Projection-based reduced-order models (ROMs) play a crucial role in simplifying the
complex dynamics of fluid systems. Such models are achieved by projecting the Navier …

A new strategy for constructing parametric Galerkin reduced order models is presented in
this article. This strategy is achieved thanks to the Riemannian manifold, quotient of the set …

Optimal control of turbulent mixed-convection flows has attracted considerable attention from
researchers. Numerical algorithms such as Genetic Algorithms (GAs) are powerful tools that …

In this paper, we construct a reduced order model (ROM) to solve the advection–diffusion-
reaction (ADR) equation with variable coefficients. In order to get the desired fidelity solution …

Within the environmental context, numerical modeling is a promising approach to assess the
energy efficiency of building. Resilient buildings need to be designed, capable of adapting …

A new application of subspaces interpolation for the construction of nonlinear Parametric
Reduced Order Models (PROMs) is proposed. This approach is based upon the …

Predicting the void fraction of a two-phase flow outside of tubes is essential to evaluate the
thermohydraulic behaviour in steam generators. Indeed, it determines two-phase mixture …

Generally, reduced order models of fluid flows are obtained by projecting the Navier-Stokes
equations onto a reduced subspace spanned by vector functions that carry the meaningful …

On s' intéresse aux algorithmes génétiques pour le contrôle optimal d'écoulements
turbulents. On propose une méthode pour améliorer leur capacité à capter les oscillations …

Optimal control of turbulent mixed-convection flows has attracted considerable attention from
researchers. Numerical algorithms such as Genetic Algorithms (GAs) are powerful tools that …