Search results for "Kernel based method"

showing 2 items of 2 documents

Highlighting numerical insights of an efficient SPH method

2018

Abstract In this paper we focus on two sources of enhancement in accuracy and computational demanding in approximating a function and its derivatives by means of the Smoothed Particle Hydrodynamics method. The approximating power of the standard method is perceived to be poor and improvements can be gained making use of the Taylor series expansion of the kernel approximation of the function and its derivatives. The modified formulation is appealing providing more accurate results of the function and its derivatives simultaneously without changing the kernel function adopted in the computation. The request for greater accuracy needs kernel function derivatives with order up to the desidered …

Computer scienceApplied MathematicsGaussianComputation010103 numerical & computational mathematicsFunction (mathematics)01 natural sciences010101 applied mathematicsSmoothed-particle hydrodynamicsComputational Mathematicssymbols.namesakeSettore MAT/08 - Analisi NumericaKernel based methods Smoothed Particle Hydrodynamics Accuracy Convergence Improved fast Gaussian transform.Convergence (routing)symbolsTaylor seriesGaussian function0101 mathematicsFocus (optics)Algorithm
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The smoothed particle hydrodynamics method via residual iteration

2019

Abstract In this paper we propose for the first time an iterative approach of the Smoothed Particle Hydrodynamics (SPH) method. The method is widespread in many areas of science and engineering and despite its extensive application it suffers from several drawbacks due to inaccurate approximation at boundaries and at irregular interior regions. The presented iterative process improves the accuracy of the standard method by updating the initial estimates iterating on the residuals. It is appealing preserving the matrix-free nature of the method and avoiding to modify the kernel function . Moreover the process refines the SPH estimates and it is not affected by disordered data distribution. W…

Iterative and incremental developmentComputer scienceMechanical EngineeringComputational MechanicsProcess (computing)General Physics and Astronomy010103 numerical & computational mathematicsBivariate analysisIterated residualResidual01 natural sciencesComputer Science Applications010101 applied mathematicsSmoothed-particle hydrodynamicsSettore MAT/08 - Analisi NumericaDistribution (mathematics)Smoothed particle hydrodynamicMechanics of MaterialsConvergence (routing)Test functions for optimization0101 mathematicsConvergenceAlgorithmAccuracyKernel based method
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