Abstract
Complex fluid dynamics encompasses a large variety of flows, such as fluids with non-Newtonian rheology, multi-phase and multi-fluid flows (suspensions, lather, solid/fluid interaction with floating objects, etc), violent flows (breaking waves, dam-breaks, etc), fluids with thermal dependencies and phase transition or free-surface flows. Correctly modeling the behavior of such flows can be quite challenging, and has led to significant advances in the field of Computational Fluid Dynamics (CFD). Recently, the Smoothed Particle Hydrodynamics (SPH) method has emerged as a powerful alternative to more classic CFD methods (such as finite volumes or finite elements) in many fields, including oceanography, volcanology, structural engineering, nuclear physics and medicine. With SPH, the fluid is discretized by means of particles and thanks to the meshless, Lagrangian nature of the model, it easily allows the modeling and simulation of both simple and complex fluids, simplifying the treatment of aspects which can be challenging with more traditional methods: dynamic free surfaces, large deformations, phase transition, fluid/solid interaction and complex geometries. In addition, the most common SPH formulations are fully parallelizable, which favors implementation on high-performance parallel computing hardware, such as modern Graphics Processing Units (GPUs). We present here how GPUSPH, an implementation of the SPH method that runs on GPUs, can model a variety of complex fluids, highlighting the computational challenges that arise in its applications to problem of great interest in volcanology.
Highlights
The ability to accurately model the behavior of fluids under the most diverse conditions is extremely important in both scientific research and applied industry, and has led to the development of Computational Fluid Dynamics (CFD)
Many geophysical flows present characteristics, such as multiple fluids or phases, non-Newtonian or temperature-dependent rheology, violent or otherwise highly dynamic behavior, which are challenging to model with the classical approaches
We model the dynamics of fluids according to the being completely parallelizable, since the evolution of Navier-Stokes equations for continuity of mass and each particle at each time-step can be computed inde- forces balance: pendently from that of the others, which makes Smoothed Particle Hydrodynamics (SPH) quite suitable for implementation on massively parallel hardware, such as modern Graphics Processing U! nits [Hérault et al 2010]
Summary
The ability to accurately model the behavior of fluids under the most diverse conditions is extremely important in both scientific research and applied industry, and has led to the development of Computational Fluid Dynamics (CFD). Lagrangian, mesh-based approaches such as finite elements can overcome some of these issues, but their application to highly dynamic flows such as dambreaks is limited due to the possible fragmentation of the flow and the computationally expensive need for remeshing when the fluid undergoes large deformations These methods have been used to model and study geophysical flows under specific conditions, such as lava tubes [Filippucci and Dragoni 2013], channel flows [Costa and Macedonio 2005], or other simple geometries [Fernandez Nieto and Narbona-Reina 2016]. Many geophysical flows present characteristics, such as multiple fluids or phases, non-Newtonian or temperature-dependent rheology, violent or otherwise highly dynamic behavior, which are challenging to model with the classical approaches. In our presentation of! the method and its application to fluid dyna!mics w!e follow Liu and
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