Repository logo
  • English
  • Deutsch
  • Español
  • Français
  • Log In
    New user? Click here to register.Have you forgotten your password?

  • English
  • Deutsch
  • Español
  • Français
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • Research Outputs
  • Fundings & Projects
  • Researchers
  • Statistics
  1. Home
  2. Browse by Author

Browsing by Author "A C Gormaz-Matamala"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • No Thumbnail Available
    Some of the metrics are blocked by your 
    consent settings
    Publication
    Analytical solutions for radiation-driven winds in massive stars – II. The δ-slow regime
    (Oxford University Press (OUP), 2021-04-10)
    I Araya
    ;
    Christen, Alejandra  
    ;
    Cure, Michel  
    ;
    L S Cidale
    ;
    R O J Venero
    ;
    Arcos, Catalina  
    ;
    A C Gormaz-Matamala
    ;
    M Haucke
    ;
    P Escárate
    ;
    H Clavería
    ABSTRACT Accurate mass-loss rates and terminal velocities from massive stars winds are essential to obtain synthetic spectra from radiative transfer calculations and to determine the evolutionary path of massive stars. From a theoretical point of view, analytical expressions for the wind parameters and velocity profile would have many advantages over numerical calculations that solve the complex non-linear set of hydrodynamic equations. In a previous work, we obtained an analytical description for the fast wind regime. Now, we propose an approximate expression for the line-force in terms of new parameters and obtain a velocity profile closed-form solution (in terms of the Lambert W function) for the δ-slow regime. Using this analytical velocity profile, we were able to obtain the mass-loss rates based on the m-CAK theory. Moreover, we established a relation between this new set of line-force parameters with the known stellar and m-CAK line-force parameters. To this purpose, we calculated a grid of numerical hydrodynamical models and performed a multivariate multiple regression. The numerical and our descriptions lead to good agreement between their values.

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback

Hosting & Support by

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science