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Numerical Analysis – Differential Equation

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Presentation on theme: "Numerical Analysis – Differential Equation"— Presentation transcript:

1 Numerical Analysis – Differential Equation
Hanyang University Jong-Il Park

2 Differential Equation

3 Solving Differential Equation
Ordinary D.E. Partial D.E. Linear eg. Nonlinear eg. Initial value problem Boundary value problem Usually no closed-form solution linearization numerical solution

4 Discretization in solving D.E.
Errors in Numerical Approach Discretization error Stability error y Exact sol. t Grid Points

5 Errors Total error truncation round-off increase as as trade-off

6 Local error & global error
The error at the given step if it is assumed that all the previous results are all exact Global error The true, or accumulated, error

7 Useful concepts(I) Useful concepts in discretization Consistency Order
Convergence

8 Useful concepts(II) stability Consistent Converge stable unstable

9 Stability Stability condition eg. Exact sol. Euler method
Amplification factor For stability

10 Implicit vs. Explicit Method
eg. = f Explicit : Implicit : h large y y ye h small h increase explicit t implicit t “conditionally stable” “stable”

11 Modification to solve D.E.
Modified Differential Eq. Diff. eq. Discretization Modified D.E. Discretization by Euler method <Consistency check> <Order>

12 Initial Value Problem: Concept

13 Initial value problem Initial Value Problem Simultaneous D.E.
High-order D.E.

14 Well-posed condition

15 Taylor series method(I)
Truncation error

16 Requiring complicated
Taylor series method(II) High order differentiation Implementation Complicated computation <Type 1> <Type 2> .... y t More computation accuracy y Requiring complicated source codes t Less computation accuracy

17 Euler method(I) Euler Method Talyor series expansion at to y .... ....

18 Euler method(II) Error Eg. y’ =-2x3+12x2-20x+8.5, y(0)=1

19 Euler method(III) Generalizing the relationship Error Analysis
Euler’s approx. truncation error Error Analysis Accumulated truncation error ; 1st order

20 Eg. Euler method

21 Modified Euler method: Heun’s method
Modified Euler’s Method Why a modification? error modify Predictor Average slope Corrector

22 Heun’s method with iteration
significant improvement

23 Error analysis Error Analysis
Taylor series Total error truncation 3rd order ; 2nd order method ※ Significant improvement over Euler’s method!

24 Eg. Euler vs. Modified Euler
Euler Method improvement

25 Runge-Kutta method Runge-Kutta Method The idea Simple computation
very accurate The idea where

26 Second-order Runge-Kutta method
Taylor series expansion ③→① Equating ② and ④

27 Modified Euler - revisited
set P2 P1  Modified Euler method Modified Euler method is a kind of 2nd-order Runge-Kutta method.

28 Other 2nd order Runge-Kutta methods
Midpoint method Ralston’s method

29 Comparison: 2nd order R-K method

30 Comparison: 2nd order R-K method
Eg. y’ =-2x3+12x2-20x+8.5, y(0)=1

31 4-th order Runge-Kutta methods
Fourth-order Runge-Kutta Taylor series expansion to 4-th order accurate short, straight, easy to use P4 P3 P1 P2 ※ significant improvement over modified Euler’s method

32 Runge-Kutta method

33 Eg. 4-th order R-K method Significant improvement

34 Discussion Better!

35 Comparison (5th order)


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