Upload
sksiddique
View
217
Download
0
Embed Size (px)
Citation preview
8/13/2019 Week 15 - Explicit vs Implicit
1/7
12/19/2
Computational Fluid Dynamics
Implicit method19-Dec-13
21
2
2
x
u
t
u
Therefore parabolic equation can be written as:
2
1
1
11
1
1 2
x
uuu
t
uu n
i
n
i
n
i
n
i
n
i
2
1
1
11
1
1 )2(x
truuuuru
n
i
n
i
n
i
n
i
n
i
Difference equation is:
Time (n+1) Time (n)
SCHEME is ORDER (t, x2)
t
uu n
i
n
i
1
2
1
1
11
1 2
x
uuu n
i
n
i
n
i
Requires Matrix Solvers.
Known as the Fully Implicit Method.
Computational Fluid Dynamics
Crank Nicholson
Approximating the derivatives at mid-point intime (n+0.5, i) with half the time step, wehave:
LHS:
RHS:
19-Dec-13
22
2
2
x
u
t
u
t
uu n
i
n
i
5.02
5.05.05.05.0
2
1
1
11
1
2
11 22
2
1
x
uuu
x
uuu n
i
n
i
n
i
n
i
n
i
n
i
2
1
11211
211
1121 22
x
uuuuuu n
i
n
i
n
i
n
i
n
i
n
i
2
5.0
1
5.05.0
1 2
x
uuu n
i
n
i
n
i
t
uu n
i
n
i
5.02
1
8/13/2019 Week 15 - Explicit vs Implicit
2/7
12/19/2
Computational Fluid Dynamics
Crank Nicholson
Crank Nicholson in 1947 proposed this method to allowgreater time steps in their calculations.
The resulting difference equation is:
In this case we have three unknowns on the RHS of theequation.
Therefore the new value +1 is not given directly in
terms of known values as is the case of the Explicitmethod.
19-Dec-13
23
Time (n+1) Time (n)
n
i
n
i
n
i
n
i
n
i
n
i ruurruruurru 111
1
11
1 )22()22(
2x
tr
SCHEME is ORDER (t2, x2)
Computational Fluid Dynamics
Explicit vs Implicit19-Dec-13
24
i-1 i i+1i-1 i i+1
n-1
n
n+
1
i-1 i i+1
Explicit Crank-Nicholson Fully Implicit
O(t, x2) O(t, x2)O(t2, x2)
Computational moleculesshow differences between the schemes
If there is more than one node at timestep n+1 the scheme is implicit
n-1
n
n+1
n-
1
n
n+1
8/13/2019 Week 15 - Explicit vs Implicit
3/7
12/19/2
Computational Fluid Dynamics
Comparison
Explicit method
Unknown values atcurrent time step dependonly on known values atprevious time step
Advantage:Easy to implement insoftware and solve
Disadvantage:
Restrictions on time stepfor stability.
Implicit method
Unknown values atcurrent time step dependon known values atprevious time step and oneach other Disadvantage:
Requires solution ofsystem of equations
Advantage:
No restrictions on time step
19-Dec-13
25
Computational Fluid Dynamics
Example
Consider heat loss from a heated rod subject
to the above equations:
Use the explicit scheme with mesh spacing0.1 and timestep 0.001 to obtain
approximate values for u(x,0.03).
Now change the timestep to 0.01. What
happens?
19-Dec-13
28
ICEICE
0),1(),0( tutu102
2
x
x
u
t
u
xxu sin)0,(
8/13/2019 Week 15 - Explicit vs Implicit
4/7
12/19/2
Computational Fluid Dynamics
Solution
The problem is set up as follows
19-Dec-13
29
=sin(*c24)
)2( 111 n
i
n
i
n
i
n
i
n
i uuuruu
Explicit Equation:
= C25+rr*(D25-2*C25+B25)
Name rr
=B22/B21^2
Computational Fluid Dynamics
19-Dec-13
30
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10.00 0 0.31 0.59 0.81 0.95 1.00 0.95 0.81 0.59 0.31 0
0.01 0 0.28 0.53 0.73 0.86 0.90 0.86 0.73 0.53 0.28 0
0.02 0 0.25 0.48 0.66 0.77 0.81 0.77 0.66 0.48 0.25 0
0.03 0 0.23 0.43 0.59 0.70 0.73 0.70 0.59 0.43 0.23 0
0.04 0 0.20 0.39 0.54 0.63 0.66 0.63 0.54 0.39 0.20 0
0.05 0 0.18 0.35 0.48 0.57 0.60 0.57 0.48 0.35 0.18 0
0.06 0 0.17 0.32 0.44 0.51 0.54 0.51 0.44 0.32 0.17 0
0.07 0 0.15 0.29 0.39 0.46 0.49 0.46 0.39 0.29 0.15 0
0.08 0 0.14 0.26 0.35 0.42 0.44 0.42 0.35 0.26 0.14 0
0.09 0 0.12 0.23 0.32 0.38 0.40 0.38 0.32 0.23 0.12 0
0.10 0 0.11 0.21 0.29 0.34 0.36 0.34 0.29 0.21 0.11 0
0.11 0 0.10 0.19 0.26 0.31 0.32 0.31 0.26 0.19 0.10 0
0.12 0 0.09 0.17 0.24 0.28 0.29 0.28 0.24 0.17 0.09 0
0.13 0 0.08 0.15 0.21 0.25 0.26 0.25 0.21 0.15 0.08 0
0.14 0 0.07 0.14 0.19 0.22 0.24 0.22 0.19 0.14 0.07 0
0.15 0 0.07 0.13 0.17 0.20 0.21 0.20 0.17 0.13 0.07 0
0.16 0 0.06 0.11 0.16 0.18 0.19 0.18 0.16 0.11 0.06 0
0.17 0 0.05 0.10 0.14 0.17 0.17 0.17 0.14 0.10 0.05 0
0.18 0 0.05 0.09 0.13 0.15 0.16 0.15 0.13 0.09 0.05 0
0.19 0 0.04 0.08 0.11 0.13 0.14 0.13 0.11 0.08 0.04 00.20 0 0.04 0.07 0.10 0.12 0.13 0.12 0.10 0.07 0.04 0
0.21 0 0.04 0.07 0.09 0.11 0.11 0.11 0.09 0.07 0.04 0
0.22 0 0.03 0.06 0.08 0.10 0.10 0.10 0.08 0.06 0.03 0
0.23 0 0.03 0.05 0.08 0.09 0.09 0.09 0.08 0.05 0.03 0
0.24 0 0.03 0.05 0.07 0.08 0.08 0.08 0.07 0.05 0.03 00.25 0 0.02 0.04 0.06 0.07 0.08 0.07 0.06 0.04 0.02 0
0.26 0 0.02 0.04 0.06 0.07 0.07 0.07 0.06 0.04 0.02 0
0.27 0 0.02 0.04 0.05 0.06 0.06 0.06 0.05 0.04 0.02 0
0.28 0 0.02 0.03 0.05 0.05 0.06 0.05 0.05 0.03 0.02 0
0.29 0 0.02 0.03 0.04 0.05 0.05 0.05 0.04 0.03 0.02 0
0.30 0 0.01 0.03 0.04 0.04 0.05 0.04 0.04 0.03 0.01 0
8/13/2019 Week 15 - Explicit vs Implicit
5/7
12/19/2
Computational Fluid Dynamics
Results for dt=0.00119-Dec-13
31
Computational Fluid Dynamics
Results for dt=0.0119-Dec-13
32
8/13/2019 Week 15 - Explicit vs Implicit
6/7
12/19/2
Computational Fluid Dynamics
Example
Solve the same equation as the previousexample, but use the Crank-Nicholson
scheme to obtain approximate values for
with the time step 0.001.
Now change the time step to 0.01. What
happens?
19-Dec-13
33
n
i
n
i
n
i
n
i
n
i
n
i ruurruruurru
11
1
1
11
1
)22()22(
2x
tr
Computational Fluid Dynamics
Solution
The problem is set up as follows:
19-Dec-13
34
1111111 )22()22(
1
ni
n
i
n
i
n
i
n
i
n
i rururuurru
ru 2
x
tr
Name FLAG
0: Initialize
1: Iterate (solve)
Implicit Equation
=IF(FLAG=0,0,(rr*B25+(2-2*rr)*C25+rr*D25+rr*B26+rr*D26)/(2+2*rr))
[B26 & D26 are at current time-step]
Name rr
=B22/B21^2
Iteration counter
=IF(FLAG=0,0,E19+1))
8/13/2019 Week 15 - Explicit vs Implicit
7/7
12/19/2
Computational Fluid Dynamics
Results
For dt = 0.001, courant number = 0.1 andafter 7 iterations.
19-Dec-13
35
Computational Fluid Dynamics
Results
For dt = 0.01, courant number = 1 and after
20 iterations, with convergence.
19-Dec-13
36