A shock-capturing SPH scheme based on adaptive kernel estimation

Sigalotti, Leonardo Di G.; López, Hender; Donoso, Arnaldo; Sira, Eloy; Klapp, Jaime

doi:10.1016/j.jcp.2005.06.016

Cited by 52 publications

(33 citation statements)

References 59 publications

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“…Neither hydrodynamic nor particle based simulations can operate with point-like energy depositions and have therefore to choose a finite size injection region. For hydrodynamic codes it has been shown that the size and shape of this region can impact the density, velocity, and pressure evolution of the shock front [93,94]. The vanishingly small number densities at the center of the simulation space can be a challenge for codes operating with a finite number of particles as densities cannot become arbitrarily small [95].…”

Section: Sedov-taylor Testmentioning

confidence: 99%

Hydrodynamic shock wave studies within a kinetic Monte Carlo approach

Sagert

Bauer

Colbry

et al. 2014

Journal of Computational Physics

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We introduce a massively parallelized test-particle based kinetic Monte Carlo code that is capable of modeling the phase space evolution of an arbitrarily sized system that is free to move in and out of the continuum limit. Our code combines advantages of the DSMC and the Point of Closest Approach techniques for solving the collision integral. With that, it achieves high spatial accuracy in simulations of large particle systems while maintaining computational feasibility. Using particle mean free paths which are small with respect to the characteristic length scale of the simulated system, we reproduce hydrodynamic behavior. To demonstrate that our code can retrieve continuum solutions, we perform a test-suite of classic hydrodynamic shock problems consisting of the Sod, the Noh, and the Sedov tests. We find that the results of our simulations which apply millions of test-particles match the analytic solutions well. In addition, we take advantage of the ability of kinetic codes to describe matter out of the continuum regime when applying large particle mean free paths. With that, we study and compare the evolution of shock waves in the hydrodynamic limit and in a regime which is not reachable by hydrodynamic codes.

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Section: Sedov-taylor Testmentioning

confidence: 99%

Hydrodynamic shock wave studies within a kinetic Monte Carlo approach

Sagert

Bauer

Colbry

et al. 2014

Journal of Computational Physics

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“…The derivation of these symmetrizations are explained in [36]. In calculations of compressible flows involving the formation and propagation of shocks, an artificial viscosity term, P ij , must be added to the SPH equations to dissipate postshock oscillations in the solution and avoid particle interpenetration in high Mach number collisions.…”

Section: The Sph Equationsmentioning

confidence: 99%

An adaptive SPH method for strong shocks

Sigalotti¹,

López²,

Trujillo³

2009

Journal of Computational Physics

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“…It has also been incorporated into a standard Smoothed Particle Hydrodynamics (SPH) method to simulate conventional fluid dynamics yielding a substantial improvement on the stability of the calculations. In recent work [15], we have reported a variant of SPH method that allows for the simulation of compressible fluid with strong shocks and rarefaction waves in one and two dimensions. The known instabilities of the conventional scheme (the wall heating phenomena) virtually dissapear when adaptive kernels, as presented here, are implemented.…”

Section: Discussionmentioning

confidence: 99%

Adaptive kernel methods to simulate quantum phase space flow

Lopez¹,

Donoso²

2006

Condens. Matter Phys.

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A technique for simulating quantum dynamics in phase space is discussed. It makes use of ensembles of classical trajectories to approximate the distribution functions and their derivatives by implementing Adaptive Kernel Density Estimation. It is found to improve the accuracy and stability of the simulations compared to more conventional particle methods. Formulation of the method in higher dimensions is straightforward.

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A shock-capturing SPH scheme based on adaptive kernel estimation

Cited by 52 publications

References 59 publications

Hydrodynamic shock wave studies within a kinetic Monte Carlo approach

Hydrodynamic shock wave studies within a kinetic Monte Carlo approach

An adaptive SPH method for strong shocks

Adaptive kernel methods to simulate quantum phase space flow

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