Depicting Fire and Other Gaseous Phenomena Using Diffusion Processes Jos Stam and Eugene Fiume Dept. of CS, University of Toronto Presentation ©2001 Brenden.

Slides:



Advertisements
Similar presentations
Stable Fluids A paper by Jos Stam.
Advertisements

My First Fluid Project Ryan Schmidt. Outline MAC Method How far did I get? What went wrong? Future Work.
MODELLING OF TWO PHASE ROCKET EXHAUST PLUMES AND OTHER PLUME PREDICTION DEVELOPMENTS A.G.SMITH and K.TAYLOR S & C Thermofluids Ltd.
Realistic Simulation and Rendering of Smoke CSE Class Project Presentation Oleksiy Busaryev TexPoint fonts used in EMF. Read the TexPoint manual.
A Prediction-Correction Approach for Stable SPH Fluid Simulation from Liquid to Rigid François Dagenais Jonathan Gagnon Eric Paquette.
Computer Graphics I, Fall 2010 Shading II.
CS 480/680 Computer Graphics Shading 2 Dr. Frederick C Harris, Jr.
Matthias Müller, Barbara Solenthaler, Richard Keiser, Markus Gross Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2005),
Thermal Performance Analysis of A Furnace
The Sun, our favorite star! WE CAN SEE IT REALLY WELL. The Sun is the basis for all of our knowledge of stars. Why?
Inferring Axon Diameter Sizes using Monte Carlo Simulations of Magnetic Resonance Oscillating Gradient Spin Echo Sequences ME Mercredi 1, TJ Vincent 2,3,
Computer Vision Optical Flow
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”
1Notes  Text:  Motion Blur A.3  Particle systems 4.5 (and 4.4.1, 6.6.2…)  Implicit Surfaces  Classic particle system papers  W. Reeves, “Particle.
William Moss Advanced Image Synthesis, Fall 2008.
Particle Systems 1 Adapted from: E. Angel and D. Shreiner: Interactive Computer Graphics 6E © Addison-Wesley 2012.
Shading II CS4395: Computer Graphics 1 Mohan Sridharan Based on slides created by Edward Angel.
Hokkaido University Efficient Rendering of Lightning Taking into Account Scattering Effects due to Clouds and Atmospheric Particles Tsuyoshi Yamamoto Tomoyuki.
Targil 2 Image enhancement and edge detection. For both we will use image derivatives.
1cs533d-winter-2005 Notes  I’m now in X663 Well, sort of…  Questions about assignment 3?
Keyframe Control of Smoke Simulations SIGGRAPH 2003.
Modeling Fluid Phenomena -Vinay Bondhugula (25 th & 27 th April 2006)
Motion Estimation Today’s Readings Trucco & Verri, 8.3 – 8.4 (skip 8.3.3, read only top half of p. 199) Numerical Recipes (Newton-Raphson), 9.4 (first.
Visual Simulation of Smoke SIGGRAPH’01 Ronald Fedkiw, Jos Stam and Henrik Wann Jensen Stanford University & Alias|wavefront.
Paper by Alexander Keller
1cs426-winter-2008 Notes  Assignment 1 is out, due immediately after reading week (Feb 25)  Please read: William T. Reeves, "Particle systems: a technique.
The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Introduction to Modeling Fluid Dynamics 1.
Fluid Simulation using CUDA Thomas Wambold CS680: GPU Program Optimization August 31, 2011.
Modeling, Simulating and Rendering Fluids Thanks to Ron Fediw et al, Jos Stam, Henrik Jensen, Ryan.
CHAPTER 4 MOISTURE AND ATMOSPHERIC STABILITY. “Too Much, Too Little, Too Bad” All life on Earth is directly tied to acquiring water in forms of sufficient.
Towards Developing a “Predictive” Hurricane Model or the “Fine-Tuning” of Model Parameters via a Recursive Least Squares Procedure Goal: Minimize numerical.
Analysis of Radiation Heat Transfer in Furnace P M V Subbarao Professor Mechanical Engineering Department Test for Cooling Capacity of Furnace Surface….
Optical Models Jian Huang, CS 594, Spring 2002 This set of slides are modified from slides used by Prof. Torsten Moeller, at Simon Fraser University, BC,
Animation of Fluids.
COMPUTATIONAL FLUID DYNAMICS IN REAL-TIME An Introduction to Simulation and Animation of Liquids and Gases.
Ye Zhao, Zhi Yuan and Fan Chen Kent State University, Ohio, USA.
Smoothed Particle Hydrodynamics (SPH) Fluid dynamics The fluid is represented by a particle system Some particle properties are determined by taking an.
-Global Illumination Techniques
09/09/03CS679 - Fall Copyright Univ. of Wisconsin Last Time Event management Lag Group assignment has happened, like it or not.
More About Matter. Physical vs. Chemical Properties Physical Properties Physical Properties Observed without changing identity of substance. Observed.
Objectives Explain how radiant energy reaches Earth.
A Unified Lagrangian Approach to Solid-Fluid Animation Richard Keiser, Bart Adams, Dominique Gasser, Paolo Bazzi, Philip Dutré, Markus Gross.
1. Endothermic: a chemical reaction that absorbs heat.
Image Processing Jitendra Malik. Different kinds of images Radiance images, where a pixel value corresponds to the radiance from some point in the scene.
Petra Zdanska, IOCB June 2004 – Feb 2006 Resonances and background scattering in gedanken experiment with varying projectile flux.
Simplified Smoothed Particle Hydrodynamics for Interactive Applications Zakiya Tamimi Richard McDaniel Based on work done at Siemens Corporate.
Computer-Generated Watercolor Curtis, Anderson, Seims, Fleischer, & Salesin SIGGRAPH 1997 presented by Dave Edwards.
Effective Optical Flow Estimation
Introduction: Lattice Boltzmann Method for Non-fluid Applications Ye Zhao.
Radiosity Jian Huang, CS594, Fall 2002 This set of slides reference the text book and slides used at Ohio State.
A Few Things about Graphics Jian Huang Computer Science University of Tennessee.
Optical Flow. Distribution of apparent velocities of movement of brightness pattern in an image.
MA354 An Introduction to Math Models (more or less corresponding to 1.0 in your book)
Physical Based Modeling and Animation of Fire 1/25.
Animating Fire by Kathleen Marty. How to create fire? Implement the paper: Structural Modeling of Flames for a Production Environment, by Arnauld Lamorlette.
Graphics Lecture 17: Slide 1 Interactive Computer Graphics Lecture 17: Fire.
Green House Effect and Global Warming. Do you believe that the planet is warming? 1.Yes 2.No.
1 Atmospheric Radiation – Lecture 9 PHY Lecture 9 Infrared radiation in a cloudy atmosphere.
Animation Demonstration No. 1. Interaction of Light with matter When light is incident on a material.
Lecture 2: Heat and radiation in the atmosphere. TEMPERATURE… is a measure of the internal heat energy of a substance. The molecules that make up all.
Scale-Space and Edge Detection Using Anisotropic Diffusion Presented By:Deepika Madupu Reference: Pietro Perona & Jitendra Malik.
November 2005 Center for Computational Visualization Institute of Computational and Engineering Sciences Department of Computer Sciences University of.
Processing Images and Video for An Impressionist Effect Automatic production of “painterly” animations from video clips. Extending existing algorithms.
Animating smoke with dynamic balance Jin-Kyung Hong Chang-Hun Kim 발표 윤종철.
Computer Graphics: Illumination
Fluid Animation CSE 3541 By: Matt Boggus.
Motion and Optical Flow
Reactive transport of CO2 in a brine cavity
Radiative Transfer & Volume Path Tracing
Shape from Shading and Texture
Presentation transcript:

Depicting Fire and Other Gaseous Phenomena Using Diffusion Processes Jos Stam and Eugene Fiume Dept. of CS, University of Toronto Presentation ©2001 Brenden Schubert

Modeling Gasses Texture Parameterization –Vary parameters to get animation  Empirical  Hard to relate parameters to physical model Particle System –User-defined wind field displaces particles each frame  More correct (think molecular)  Computationally intense

“warped blobbies” Start with a particle system Use blobs instead of particles –Replace lots of particles with single blob Wind field advects and diffuses blobs –Key: diffusion is non-uniform

Diffusion Processes Toronto must require CS majors to take Differential Equations too Is applied to both particles (blobs), and temperature Simple enough to be understood by animators with “limited knowledge of physics” –What could be more simple than milk dissolving in a coffee cup..?

The Diffusion Equation u = wind field  = scalar field (density of the gas)  = gradient operator   = diffusion coefficient (like viscosity) S  = source field (producing gas) L  = sink field (sucking gas in)

The Diffusion Equation Diffusion depends on the (square of) the gradient of the scalar field *   Advection depends on the gradient of the scalar field * u Sources and sinks are like adding constant (over time) fields to the wind field Apply to both gas “density” and temperature

There’s no gluDiffEQ() function Approximate by convolving the exact solution with a smoothing function The Smoothing Function –Modified Gaussian: incorporates How much the blob has changed from original  = function of the wind field

There’s no gluDiffEQ() function Approximate by convolving the exact solution with a smoothing function The Smoothing Function –Modified Gaussian: incorporates  = original blob attributes  = function of the wind field

Light and Gas Internally produced light –Emission spectra known –Proportional to T 4 Externally produced light –Scattered: albedo (  ) contstant Phase function p –Absorbed (1 –  * absorption spectra

Shooting Operations Light sources are a field Discretize environment into patches Repeatedly shoot light from patch to patch, blob to patch, and patch to blob Eventually will converge to an intensity field

Fire Why I picked this paper (you can’t burn stuff with differential equations) The key: Temperature field –Define an activation temperature T a –When T reaches T a … –Render flames Smoke –When gas cools below T s render smoke particle

Conclusions Warping blobs is good Convolution must be slow –“typical resolutions for our simulations were 20 x 20” –Video res frame takes 20 min on SGI Indigo 2 Manipulation of wind field is key to usability Fire –still requires lots of tweaking –good movement, but coloration not addressed