Modeling Solids in Nuclear Astrophysics with Smoothed Particle Hydrodynamics

ORAL

Abstract

Smoothed Particle Hydrodynamics (SPH) is a frequently applied tool in computational astrophysics. In addition to solving the fluid dynamics equations, some problems, for example when involving asteroids and asteroid impacts require the inclusion of material strength to accurately describe the dynamics of the system. In nuclear astrophysics, neutron stars and their binary mergers are usually approached as purely fluid dynamics problems. However, neutron stars also a have solid component, the crust. The latter is the strongest material known in nature but is usually not considered when modeling the dynamical of neutron stars in 3D. Here, we present the first 3D simulations of neutron-star crustal toroidal oscillations with SPH including material strength. We use the Los Alamos National Laboratory SPH code FleCSPH which has been developed as a general-purpose fluid dynamics code with material strength and has been applied to compact star oscillations and mergers. In the first half of the talk, we describe the implementation of solid material modeling in FleCSPH and present standard tests including the Verney implosion and the Taylor anvil impact. The second half is dedicated to simulations of crustal oscillations in the fundamental toroidal mode where we focus on exploring approaches to suppress numerical noise which can otherwise disturb the shear motion.

*The presented work was supported by the Advanced Simulation and Computing program (NNSA/DOE) and the Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200145ER. The research used resources provided by the LANL Institutional Computing Program and the LANL Darwin testbed.This work is authorized for unlimited release under LA-UR-22-29848

Presenters

  • Irina Sagert

    • Los Alamos National Laboratory

Authors

  • Irina Sagert

    • Los Alamos National Laboratory
  • Oleg Korobkin

    • Los Alamos National Laboratory
  • Bing-Jyun Tsao

    • Los Alamos National Laboratory
  • Hyun Lim

    • Los Alamos National Laboratory
  • Ingo Tews

    • Los Alamos National Laboratory
  • Michael Falato

    • Los Alamos National Laboratory
  • Julien Loiseau

    • Los Alamos National Laboratory