This survey addresses sampling discretization and its connections with other areas of mathematics. The concentrates on norms elements finite-dimensional subspaces. We present here known results both integral the uniform norm beginning classical ending very recent achievements. also show how connects to spectral properties operator submatrices, embedding subspaces, moments marginals high-dimensi...

A model to predict the effective stiffness of woven fabric composite materials is presented. Taking advantage of the inherent periodicity of woven fabric architecture, periodic microstructure theory is used at the mesoscale for the case of a two-phase heterogeneous material with multiple periodic inclusions. For plain weave fabrics, the representative volume element (RVE) is discretized into fi...

Thermal buckling analysis of square composite laminates with variable stiffness properties is presented. Fiber angles vary spatially and result in material properties that are functions of position. The thermal critical buckling temperatures for such laminates are obtained numerically based on classical lamination theory and the finite element method. In this work, the domain is discretized to ...

This work deals with the simulation and discretization of continuous time models with fractional order differentiation or integration. It addresses the issue of direct discretization of analog fractional order systems followed by approximating the discretization result with an integer order transfer function or approximating the analog fractional order system with an integer analog order system...

We are interested in numerical methods for computing the effective heat conductivity of fibrous insulation materials, such as glass or mineral wool, characterized by low solid volume fractions and high contrasts, i.e. high ratios between the thermal conductivities of the fibers and the surrounding air. We consider a fast numerical method for solving some auxiliary cell problems appearing in thi...

We study a central difference discretization of Rudin-Osher-Fetami model for image de-noising. We show that the discrete solution uk converges to the continuous solution u in L2 norm and a rate of convergence is given.