Skeletal Kinetics Reduction for Astrophysical Reaction Networks
| Autor: | A. G. Nouri, Y. Liu, P. Givi, H. Babaee, D. Livescu |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | The Astrophysical Journal Supplement Series, Vol 272, Iss 2, p 34 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1538-4365 0067-0049 |
| DOI: | 10.3847/1538-4365/ad454a |
| Popis: | A novel methodology is developed to extract accurate skeletal reaction models for nuclear combustion. Local sensitivities of isotope mass fractions with respect to reaction rates are modeled based on the forced optimally time-dependent (f-OTD) scheme. These sensitivities are then analyzed temporally to generate skeletal models. The methodology is demonstrated by conducting skeletal reduction of constant density and temperature burning of carbon and oxygen relevant to Type Ia supernovae (SNe Ia). The 495-isotopes Torch model is chosen as the detailed reaction network. A map of maximum production of ^56 Ni in SNe Ia is produced for different temperatures, densities, and proton-to-neutron ratios. The f-OTD simulations and the sensitivity analyses are then performed with initial conditions from this map. A series of skeletal models are derived and their performances are assessed by comparison against currently existing skeletal models. Previous models have been constructed intuitively by assuming the dominance of α -chain reactions. The comparison of the newly generated skeletal models against previous models is based on the predicted energy release and ^44 Ti and ^56 Ni abundances by each model. The consequences of y _e ≠ 0.5 in the initial composition are also explored where y _e is the electron fraction. The simulated results show that ^56 Ni production decreases by decreasing y _e as expected, and that the ^43 Sc is a key isotope in proton and neutron channels toward ^56 Ni production. It is shown that an f-OTD skeletal model with 150 isotopes can accurately predict the ^56 Ni abundance in SNe Ia for y _e ≲ 0.5 initial conditions. |
| Databáze: | Directory of Open Access Journals |
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