34 citations · 125 across the 15 of their papers we have counts for
15 papers
Artificial Intelligence in Reactor Physics: Current Status and Future Prospects
Ruizhi Zhang, Shengfeng Zhu, Kan Wang +5
Reactor physics is the study of neutron properties, focusing on using models to examine the interactions between neutrons and materials in nuclear reactors. Artificial intelligence…
Projection-based model order reduction for prestressed concrete with an application to the standard section of a nuclear containment building
Eki Agouzal, Jean-Philippe Argaud, Michel Bergmann +3
We propose a projection-based model order reduction procedure for the ageing of large prestressed concrete structures. Our work is motivated by applications in the nuclear industry…
Exact and general decoupled solutions of the LMC Multitask Gaussian Process model
Olivier Truffinet, Karim Ammar, Jean-Philippe Argaud +1
The Linear Model of Co-regionalization (LMC) is a very general multitask gaussian process model for regression or classification. While its expressiveness and conceptual simplicity…
A projection-based reduced-order model for parametric quasi-static nonlinear mechanics using an open-source industrial code
Eki Agouzal, Jean-Philippe Argaud, Michel Bergmann +2
We propose a projection-based model order reduction procedure for a general class of parametric quasi-static problems in nonlinear mechanics with internal variables. The methodolog…
Observation data compression for variational assimilation of dynamical systems
Sibo Cheng, Didier Lucor, Jean-Philippe Argaud
Accurate estimation of error covariances (both background and observation) is crucial for efficient observation compression approaches in data assimilation of large-scale dynamical…
A graph clustering approach to localization for adaptive covariance tuning in data assimilation based on state-observation mapping
Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss +2
An original graph clustering approach to efficient localization of error covariances is proposed within an ensemble-variational data assimilation framework. Here the localization t…
Background Error Covariance Iterative Updating with Invariant Observation Measures for Data Assimilation
Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss +2
In order to leverage the information embedded in the background state and observations, covariance matrices modelling is a pivotal point in data assimilation algorithms. These matr…
An Advanced Computational Scheme for the Optimization of 2D Radial Reflectors in Pressurized Water Reactors
Thomas Clerc, Alain Hébert, Hadrien Leroyer +3
This paper presents a computational scheme for the determination of equivalent 2D multi-group heterogeneous reflectors in a Pressurized Water Reactor (PWR). The proposed strategy i…
Reconstruction by data assimilation of the inner temperature field from outer measurements in a thick pipe
Jean-Philippe Argaud, Bertrand Bouriquet, Aimery Assire +1
The detailed knowledge of the inner skin temperature behavior is very important to evaluate and manage the aging of large pipes in cooling systems. We describe here a method to obt…
Variational Assimilation for Xenon Dynamical Forecasts in Neutronic using Advanced Background Error Covariance Matrix
Angélique Ponçot, Jean-Philippe Argaud, Bertrand Bouriquet +3
Data assimilation method consists in combining all available pieces of information about a system to obtain optimal estimates of initial states. The different sources of informatio…
Unified nuclear core activity map reconstruction using heterogeneous instruments with data assimilation
Bertrand Bouriquet, Jean-Philippe Argaud, Patrick Erhard +1
Evaluating the neutronic state of the whole nuclear core is a very important topic that have strong implication for nuclear core management and for security monitoring. The core st…
Optimal design of measurement network for neutronic activity field reconstruction by data assimilation
Bertrand Bouriquet, Jean-Philippe Argaud, Romain Cugnart
Using data assimilation framework, to merge information from model and measurement, an optimal reconstruction of the neutronic activity field can be determined for a nuclear reacto…
Differential influence of instruments in nuclear core activity evaluation by data assimilation
Bertrand Bouriquet, Jean-Philippe Argaud, Patrick Erhard +4
The global activity fields of a nuclear core can be reconstructed using data assimilation. Data assimilation allows to combine measurements from instruments, and information from a…
Robustness of nuclear core activity reconstruction by data assimilation
Bertrand Bouriquet, Jean-Philippe Argaud, Patrick Erhard +4
We apply a data assimilation techniques, inspired from meteorological applications, to perform an optimal reconstruction of the neutronic activity field in a nuclear core. Both mea…
Best linear unbiased estimation of the nuclear masses
Bertrand Bouriquet, Jean-Philippe Argaud
This paper presents methods to provide an optimal evaluation of the nuclear masses. The techniques used for this purpose come from data assimilation that allows combining, in an op…