Simulations of planetary-scale collisions between rotating, differentiated bodies
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.j6q573n94
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资源简介:
In the late stages of terrestrial planet formation, pairwise collisions between planetary-sized bodies act as the fundamental agent of planet growth. These collisions can lead to either growth or disruption of the bodies involved and are largely responsible for shaping the final characteristics of planets. Despite their critical role in planet formation, an accurate treatment of collisions has yet to be realized. Therefore, we simulated a new set of 10,700 smoothed-particle hydrodynamics (SPH) simulations of pairwise collisions between rotating, differentiated bodies. This dataset is an order of magnitude larger than any previous collision dataset and is intended to serve as a training dataset for machine learning models, so that accurate surrogate models for planetary-scale collisions can be developed.
Methods
Each collision is uniquely defined by a set of 12 pre-impact parameters. Together, these parameters define the geometry of the impact and the physical and rotational characteristics of the bodies involved in the collision. The colliding bodies are referred to as the target and projectile, where the target is the more massive of the two. The pre-impact parameter space was constructed using Latin hypercube sampling (LHS). For the LHS10K set, a LHS-based adaptive surface response method (ARSM) was used to progressively enrich the sample from an initial LHS sample of 1000 collisions.
The collisions were simulated with Gasoline, a massively-parellel smoothed-particle hydrodynamics (SPH) code (Wadsley et al. 2004). The number of particles in each collision is set by the ratio of the projectile mass to target mass, whereby the projectile always contains 10,000 particles and the number of particles in the target is scaled relative to its mass. Each collision was simulated for 100 times its collision timescale, which is equivalent to the crossing time of the encounter.
创建时间:
2020-02-06



