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Assimilating fission-code FIFRELIN using machine learning
- Source :
- EPJ Web of Conferences, Vol 294, p 03002 (2024)
- Publication Year :
- 2024
- Publisher :
- EDP Sciences, 2024.
-
Abstract
- This paper presents work that has been done on the FIFRELIN Monte-Carlo code. The purpose of the code is to simulate the de-excitation process of fission fragments. Numerous quantity of insterest are calculated (mass yields, prompt particle spectra, mulitiplicities … ). Up to now the code relies on four free parameters which control the initial excitation and total angular momentum of fission fragment. Finding the good set of the free parameters is a diffucult task. In this work, we have developed an optimization algorithm based on Gaussian Process regression.
Details
- Language :
- English
- ISSN :
- 2100014X
- Volume :
- 294
- Database :
- Directory of Open Access Journals
- Journal :
- EPJ Web of Conferences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.be36656829db48c8bdd305c265a9b29e
- Document Type :
- article
- Full Text :
- https://doi.org/10.1051/epjconf/202429403002