Tercera Jornada Ceiden-UPM: “Machine Learning in Nuclear Science and Technology Applications”

Date

14 May 2021, from 09:00 to 13:00h.

Review of the event (Spanish)

Presentations

Introduction and Program

Tadahiro Kin (Kyushu University, Japan) – «ML in radiation metrology: Application of Gamma-ray spectrometry»

Berenguer Bríquez (Tecnatom) – «Machine Learning in Nuclear Science and Technology Applications»

Adrián Sánchez (CIEMAT) – «Deep Learning applied to Capture Cross Section Data Analysis»

Aris Villacorta (CIEMAT) – «Unsupervised Learning for nuclear fuel cycle applications«

Emilio Mendoza (CIEMAT) – «Machine learning applied to modelling of nuclear deexcitation cascades»

Arnau Albà (Paul Scherrer Institut, Switzerland) – «Surrogate Models for Uncertainties on Decay Heat and Nuclide Inventory in Nuclear Depletion Calculations»

Ahmed Shama (Paul Scherrer Institut) – «Predicting the Bias in Calculations of Spent Nuclear Fuel Characteristics»

Joachim Hansson (Uppsala University, Sweden) – «Gaussian Processes and Levenberg-Marquardt»

Virginie Solans (Uppsala University, PSI) – «Optimization of spent fuel canister loading using a neural network and genetic algorithm»

INGENIA UPM – «Machine Learning techniques in V&V of Nuclear Data Bases»

INGENIA UPM – «Machine learning in Reactor-oriented applications»

Norberto Sebastián Schmidt (Bariloche Atomic Center, Argentina) – «Neutron and gamma beam simulation using OpenMC and Python’s libraries for Machine Learning»

Denise Neudecker (Los Alamos National Laboratory, USA) – «Using Machine Learning Algorithms for Large-scale Nuclear-data Validation»

Georg Schnabel (IAEA) – «Annonuncement of Technical Meeting AI4Atoms»

Summary record