Physics of Fluids - Publications

A comparative evaluation of three volume rendering libraries for the visualization of sheared thermal convection

arΧiv
Parallel Computing 88, 102543 (2019)

Authors

	Jean Michel Favre
	Alexander Blass

BibTeΧ

@article{FAVRE2019102543,
title = "A comparative evaluation of three volume rendering libraries for the visualization of sheared thermal convection",
journal = "Parallel Computing",
volume = "88",
pages = "102543",
year = "2019",
issn = "0167-8191",
doi = "https://doi.org/10.1016/j.parco.2019.07.003",
url = "http://www.sciencedirect.com/science/article/pii/S0167819119301280",
author = "Jean M. Favre and Alexander Blass",
keywords = "Scientific visualization, High performance computing, Navier-Stokes solver, Direct numerical simulation, Computational fluid dynamics",
abstract = "Oceans play a big role in the nature of our planet, about 70% of our earth is covered by water [1]. Strong currents are transporting warm water around the world making life possible, and allowing us to harvest its power producing energy. Yet, oceans also carry a much more deadly side. Floods and tsunamis can easily annihilate whole cities and destroy life in seconds. The earth’s climate system is also very much linked to the currents in the ocean due to its large coverage of the earth’s surface, thus, gaining scientific insights into the mechanisms and effects through simulations is of high importance. Deep ocean currents can be simulated by means of wall-bounded turbulent flow simulations. To support these very large scale numerical simulations and enable the scientists to interpret their output, we deploy an interactive visualization framework to study sheared thermal convection. The visualizations are based on volume rendering of the temperature field. To address the needs of supercomputer users with different hardware and software resources, we evaluate different volume rendering implementations supported in the ParaView [2] environment: two GPU-based solutions with Kitware’s native volume mapper or NVIDIA’s IndeX library, and a CPU-only Intel OSPRay-based implementation."
}