Search results for "ANALISI NUMERICA."
showing 6 items of 106 documents
Separatrix reconstruction to identify tipping points in an eco-epidemiological model
2018
Many ecological systems exhibit tipping points such that they suddenly shift from one state to another. These shifts can be devastating from an ecological point of view, and additionally have severe implications for the socio-economic system. They can be caused by overcritical perturbations of the state variables such as external shocks, disease emergence, or species removal. It is therefore important to be able to quantify the tipping points. Here we present a study of the tipping points by considering the basins of attraction of the stable equilibrium points. We address the question of finding the tipping points that lie on the separatrix surface, which partitions the space of system traj…
Viscoelasticity: an electrical point of view
2014
Time dependent hereditary properties of complex materials are well described by power-laws with real order exponent. This experimental observation and analogous electrical experiments, yield a description of these properties by using fractional-order operators. In this paper, elasto-viscous and visco-elastic behaviors of fractional order hereditary materials are firstly described by using fractional mathematical operators, based on recent work of some of the authors. Then, electrical analogous models are introduced. Viscoelastic models have elastic and viscous components which can be obtained by combining springs and dashpots: these models can be equivalently viewed as electrical circuits, …
Towards an efficient meshfree solver
2016
In this paper we focus on the enhancement in accuracy approximating a function and its derivatives via smoothed particle hydrodynamics. We discuss about improvements in the solution by reformulating the original method by means of the Taylor series expansion and by projecting with the kernel function and its derivatives. The accuracy of a function and its derivatives, up to a fixed order, can be simultaneously improved by assuming them as unknowns of a linear system. The improved formulation has been assessed with gridded and scattered data points distribution and the convergence has been analyzed referring to a case study in a 2D domain.
A CUDA-based implementation of an improved SPH method on GPU
2021
We present a CUDA-based parallel implementation on GPU architecture of a modified version of the Smoothed Particle Hydrodynamics (SPH) method. This modified formulation exploits a strategy based on the Taylor series expansion, which simultaneously improves the approximation of a function and its derivatives with respect to the standard formulation. The improvement in accuracy comes at the cost of an additional computational effort. The computational demand becomes increasingly crucial as problem size increases but can be addressed by employing fast summations in a parallel computational scheme. The experimental analysis showed that our parallel implementation significantly reduces the runti…
SPH method: numerical investigations and applications
2018
In this paper we discuss on the enhancements in accuracy and computational demanding in approx- imating 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 are con- sidered. In this paper we discuss on some numerical behaviors of the method. Some variants of the process are analyzed and results on the accuracy and the computational demanding, dealing with different sets of data and bivariate functions, are proposed.
Enhancing the Iterative Smoothed Particle Hydrodynamics Method
2021
Motivated by recent research on the iterative approach proposed for the smoothed particle hydrodynamics (ISPH) method, some ideas to improve the process are introduced. The standard procedure is enhanced iterating on the residuals preserving the matrix-free nature of the process. The method is appealing providing reasonable results with disordered data distribution too and no kernel variations are needed in the approximation. This work moves forward with a novel formulation requiring a lower number of iterations to reach a desired accuracy. The computational procedure is described and some results are introduced to appreciate the proposed formulation.