Numeric Integration Methods Marq Singer Red Storm Entertainment marqs@redstorm.com.
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Numeric IntegrationMethods
Marq SingerRed Storm Entertainment
marqs@redstorm.com
22
Talk Summary
Going to talk about: Euler’s method subject to errors Implicit methods help, but complicated Verlet methods help, but velocity
inaccurate Symplectic methods can be good for
both
33
Forces Encountered
Dependant on position: springs, orbits Dependant on velocity: drag, friction Constant: gravity, thrust
Will consider how methods handle these
44
Euler’s Method
Has problems Expects the derivative at the current point is a
good estimate of the derivative on the interval Approximation can drift off the actual function –
adds energy to system! Worse farther from known values Especially bad when:
System oscillates (springs, orbits, pendulums) Time step gets large
55
Euler’s Method (cont’d)
Example: orbiting object
x0 x1
x2
t
x
x4
x3
66
Stiffness
Have similar problems with “stiff” equations Have terms with rapidly decaying values Larger decay = stiffer equation = req. smaller h
Often seen in equations with stiff springs (hence the name)
t
x
77
Euler
Lousy for forces dependant on position
Okay for forces dependant on velocity
Bad for constant forces
88
Runge-Kutta
Idea: single derivative bad estimate Use weighted average of derivatives
across interval How error-resistant indicates order Midpoint method Order Two Usually use Runge-Kutta Order Four,
or RK4
99
Runge-Kutta (cont’d)
RK4 better fit, good for larger time steps
Tends to dampen energy Expensive – requires many evaluations If function is known and fixed (like in
physical simulation) can reduce it to one big formula
1010
Runge-Kutta
Okay for forces dependant on position Okay for forces dependant on velocity Great for constant forces
But expensive: four evaluations of derivative
1111
Implicit Methods
Explicit Euler method adds energy Implicit Euler dampens it Use new velocity, not current E.g. Backwards Euler:
Better for stiff equations11
11
iii
iii
h
h
vvv
xxx
1212
Implicit Methods
Result of backwards Euler Solution converges - not great But it doesn’t diverge!
x0
x1
x2x3
1313
Implicit Methods
How to compute or ? Derive from formula (most accurate) Solve using linear system (slowest, but
general) Compute using explicit method and
plug in value (predictor-corrector)
1ix 1iv
1414
Implicit Methods
Solving using linear system:
Resulting matrix is sparse, easy to invert
)()(1
))()((
)(
)(
1
11
iii
i
iiiii
iiii
iiiiii
iiii
h
h
h
h
h
xfxfIx
xxfxfx
xxfx
xxfxxx
xxx
1515
Implicit Methods
Example of predictor-corrector:
mh
h
mh
h
iiiiii
iiii
iiii
iii
/)),()~,~((2/
)~(2/
/),(~
~
111
11
1
1
vxFvxFvv
vvxx
vxFvv
vxx
1616
Backward Euler
Okay for forces dependant on position Great for forces dependant on velocity Bad for constant forces
But tends to converge: better but not ideal
1717
Verlet Integration
Velocity-less scheme From molecular dynamics Uses position from previous time
step Very stable, but velocity estimated Good for particle systems, not rigid
body iiii h axxx 2
11 2
1818
Verlet Integration
Leapfrog Verlet
Velocity Verlet
vi1/ 2 vi hi /2a ix i1 x i hvi1/ 2
vi1 vi1/ 2 hi /2a i1
vi1/ 2 vi 1/ 2 hi a ix i1 x i hi vi1/ 2
1919
Verlet Integration
Better for forces dependant on position Okay for forces dependant on velocity Okay for constant forces
Not too bad, but still have estimated velocity problem
2020
Symplectic Euler
Idea: velocity and position are not independent variables
Make use of relationship Run Euler’s in reverse: compute
velocity first, then position Very stable
2121
Symplectic Euler
Applied to orbit example
(Admittedly this is a bit contrived)
x0 x1
x2
x3
2222
Symplectic Euler
Good for forces dependant on position Okay for forces dependant on velocity Bad for constant forces
But cheap and stable!
2323
Which To Use?
With simple forces, standard Euler or higher order RK might be okay
But constraints, springs, etc. require stability Recommendation: Symplectic Euler
Generally stable Simple to compute (just swap velocity and position
terms) More complex integrators available if you need
them -- see references
2424
References
Burden, Richard L. and J. Douglas Faires, Numerical Analysis, PWS Publishing Company, Boston, MA, 1993.
Witken, Andrew, David Baraff, Michael Kass, SIGGRAPH Course Notes, Physically Based Modelling, SIGGRAPH 2002.
Eberly, David, Game Physics, Morgan Kaufmann, 2003.
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References
Hairer, et al, “Geometric Numerical Integration Illustrated by the Störmer/Verlet method,” Acta Numerica (2003), pp 1-51.
Robert Bridson, Notes from CPSC 533d: Animation Physics, University of BC.
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