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곽규진

Kwak, Kyujin
Computational Astrophysics Lab.
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dc.citation.conferencePlace KO -
dc.citation.title 14th International Symposium on Origin of Matter and Evolution of Galaxies, OMEG2017 -
dc.citation.volume 1947 -
dc.contributor.author Park, Byeongchan -
dc.contributor.author Kwak, Kyujin -
dc.date.accessioned 2023-12-19T18:39:23Z -
dc.date.available 2023-12-19T18:39:23Z -
dc.date.created 2018-11-01 -
dc.date.issued 2017-06-27 -
dc.description.abstract Core-collapsed Supernova (CCSN) is one of violent phenomena in the universe. CCSN generates heavy elements and leaves a neutron star behind. It has been known that the physical properties of CCSN depend on those of pre-supernova such as mass, metallicities including distribution of elements, and the density and temperature profile which are obtained from the stellar evolution calculation. In particular, the production of heavy elements in CCSN is sensitive to the abundance profiles in the pre-supernova models. In this study, we evolve a massive main sequence star with 15Msun and solar metallicity to the pre-supernova stage by using two different networks, small and large. The large nuclear reaction network includes more than four times isotopes than the small network. Our calculations were done by MESA (Modules for Experiments in Stellar Astrophysics) which allowed us to use the large network containing about a hundred isotopes. We compare the results obtained with two networks. -
dc.identifier.bibliographicCitation 14th International Symposium on Origin of Matter and Evolution of Galaxies, OMEG2017, v.1947 -
dc.identifier.doi 10.1063/1.5030832 -
dc.identifier.isbn 978-073541642-0 -
dc.identifier.issn 0094-243X -
dc.identifier.scopusid 2-s2.0-85047468514 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/37530 -
dc.identifier.url https://aip.scitation.org/doi/abs/10.1063/1.5030832 -
dc.language 영어 -
dc.publisher 14th International Symposium on Origin of Matter and Evolution of Galaxies, OMEG2017 -
dc.title Pre-supernova models for massive stars produced with large nuclear reaction network by MESA -
dc.type Conference Paper -
dc.date.conferenceDate 2017-06-27 -

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