Transcript Fast Simulation of Lightning for 3D Games

Fast Simulation of Lightning
for 3D Games
Jeremy Bryan
Advisor: Sudhanshu Semwal
Overview
Introduction
 Applications
 Previous Research
 Design
 Implementation
 Results
 Future Work
 Conclusion

Introduction
Realistic cloud-to-ground lightning strike
 3D game emphasis
 Real-time requirement
 Cellular Automata implementation

Introduction (cont.)

Lightning Basics
Strong electrical field
 Stepped leader
 Upward positive leader
 Attachment process
 Return stroke

Applications
3D Games
 Movies
 Physical modeling
 ???

Previous Research

Reed
“Visual Simulation of Lightning”
 Emphasis on rendering with ray-tracing
 Simple 3D model generation

Previous Research (cont.)
Previous Research (cont.)

Dobashi
Identical modeling technique as Reed
 Takes scattering effect due to atmospheric
particles and clouds into account

Previous Research (cont.)
Previous Research (cont.)

UCCS Physics website
r is a generated random number that represents atmospheric properties.
E is the electric field and can be found by using Maxwell’s Equations.
α controls the weight of E on r.
Find largest breakdown number
(X)
α
Cellular Automata
Discreet lattice
 Discreet time-steps drive simulation
 Each cell has finite set of values
 Each cell evolves according to same set of
rules
 Evolution of cell depends only upon local
neighborhood interaction

Design

Complex Lightning Algorithm
Ground up
 Assign values on the fly

 Random

numbers for “r”
Make the calculations
 Find
largest breakdown number (X)
α
 X=E r

Segment length
Design (cont.)

Pseudocode
Proc GenerateComplexLightning
// Load the starting coordinates
list.add target.coords
while height <= MAX_ALTITUDE
Assign r to 26 neighbor cells if they do not have one
Calculate E for 26 neighbor cells if not done previously
Find maximum X
list.add maxE.coords
end while
for each voxel in list
temp = rand()
if temp < BRANCH_PROBABILITY then
GenerateComplexBranch()
end if
end for
end proc
Design (cont.)
Design (cont.)

Complex Branch Algorithm
Parent iteration
 Uniformly distributed probability function
 Recursive
 Random branch length

Design (cont.)

Pseudocode
Proc GenerateComplexBranch
BranchLength = rand()
while (BranchHeight >= 0 And BranchLength >=0)
Assign r to neighbor cells if they do not have one
Calculate E for cells if not done previously
Find maximum X
BranchList.add maxE.coords
end while
for each coord in BranchList.coords
if (rand() < BRANCH_PROBABILITY) then
GenerateComplexBranch()
end if
end for
end proc
Implementation
Object-Oriented Design
 Programming Languages
 Supporting packages

HeightMap Tutorial
 Linked list library
 OpenGL car tutorial

Implementation (cont.)
Development model
 Class structures

CCamera
 CVoxel

Lightning
 Camera
 Target
 Car
 Explosion

Implementation (cont.)

Observations
1.
2.
3.
Run-time dependent on max branch depth
and probability of branching
Large branch clusters detract from final
product and are time intensive
Number of voxels in a given dimension
match map size. Increasing resolution
would not enhance results.
Results
Results (cont.)
Results (cont.)

Survey
Results (cont.)
Glassner
Mean
Bryan
Reed
Dobashi
3.171875
2.25
2.28125
2.296875
Median
4
2
2.5
2
Mode
4
1
3
2
0.96863
1.140871
1.075982
1.03402
StdDev
Sample Size = 64
Future Work
Efficiency
 Support for light sources
 Branch modeling
 Control point support
 ???

Conclusion
Aesthetically pleasing results
 No discernable lag-time
 3D game environment
