R EAL TIME SIMULATION OF A TORNADO Shiguang Liu, Zhangye Wang, Zheng Gong, Lei Huang, and Qunsheng Peng.

Slides:



Advertisements
Similar presentations
Simulation of Fluids using the Navier-Stokes Equations Kartik Ramakrishnan.
Advertisements

Matthias Müller, Barbara Solenthaler, Richard Keiser, Markus Gross Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2005),
Basic Governing Differential Equations
Mode-Splitting for Highly Detail, Interactive Liquid Simulation H. Cords University of Rostock Presenter: Truong Xuan Quang.
1 Modeling Highly- Deformable Liquid Chih-Wei Chiu Computer Graphics and Geometry Modeling Laboratory National Chiao Tung University June 25, 2002 Advisors:
Transport phenomena in chemical processes part III Michał Araszkiewicz PhD.
The Art of Comparing Force Strengths… P M V Subbarao Professor Mechanical Engineering Department I I T Delhi Diagnosis of NS Equations.
II. Properties of Fluids. Contents 1. Definition of Fluids 2. Continuum Hypothesis 3. Density and Compressibility 4. Viscosity 5. Surface Tension 6. Vaporization.
Results It was found that variations in wettability disturb the flow of adjacent liquid (Fig. 3). Our results suggest that for a given liquid the normal.
More Accurate Pressure Solves. Solid Boundaries  Voxelized version works great if solids aligned with grid  If not: though the error in geometry is.
1Notes  Textbook: matchmove 6.7.2, B.9. 2 Match Move  For combining CG effects with real footage, need to match synthetic camera to real camera: “matchmove”
William Moss Advanced Image Synthesis, Fall 2008.
P HYSICALLY BASED ANIMATION OF SANDSTORM Shiguang Liu, Zhangye Wang, Zheng Gong, Lei Huang, and Qunsheng Peng (presented by Kam,
C ROWD P ATCHES : P OPULATING L ARGE - S CALE V IRTUAL E NVIRONMENTS FOR R EAL -T IME A PPLICATIONS Barbara Yersin, Jonathan Maïm, Julien Pettré, Daniel.
Peyman Mostaghimi, Martin Blunt, Branko Bijeljic 11 th January 2010, Pore-scale project meeting Direct Numerical Simulation of Transport Phenomena on Pore-space.
Experimental Thermo and Fluid Mechanics Lab. 4. Fluid Kinematics 4.1. Velocity Field 4.2. Continuity Equation.
Basic Governing Differential Equations
University of North Carolina - Chapel Hill Fluid & Rigid Body Interaction Comp Physical Modeling Craig Bennetts April 25, 2006 Comp Physical.
Combined Lagrangian-Eulerian Approach for Accurate Advection Toshiya HACHISUKA The University of Tokyo Introduction Grid-based fluid.
Fluid Mechanics Wrap Up CEE 331 June 27, 2015 CEE 331 June 27, 2015 
Modeling Fluid Phenomena -Vinay Bondhugula (25 th & 27 th April 2006)
ABSTRACT Many new devices and applications are being created that involve transporting droplets from one place to another. A common method of achieving.
Adaptive Cloud Simulation Using Position Based Fluids
Monroe L. Weber-Shirk S chool of Civil and Environmental Engineering Basic Governing Differential Equations CEE 331 July 14, 2015 CEE 331 July 14, 2015.
Fluid mechanics 3.1 – key points
Modelling Realistic Water & Fire Sérgio Leal Socrates/Erasmus student at: AK Computer Graphics Institute for Computer Graphics and Vision Technical University.
A Simple, Efficient Method for Realistic Animation of Clouds
Modeling, Simulating and Rendering Fluids Thanks to Ron Fediw et al, Jos Stam, Henrik Jensen, Ryan.
Fluid Simulation for Computer Animation Greg Turk College of Computing and GVU Center Georgia Institute of Technology.
Flow and Thermal Considerations
Paul Drosinis UBC Phys 420. Introduction Short history on fluid dynamics Why bother studying fluid flow? Difference between Newtonian and Non-Newtonian.
Blood effects for Flinders Sinus Surgery Simulator
Fluid Animation CSE 3541 Matt Boggus. Procedural approximations – Heightfield fluids Mathematical background – Navier-Stokes equation Computational models.
Modelling and Simulation Dynamics. Dynamics Dynamics is a branch of physics that describes how objects move. Dynamic animation uses rules of physics to.
Modelling of the particle suspension in turbulent pipe flow
Animation of Fluids.
Cloud Kwang Hee Ko September, 27, 2012 This material has been prepared by Y. W. Seo.
COMPUTATIONAL FLUID DYNAMICS IN REAL-TIME An Introduction to Simulation and Animation of Liquids and Gases.
A Fast Simulation Method Using Overlapping Grids for Interactions between Smoke and Rigid Objects Yoshinori Dobashi (Hokkaido University) Tsuyoshi Yamamoto.
Smoothed Particle Hydrodynamics (SPH) Fluid dynamics The fluid is represented by a particle system Some particle properties are determined by taking an.
Let’s play snooker!. Overview Introduction to snooker UML diagram Physics Simulation techniques Result Conclusion Further research.
Position Based Multi- Fluids Tao Yang 2014/10/24.
A Unified Lagrangian Approach to Solid-Fluid Animation Richard Keiser, Bart Adams, Dominique Gasser, Paolo Bazzi, Philip Dutré, Markus Gross.
GPU-Accelerated Surface Denoising and Morphing with LBM Scheme Ye Zhao Kent State University, Ohio.
CHAPTER 1 INTRODUCTION.  At the end of this chapter, you should be able to: 1. Understand the basic concepts of fluid mechanics and recognize the various.
Detail-Preserving Fluid Control N. Th ű rey R. Keiser M. Pauly U. R ű de SCA 2006.
Introduction: Lattice Boltzmann Method for Non-fluid Applications Ye Zhao.
Point Sprites Course Information CVG: Programming 4 My Name: Mark Walsh Website: Recommended.
FlowFixer: Using BFECC for Fluid Simulation ByungMoon Kim Yingjie Liu Ignacio Llamas Jarek Rossignac Georgia Institute of Technology.
ME 101: Fluids Engineering Chapter 6 ME Two Areas for Mechanical Engineers Fluid Statics –Deals with stationary objects Ships, Tanks, Dams –Common.
Gas-kineitc MHD Numerical Scheme and Its Applications to Solar Magneto-convection Tian Chunlin Beijing 2010.Dec.3.
Conservation of Salt: Conservation of Heat: Equation of State: Conservation of Mass or Continuity: Equations that allow a quantitative look at the OCEAN.
Perpetual Visualization of Particle Motion and Fluid Flow Presented by Tsui Mei Chang.
© Fox, Pritchard, & McDonald Introduction to Fluid Mechanics Chapter 5 Introduction to Differential Analysis of Fluid Motion.
CE 1501 Flow Over Immersed Bodies Reading: Munson, et al., Chapter 9.
Smoothed Particle Hydrodynamics Matthew Zhu CSCI 5551 — Fall 2015.
Particles and their home in Geometry Shaders Paul Taylor 2010.
Efficient Simulation of Large Bodies of Water by Coupling Two and Three Dimensional Techniques SIGGRAPH 2006 Geoffrey Irving Eran Guendelman Frank Losasso.
CSE 872 Dr. Charles B. Owen Advanced Computer Graphics1 Water Computational Fluid Dynamics Volumes Lagrangian vs. Eulerian modelling Navier-Stokes equations.
SIGGRAPH 2005 신 승 호 신 승 호. Water Drops on Surfaces Huamin Wang Peter J. Mucha Greg Turk Georgia Institute of Technology.
A Massively Parallel Incompressible Smoothed Particle Hydrodynamics Simulator for Oilfield Applications Paul Dickenson 1,2, William N Dawes 1 1 CFD Laboratory,
Fluid Animation CSE 3541 By: Matt Boggus.
International Institute of Information Technology, Hyderabad
Computer Animation Ying Zhu Georgia State University
Computer Graphics Imaging Ying Zhu Georgia State University
Iterative Optimization
Fluid properties 1.
Computer Graphics Lecture 15.
12. Navier-Stokes Applications
Introduction to Fluid Mechanics
Presentation transcript:

R EAL TIME SIMULATION OF A TORNADO Shiguang Liu, Zhangye Wang, Zheng Gong, Lei Huang, and Qunsheng Peng

A BSTRACT simulating a tornado scene Based on Reynold-average Navier-Stokes equations. The dust particle flow is modeled by non-viscosity Navier–Stokes equations Multi-Fluid Solver is designed and implemented on GPU. Efficient method is proposed to simulate the tornado’s interaction with surrounding large objects.

I NTRODUCTION RATFM is proposed to simulate the chaos appearance of tornados more realistically than previous methods A novel two-fluid system solver is designed to achieve real time simulation To our knowledge, it is the first attempt to simulate damage from a tornado on surrounding objects Our system is easy to implement. By inputting different initial parameters, different tornado scenes can be produced automatically

R ELATED W ORK simulating natural phenomena smoke,water & fire semi-Lagrangian method Mizuno volcanic clouds consist of two fluids Müller et al. smoothed particle hydrodynamics Losasso et al. particle level set method simulate the interactions among multiple liquids Zhu et al. two-fluid lattice Boltzmann model

R ELATED W ORK Modeling the motion of dust particles contact force, normal force, and shear force Ding et al. propose an approach for tornado simulation To use many particles (not real time)  Our  TFM method  Real-time  interaction with large objects

R EYNOLD - AVERAGE N AVIER –S TOKES EQUATIONS

Interaction force Between air flow and dust particle flow plays an important part in modeling a tornado

Reynolds shear stress

R EYNOLD - AVERAGE TWO - FLUID MODEL dust particle flow model non-viscosity, incompressible fluid

B OUNDARY CONDITIONS

TORNADO ’ S CONDITIONS horizontal velocity field : rotating vertical velocity field : uplifting

M ODELING CONTRAST BETWEEN RATFM AND TFM ( RESULTS ) RATFM TFM

T HE TORNADO ’ S INTERACTION WITH LARGE OBJECTS Tonado 에 의해 부서지는 object 를 시뮬레이션 Object 는 voxel 에 연결 되어 있음 Voxcel 이 큰 압력을 받으면 연결된 object 부분을 부 숨

T HE TORNADO ’ S INTERACTION WITH LARGE OBJECTS Object 가 받는 힘 Torque

T HE TORNADO ’ S INTERACTION WITH LARGE OBJECTS

T HE TORNADO ’ S INTERACTION WITH LARGE OBJECTS ( RESULTS )

T HE TORNADO ’ S INTERACTION WITH LARGE OBJECTS ( RESULTS )

T HE TORNADO ’ S INTERACTION WITH LARGE OBJECTS ( RESULTS )

M ULTI -F LUID S OLVER ON GPU Our model describes a multiple fluid system Air flow particle flows. We solve the multiple Navier-Stokes equations in parallel in one rendering pass by combining multiple field data texture into one texture. It reduces the calculating time Flat 3D texture technique It’s easy to read and store velocity data

M ULTI -F LUID S OLVER ON GPU Flow chart of Multi-Fluid Solver With this, we can solve multiple NS in parallel in one rendering pass.

M ULTI -F LUID S OLVER ON GPU ( RESULTS )

R ESULTS AND D ISCUSSION Successfully generated dynamic tornado scenes Calculating the Poisson equation use the Jacobi iterative method 25 frames per second More iterations, lower frame rate

C ONCLUSION AND F UTURE W ORKS Simulating realistic tornado scenes To use RATFM The tornado’s interaction with surrounding large objects was simulated Future Works mixtures with three or more fluid components Water & Oil Other phenomena