In this paper, we introduce an uplifted reduced order modeling (UROM) approach through
the integration of standard projection based methods with long short-term memory (LSTM) …

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 …

Approximating solutions of non-linear parametrized physical problems by interpolation
presents a major challenge in terms of accuracy. In fact, pointwise interpolation of such …

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 …

Many engineering problems are parameterized. In order to minimize the computational cost
necessary to evaluate a new operating point, the interpolation of singular matrices …

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

Effective data reduction techniques are crucial for enhancing computational efficiency in
complex industrial processes such as forging. In this study, we investigate various …

Many applications of the matrix exponential exp (A t) of a real matrix A and a real parameter t
require repeated evaluation of it for different values of t. Such evaluations are time …

Most genetic algorithms (GAs) used in the literature to solve control problems are time
consuming and involve important storage memory requirements. In fact, the search in GAs is …

In this paper, we construct a reduced-order finite element (ROFE) method holding seldom
unknowns for the parabolic optimal control problem. We apply the proper orthogonal …