Shallow Recurrent Decoder for Nuclear Reactors applications (NuSHRED)
This repository collects the codes regarding the application of the Shallow REcurrent Decoder (SHRED) method to Nuclear Reactors systems.
In particular, this repository serves as complementary code to the following paper:
- [P1] Riva, S., Introini, C., Cammi, A., & Kutz, J. N. (2024). Robust State Estimation from Partial Out-Core Measurements with Shallow Recurrent Decoder for Nuclear Reactors. arXiv [Physics.Ins-Det]. Retrieved from http://arxiv.org/abs/2409.12550
The simulation data (compressed) are available on Zenodo
- [D1] Molten Salt Fast Reactor (MSFR) in the accidental scenario Unprotected Loss Of Fuel Flow (ULOFF)
The SHRED method was first proposed and developed in this paper:
- J. Williams, O. Zahn and J. N. Kutz, Sensing with shallow recurrent decoder networks, arxiv (2023) arXiv:2301.12011
The original code base is here: https://github.com/Jan-Williams/pyshred
The pyforce package is used as support for sensor placements and dimensionality reduction, see Riva et al. (2024) and Cammi et al. (2024).
Structure of the repository
In the folder shred, the modules for the
implementation of the Shallow Recurrent Decoder (SHRED)
network from pyshred
are reported. On the other hand, the folder
Code is divided into subfolders corresponding
to the papers regarding the application of SHRED to nuclear
reactor concepts; the dataset are associated as follows
| MSFR-ULOFF D1 | |
|---|---|
| P1 | x |
How to execute
Clone or download the repository, download the correspondent datasets and move in the same directory of the notebooks to execute.
The main requirements to execute the notebooks are pytorch and pyforce, see instructions here; other packages will be installed as part of the requirements.
Contact Information
If interested, please contact stefano.riva@polimi.it, carolina.introini@polimi.it, antonio.cammi@polimi.it, kutz@uw.edu.
In case of any problems, refer to Github Issues of this repository.