Small dust grain dynamics on adaptive mesh refinement grids

U. Lebreuilly,G. Laibe,B. Commerçon

doi:10.1051/0004-6361/201834147

Abstract

Context. Small dust grains are essential ingredients of star, disk and planet formation. Aims. We present an Eulerian numerical approach to study small dust grain dynamics in the context of star and protoplanetary disk formation. It is designed for finite volume codes. We use it to investigate dust dynamics during the protostellar collapse. Methods. We present a method to solve the monofluid equations of gas and dust mixtures with several dust species in the diffusion approximation implemented in the adaptive-mesh-refinement code RAMSES. It uses a finite volume second-order Godunov method with a predictor-corrector MUSCL scheme to estimate the fluxes between the grid cells. Results. We benchmark our method against six distinct tests, DUSTYADVECT, DUSTYDIFFUSE, DUSTYSHOCK, DUSTYWAVE, SETTLING, and DUSTYCOLLAPSE. We show that the scheme is second-order accurate in space on uniform grids and intermediate between second- and first-order on non-uniform grids. We apply our method on various DUSTYCOLLAPSE simulations of 1 M⊙ cores composed of gas and dust. Conclusions. We developed an efficient approach to treat gas and dust dynamics in the diffusion regime on grid-based codes. The canonical tests were successfully passed. In the context of protostellar collapse, we show that dust is less coupled to the gas in the outer regions of the collapse where grains larger than ≃100 μm fall significantly faster than the gas.

Highlights

Dust grains are thought to represent on average only 1% of the mass of the diffuse interstellar medium (ISM, Mathis et al 1977; Weingartner & Draine 2001)
Before we present our method, we recall the main features of the RAMSES code (Teyssier 2002) in order to facilitate the understanding of our implementation of dust dynamics in the diffusion approximation
RAMSES is a finite volume Eulerian code that integrates the equation of hydrodynamics in their conservative form on an AMR grid (Berger & Oliger 1984)

Summary

Introduction

Dust grains are thought to represent on average only 1% of the mass of the diffuse interstellar medium (ISM, Mathis et al 1977; Weingartner & Draine 2001) Their typical size distribution is usually modeled as a power law (Mathis et al 1977, hereafter MRN). A dynamical size sorting may operate in molecular clouds (Hopkins & Lee 2016; Tricco et al 2017) or during the protostellar collapse (Bate & Lorén-Aguilar 2017). This sorting leads to important variations in the dust-to-gas ratio, especially for large dust grains. As we need to know the dust concentration, a treatment of its dynamics is essential to improve our understanding of stellar, disk, and planet formation

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Conclusion