| Issue |
EPJ Web Conf.
Volume 338, 2025
ANIMMA 2025 – Advancements in Nuclear Instrumentation Measurement Methods and their Applications
|
|
|---|---|---|
| Article Number | 04028 | |
| Number of page(s) | 8 | |
| Section | Research Reactors and Particle Accelerators | |
| DOI | https://doi.org/10.1051/epjconf/202533804028 | |
| Published online | 06 November 2025 | |
https://doi.org/10.1051/epjconf/202533804028
The NEREA Python Package for Integral Experiment Analysis: A Fission Chamber Calibration Case Study
1 SCK CEN Belgian nuclear research centre, Boeretang 200, Mol, 2400, Antwerp, Belgium
2 Université libre de Bruxelles, Avenue Franklin D. Roosevelt 50, Bruxelles, 1050, Belgium
* This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 6 November 2025
Abstract
NEREA is a Python package designed for integral experiment processing in nuclear reactors. In this work we present the main features of NEREA to date, including data processing for pulse height spectrum analysis, fission chamber calibration, fission rate traverse measurement processing, control rod calibration and reactivity worth calculation. NEREA offers high control of the processing flow yet keeping it smooth and user-friendly thanks to is object-oriented conception.
We showcase the capabilities of NEREA presenting the calibration of a large set of fission chambers at the BR1 MARK-III converter. NEREA allows for analysis of the impact of processing choices and for considerations over several measurements. Strengths and weaknesses of the implemented calibration methodology are also discussed, highlighting room for future work on this. This is particularly true when the measured pulse height spectrum is characterized by low peak-to-valley ratio, making the choice of a proper discrimination level challenging.
Key words: Fission Chambers / MARK-III converter / NEREA Python API / Integral Experiments
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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