20,433 research outputs found
A fast framework construction and visualization method for particle-based fluid
© 2017, The Author(s). Fast and vivid fluid simulation and visualization is a challenge topic of study in recent years. Particle-based simulation method has been widely used in the art animation modeling and multimedia field. However, the requirements of huge numerical calculation and high quality of visualization usually result in a poor computing efficiency. In this work, in order to improve those issues, we present a fast framework for 3D fluid fast constructing and visualization which parallelizes the fluid algorithm based on the GPU computing framework and designs a direct surface visualization method for particle-based fluid data such as WCSPH, IISPH, and PCISPH. Considering on conventional polygonization or adaptive mesh methods may incur high computing costs and detail losses, an improved particle-based method is provided for real-time fluid surface rendering with the screen-space technology and the utilities of the modern graphics hardware to achieve the high performance rendering; meanwhile, it effectively protects fluid details. Furthermore, to realize the fast construction of scenes, an optimized design of parallel framework and interface is also discussed in our paper. Our method is convenient to enforce, and the results demonstrate a significant improvement in the performance and efficiency by being compared with several examples
A Multi-Code Analysis Toolkit for Astrophysical Simulation Data
The analysis of complex multiphysics astrophysical simulations presents a
unique and rapidly growing set of challenges: reproducibility, parallelization,
and vast increases in data size and complexity chief among them. In order to
meet these challenges, and in order to open up new avenues for collaboration
between users of multiple simulation platforms, we present yt (available at
http://yt.enzotools.org/), an open source, community-developed astrophysical
analysis and visualization toolkit. Analysis and visualization with yt are
oriented around physically relevant quantities rather than quantities native to
astrophysical simulation codes. While originally designed for handling Enzo's
structure adaptive mesh refinement (AMR) data, yt has been extended to work
with several different simulation methods and simulation codes including Orion,
RAMSES, and FLASH. We report on its methods for reading, handling, and
visualizing data, including projections, multivariate volume rendering,
multi-dimensional histograms, halo finding, light cone generation and
topologically-connected isocontour identification. Furthermore, we discuss the
underlying algorithms yt uses for processing and visualizing data, and its
mechanisms for parallelization of analysis tasks.Comment: 18 pages, 6 figures, emulateapj format. Resubmitted to Astrophysical
Journal Supplement Series with revisions from referee. yt can be found at
http://yt.enzotools.org
Simultaneous Coherent Structure Coloring facilitates interpretable clustering of scientific data by amplifying dissimilarity
The clustering of data into physically meaningful subsets often requires
assumptions regarding the number, size, or shape of the subgroups. Here, we
present a new method, simultaneous coherent structure coloring (sCSC), which
accomplishes the task of unsupervised clustering without a priori guidance
regarding the underlying structure of the data. sCSC performs a sequence of
binary splittings on the dataset such that the most dissimilar data points are
required to be in separate clusters. To achieve this, we obtain a set of
orthogonal coordinates along which dissimilarity in the dataset is maximized
from a generalized eigenvalue problem based on the pairwise dissimilarity
between the data points to be clustered. This sequence of bifurcations produces
a binary tree representation of the system, from which the number of clusters
in the data and their interrelationships naturally emerge. To illustrate the
effectiveness of the method in the absence of a priori assumptions, we apply it
to three exemplary problems in fluid dynamics. Then, we illustrate its capacity
for interpretability using a high-dimensional protein folding simulation
dataset. While we restrict our examples to dynamical physical systems in this
work, we anticipate straightforward translation to other fields where existing
analysis tools require ad hoc assumptions on the data structure, lack the
interpretability of the present method, or in which the underlying processes
are less accessible, such as genomics and neuroscience
A Vortex Method for Bi-phasic Fluids Interacting with Rigid Bodies
We present an accurate Lagrangian method based on vortex particles,
level-sets, and immersed boundary methods, for animating the interplay between
two fluids and rigid solids. We show that a vortex method is a good choice for
simulating bi-phase flow, such as liquid and gas, with a good level of realism.
Vortex particles are localized at the interfaces between the two fluids and
within the regions of high turbulence. We gain local precision and efficiency
from the stable advection permitted by the vorticity formulation. Moreover, our
numerical method straightforwardly solves the two-way coupling problem between
the fluids and animated rigid solids. This new approach is validated through
numerical comparisons with reference experiments from the computational fluid
community. We also show that the visually appealing results obtained in the CG
community can be reproduced with increased efficiency and an easier
implementation
Diffusion-Based Coarse Graining in Hybrid Continuum-Discrete Solvers: Applications in CFD-DEM
In this work, a coarse-graining method previously proposed by the authors in
a companion paper based on solving diffusion equations is applied to CFD-DEM
simulations, where coarse graining is used to obtain solid volume fraction,
particle phase velocity, and fluid-particle interaction forces. By examining
the conservation requirements, the variables to solve diffusion equations for
in CFD-DEM simulations are identified. The algorithm is then implemented into a
CFD-DEM solver based on OpenFOAM and LAMMPS, the former being a
general-purpose, three-dimensional CFD solver based on unstructured meshes.
Numerical simulations are performed for a fluidized bed by using the CFD-DEM
solver with the diffusion-based coarse-graining algorithm. Converged results
are obtained on successively refined meshes, even for meshes with cell sizes
comparable to or smaller than the particle diameter. This is a critical
advantage of the proposed method over many existing coarse-graining methods,
and would be particularly valuable when small cells are required in part of the
CFD mesh to resolve certain flow features such as boundary layers in wall
bounded flows and shear layers in jets and wakes. Moreover, we demonstrate that
the overhead computational costs incurred by the proposed coarse-graining
procedure are a small portion of the total costs in typical CFD-DEM simulations
as long as the number of particles per cell is reasonably large, although
admittedly the computational overhead of the coarse graining often exceeds that
of the CFD solver. Other advantages of the present algorithm include more
robust and physically realistic results, flexibility and easy implementation in
almost any CFD solvers, and clear physical interpretation of the computational
parameter needed in the algorithm. In summary, the diffusion-based method is a
theoretically elegant and practically viable option for CFD-DEM simulations
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