EPJ Web Conf.
Volume 170, 2018ANIMMA 2017 – Advancements in Nuclear Instrumentation Measurement Methods and their Applications
|Number of page(s)||8|
|Section||Severe accident monitoring|
|Published online||10 January 2018|
Malfunctions in radioactivity sensors' networks
SCM SA, Paris, France
CEO of SCM SA, Paris, France firstname.lastname@example.org
SCM SA, Paris, France email@example.com
IRSN, Fontenay-aux-Roses, France firstname.lastname@example.org
Published online: 10 January 2018
The capacity to promptly and efficiently detect any source of contamination of the environment (a radioactive cloud) at a local and a country scale is mandatory to a safe and secure exploitation of civil nuclear energy. It must rely upon a robust network of measurement devices, to be optimized vs. several parameters, including the overall reliability, the investment, the operation and maintenance costs. We show that a network can be arranged in different ways, but many of them are inadequate. Through simulations, we test the efficiency of several configurations of sensors, in the same domain. The denser arrangement turns out to be the more efficient, but the efficiency is increased when sensors are non-uniformly distributed over the country, with accumulation at the borders. In the case of France, as radioactive threats are most likely to come from the East, the best solution is densifying the sensors close to the eastern border. Our approach differs from previous work because it is "failure oriented": we determine the laws of probability for all types of failures and deduce in this respect the best organization of the network.
Key words: Environmental radiation surveillance / network / failure / probabilities / sensor
© The Authors, published by EDP Sciences, 2018
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. (http://creativecommons.org/licenses/by/4.0/).
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