Large Nuclear Networks in Presupernova Models

Physics – Nuclear Physics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

1

Scientific paper

We outline the role of multidimensional hydrodynamics coupled to large nuclear networks in the case of core silicon burning in massive stars. Using an implementation of the Piecewise Parabolic Method (PPM) of solving the Euler equations for mass, momentum, and total energy, we examine the differences and similarities between a 1-D hydrostatic stellar evolution model and a 2-D hydrodynamical model at two resolutions. We find that 2-D models exhibit significantly less vigorous convection than 1-D hydrostatic models, and that the core compensates for the lack of energy production by increasing temperatures and densities through contraction. Equilibration between the Si-burning and convective timescales appears to occur. Including an 123 isotope network from Ye to 66Ge to the hydrodynamic code leads to similar global behaviors as the 2-D model with the simplified burning algorithm used in the 1-D models. However, significant inhomogeneity in iron peak isotope composition occurs, which could have important consequences to energy losses via electron captures onto G-T resonances and the local energetics which drive convective silicon burning.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Large Nuclear Networks in Presupernova Models does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Large Nuclear Networks in Presupernova Models, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Large Nuclear Networks in Presupernova Models will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-1606991

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.