Determination of spent nuclear fuel parameters using modelled signatures from non-destructive assay and Random Forest regression-Reference-Cited by-同舟云学术

Determination of spent nuclear fuel parameters using modelled signatures from non-destructive assay and Random Forest regression

Published:2020-07 Issue: Volume:969 Page:163979
ISSN:0168-9002
Container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
language:en
Short-container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Author:

Grape S.,Branger E.,Elter Zs.,Pöder Balkeståhl L.

Funder

Swedish Radiation Safety Authority

Publisher

Elsevier BV

Subject

Instrumentation,Nuclear and High Energy Physics

Reference35 articles.

1. IAEA, Safeguards criteria: Special Criteria for Difficult-to-Access Fuel Items, SG-SC-Annex-04, Version 2, Version Date: 2009-09-02. International Atomic Energy Agency, Vienna.

2. Advancing the Fork detector for quantitative spent nuclear fuel verification;Vaccaro;Nucl. Instrum. Methods Phys. Res. A,2018

3. Gamma emission tomography for the inspection of spent nuclear fuel;Mayorov,2017

4. A new approach to fork measurements data analysis by RADAR-CRISP and ORIGEN integration;Vaccaro;IEEE Trans. Nucl. Sci.,2014

5. Nuclear spent fuel parameter determination using multivariate analysis of fission product gamma spectra;Hellesen;Ann. Nucl. Energy,2017

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of machine learning methods for spent fuel characterization based on gamma spectrometry measurements;Annals of Nuclear Energy;2024-09

2. Material attractiveness of irradiated fuel salts from the Seaborg Compact Molten Salt Reactor;Nuclear Engineering and Technology;2024-09

3. An inversion model for burnup history of spent fuels in pebble bed HTGR based on optimization algorithm;Nuclear Engineering and Design;2024-09

4. Data library of irradiated fuel salt and off-gas tank composition for a molten salt reactor concept produced with Serpent2 and SOURCES 4C codes;Data in Brief;2024-06

5. Application of Machine Learning to Predict Safeguards Parameters for Irradiated Salts from a Molten Salt Reactor Concept;2024