Issue |
EPJ Nuclear Sci. Technol.
Volume 8, 2022
|
|
---|---|---|
Article Number | 17 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.1051/epjn/2022008 | |
Published online | 07 September 2022 |
https://doi.org/10.1051/epjn/2022008
Regular Article
Algorithms for processing self-powered neutron detector signals important for determination of local parameters in each part of the VVER core
1
Lviv Polytechnic National University, Department of Heat Engineering and Thermal and Nuclear Power Plants, Lviv, Ukraine
2
Belarusian NPP, Belarus
* e-mail: lysss@ukr.net
Received:
17
February
2022
Received in final form:
14
March
2022
Accepted:
25
May
2022
Published online: 7 September 2022
These investigation findings prove the possibility of a engineering solution for VVER core automatic protection during operation in both nominal and transient conditions within ICIS using local parameters (i.e. linear heat power of the most stressed fuel rod, departure from nucleate boiling ratio). Such engineering solution will be implemented by safety system software-hardware (PTK-Z) on the basis of signals coming from in-core neutron flux detectors, temperature sensors, primary coolant flow and coolant pressure transducers. The article presents the following: a list of in-core neutron flux detectors, a list of transducers of primary coolant monitoring for thermal engineering conditions (temperature, flow rate, pressure), whose signals are delivered to the terminals of instrumentation gauges (PTK-Z) for the purpose of actuating safety actions in accordance with local parameters. The paper shows arrangement of in-core neutron flux detector equipment, above view of self-powered neutron detector (SPND) location in safety channels, axial arrangement of SPND along the core, algorithms for processing SPND signals important for determination of local parameters in each part of the core in both normal and abnormal operation conditions.
© S. Lys and A. Kanyuka: Published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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