Data-enabled physics-informed machine learning for reduced-order modeling digital twin: application to nuclear reactor physics
This paper proposes an approach that combines reduced-order models with machine
learning in order to create physics-informed digital twins to predict high-dimensional output …
learning in order to create physics-informed digital twins to predict high-dimensional output …
Generalized Empirical Interpolation Method With H 1 Regularization: Application to Nuclear Reactor Physics
H Gong, Z Chen, Q Li - Frontiers in Energy Research, 2022 - frontiersin.org
The generalized empirical interpolation method (GEIM) can be used to estimate the physical
field by combining observation data acquired from the physical system itself and a reduced …
field by combining observation data acquired from the physical system itself and a reduced …
A real-time variational data assimilation method with data-driven model enrichment for time-dependent problems
We propose an extension of the Parameterized-Background-Data-Weak (PBDW)
formulation, introduced in Maday et al.(2015), to the time-dependent context for state …
formulation, introduced in Maday et al.(2015), to the time-dependent context for state …
Optimal and fast field reconstruction with reduced basis and limited observations: Application to reactor core online monitoring
The fast reconstruction of neutronic field in a nuclear core using reduced modeling and
limited observations has attracted considerable attention. In particular, four design …
limited observations has attracted considerable attention. In particular, four design …
PBDW: A non-intrusive Reduced Basis Data Assimilation method and its application to an urban dispersion modeling framework
JK Hammond, R Chakir, F Bourquin… - Applied Mathematical …, 2019 - Elsevier
The challenges of understanding the impacts of air pollution require detailed information on
the state of air quality. While many modeling approaches attempt to treat this problem …
the state of air quality. While many modeling approaches attempt to treat this problem …
Reactor power distribution detection and estimation via a stabilized gappy proper orthogonal decomposition method
H Gong, Y Yu, Q Li - Nuclear Engineering and Design, 2020 - Elsevier
The proper orthogonal decomposition (POD) method has been applied in nuclear reactor
physics to extract features of dominant flux or power. In particular, the gappy POD method is …
physics to extract features of dominant flux or power. In particular, the gappy POD method is …
[HTML][HTML] Hybrid Data Assimilation methods, Part II: Application to the DYNASTY experimental facility
Abstract Hybrid Data Assimilation (HDA) methods aim at combining the advantages of
mathematical models and experimental observations by integrating Model Order Reduction …
mathematical models and experimental observations by integrating Model Order Reduction …
Inverse problems: A deterministic approach using physics-based reduced models
O Mula - Model Order Reduction and Applications: Cetraro, Italy …, 2023 - Springer
These lecture notes summarize various summer schools that I have given on the topic of
solving inverse problems (state and parameter estimation) by combining optimally …
solving inverse problems (state and parameter estimation) by combining optimally …
[HTML][HTML] Hybrid data assimilation methods, Part I: Numerical comparison between GEIM and PBDW
Abstract Hybrid Data Assimilation (HDA) methods are a class of numerical methods that aim
at integrating Model Order Reduction (MOR) techniques into a Data Assimilation (DA) …
at integrating Model Order Reduction (MOR) techniques into a Data Assimilation (DA) …
State estimation with model reduction and shape variability. Application to biomedical problems
We develop a mathematical and numerical framework to solve state estimation problems for
applications that present variations in the shape of the spatial domain. This situation arises …
applications that present variations in the shape of the spatial domain. This situation arises …