Pattern recognition issues on anisotropic smoothed particle hydrodynamics
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Data
2014-01-01
Autores
Marinho, Eraldo Pereira
Vagenas, E. C.
Vlachos, D. S.
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Iop Publishing Ltd
Resumo
This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.
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2nd International Conference On Mathematical Modeling In Physical Sciences 2013 (ic-msquare 2013). Bristol: Iop Publishing Ltd, v. 490, 4 p., 2014.