The Computable Differential Equation Lecture ... - Bruce E. Shapiro
The Computable Differential Equation Lecture ... - Bruce E. Shapiro
The Computable Differential Equation Lecture ... - Bruce E. Shapiro
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CHAPTER 5. RUNGE-KUTTA METHODS 101<br />
and hence the most general form of the iteration formula is<br />
K 1 = f(t n−1 + c 1 h, y n−1 + ha 11 K 1 + ha 12 K 2 ) (5.108)<br />
= f(t n−1 , y n−1 ) = f (5.109)<br />
K 2 = f(t n−1 + c 2 h, y n−1 + ha 21 K 1 + ha 22 K 2 ) (5.110)<br />
= f(t n−1 + ah, y n−1 + haK 1 ) ⇐= (5.111)<br />
= f(t n−1 + ah, y n−1 + haf) ⇐= (5.112)<br />
y n = y n−1 + hb 1 K 1 + hb 2 K 2 (5.113)<br />
= y n−1 + hb 1 f + hb 2 f(t n−1 + ah, y n−1 + haf) (5.114)<br />
where we have use the shorthand notation f = f(t n−1 , y n−1 ). To determine the<br />
coefficients to minimize error, we expand the last term in a Taylor series about<br />
(t n−1 , y n−1 )<br />
f(t n−1 + ah,y n−1 + haf) = f + ahf t + haff y + (5.115)<br />
a 2 h 2<br />
2 (f tt + 2ff ty + f 2 f yy + f y (f t + ff y )) + O(h 3 ) (5.116)<br />
To simplify the notation we let (after Lambert) F = f t + ff y and G = f tt + 2ff ty +<br />
f 2 f yy<br />
(<br />
y n = y n−1 + hb 1 f + hb 2 f + ahf t + haff y + a2 h 2 )<br />
2 (G + f yF ) (5.117)<br />
Hence we need<br />
= y n−1 + h(b 1 + b 2 )f + h 2 b 2 aF + O(h 3 ) (5.118)<br />
b 1 + b 2 = 1 (5.119)<br />
b 2 a = 1 2<br />
(5.120)<br />
to match a Taylor expansion. This gives us a family of two stage explicit methods<br />
that are second order:<br />
0 0<br />
a a 0<br />
1 − 1 1<br />
2a 2a<br />
(5.121)<br />
When a = 1, this gives the trapezoidal method, and when a = 1/2, it gives the<br />
explicit midpoint method.<br />
Two popular explicit three-stage third-order methods include Heun’s thirdorder<br />
method<br />
0 0<br />
1/3 1/3 0<br />
(5.122)<br />
2/3 0 2/3 0<br />
1/4 0 3/4<br />
c○2007, B.E.<strong>Shapiro</strong><br />
Last revised: May 23, 2007<br />
Math 582B, Spring 2007<br />
California State University Northridge