On a Model for Mass Aggregation with Maximal Size

Mathematics – Analysis of PDEs

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

new version with revised proofs; 13 pages, several figures

Scientific paper

We study a kinetic mean-field equation for a system of particles with different sizes, in which particles are allowed to coagulate only if their sizes sum up to a prescribed time-dependent value. We prove well-posedness of this model, study the existence of self-similar solutions, and analyze the large-time behavior mostly by numerical simulations. Depending on the parameter $\Dconst$, which controls the probability of coagulation, we observe two different scenarios: For $\Dconst>2$ there exist two self-similar solutions to the mean field equation, of which one is unstable. In numerical simulations we observe that for all initial data the rescaled solutions converge to the stable self-similar solution. For $\Dconst<2$, however, no self-similar behavior occurs as the solutions converge in the original variables to a limit that depends strongly on the initial data. We prove rigorously a corresponding statement for $\Dconst\in (0,1/3)$. Simulations for the cross-over case $\Dconst=2$ are not completely conclusive, but indicate that, depending on the initial data, part of the mass evolves in a self-similar fashion whereas another part of the mass remains in the small particles.

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

On a Model for Mass Aggregation with Maximal Size 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 On a Model for Mass Aggregation with Maximal Size, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On a Model for Mass Aggregation with Maximal Size will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-276647

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