S.R. et al 2015a - Revision history

Onate at 09:51, 28 October 2019

2019-10-28T09:51:51Z

Onate at 09:47, 28 October 2019

2019-10-28T09:47:04Z

Onate at 11:38, 29 April 2019

2019-04-29T11:38:06Z

Scipediacontent at 09:01, 22 November 2017

2017-11-22T09:01:02Z

Scipediacontent at 09:00, 22 November 2017

2017-11-22T09:00:43Z

Move page script: Move page script moved page S.R. et al 1970a to S.R. et al 2015a

2017-11-21T14:31:26Z

Move page script moved page S.R. et al 1970a to S.R. et al 2015a

Scipediacontent: Scipediacontent moved page Draft Content 836490400 to S.R. et al 1970a

2017-11-21T12:26:05Z

Scipediacontent moved page Draft Content 836490400 to S.R. et al 1970a

Scipediacontent: Created page with "== Abstract == Particle methods in Computational Fluid Dynamics (CFD) are numerical tools for the solution of the equations of f luid dynamics obtained by replacing the fluui..."

2017-11-21T12:25:01Z

Created page with "== Abstract == Particle methods in Computational Fluid Dynamics (CFD) are numerical tools for the solution of the equations of f luid dynamics obtained by replacing the fluui..."

New page

== Abstract ==

Particle methods in Computational Fluid Dynamics (CFD) are numerical tools for the solution of the equations of f
luid dynamics obtained by replacing the fluuid continuum with a finite set of particles. For mathematicians, particles are just points from which properties of the
uid can be interpolated. For physicists the particles are material points, which can be treated like any other particle system. Either way, particle methods have a number of attractive features. One of the key attributes is that pure advection is treated exactly. For example, if the particles are given a determined colour and the velocity is specified, the transport of colours by the particle system is exact. The convection of properties also eases the solution of multi material problems, simplifying the detection of interfaces. The use of particles also allows to bridge the gap between the continuum and fragmentation in a natural way, for example in fracture or droplets problems. Since the computation domain, the particles, matches exactly the material domain of interest, the computational resources are optimized with the corresponding reduction in storage and calculation time compared to other methods. Finally, because of the close similarity between particle methods and the physics of the problems to be solved, it is often possible to account for complex physics more easily than with other methods.

== Full document ==
<pdf>Media:draft_Content_836490400con337.pdf</pdf>

← Older revision		Revision as of 09:51, 28 October 2019
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−	Published in ''Encyclopedia of Computational Mechanics. Second Edition'' Edited by E. Stein, R. de Borst and T. J. R. Hughes. Chichester, UK: John Wiley & Sons, Ltd, pp. 1-41, 2018<br />	+	Published in ''Encyclopedia of Computational Mechanics. Second Edition''. Edited by E. Stein, R. de Borst and T. J. R. Hughes. Chichester, UK: John Wiley & Sons, Ltd, pp. 1-41, 2018<br />
	DOI: 10.1002/9781119176817.ecm2113		DOI: 10.1002/9781119176817.ecm2113

← Older revision		Revision as of 09:47, 28 October 2019
Line 1:		Line 1:
−	Published in ''Encyclopedia of Computational Mechanics. Second Edition'' Edited by E. Stein, R. de Borst and T. J. R. Hughes. Chichester, UK: John Wiley & Sons, Ltd, pp. 1-41, 2018	+	Published in ''Encyclopedia of Computational Mechanics. Second Edition'' Edited by E. Stein, R. de Borst and T. J. R. Hughes. Chichester, UK: John Wiley & Sons, Ltd, pp. 1-41, 2018<br />
		+	DOI: 10.1002/9781119176817.ecm2113
		+
	== Abstract ==		== Abstract ==

← Older revision		Revision as of 11:38, 29 April 2019
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		+	Published in ''Encyclopedia of Computational Mechanics. Second Edition'' Edited by E. Stein, R. de Borst and T. J. R. Hughes. Chichester, UK: John Wiley & Sons, Ltd, pp. 1-41, 2018
	== Abstract ==		== Abstract ==

@@ Line 1: / Line 1: @@
 == Abstract ==
-Particle methods in Computational Fluid Dynamics (CFD) are numerical tools for the solution of the equations of fluid dynamics obtained by replacing the fluuid continuum with a finite set of particles. For mathematicians, particles are just points from which properties of the
+Particle methods in Computational Fluid Dynamics (CFD) are numerical tools for the solution of the equations of fluid dynamics obtained by replacing the fluid continuum with a finite set of particles. For mathematicians, particles are just points from which properties of the
 uid can be interpolated. For physicists the particles are material points, which can be treated like any other particle system. Either way, particle methods have a number of attractive features. One of the key attributes is that pure advection is treated exactly. For example, if the particles are given a determined colour and the velocity is specified, the transport of colours by the particle system is exact. The convection of properties also eases the solution of multi material problems, simplifying the detection of interfaces. The use of particles also allows to bridge the gap between the continuum and fragmentation in a natural way, for example in fracture or droplets problems. Since the computation domain, the particles, matches exactly the material domain of interest, the computational resources are optimized with the corresponding reduction in storage and calculation time compared to other methods. Finally, because of the close similarity between particle methods and the physics of the problems to be solved, it is often possible to account for complex physics more easily than with other methods.
 == Full document ==
 <pdf>Media:draft_Content_836490400con337.pdf</pdf>

← Older revision	Revision as of 14:31, 21 November 2017
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← Older revision	Revision as of 12:26, 21 November 2017
(No difference)