Generalized neural closure models with interpretability
A Gupta, PFJ Lermusiaux - Scientific Reports, 2023 - nature.com
Improving the predictive capability and computational cost of dynamical models is often at
the heart of augmenting computational physics with machine learning (ML). However, most …
the heart of augmenting computational physics with machine learning (ML). However, most …
From modelling to inversion: designing a well‐adapted simulator
WW Symes, D Sun, M Enriquez - Geophysical Prospecting, 2011 - earthdoc.org
This paper describes a few mild design constraints that permit rapid adaptation of the
modelling code for linear wave propagation to imaging/inversion or design optimization …
modelling code for linear wave propagation to imaging/inversion or design optimization …
Adjoint based optimal control of partially miscible two-phase flow in porous media with applications to CO2 sequestration in underground reservoirs
M Simon, M Ulbrich - Optimization and Engineering, 2015 - Springer
With the target of optimizing CO 2 sequestration in underground reservoirs, we investigate
constrained optimal control problems with partially miscible two-phase flow in porous media …
constrained optimal control problems with partially miscible two-phase flow in porous media …
Optimal Control of Partially Miscible Two-Phase Flow with Applications to Subsurface CO2 Sequestration
M Simon, M Ulbrich - Advanced Computing, 2013 - Springer
Motivated by applications in subsurface CO 2 sequestration, we investigate constrained
optimal control problems with partially miscible two-phase flow in porous media. The …
optimal control problems with partially miscible two-phase flow in porous media. The …