the diffusion equation a nd other similar equations
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The Diffusion Equation a nd other Similar Equations. Introduction and Preliminary Concepts Separation of Variables Sturm-Liouville Theory Fourier and Laplace Transforms. Preliminary Concepts. Linearity, Superposition and Classifications: . - PowerPoint PPT PresentationTRANSCRIPT
Introduction and Preliminary Concepts
Separation of Variables
Sturm-Liouville Theory
Fourier and Laplace Transforms
The Diffusion Equation and other Similar Equations
Preliminary Concepts
Linearity, Superposition and Classifications: A partial differential operator (PDO) L is considered linear if the following is satisfied
functionsarevuandscalaraiscwherecLvLucvuL & )(
Linearity, Superposition and Classification (3)
For example,
cLvLuvvcuu
cvuy
cvuL
yy
)2()2(
)(2)(
therefore, PDO L is linear.
It follows that for a linear PDO the equationfLu
is homogeneous if 0f and heterogeneous if f is any other function.The order of a PDE is determined based on the highest order derivative that is in it. For example, the inviscid Burgers’ equation below
0 xt uuu
is first-order while the Korteweg-deVries (KdV) equation
0 xxxxt uuuu
is third-order due to the additional term.If the linear homogeneous equation
0Lvis satisfied by it also follows that will satisfy it.nuu ,...1 nnucucu ...11
Linearity, Superposition and Classification (3)
In addition, PDEs can be classified based on the sign of the discriminant B2-AC using the following criteria.
0 if elliptic,0 if hyperbolic,0 if parabolic
2
2
2
ACBACBACB
The heat/diffusion equation, which we will be discussing, is parabolic since,
0)0)((0constant a is where
222
2
ACBuu txx
Examples of solutions of the equation are shown below.
Image modified from http://home.comcast.net/~sharov/PopEcol/lec12/diffus.htmlMathematical techniques for engineers and scientists (2)
Separation of Variables
Diffusion in chemical reaction*
X=0
X=R
Catalyst wallr=kA
First order chemical reaction takes place on the catalyst wall of cylindrical containerFind out the concentration change of A inside the containerSet up PDE:D*Axx=At, or D*∂2A/∂x2 =∂A/∂tA-concentration of AD-diffusivity
*from Chemical Engineering Kinetics (6)
Diffusion in chemical reaction
X=0
X=R
Catalyst wallr=kA
First order chemical reaction takes plane on the catalyst wallFind out the concentration change of A inside the cylindrical contatinerBoundary and initial conditions:I.C t=0, A=A0
B.C1 x=0, ∂A/∂x │x=0 =0, by symmetryB.C2 x=R, D*∂A/∂x │x=R =k*A, diffusion =reaction at wall
Diffusion in chemical reaction
X=0
X=R
Catalyst wallr=kA
Run dimensionless:u=A/A0, s=x/R, τ=t/tc (=tD/R2)Then we get:tc*D/R2∂2u/∂s2 =∂u/∂τ, let tc*D/R2=1, then tc=R2/D
BCs: ∂u/∂s =0 at s=0∂u/∂s =kR/D*u=φu, φ=kR/Dat s=1
Diffusion in chemical reaction
X=0
X=R
Catalyst wallr=kA
Assume: u=F(s)*G(τ)
G(τ)*dF2/ds2=F(s)*dG(τ)/ds, 1/F(s)*dF2/ds2=1/G(τ)*dG(τ)/ds=-λn
2
Solve 1/G(τ)*dG(τ)/ds=-λn2
we get: dG(τ)=exp(-λn2τ)
For 1/F(s)*dF2/ds2=-λn2
assume F(s)=∑(Ansinλns+ Bncosλns)
Diffusion in chemical reaction
X=0
X=R
Catalyst wallr=kA
Use BC1: ∂u/∂s =0 at s=0∂u/∂s=G(τ)*dF/ds=0∑(Anλncosλn*0- Bnλnsinλn*0)=0An=0F(s)= ∑Bncosλns
Use BC2: ∂u/∂s =φu at s=1-Bnλnsinλn=φBncosλn-λntanλn=φ, λncan be solved
Diffusion in chemical reaction
X=0
X=R
Catalyst wallr=kA
u(s, τ) =∑exp(-λn2 τ) Bncosλns
How to get Bn?
τ =0, u(s,0)=1= ∑1*Bncosλns
Use orthogonality principle∫0
1 *cos(λns)ds=Bn∫0
1cos2(λns)ds
Bn = ∫01
cos(λns)ds/∫01cos2(λns)ds
Bn =4sin(λn )/(2λn+sin2λn)
When ψ is large When ψ is small
0
5
10
15
20
25
30
35
40
45
0 2 4 6 8 10 12ti me(t)
Conc
entr
atio
n A
0
5
10
15
20
25
30
35
40
45
0 2 4 6 8 10 12ti me(t)
Conc
entr
atio
n A
Strum-Liouville Problems
Second order, homogenous, linear differential equation with boundary conditions.
Solutions to such problems contain an infinite set of eigenvalues with corresponding eigenfunction solutions
What are Strum-Liouville Problems?
Equations from Advanced Engineering Mathematics (9)
A simple example:
Problem from Introduction to Differential Equations (7)
Problem from Introduction to Differential Equations (7)
Problem from Introduction to Differential Equations (7)
Problem from Introduction to Differential Equations (7)
Problem from Introduction to Differential Equations (7)
Problem from Introduction to Differential Equations (7)
Many differential equations are in the form of the Sturm-Liouville problem.
Sturm-Liouville analysis can help determine integration constants for equations with an infinite number of terms (eigenfunctions).
How is this useful for Separation of Variables?
A more complex example:
Problem from Heat Conduction (8)
The boundary conditions are such that
Figure from Heat Conduction (8)
Problem from Heat Conduction (8)
Problem from Heat Conduction (8)
Problem from Heat Conduction (8)
Problem from Heat Conduction (8)
Problem from Heat Conduction (8)
Problem from Heat Conduction (8)
Problem from Heat Conduction (8)
Problem from Heat Conduction (8)
• Other types of problems• Wave equation, diffusion equation…
• Other types of boundaries:• Fixed, Periodic, Moving
• Handled same as in regular Sturm-Liouville Problem
Other considerations considerations:
Fourier and Laplace Transforms
)( uuxhs
xxkAu
x
xx xxxkAu
Image modified from http://www.ceb.cam.ac.uk/pages/finite-element-simulations.html
The energy balance over the infinitesimal volume of a rod shown in the figure is as follows
Diffusion Equation:
tmcucuvAcuvAuuxhskAukAu
xxxxxxxx
)()(
where, m=AΔxσc. Dividing the full equation by AΔxσc and taking the limit as x goes to 0 yields
AchsH
ckuuHvuuu xtxx & e, wher)( 22
Variables:
tyconductivi thermaltcoefficienfer heat trans
area sectional -crossdifference etemperatur
rod of speedncecircumfere
density massheat specific
khA
uuvs
c
Heat Conduction and the Heat Equation (5)
Initial/Boundary Conditions: For all subsequent calculations we assume that diffusion in the rod is one-dimensional and thus set H and and v to zero.
txx uu 2
The initial condition is simply a set function for u(x,t) over the length of the rod at t=0 and is written thus,
)0( )()0,( Lxxfxu
The boundary condition can fall into one of three categories.Dirichlet boundary condition:
)(),0( ttu
Fundamental Solutions (4)
Meaning that the left end of the bar is kept at a set temperature.Neumann boundary condition:
)(),0(),0( ttkutq x
This boundary condition specifies the heat flow out of the rod. Particularly, setting 0)( t means insulating the left end of the rod.
Heat Conduction and the Heat Equation (5)
Initial/Boundary Conditions (cont`d):
Robin boundary condition:Starting with Newton’s Law of Cooling
fx
fx
f
hutLhutLkutLuuhtLku
tLuuhtL
),(),()],([),(
)],([),(
)( fs uuhAq
where, us and uf are temperatures of the solid and fluidrespectively. It then follows that,
Heat Conduction of an Infinite Rod (Fourier Transforms)
xx)(xf
)()0,( xfxu t
For non-periodic functions [f(x)] the heat equation can be solved using Fourier exponential transform and a known Gaussian function g(x,t) the steps follow…..
Mathematical techniques for engineers and scientists (2)
),(),();,( tsUdxtxuesxtxuF isx
The Fourier exponential transform can be written as
Using the above definition we can write
The heat equation can then be rewritten as
We can solve for U using the initial condition to yield
),();,(
),();,( 2
tsUsxtxuFtsUssxtxuF
tt
xx
sxfF)where, G(ssGsUICtUsut
);()()0,(:0,022
sesGtsU ts ,)(),(22
yields ))()()()(( n theoremconvolutio theand
)2
1( ansformFourier tr inverse theUsing2222 )2/(
dgxfsgsf
ee xs
txet
txgdtxgftxu22 4/
21),( where, )()(),(
deft
txu tx
22 4/)()(
)(21),(
Thus,
Mathematical techniques for engineers and scientists (2)
……(1)
Special Case 1:
The simplest solution to the heat equation is for Fxf constant)(
asrewritten becan (1)equation 2
settingby txa
datet
Ftxu a
22
),(2
Assuming that all terms except a are constant the function can be integrated to yield
FFtxu ),(
Thus, for the limiting case of f(x) = constant the heat will also equal that constant.
Advanced engineering mathematics (9)
Special Case 2:
In this case, assume the initial condition is as follows
Using these initial conditions the heat equation can be solved to yield
))2
(1(*504100),(
0
4)( 2
txerfde
ttxu t
x
since the integral can then be rewritten as
dezerfz
0
22)(
Beny Neta Presentation (1)
-400 -300 -200 -100 0 100 200 300 4000
102030405060708090
100t=10t=500t=1000t=10000100000100000001000000000
x
u(x,t)
From the chart we can see the function “smoothing” out at large values of t. This is due to the behavior of the error function, erf(∞)=1 and erf(~0)=0. Thus, for positive values of x at small times u(x,t) approaches F and at large times u(x,t) approaches F/2. For negative values of x the negative sign can be taken outside of the error function so the value of the error function is subtracted from 1. Thus at small times u(x,t) approaches 0 and at large times u(x,t) approaches F/2.
Typical Behavior
Images taken from http://en.wikipedia.org/wiki/File:Heatequation_exampleB.gif
The following curves are of temperature collected at different times. From the plots a “smoothing” effect can again be seen as the temperature along entire length of the rod approaches an equilibrium value.
t1
t2
x
Kto
figure modified from: http://mobjectivist.blogspot.com/2010_06_01_archive.html
Similar to the error function the integral of equation (1) can be rewritten as the kernel
Special Case 3:
tetxK
tx
2);(
22 4/)(
and the function becomes….
dtxKftxu );()(),(
shown that becan it 2
settingby txa
1);(),(
dtxKtxu
)( ,0 as hus xKtT
From the graph you can see that similar “smoothing” process occurs for the Kernel as for the temperature profile. It is also important to note that the Kernel is a response function to an initial temperature function described by the delta function
Heat Conduction of a Semi-Infinite Rod (Laplace Transforms)
x)(xf
)()0,( xfxu t
)(),0(
tgtu
)0,0(,2 txuu txx 0,0),(),(),0(: txastxutftuBC
)0( ,0)0,( : xxuIC
For non-periodic functions [f(x)] the heat equation can be solved in the semi-infinite domain using Laplace exponential transform the steps follow…..
Mathematical techniques for engineers and scientists (2)
2/3
4 2
2
2t
eex
t
xpx
………(2)
Using the inverse Laplace transform U(x,p) becomes,
t
dtgftgf0
)()())(*(
)(2)(),(
2/3
)4/( 22
txetgtxu
tx
Then using the convolution theorem
u(x,t) becomes,
detgxtxut x
0
2/3
4/ 22
)(2
),(
Mathematical techniques for engineers and scientists (2)
),(),();,( pxUdttxuepttxu ptL
The Laplace exponential transform can be written as
Using the above definition we can write
The heat equation can then be rewritten as
We can solve for U using the boundary condition to yield
),();,(
),();,(pxpUpttxupxUpttxu
t
xxxx
LL
)()(0),()(),0(:
0,02
tfpGwherexaspxUpGpUBC
xUpU xx
L
pepGpxUpx
,)(),(
Mathematical techniques for engineers and scientists (2)
Special Case :The simplest solution to the heat equation is for
Ftconsxg tan)(
By setting 2
22
4xa we can solve
for
22
2
4 ax
and da
axd
32
2
42
Thus equation (2) becomes
daeF tx
a
2
0
22
or otherwise
)2
(*),(t
xerfcFtxu
Advanced engineering mathematics (9)
For F=50 and α=1 u(x,t) is plotted below
0 100 200 300 400 500 600 700 800 90005
101520253035404550
t=10 t=500 t=1000 t=10000100000 10000000 1000000000
x
u(x,t)From the chart we can see a similar “smoothing” process as in the case of the infinite domain at large values of t. Again, erf(∞)=1 and erf(~0)=0. Thus at small times u(x,t) approaches F and at large times u(x,t) approaches 0.
References
1.Neta, Beny. "PARTIAL DIFFERENTIAL EQUATIONS MA 3132 LECTURE NOTES." math.nps.navy. Department of Mathematics Naval Postgraduate School, n.d. Web. 20 Oct. 2011. <www.math.nps.navy.mil/~bneta/pde.pdf>.
2.Andrews, Larry C., and Ronald L. Phillips. Mathematical techniques for engineers and scientists. Bellingham, Wash.: SPIE Press, 2003. Print.
3."Linearity, Superposition and Classification." math.unl. N.p., n.d. Web. 21 Oct. 2011. <www.math.unl.edu/~scohn1/8423/class.pdf>.
4."CHAPTER 2: The Diffusion Equation." mth.pdx. N.p., n.d. Web. 21 Oct. 2011. <www.mth.pdx.edu/~marek/mth510pde/notes%202.pdf>.
5."Heat Conduction and the Heat Equation." ncsu. N.p., n.d. Web. 21 Oct. 2011. <www4.ncsu.edu/~rsmith/MA573_F09/Heat_Equation.pdf>.
6.Platnaik. Introduction to Differential Equations. PHI Learning Pvt. Ltd.7.Jiji, Latif M. Heat Conduction. 3rd Ed. Springer Publishing. 2009.8.Greenberg, Michael D.. Advanced engineering mathematics. 2nd ed.
Upper Saddle River, N.J.: Prentice Hall, 1998. Print.