Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-
order) aerodynamic models or flight testing are some of the fundamental but complex steps …

A dimension reduction method called discrete empirical interpolation is proposed and
shown to dramatically reduce the computational complexity of the popular proper orthogonal …

A two-step online method is proposed for interpolating projection-based linear parametric
reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter …

This paper derives state space error bounds for the solutions of reduced systems
constructed using proper orthogonal decomposition (POD) together with the discrete …

In this paper, optimal control theory is used to minimize the total mean drag for a circular
cylinder wake flow in the laminar regime (Re= 200). The control parameters are the …

Proper orthogonal decomposition (POD) is a powerful technique for model reduction of non-
linear systems. It is based on a Galerkin type discretization with basis elements created from …

Computational fluid dynamics coupled with the discrete element method (CFD-DEM) is
widely employed for simulating multiphase flows involving particles, but the heavy …

The derivations of existing error bounds for reduced order models of time varying partial
differential equations (PDEs) constructed using proper orthogonal decomposition (POD) …

Finite element simulations of nonlinear deformable models are computationally costly,
routinely taking hours or days to compute the motion of detailed meshes. Dimensional …

A new reduced-order model based on trajectory piecewise quadratic (TPWQ)
approximations and proper orthogonal decomposition (POD) is introduced and applied for …