Hydrodynamical simulations of Multiple Shell Planetary Nebulae

Bibcode
1998IAUS..191P.534V
Villaver, Eva; Manchado, A.; Garcia-Segura, Guillermo; Guerrero, Martin
Bibliographical reference

Asymptotic Giant Branch Stars, IAU Symposium 191 Poster Session, #P5-34, held in Montpellier, France, Aug 28 - Sept 1, 1998.

Advertised on:
0
1998
Number of authors
4
IAC number of authors
3
Citations
0
Refereed citations
0
Description
We present hydrodynamical simulations of multiple shell planetary nebulae (MSPN) formation using evolutionary models of 1, 1.5, 2, 2.5, 3.5 and 5 M_odot. Stellar evolution from the AGB (Vassiliadis & Wood 1993) to the post-AGB phase (Vassiliadis & Wood 1994) was followed. Included in our simulations are the effect of stellar evolution and fast wind. The hardening of the stellar spectra as the central star moves across the H-R diagram is also taken into account. The formation of detached haloes as consequence of thermal pulses during the AGB is investigated as well as the effects of the ionization front on the formation of attached shells. Comparison with observations is also shown. Hydrodynamical simulation were carried out with the MHD code ZEUS-3D.
Type
Non-refereed

It may interest you

  • Non-refereed
    Convection, rotation, and magnetic activity of solar-like stars from asteroseismology
    During the last decade, our understanding of stellar physics and evolution has undergone a tremendous revolution thanks to asteroseismology. Space missions such as CoRoT, Kepler, K2, and TESS have already been observing millions of stars providing high-precision photometric data. With these data, it is possible to study the convection of stars
    Mathur, Savita

    Advertised on:

    0
    2024
    Bibcode
    2024IAUS..365..195M
    Citations
    0
  • Non-refereed
    Tales of stellar & binary co-evolution, told by stellar oscillations
    Stellar binarity and stellar oscillations are mostly seen and studied as two separate phenomena. Sometimes, one process is even complicating the analysis of the other beyond the liking of one or the other research community. However, the complete picture painted by the physical constraints provided by the combination of both processes represents a
    Beck, Paul G.

    Advertised on:

    10
    2024
    Bibcode
    2024bss..confE..35B
    Citations
    0
  • Non-refereed
    The Multimodal Universe: 100 TB of Machine Learning Ready Astronomical Data
    We present the Multimodal Universe, a new framework collating over 100 TB of multimodal astronomical data for its first release, spanning images, spectra, time series, tabular and hyper-spectral data. This unified collection enables a wide variety of machine learning (ML) applications and research across astronomical domains. The dataset brings
    Angeloudi, Eirini et al.

    Advertised on:

    12
    2024
    Bibcode
    2024RNAAS...8..301A
    Citations
    0