Simulated observables for spent fuel non-destructive assay

Research output: Contribution to report/book/conference proceedingsIn-proceedings paper

Standard

Simulated observables for spent fuel non-destructive assay. / Borella, Alessandro; Rossa, Riccardo; van der Meer, Klaas.

Proceedings of the 2018 INMM annual meeting. INMM - Institute of Nuclear Materials Management , 2018.

Research output: Contribution to report/book/conference proceedingsIn-proceedings paper

Harvard

Borella, A, Rossa, R & van der Meer, K 2018, Simulated observables for spent fuel non-destructive assay. in Proceedings of the 2018 INMM annual meeting. INMM - Institute of Nuclear Materials Management , INMM 59th Annual Meeting, Baltimore, United States, 2018-07-22.

APA

Borella, A., Rossa, R., & van der Meer, K. (2018). Simulated observables for spent fuel non-destructive assay. In Proceedings of the 2018 INMM annual meeting INMM - Institute of Nuclear Materials Management .

Vancouver

Borella A, Rossa R, van der Meer K. Simulated observables for spent fuel non-destructive assay. In Proceedings of the 2018 INMM annual meeting. INMM - Institute of Nuclear Materials Management . 2018

Author

Borella, Alessandro ; Rossa, Riccardo ; van der Meer, Klaas. / Simulated observables for spent fuel non-destructive assay. Proceedings of the 2018 INMM annual meeting. INMM - Institute of Nuclear Materials Management , 2018.

Bibtex - Download

@inproceedings{6d7d81b1b8f446dea72267222e3d261c,
title = "Simulated observables for spent fuel non-destructive assay",
abstract = "Measurements on spent fuel assemblies are a complex task due to the fact that the assemblies are typically stored underwater, the contamination and irradiation risks, and the safety concerns associated to fuel handling. For these reasons the development or study of new techniques relies strongly on simulations with often little possibilities for an experimental verification with actual spent fuel. This paper reports about the work being done at SCK•CEN to develop a spent fuel observables library for several detector types. This work builds upon previous efforts to develop a spent fuel library containing the radionuclide composition, gamma and neutron emissions of PWR and BWR spent fuel assemblies for 2940 irradiation cases. The detector considered are the Fork Ball detector in wet and dry conditions and a SINRD prototype for measurements in air. The current status of the observables library and future plans are discussed as well as a strategy to use artificial neural networks to process the data and verify operator declared data from a limited set of observables.",
keywords = "Spent fuel verification, Simulated observables, Big data, Data mining, Artificial neural network",
author = "Alessandro Borella and Riccardo Rossa and {van der Meer}, Klaas",
note = "Score=3",
year = "2018",
month = "7",
day = "22",
language = "English",
booktitle = "Proceedings of the 2018 INMM annual meeting",
publisher = "INMM - Institute of Nuclear Materials Management",

}

RIS - Download

TY - GEN

T1 - Simulated observables for spent fuel non-destructive assay

AU - Borella, Alessandro

AU - Rossa, Riccardo

AU - van der Meer, Klaas

N1 - Score=3

PY - 2018/7/22

Y1 - 2018/7/22

N2 - Measurements on spent fuel assemblies are a complex task due to the fact that the assemblies are typically stored underwater, the contamination and irradiation risks, and the safety concerns associated to fuel handling. For these reasons the development or study of new techniques relies strongly on simulations with often little possibilities for an experimental verification with actual spent fuel. This paper reports about the work being done at SCK•CEN to develop a spent fuel observables library for several detector types. This work builds upon previous efforts to develop a spent fuel library containing the radionuclide composition, gamma and neutron emissions of PWR and BWR spent fuel assemblies for 2940 irradiation cases. The detector considered are the Fork Ball detector in wet and dry conditions and a SINRD prototype for measurements in air. The current status of the observables library and future plans are discussed as well as a strategy to use artificial neural networks to process the data and verify operator declared data from a limited set of observables.

AB - Measurements on spent fuel assemblies are a complex task due to the fact that the assemblies are typically stored underwater, the contamination and irradiation risks, and the safety concerns associated to fuel handling. For these reasons the development or study of new techniques relies strongly on simulations with often little possibilities for an experimental verification with actual spent fuel. This paper reports about the work being done at SCK•CEN to develop a spent fuel observables library for several detector types. This work builds upon previous efforts to develop a spent fuel library containing the radionuclide composition, gamma and neutron emissions of PWR and BWR spent fuel assemblies for 2940 irradiation cases. The detector considered are the Fork Ball detector in wet and dry conditions and a SINRD prototype for measurements in air. The current status of the observables library and future plans are discussed as well as a strategy to use artificial neural networks to process the data and verify operator declared data from a limited set of observables.

KW - Spent fuel verification

KW - Simulated observables

KW - Big data

KW - Data mining

KW - Artificial neural network

UR - http://ecm.sckcen.be/OTCS/llisapi.dll/open/31025341

M3 - In-proceedings paper

BT - Proceedings of the 2018 INMM annual meeting

PB - INMM - Institute of Nuclear Materials Management

ER -

ID: 4521218