1 / 33

Mode-Splitting for Highly Detail, Interactive Liquid Simulation

Mode-Splitting for Highly Detail, Interactive Liquid Simulation. H. Cords University of Rostock. Presenter: Truong Xuan Quang. Content. 0. Abstract Introduction 2. Related work 3. Our Approach 4. Implement and Result. Abstract.

viveka
Download Presentation

Mode-Splitting for Highly Detail, Interactive Liquid Simulation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Mode-Splitting for Highly Detail, Interactive Liquid Simulation H. Cords University of Rostock Presenter: Truong Xuan Quang

  2. Content • 0. Abstract • Introduction • 2. Related work • 3. Our Approach • 4. Implement and Result

  3. Abstract • A new technique for highly detailed interactive liquid simulation • Separated low-frequency (LF) and high-frequency (HF) LF: free surface wave, 2D wave equation HF: liquid follow, 3D Navier-Stock equation Rendering in 2.5 D • Simulation liquid follow according to gravity, ground, obstacles and interaction with impacts, moving impact, etc

  4. Introduction Real-time liquid simulation can be classified as follows: • Empirical (expert) surface simulation • Physically-based surface simulation (wave equation) • Physically-based volume simulation (Navier-Stokes equations )

  5. Introduction • The Goal : mode-splitting to increase quality of the simulate liquid. • Moving obstacles, rain, surface wave generation, etc…… • Splitting based: • Navier-Stockes based method: Fluid flow, movement of free surface • 2D wave equation: fast solve wave equation • Finally combines the advantages of both physically-based approaches • Limitation: not valid in splashing or breaking wave

  6. Related work • Simulation and rendering liquids and effected (e.g. [Carlson et al. 2004] [Hong and Kim 2005] [Guendelman et al. 2005] [Muller et al. 2005]). • The Navier-Stokes equations are usually solved with particle-based systems (e.g Smoothed Particle Hydrodynamics - SPH), [Adabala and Manohar 2002]. • In [Stam and Fiume 1995] the first real-time approach using SPH is presented. • Interactive simulation of fluids was introduced in [Stam 1999] • Execution on the GPU with reasonable frame rates [Harris-2005] • Solving the wave equation was presented [Yuksel et al. 2007] • And etc..

  7. Our Approach Goal for simulation: real-time and large scale • Lagrangian methods few particles • Liquid volume Small grid size (Eulerain) Propose model-slitting method to simulate highly detailed surface: described by 2D wave equation is solve by FDM and liquid flow by Navier-Stockes equations there is solve with the (SPH)

  8. Our Approach

  9. Our Approach • For visualization we use a height field-based rendering approach most liquid surface can be rendered appropriately as height fields. • However, complex liquid phenomena, such as breaking waves or splashes, cannot be visualized as height fields.

  10. Mode Splitting c : speed of light l :amplify frequency Nth mode Using oceanography the method is used to simulated high frequency waves isexternal gravity waves-included by tide and atmospheric pressure, water waves, free surface water. And low frequency waves Internal gravity wave included by wind and density gradients, vertical turbulences. Different algorithms are used, external and internal algorithms are solved separately with different time steps

  11. Mode Splitting • Moving external waves need to be solved at small time steps • The slow moving internal waves are more expensive to solve (due to complex turbulences), large time step can be used • We used the 2D equation for surface simulation and a 3D SPH-based Navier-Stokes equations solver for volume flow simulation

  12. Surface simulation The general wave equation describes the propagations of wave in time t and space x, liquid surface wave the 2D Wave equation can be used, describing the circular wave Propagation Laplace operator in 2D and c is the velocity at the which wave propagate across The wave equation can be solved with Eulerian finite difference approach

  13. Implicit different method α is constant, m>0 is integer and time step size k>0, with h=l/m for each i=0, 1…, m for each i=0, 1…, m

  14. Implicit different method

  15. 2 3 1 Implicit different method 1. Several radius wave propagations 2. Rain-Drop 3. A swimming object is moving

  16. Liquid simulation Navier-Stokes equations V is velocity filed Ρ the pressure field μ: viscosity f: external force Conservation of mass (continuity equation ) in rest position Incompressible liquids, density is constant Resulting in the mass conservation

  17. SPH for real-time simulation Simple and fast handling of boundary conditions as collisions Mass conservation is guaranteed (number of particles = const; mass of each particle = const) Nonlinear convective acceleration can be neglected

  18. SPH SPH (Smooth Particle Hydro-dynamics) is an simulation method for particle systems defined at discrete particle locations can be evaluated everywhere in the space. Continuous field quantities distributed in the local neighborhood according to the discrete particle positions and the smoothing kernels Wh(x). Scalar quantities A(x) can be estimated for n particles as :

  19. Pressure force External force Viscosity force neglected SPH Smoothing kernel for pressure and viscosity

  20. zi a(t0+Δt) v(t0+ Δt) xi(t0+ Δt) xi a(t0) v(t0) xi(t0) yi SPH The liquid volume is discredited by particles

  21. SPH

  22. Collisions Collisions of liquids particles with objects are using a force vector field surrounding collision objects Where d is the closet distance between object and particle nObjectis normal vector of the object at the points closet object Fcol: is acting on each particle being close to collision objects V: reflect velocity, friction coefficient

  23. Free surface Extraction • Generated height surface: number of neighbors potential Φ for n particles with position xi (i=1..n) is determined by the following spherical potential These particles can be detected according to their actual number of neighbors • Threshold (condition of the smoothness), to reduce unwanted surface ripples cause by the discrete sampling of the liquids

  24. Free surface Extraction (2/2) Depending kinetic energy n particles vi velocities mi mass (i=1..m) If Ekin exceeds a defined of threshold, no smoothing occurs Else bellow threshold, the number of smoothing steps is increased, until the Maximum number of smoothing step is reach

  25. be integer fraction Ntime of WE-TS N-S TS Simulation time-steps Surface simulation (wave equation) and volume simulation (SPH) should be synchronized Example of time step (TS) Synchronization, Ntime=3 WE is solved 3 times, while Navier-Stockes is solve once

  26. Combine surface and volume simulation • Final surface just depends on the different field resolution SPH generated surface Xsph x Ysph Wave equation surface size XWE x YWE

  27. Rendering (1/2) • Using cube map contain the environment for approximating the effects. • Surface variation (position and normal) calculating reflection and refraction vectors. • Reflection and refraction is described by Fresnel equation.

  28. Rendering (2/2) • Planar light map is generated via light ray tracing using Snell’s law • Other liquid can be also applied, simple liquid like: • milk, cola, oil. WE SPH

  29. 4.1 Implementation and Results • Using OpenGL 2.0 and shading language GLSL in C++, dual core PC 2.6 GHz AMD Athlon 64 CPU. • 2 GBs of RAM and graphics card ATIRadeon x 1900 GPU. Using Parallel implementation with one core simulation SPH and one core solving wave equation

  30. 4.1 Implementation and Results Performance of the technique mainly depend on the following parameter: Number of SPH particles XSPH . YSPH XWE . YWE Results of experiments show that SPH simulation account for 40-70% of the run time-less than 4000 particles. Disadvantage is impossible to visualize 3D liquid effects like: splashes, breaking waves, cause by 2.5D rendering approach (2D WE + 3D SPH+ rendering)=2.5D

  31. 4.1 Implementation and Results • Advantaged: • Volume interaction (moving glass of water, obstacles) • Surface interaction (rain, moving objects) • Automatic, natural and global flow • Object moving with the follow • Simulation pool or sea

  32. 4.2 Conclusion and future work • Simulation of the low frequency liquid flow and the high frequency free surface waves are separated • 2D WE and 3D fluid (SPH-method) presented realistic and highly detailed results Future works: • Simulation in real-time environments at high frame rates, better rendering approach. • GPU or PPU (Physic Processing Unit) for physical calculations. • Applied for larger liquid volume

  33. Thank for your attention

More Related