Data-Driven Predictive Models: Calculational Bias in Characterization of Spent Nuclear Fuel
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High-level waste, stemming from nuclear electricity generation poses significant environmental and safety concerns. Currently, high-level wastes are stored in interim facilities needing constant monitoring and waiting for a definitive solution. Deep geolog ...
Microstructural evolution during in-pile irradiation, radiation damage effects and fission products behavior in UO2 nuclear fuel are key issues in understanding and for the modeling of the performance as well as safety characteristics of nuclear fuels in t ...
EPFL2024
Currently, most Spent Nuclear Fuel (SNF) is kept safely in storage either at on-site facilities or at centralized interim storage sites. Moreover, many countries face delays in implementing their waste management programmes for SNF and high-level waste dis ...
EPFL2021
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Decay heat calculations of spent nuclear fuel (SNF) using Polaris and ORIGEN codes in the SCALE code sys-tem, and CASMO5 code, are validated using measurements from the Clab and GE-Morris facilities. Multiple hypothesis testing, relying on permutations and ...
PERGAMON-ELSEVIER SCIENCE LTD2022
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Algorithms are now routinely used to make consequential decisions that affect human lives. Examples include college admissions, medical interventions or law enforcement. While algorithms empower us to harness all information hidden in vast amounts of data, ...
2021
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Decay heat residuals of spent nuclear fuel (SNF), i.e., the differences between calculations and measurements, were obtained previously for various spent fuel assemblies (SFA) using the Polaris module of the SCALE code system. In this paper, we compare dec ...
KOREAN NUCLEAR SOC2021
Radioactive waste is among the most dangerous anthropogenic waste and its safe disposal is a challenging multi-generational task. Many nations have sought for the peaceful application of nuclear fission for the reliable production of electric energy to pow ...
EPFL2021
We probe the accuracy of linear ridge regression employing a three-body local density representation derived from the atomic cluster expansion. We benchmark the accuracy of this framework in the prediction of formation energies and atomic forces in molecul ...
AIP Publishing2021
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We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits artificial neural networks. Our approach builds directly on the specific Maximum Likelihood ratio treatment of uncertainties a ...
SPRINGER2022
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ObjectiveTo construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure. MethodsThis study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) ...
