957 research outputs found
Conforming restricted Delaunay mesh generation for piecewise smooth complexes
A Frontal-Delaunay refinement algorithm for mesh generation in piecewise
smooth domains is described. Built using a restricted Delaunay framework, this
new algorithm combines a number of novel features, including: (i) an
unweighted, conforming restricted Delaunay representation for domains specified
as a (non-manifold) collection of piecewise smooth surface patches and curve
segments, (ii) a protection strategy for domains containing curve segments that
subtend sharply acute angles, and (iii) a new class of off-centre refinement
rules designed to achieve high-quality point-placement along embedded curve
features. Experimental comparisons show that the new Frontal-Delaunay algorithm
outperforms a classical (statically weighted) restricted Delaunay-refinement
technique for a number of three-dimensional benchmark problems.Comment: To appear at the 25th International Meshing Roundtabl
Gap Processing for Adaptive Maximal Poisson-Disk Sampling
In this paper, we study the generation of maximal Poisson-disk sets with
varying radii. First, we present a geometric analysis of gaps in such disk
sets. This analysis is the basis for maximal and adaptive sampling in Euclidean
space and on manifolds. Second, we propose efficient algorithms and data
structures to detect gaps and update gaps when disks are inserted, deleted,
moved, or have their radius changed. We build on the concepts of the regular
triangulation and the power diagram. Third, we will show how our analysis can
make a contribution to the state-of-the-art in surface remeshing.Comment: 16 pages. ACM Transactions on Graphics, 201
One machine, one minute, three billion tetrahedra
This paper presents a new scalable parallelization scheme to generate the 3D
Delaunay triangulation of a given set of points. Our first contribution is an
efficient serial implementation of the incremental Delaunay insertion
algorithm. A simple dedicated data structure, an efficient sorting of the
points and the optimization of the insertion algorithm have permitted to
accelerate reference implementations by a factor three. Our second contribution
is a multi-threaded version of the Delaunay kernel that is able to concurrently
insert vertices. Moore curve coordinates are used to partition the point set,
avoiding heavy synchronization overheads. Conflicts are managed by modifying
the partitions with a simple rescaling of the space-filling curve. The
performances of our implementation have been measured on three different
processors, an Intel core-i7, an Intel Xeon Phi and an AMD EPYC, on which we
have been able to compute 3 billion tetrahedra in 53 seconds. This corresponds
to a generation rate of over 55 million tetrahedra per second. We finally show
how this very efficient parallel Delaunay triangulation can be integrated in a
Delaunay refinement mesh generator which takes as input the triangulated
surface boundary of the volume to mesh
A Fast Algorithm for Well-Spaced Points and Approximate Delaunay Graphs
We present a new algorithm that produces a well-spaced superset of points
conforming to a given input set in any dimension with guaranteed optimal output
size. We also provide an approximate Delaunay graph on the output points. Our
algorithm runs in expected time , where is the
input size, is the output point set size, and is the ambient dimension.
The constants only depend on the desired element quality bounds.
To gain this new efficiency, the algorithm approximately maintains the
Voronoi diagram of the current set of points by storing a superset of the
Delaunay neighbors of each point. By retaining quality of the Voronoi diagram
and avoiding the storage of the full Voronoi diagram, a simple exponential
dependence on is obtained in the running time. Thus, if one only wants the
approximate neighbors structure of a refined Delaunay mesh conforming to a set
of input points, the algorithm will return a size graph in
expected time. If is superlinear in , then we
can produce a hierarchically well-spaced superset of size in
expected time.Comment: Full versio
Unstructured mesh algorithms for aerodynamic calculations
The use of unstructured mesh techniques for solving complex aerodynamic flows is discussed. The principle advantages of unstructured mesh strategies, as they relate to complex geometries, adaptive meshing capabilities, and parallel processing are emphasized. The various aspects required for the efficient and accurate solution of aerodynamic flows are addressed. These include mesh generation, mesh adaptivity, solution algorithms, convergence acceleration, and turbulence modeling. Computations of viscous turbulent two-dimensional flows and inviscid three-dimensional flows about complex configurations are demonstrated. Remaining obstacles and directions for future research are also outlined
Integration of finite element modeling with solid modeling through a dynamic interface
Finite element modeling is dominated by geometric modeling type operations. Therefore, an effective interface to geometric modeling requires access to both the model and the modeling functionality used to create it. The use of a dynamic interface that addresses these needs through the use of boundary data structures and geometric operators is discussed
ImMesh: An Immediate LiDAR Localization and Meshing Framework
In this paper, we propose a novel LiDAR(-inertial) odometry and mapping
framework to achieve the goal of simultaneous localization and meshing in
real-time. This proposed framework termed ImMesh comprises four tightly-coupled
modules: receiver, localization, meshing, and broadcaster. The localization
module utilizes the prepossessed sensor data from the receiver, estimates the
sensor pose online by registering LiDAR scans to maps, and dynamically grows
the map. Then, our meshing module takes the registered LiDAR scan for
incrementally reconstructing the triangle mesh on the fly. Finally, the
real-time odometry, map, and mesh are published via our broadcaster. The key
contribution of this work is the meshing module, which represents a scene by an
efficient hierarchical voxels structure, performs fast finding of voxels
observed by new scans, and reconstructs triangle facets in each voxel in an
incremental manner. This voxel-wise meshing operation is delicately designed
for the purpose of efficiency; it first performs a dimension reduction by
projecting 3D points to a 2D local plane contained in the voxel, and then
executes the meshing operation with pull, commit and push steps for incremental
reconstruction of triangle facets. To the best of our knowledge, this is the
first work in literature that can reconstruct online the triangle mesh of
large-scale scenes, just relying on a standard CPU without GPU acceleration. To
share our findings and make contributions to the community, we make our code
publicly available on our GitHub: https://github.com/hku-mars/ImMesh
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