Temporal Blending for Adaptive SPH

Orthmann, Jens; Kolb, Andreas

doi:10.1111/j.1467-8659.2012.03186.x

Cited by 44 publications

(22 citation statements)

References 30 publications

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“…Note, with increasing resolution, the surface area converges towards the ground truth area of the underlying sine function. However, we believe that in the future the surface resolution can be easily decoupled from the bulk resolution by incorporating an adaptive particle sampling as proposed by Orthmann and Kolb [2012] or Solenthaler and Gross [2011]. Moreover, the effect simulation would benefit from more complex reaction kinetics, which account for temperature dependencies or non-linear reactions like explosions and can easily be enriched with other effects like foam dynamics.…”

Section: Resultsmentioning

confidence: 97%

“…Beside mass convection, a diffusive flux is incorporated to simulate thermodynamics [Müller et al 2005] and transport of sediments [Kristof et al 2009] or soluble substances [Cleary and Monaghan 1999]. Compact smoothing kernels [Müller et al 2003], an adaptive sampling [Adams et al 2007;Solenthaler and Gross 2011;Orthmann and Kolb 2012], adaptive time-steps [Ihmsen et al 2010] and parallelization [Kolb and Cuntz 2005;Goswami et al 2010;Ihmsen et al 2011b] are essential in order to reduce simulation times. A rigid-fluid coupling is simulated using distance fields [Harada et al 2007], via direct forcing [Becker et al 2009], or by considering relative contributions of inhomogeneously sampled rigid particles [Akinci et al 2012b].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Consistent surface model for SPH-based fluid transport

Orthmann

Hochstetter

Bader

et al. 2013

Proceedings of the 12th ACM SIGGRAPH/Eurographics Symposium on Computer Animation

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a) tsim = 3 s (b) tsim = 16 s (c) tsim = 16 s (detergent in blue) Figure 1: The pan's surface is cleansed from grease (orange) due to detergent concentration (blue in 1(c)) on the fluid's surface. AbstractSurface effects play an essential role in fluid simulations. A vast number of dynamics including wetting of surfaces, cleansing, and foam dynamics are based on surface-surface and surface-bulk interactions, which in turn rely on a robust surface computation. In this paper we introduce a conservative Lagrangian formulation of surface effects based upon incompressible smoothed particle hydrodynamics (SPH). The key concept of our approach is to realize an implicit definition of the fluid's (free) surface by assigning each particle a value estimating its surface area. Based on this consistent surface representation, a conservative coupling of bulk and surface is achieved. We demonstrate the applicability and robustness of our approach for several types of surface-relevant effects including adsorption, diffusion and reaction kinetics.

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Section: Resultsmentioning

confidence: 97%

Section: Related Workmentioning

confidence: 99%

Consistent surface model for SPH-based fluid transport

Orthmann

Hochstetter

Bader

et al. 2013

Proceedings of the 12th ACM SIGGRAPH/Eurographics Symposium on Computer Animation

Self Cite

View full text Add to dashboard Cite

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“…Firstly, the support radius of control particles is currently unified. Using the techniques similar to adaptive SPH [Adams et al 2007] [Hong et al 2008] [Orthmann and Kolb 2012], setting different length of support radius according to the density or motion of the control particles will decrease the number of control particles to some extent. Secondly, the current spring constraint in our method has a limit that the control particles should keep a consistent index during the simulation.…”

Section: Discussionmentioning

confidence: 99%

Position-based fluid control

Zhang

Yang

et al. 2015

Proceedings of the 19th Symposium on Interactive 3D Graphics and Games

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Figure 1: An animated dancer made of fluid using our position-based fluid control method. AbstractWe present a novel fluid control method that is capable of driving particle-based fluid simulation to match a rapidly changing target while keeping natural fluid-like motion. To achieve the desired behavior, we first generate control particles by sampling the target shape and then apply a non-linear constraint to each control particle, with its neighboring fluid particles keeping a constant fluid density within its influence region. This density constraint is highly in line with the incompressible nature of the fluid, which can drive the fluid to match the target shape in a natural way. In addition, to match a fast moving or deforming target, we add an adaptive spring for each fluid particle in the control region, connecting with its nearest control particle. The spring constraint takes effect only when the fluid particle is far from its corresponding control particle to avoid introducing artificial viscosity. Therefore, the fluid particles are well controlled even if the target shape changes rapidly. Furthermore, we integrate a velocity constraint to adjust the stiffness of the controlled fluid. All these three constraints are solved under position-based framework which enables our simulation fast, robust and well-suitable for interactive applications. We demonstrate the efficiency and effectiveness of our method in various scenarios in real time.

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“…The important observation here is that the SPH calculations are easy to parallelize. As a result many researchers have used parallel SPH formulations for fluids [18], [13], in general, but the concepts remain same when it comes to deformable solids. Corotated formulation for SPH introduced by Solenthaler et al [23] have given stable results for various material types.…”

Section: Handling Deformationmentioning

confidence: 98%

Particle Coding for Meshfree Cutting of Deformable Assets

Shrivastava

Das

2014

Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing

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In this paper we propose a novel algorithm for cutting deformable (soft) assets, modeled using the meshfree method of Smoothed Particle Hydrodynamics (SPH). The key idea of the algorithm is to label all particles during the virtual cut operation to obtain particle codes. Since the traditional SPH formulations ignore particle separation due to cuts, we had to account for the change in topology due to virtual cuts in the SPH formulation. Virtual cut causes disruption in internal forces between separated particles. To avoid separated particles (i.e., particles belonging to different regions) affecting each other's dynamics, the generated particle codes are used for filtering the neighbours before SPH dynamics are computed. Assignment of particle codes eliminates the need for an external grid like structure for detecting newly generated cut surfaces. We exploit the region information extracted from the particle codes to obtain a color field for surface generation. We show that our algorithm can easily be integrated with existing SPH techniques. Our proposed method generates minimum overhead in scenarios where multiple cutting operations are performed on a deformable asset. Particle coding is applied across all particles in parallel and is hence computationally efficient when implemented on a GPU.

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Temporal Blending for Adaptive SPH

Cited by 44 publications

References 30 publications

Consistent surface model for SPH-based fluid transport

Consistent surface model for SPH-based fluid transport

Position-based fluid control

Particle Coding for Meshfree Cutting of Deformable Assets

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