NDLI: A novel, integrated smoke simulation design method supporting local projection and guiding control over adaptive grids

Content Provider	Springer Nature Link
Author	Zuo, Qing Qi, Yue Qin, Hong
Copyright Year	2013
Abstract	High-fidelity smoke simulation in a large-scale complex environment is extremely time-consuming due to the expensive computational cost of using highly dense regular grids. There have been quite a few improved algorithms/techniques aiming to enhance the simulation’s visual effects and reduce the time consumption during the last two decades. However, most of the state-of-the-art methods will encounter difficulties of not being able to model fine turbulent details during simulation or losing high-frequency shape details at the fine scale when simulated smoke interacting with nearby obstacles. One straightforward solution is to continue to refine spatial resolution at the expense of increased time complexity. This paper, however, advocates an improved strategy for smoke simulation design over adaptive grids, while simultaneously enabling the functionalities of local projection and guiding control. First, our new integrated method supports adaptive grid projection that can significantly reduce the computational cost during the velocity projection phase. During smoke simulation design, the use of adaptive grids flexibly accommodates finer cells near obstacles with fine details, and coarser cells anywhere else, as a result, fine-scale object features can be faithfully retained without the need of global grid refinement. Second, our integrated solution over adaptive grids can tightly couple guiding control with local projection, which is capable of handling tiny obstacles that are impossible to model with global coarse grids alone during simulation preview. Comprehensive experiments have shown that our integrated method has the advantage of generating turbulent phenomena when interacting with small-scale features of obstacles, and at the same time offering the preview mechanism for efficient large-scale smoke simulation design.
Starting Page	883
Ending Page	892
Page Count	10
File Format	PDF
ISSN	01782789
Journal	The Visual Computer
Volume Number	29
Issue Number	9
e-ISSN	14322315
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2013-06-05
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Smoke simulation Guiding control Adaptive grid Computer Graphics Computer Science Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Computer Vision and Pattern Recognition Software

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