Computer Science – Performance
Scientific paper
Jan 2012
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012aas...21924226p&link_type=abstract
American Astronomical Society, AAS Meeting #219, #242.26
Computer Science
Performance
Scientific paper
Presently, the scenario best capable of explaining the observational properties of "normal" type Ia supernovae (SNIa), which are of primary importance for cosmology, is the delayed-detonation model. This model postulates that a subsonic thermonuclear deflagration, which originates close to the center of a Chandrasekhar-mass white dwarf (WD) in a single-degenerate binary system, transitions to a supersonic detonation (deflagration-to-detonation transition, or DDT) during the later stages of the explosion. Modern large-scale multidimensional simulations of SNIa cannot capture the DDT process and, thus, are forced to make two crucial assumptions, namely (a) that DDT does occur at some point, and (b) when and where it occurs. Significant progress has been made over the years in elucidating the nature of DDT in terrestrial confined systems with walls, obstacles, or pre-existing shocks. It remains unclear, however, whether and how a detonation can form in an unpressurized, unconfined system such as the interior of a WD. Here we show, through first-principles numerical simulations, that sufficiently fast, but subsonic, turbulent flames in such unconfined environments are inherently susceptible to DDT. The associated mechanism is based on the unsteady evolution of turbulent flames faster than the Chapman-Jouguet deflagrations and is qualitatively different from the traditionally suggested gradient (spontaneous reaction wave) model. It also does not require the formation of distributed flames. The proposed mechanism predicts the DDT density in SNIa to be 107 g/cm3, in agreement with the values previously found to give the best match with observations. This DDT mechanism opens the possibility for eliminating the transition density as a free parameter and, thus, for developing fully self-consistent global multidimensional SNIa models.
This work was supported in part by the Naval Research Laboratory, the Air Force Office of Scientific Research, and by the Department of Defense High Performance Computing Modernization Program.
Oran Elaine S.
Poludnenko Alexei Y.
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