Search results for " Analisi numerica"
showing 10 items of 107 documents
An improved Smoothed Particle ElectroMagnetics method in 3D time domain simulations
2012
In this paper, an enhanced variant of the meshless smoothed particle electromagnetics (SPEM) method is performed in order to solve PDEs in time domain describing 3D transient electromagnetic phenomena. The method appears to be very efficient in approximating spatial derivatives in the numerical treatment of Maxwell's curl equations. In many cases, very often, accuracy degradation, due to a lack of particle consistency, severely limits the usefulness of this approach. A numerical corrective strategy, which allows to restore the SPEM consistency, without any modification of the smoothing kernel function and its derivatives, is presented. The method allows to restore the same order of consiste…
Numerical insights of an improved SPH method
2018
In this paper we discuss on the enhancements in accuracy and computational demanding in approximating a function and its derivatives via Smoothed Particle Hydrodynamics. The standard method is widely used nowadays in various physics and engineering applications [1],[2],[3]. However it suffers of low approximation accuracy at boundaries or when scattered data distributions is considered. Here we reformulate the original method by means of the Taylor series expansion and by employing the kernel function and its derivatives as projection functions and integrating over the problem domain [3]. In this way, accurate estimates of the function and its derivatives are simultaneously provided and no …
Admissible perturbations of alpha-psi-pseudocontractive operators: convergence theorems
2015
In the last decades, the study of convergence of fixed point iterative methods has received an increasing attention, due to their performance as tools for solving numerical problems. As a consequence of this fact, one can access to a wide literature on iterative schemes involving different types of operators; see [2, 4, 5]. We point out that fixed point iterative approximation methods have been largely applied in dealing with stability and convergence problems; see [1, 6]. In particular, we refer to various control and optimization questions arising in pure and applied sciences involving dynamical systems, where the problem in study can be easily arranged as a fixed point problem. Then, we …
Polynomial mapped bases: theory and applications
2022
Abstract In this paper, we collect the basic theory and the most important applications of a novel technique that has shown to be suitable for scattered data interpolation, quadrature, bio-imaging reconstruction. The method relies on polynomial mapped bases allowing, for instance, to incorporate data or function discontinuities in a suitable mapping function. The new technique substantially mitigates the Runge’s and Gibbs effects.
Analysis of the Allee threshold via moving least square approximation
2016
Cooperation is a common behavior between the members of predators species, because it can improve theirs skill in hunt, especially in endangered eco-systems. This behavior it is well known to induce the Strong Allee effect, that can induce the extinction when the initial populations’ is under a critical density called ”Allee threshold ”. Here we investigate the impact of the pack hunting in a predator-prey system in which the predator suffers of an infectious disease with frequency and vertical transmission. The result is a three dimensional system with the predators population divided into susceptible and infected individuals. Studying the system dynamics a scenario was identified in which…
An adaptive algorithm for determining the optimal degree of regression in constrained mock-Chebyshev least squares quadrature
2022
In this paper we develop an adaptive algorithm for determining the optimal degree of regression in the constrained mock-Chebyshev least-squares interpolation of an analytic function to obtain quadrature formulas with high degree of exactness and accuracy from equispaced nodes. We numerically prove the effectiveness of the proposed algorithm by several examples.
A comparison of local parametric C0 Bézier interpolants for triangular meshes
2011
Parametric curved shape surface schemes interpolating vertices and normals of a given triangular mesh with arbitrary topology are widely used in computer graphics for gaming and real-time rendering due to their ability to effectively represent any surface of arbitrary genus. In this context, continuous curved shape surface schemes using only the information related to the triangle corresponding to the patch under construction, emerged as attractive solutions responding to the requirements of resource-limited hardware environments. In this paper we provide a unifying comparison of the local parametric C^0 curved shape schemes we are aware of, based on a reformulation of their original constr…
Shock-Capturing methods: Well-Balanced Approximate Taylor and Semi-Implicit schemes
2022
Iterative Reconstruction of Signals on Graph
2020
We propose an iterative algorithm to interpolate graph signals from only a partial set of samples. Our method is derived from the well known Papoulis-Gerchberg algorithm by considering the optimal value of a constant involved in the iteration step. Compared with existing graph signal reconstruction algorithms, the proposed method achieves similar or better performance both in terms of convergence rate and computational efficiency.
First Experiences on an Accurate SPH Method on GPUs
2017
It is well known that the standard formulation of the Smoothed Particle Hydrodynamics is usually poor when scattered data distribution is considered or when the approximation near the boundary occurs. Moreover, the method is computational demanding when a high number of data sites and evaluation points are employed. In this paper an enhanced version of the method is proposed improving the accuracy and the efficiency by using a HPC environment. Our implementation exploits the processing power of GPUs for the basic computational kernel resolution. The performance gain demonstrates the method to be accurate and suitable to deal with large sets of data.