Lattice-based flow field modeling

Wei, Xiaoming; Zhao, Ye; Fan, Zhe; Li, W.; Qiu, Feng; Yoakum-Stover, Suzanne; Kaufman, Arie

doi:10.1109/tvcg.2004.48

Cited by 59 publications

(22 citation statements)

References 35 publications

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“…This includes simple geometries where the boundary is aligned with the grid, complex boundaries such as curves and porous media, and moving boundaries representing dynamic objects. The exchange of momentum at the boundary between a fluid and a free object immersed in it can further be used to deform or move the object [Wei et al 2004].…”

Section: Appendix: Lattice Boltzmann Methodsmentioning

confidence: 99%

“…In computer graphics, LBM has been used in simulating a variety of fluid phenomena, such as ink dispersion [Chu and Tai 2005], free-surface fluid [Thurey and Rude 2004], floating objects [Wei et al 2004], flows on the surface , and heat shimmering and mirage [Zhao et al 2007]. In physics, the LBM can handle adaptive mesh refinement (AMR) with locally embedded grids [Dupuis and Chopard 2003;Filippova and Hänel 1998].…”

Section: Previous Workmentioning

confidence: 99%

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Flow simulation with locally-refined LBM

Zhao

Qiu

Fan

et al. 2007

Proceedings of the 2007 Symposium on Interactive 3D Graphics and Games

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We simulate 3D fluid flow by a locally-refined lattice Boltzmann method (LBM) on graphics hardware. A low resolution LBM simulation running on a coarse grid models global flow behavior of the entire domain with low consumption of computational resources. For regions of interest where small visual details are desired, LBM simulations are performed on fine grids, which are separate grids superposed on the coarse one. The flow properties on boundaries of the fine grids are determined by the global simulation on the coarse grid. Thus, the locally refined fine-grid simulations follow the global fluid behavior, and model the desired small-scale and turbulent flow motion with their denser numerical discretization. A fine grid can be initiated and terminated at any time while the global simulation is running. It can also move inside the domain with a moving object to capture small-scale vortices caused by the object. Besides the performance improvement due to the adaptive simulation, the locally-refined LBM is suitable for acceleration on contemporary graphics hardware (GPU), since it involves only local and linear computations. Therefore, our approach achieves fast and adaptive 3D flow simulation for computer games and other interactive applications.

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Section: Appendix: Lattice Boltzmann Methodsmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Flow simulation with locally-refined LBM

Zhao

Qiu

Fan

et al. 2007

Proceedings of the 2007 Symposium on Interactive 3D Graphics and Games

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“…Considerable advancements in physically-based simulation have been made recently due to their application in games and graphics [22]. In particular, fluid simulations on GPUs have gained significant momentum [23,24,25,26]. Recently, Phillips et al [27] used a cluster of GPUs to accelerate solver for 2D compressible Euler equation and MBFLO solvers.…”

Section: Related Workmentioning

confidence: 99%

Using GPUs for Realtime Prediction of Optical Forces on Microsphere Ensembles

Bista

Chowdhury

Gupta

et al. 2013

Journal of Computing and Information Science in Engineering

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Laser beams can be used to create optical traps that can hold and transport small particles. Optical trapping has been used in a number of applications ranging from prototyping at the microscale to biological cell manipulation. Successfully using optical tweezers requires predicting optical forces on the particle being trapped and transported. Reasonably accurate theory and computational models exist for predicting optical forces on a single particle in the close vicinity of a Gaussian laser beam. However, in practice the workspace includes multiple particles that are manipulated using individual optical traps. It has been experimentally shown that the presence of a particle can cast a shadow on a nearby particle and hence affect the optical forces acting on it. Computing optical forces in the presence of shadows in real-time is not feasible on CPUs. In this paper, we introduce a ray-tracing-based application optimized for GPUs to calculate forces exerted by the laser beams on microparticle ensembles in an optical tweezers system. When evaluating the force exerted by a laser beam on 32 interacting particles, our GPU-based approach is able to get a 66-fold speed up compared to a single core CPU implementation of traditional Ashkin's approach and a 10-fold speedup over the single core CPU-based implementation of our approach.

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“…An index function similar to distance field was combined with the LBM to track the interface in multiphase flow dynamics [11]. In computer graphics and visualization, the LBM was used to visually simulate fluid flow phenomena with complex boundary conditions, such as wind flow and fire [37,27], ink dispersion [4], free surface liquids [35,36], floating objects [38], melting and flowing [45], fluid control [34], heat shimmering and mirage [44]. A level-of-detail scheme was adopted to simulate 3D fluid dynamics based on the locally-refined LBM on multiple grids, which improves the simulation accuracy and performance.…”

Section: Related Workmentioning

confidence: 99%

GPU-accelerated surface denoising and morphing with lattice Boltzmann scheme

Zhao

2008

2008 IEEE International Conference on Shape Modeling and Applications

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In this paper, we introduce a parallel numerical scheme, the lattice Boltzmann method, to shape modeling applications. The motivation of using this originally-designed fluid dynamics solver in surface modeling is its simplicity, locality, parallelism from the cellular-automata-originated updating rules, which can directly be mapped onto modern graphics hardware. A surface is implicitly represented by the signed distance field. The distances are then used in a modified LBM scheme as its computing primitive, instead of the densities in traditional LBM. The scheme can simulate curvature motions to smooth the surface with a diffusion process. Furthermore, an initial value level set method can be implemented for surface morphing. The distance difference between a morphing surface and a target surface defines the speed function of the evolving level sets, and is used as the driving force in the LBM. Our GPUaccelerated LBM algorithm has achieved outstanding performance for the denoising and morphing examples. It has the great potential to be further applied as a general GPU computing framework to many other solid and shape modeling applications.

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Lattice-based flow field modeling

Cited by 59 publications

References 35 publications

Flow simulation with locally-refined LBM

Flow simulation with locally-refined LBM

Using GPUs for Realtime Prediction of Optical Forces on Microsphere Ensembles

GPU-accelerated surface denoising and morphing with lattice Boltzmann scheme

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