is the public training-and-config component of the CTF4Nuclear Common Task Framework. The accompanying test sets are held out and used to score submissions to the public leaderboard at huggingface.co/spaces/ctf4science/ctf4nuclear-msfr-leaderboard.

Quick start

from huggingface_hub import snapshot_download

# 1. Download into the layout the ctf4science loader expects
snapshot_download(
    repo_id="ctf4science/ctf4nuclear-msfr",
    repo_type="dataset",
    local_dir="ctf4science/data/msfr",
)

# 2. Load any of the 9 evaluation pairs
from ctf4science.data_module import load_dataset
train_list, init_data = load_dataset("msfr", pair_id=1, transpose=True)

The ctf4science Python package is open source at github.com/CTF-for-Science/ctf4science. A ready-to-run Baseline Last notebook is provided in the leaderboard repo under baselines/baseline_last.ipynb.

Files

File	Shape	Used in (pairs / metrics)
train/X1train.npz	2000 × 19400	pair 1 (E1, E2)
train/X2train.npz	2000 × 19400	pair 2 (E3), pair 3 (E4)
train/X3train.npz	2000 × 19400	pair 4 (E5), pair 5 (E6)
train/X4train.npz	500 × 19400	pair 6 (E7, E8)
train/X5train.npz	500 × 19400	pair 7 (E9, E10)
train/X6train.npz	1500 × 19400	pair 8, pair 9 (parametric)
train/X7train.npz	1500 × 19400	pair 8, pair 9 (parametric)
train/X8train.npz	1500 × 19400	pair 8 (parametric)
train/X9train.npz	500 × 19400	pair 8 (initialization for E11)
train/X10train.npz	1500 × 19400	pair 9 (parametric)
train/X11train.npz	500 × 19400	pair 9 (initialization for E12)
nodes.npy	3880 × 2	(x, z) mesh coordinates in metres
msfr.yaml	—	benchmark configuration (pairs, metrics, matrix metadata)
croissant.json	—	Croissant 1.0 RAI metadata

Each .npz stores a single float32 array under key X with shape (n_timesteps, 19400). The held-out test files X1test.npz–X9test.npz referenced in msfr.yaml are not released — they are used by the leaderboard's scoring backend only.

Evaluation pairs and metrics

The benchmark defines 9 evaluation pairs producing 12 metric scores (E1–E12) across three task families:

Task family	Metrics	Description
Short-time forecasting	E1, E7, E9, E11, E12	Relative L2 error over the first k = 20 forecast steps
Long-time forecasting	E2, E4, E6, E8, E10	Spectral L2 error on the last k = 200 steps (100 Fourier modes)
Reconstruction (denoising)	E3, E5	Relative L2 error over the full denoised trajectory

The composite score is the mean of E1–E12, with each metric clipped to [−100, 100]. See the ctf4science documentation for the formal definitions.

Data generation

Trajectories were produced by the msfrPimpleFoam OpenFOAM v2312 solver (Aufiero et al., 2014) on the EVOL MSFR geometry (Brovchenko et al., 2013). Four simulations span a 1D sweep of the momentum-source base level (pump velocity) from 10 to 15. The solver couples RANS computational fluid dynamics (realisable k–ε) with multi-group diffusion neutronics. All fields are z-score normalised per field with global standard deviations (means and std are available from the dataset authors).

Citation

@misc{riva2026msfr,
  title  = {A spatio-temporal benchmark for reduced-order and surrogate
            modelling of Molten Salt Fast Reactor (MSFR) multiphysics
            simulations},
  author = {Riva, Stefano and Introini, Carolina and Cammi, Antonio},
  year   = {2026},
  url    = {https://huggingface.co/datasets/ctf4science/ctf4nuclear-msfr},
}

@article{aufiero2014openfoam,
  title   = {Development of an OpenFOAM model for the Molten Salt Fast
             Reactor transient analysis},
  author  = {Aufiero, Manuele and Cammi, Antonio and Geoffroy, Olivier
             and Losa, Mario and Luzzi, Lelio and Ricotti, Marco E. and
             Rouch, Herv\'e},
  journal = {Chemical Engineering Science},
  volume  = {111},
  pages   = {390--401},
  year    = {2014},
  doi     = {10.1016/j.ces.2014.03.003},
}

@misc{brovchenko2013evol,
  title  = {Optimization of the pre-conceptual design of the MSFR},
  author = {Brovchenko, Mariya and Merle Lucotte, Elsa and Rouch, Herv\'e
            and others},
  year   = {2013},
  url    = {https://www.janleenkloosterman.nl/reports/evol_d22_201309.pdf},
}

License

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).

Mirrors

• Hugging Face (this repo) — primary, fastest for snapshot_download
• Open Science Framework — original distribution, full tarball

Contact

Stefano Riva — stefano.riva@autodesk.com