Fast Simulation of Lightning for 3D Games

1. Fast Simulation of Lightning for 3D Games Jeremy Bryan Advisor: Sudhanshu Semwal

2. Overview • Introduction • Applications • Previous Research • Design • Implementation • Results • Future Work • Conclusion

3. Introduction • Realistic cloud-to-ground lightning strike • 3D game emphasis • Real-time requirement • Cellular Automata implementation

4. Introduction (cont.) • Lightning Basics • Strong electrical field • Stepped leader • Upward positive leader • Attachment process • Return stroke

5. Applications • 3D Games • Movies • Physical modeling • ???

6. Previous Research • Reed • “Visual Simulation of Lightning” • Emphasis on rendering with ray-tracing • Simple 3D model generation

7. Previous Research (cont.)

8. Previous Research (cont.) • Dobashi • Identical modeling technique as Reed • Takes scattering effect due to atmospheric particles and clouds into account

9. Previous Research (cont.)

10. 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) • X=Eαr

11. 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

12. Design • Complex Lightning Algorithm • Ground up • Assign values on the fly • Random numbers for “r” • Make the calculations • Find largest breakdown number (X) • X=Eαr • Segment length

13. 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

14. Design (cont.)

15. Design (cont.) • Complex Branch Algorithm • Parent iteration • Uniformly distributed probability function • Recursive • Random branch length

16. 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

17. Implementation • Object-Oriented Design • Programming Languages • Supporting packages • HeightMap Tutorial • Linked list library • OpenGL car tutorial

18. Implementation (cont.) • Development model • Class structures • CCamera • CVoxel • Lightning • Camera • Target • Car • Explosion

19. Implementation (cont.) • Observations • 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.

20. Results

21. Results (cont.)

22. Results (cont.) • Survey

23. Results (cont.) Sample Size = 64

24. Future Work • Efficiency • Support for light sources • Branch modeling • Control point support • ???

25. Conclusion • Aesthetically pleasing results • No discernable lag-time • 3D game environment