Algebraic Mesh Quality Metrics
SIAM Journal on Scientific Computing
Streaming computation of Delaunay triangulations
ACM SIGGRAPH 2006 Papers
Streaming compression of tetrahedral volume meshes
GI '06 Proceedings of Graphics Interface 2006
Streaming Simplification of Tetrahedral Meshes
IEEE Transactions on Visualization and Computer Graphics
Streaming compression of triangle meshes
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
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Improving the quality of tetrahedral meshes is an important operation in many scientific computing applications. Meshes with badly shaped elements impact both the accuracy and convergence of scientific applications. State-of-the-art mesh improvement techniques rely on sophisticated numerical optimization methods such as feasible Newton or conjugate gradient. Unfortunately, these methods cannot be practically applied to very large meshes due to their global nature. Our contribution in this paper is to describe a streaming framework for tetrahedral mesh optimization. This framework enables the optimization of meshes an order of magnitude larger than previously feasible, effectively optimizing meshes too large to fit in memory. Our results show that streaming is typically faster than global optimization and results in comparable mesh quality. This leads us to conclude that streaming extends mesh optimization to a new class of mesh sizes without compromising the quality of the optimized mesh.