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Math for CS Lecture 12 1
Lecture 12
Partial Differential Equations
Boundary Value Problems
Math for CS Lecture 12 2
Contents
1. Partial Differential Equations
2. Boundary Value Problems
3. Differential Operators
4. Cylindrical and Spherical coordinate systems
5. Examples of the Problems
6. Solution of the heat equation
7. Solution of the string equation
Math for CS Lecture 12 3
Partial Derivatives
Consider a function of two or more variables e.g. f(x,y). We can talk about derivatives of such
a function with respect to each of its variables:
The higher order partial derivatives are defined recursively and include the mixed x,y
derivatives:
(1)



 2
)
,
(
)
,
(
lim
)
,
(
0
y
x
f
y
x
f
x
y
x
f
fx











 2
)
,
(
)
,
(
lim
)
,
(
0








y
x
f
y
x
f
y
y
x
f
fy



 2
)
,
(
)
,
(
lim
0











y
x
f
y
x
f
x
f
y
f
f x
x
y
x
xy
Math for CS Lecture 12 4
Partial Differential Equations
Partial differential equation (PDE) is an equation containing an unknown function of two or
more variables and its partial derivatives.
Invention of PDE’s by Newton and Leibniz in 17th century mark the beginning of modern
science. PDE’s arise in the physical problems, both in classical physics and quantum
mechanics.
Orbits of the planets or spaceships, flow of the liquid around a submarine or air around an
airplane, electrical currents in the circuit or processor, and actually majority of the physics
and engineering inspired problems are described by partial differential equations.
Math for CS Lecture 12 5
Boundary Value Problem
Consider the shape of the soap film stretched on approximately horizontal frame. Let
z=h(x,y) be the description of the shape (height) of this film. The tension force, acting on the
unit piece of the surface is proportional to
And equals zero for an equilibrium solution. Let h(x(t),y(t))=g(t) be the parametric
description of the frame. Thus, the following differential equation defines the shape of the
soap film:
This is the Laplace equation with Dirichlet boundary conditions.
2
2
2
2
y
f
x
f





  )
(
)
(
),
(
0
2
2
2
2
t
g
t
y
t
x
f
y
f
x
f







Inside the region
Along the Boundary
Math for CS Lecture 12 6
Differential Operators
In the differential equations, there are several derivatives that occur very often. For example
the vector of first derivatives or gradient of the function:
To clarify the notation of PDE’s and facilitate the calculations, the notation of differential
operators was invented.
Thus, nabla stands for gradient:
The sum of second derivatives of f(x,y,z), formally obtained as the scalar product of two
gradient operators is called a Laplacian:
















z
f
y
f
x
f
f ,
,
(3)
















z
y
x
,
,
























































 2
2
2
2
2
2
2
,
,
,
,
,
z
y
x
z
y
x
z
y
x
(2)
Math for CS Lecture 12 7
Differential Operators 2
The divergence of a vector function (f1(x,y,z), f2(x,y,z), f3(x,y,z)) is the sum of its first
derivatives, or a scalar product of the function with nabla:
The rotor of a vector function (f1(x,y,z), f2(x,y,z), f3(x,y,z)) is the vector product of the
function with nabla:
Several identities can be derived for the operators of gradient, divergence, rotor and
Laplacian.
 
z
f
y
f
x
f
f
f










 3
2
1
,
div
  














































y
f
x
f
z
f
x
f
z
f
y
f
x
f
x
f
x
f
z
y
x
k
j
i
f
f 1
2
1
3
2
3
3
2
1
,
,
)
(
)
(
)
(
rot
(4)
(5)
Math for CS Lecture 12 8
Other Coordinate Systems
We defined the differential operators in Euclidian
coordinates. However, it is sometimes more convenient
to use other systems, like spherical coordinates (r,φ,θ)
for spherically symmetric problems or cylindrical
(ρ,φ,z) for cylindrically symmetrical problems.
Using the identities:
...
...
2
2
x
f
x
f
x
r
r
f
x
f
x
f
x
f
x
f
x
r
r
f
x
f
f
x
x
x
x
x














































Cylindrical coordinates
Math for CS Lecture 12 9
Other Coordinate Systems
We can obtain in cylindrical coordinates
And in spherical:
z
f
f
f
f
f
f
f
f
z
y
x

























cos
1
sin
sin
1
cos
(2)
Spherical coordinates











































f
r
r
f
f
r
f
r
f
r
f
f
r
f
r
f
r
f
f
z
y
x
sin
cos
sin
cos
sin
cos
sin
sin
sin
sin
cos
cos
sin
cos
Math for CS Lecture 12 10
Laplacian in Cylindrical and Spherical systems
We can obtain in cylindrical coordinates
And in spherical:
2
2
2
2
2
2
2
1
1
z
f
f
f
f
f


















2
2
2
2
2
2
2
sin
1
sin
sin
1
1





 

























f
r
f
r
r
f
r
r
r
f
(6)
(7)
Math for CS Lecture 12 11
1. The heat equation, describing the temperature in solid u(x,y,z,t) as a function of
position (x,y,z) and time t:
This equation is derived as follows:
Consider a small square of size δ, shown on
the figure. Its heat capacitance is δ2·q, where
q is the heat capacitance per unit area. The
heat flow inside this square is the difference
of the flows through its four walls. The heat
flow through each wall is:
Example: The Heat Equation
2
/
0 







x
x
u

y
x
x
u
W




 

2
/
0 







x
x
u
2
/
0 







y
y
u
Math for CS Lecture 12 12
Here δ is the size of the square, µ is the heat conductivity
of the body and is the temperature
gradient. The change of the temperature
of the body is the total thermal flow
divided by its heat capacitance:
the last expression is actually the definition of the second derivative, therefore:
The Heat Equation
2
/
1
0 








x
x
u
F
q
y
u
y
u
q
x
u
x
u
q
F
F
F
F
t
u y
y
x
x







































 



2
2
/
2
/
2
2
/
2
/
2
4
3
2
1 0
0
0
0











2
/
2
0 








x
x
u
F
2
/
3
0 








y
y
u
F
2
/
4
0 








y
y
u
F
u
q
t
u
y
u
x
u
q
t
u






















2
2
2
2
(9)
t
u


Math for CS Lecture 12 13
Examples of Physical Equations
2. The vibrating string equation, describing the deviation y(x,t) of the taut string from its
equilibrium y=0 position:
The derivation of this equation is somewhat similar to the heat equation: we consider a small
piece of the string; the force acting on this piece is ; it causes the acceleration of the
piece which is .
3. The Schrödinger equation. This equation defines the wave function of the particle in the
static field, and used, for example to calculate the electron orbits of the atoms.

 2
2
2
)
( 



m
V
E

2
2
2
2
2
x
y
a
t
y





2
2
x
y
k
F



2
2
t
y


(11)
(10)
Math for CS Lecture 12 14
Solution of the Heat Equation
Consider again the Heat Equation:
Let u=XT, where X(x) and T(t); then
In the last equation the left part is function of t, while the right part is the function of x.
Therefore, this equation can only be valid if both parts are constant, say –λ2. Then:
We have chosen a negative constant in order to obtain a bounded solution.
2
2
x
u
c
t
u





X
X
T
T
c
T
X
c
T
X








1
t
c
e
T
T
c
T
2
2







(12)
Math for CS Lecture 12 15
Solution of the Heat Equation 2
Thus, the bounded solution of (12) is a linear combination of the functions from the
parametric family
the solution ax+b corresponds to λ=0.
The specific solution of equation (12) with initial conditions f(0,x) and f(t,x1) f(t,x2) is found
via decomposition of f(0,x) in the basis (13), satisfying f(t,x1) f(t,x2).
x
b
x
a
X
X
X



sin
cos
2






  b
ax
x
b
x
a
e t
c



;
)
sin
cos
(
2

 


(13)
Math for CS Lecture 12 16
Solution of the Heat Equation 3
Boundary and initial conditions restrict the family of these functions:
The limitation of the domain to [-a,a] restricts the functions from a parametric family to a
countable set of 2a periodic functions:
The symmetry (odd or even) of the initial conditions further restricts the basis to sin(..) or
cos(..).
Similarly, the Dirichlet (constant value) or Neuman (zero derivative) boundary conditions
restrict the basis to the functions, satisfying the conditions.


















)
sin
cos
(
2
x
a
x
n
b
x
a
x
n
a
e
t
a
n
c 




Math for CS Lecture 12 17
Example 1
Solve
Given
Solution
The solution consists of functions:
The condition u(0,t)=u(3,t)=0 is fulfilled by
x
x
x
x
u
t
u
t
u


 10
sin
2
8
sin
3
4
sin
5
)
0
,
(
0
)
,
3
(
)
,
0
(





0
,
3
0
,
2 2
2








t
x
x
u
t
u
  b
ax
x
b
x
a
e t



;
)
sin
cos
(
2
2

 


(14)
(15)









 






3
sin
2
3
2 x
n
e
b
t
n
n


(16)
Math for CS Lecture 12 18
Example 1
We need only n=12, 24 and 30 in order to fit f(x,0). The solution is









 






3
sin
2
3
2 x
n
e
b
t
n
n


x
e
x
e
x
e
t
x
f t
t
t


 


10
sin
2
8
sin
3
4
sin
5
)
,
(
2
2
2
200
128
32 




 (17)
Math for CS Lecture 12 19
Solution of the String Equation
The vibrating string equation
Can be solved in the way similar to solution of the heat equation. Substituting
into (14), we obtain
   
 
b
ax
t
c
b
t
c
a
x
b
x
a 


 ;
sin
cos
sin
cos 2
2
1
1 


 



(18)
2
2
2
2
2
x
y
c
t
y





XT
y 
Math for CS Lecture 12 20
Example 2 (1/3)
The taut string equation is fixed at points x=-1 and x=1; f(-1,t)=f(1,t)=0; Its equation of
motion is
Initially it is pulled at the middle, so that
Find out the motion of the string.
Solution:
The solution of (19) is comprised of the functions, obtaining zero values at x=-1 and x=1:
 


























 




}
,
0
{
,
sin
cos
sin
2
)
1
2
(
2
)
1
2
(
2
)
1
2
(
cos
1
N
m
n
t
m
b
t
m
a
x
m
a
t
n
b
t
n
a
x
n
m
m
n
n
n






(19)
2
2
2
2
x
y
c
t
y
















1
0
,
1
0
1
,
1
)
0
,
(
x
x
x
x
x
y
(20)
Math for CS Lecture 12 21
Example 2 (2/3)
Solution (continued):
Moreover, since the initial condition
is symmetric, only the cos(…x) remains in the solution.
The coefficients bn in (20) are zeros, since
Therefore, the solution has the form
(21)











1
0
,
1
0
1
,
1
)
0
,
(
x
x
x
x
x
y
0
)
0
,
(



t
x
y
t
n
x
n
a
t
x
y
n
n 

cos
2
)
1
2
(
cos
)
,
(
0


 


Math for CS Lecture 12 22
Example 2 (3/3)
Where
 
  dx
n
dx
x
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L4 PartialDifferentialEquations-(L1).ppt

  • 1. Math for CS Lecture 12 1 Lecture 12 Partial Differential Equations Boundary Value Problems
  • 2. Math for CS Lecture 12 2 Contents 1. Partial Differential Equations 2. Boundary Value Problems 3. Differential Operators 4. Cylindrical and Spherical coordinate systems 5. Examples of the Problems 6. Solution of the heat equation 7. Solution of the string equation
  • 3. Math for CS Lecture 12 3 Partial Derivatives Consider a function of two or more variables e.g. f(x,y). We can talk about derivatives of such a function with respect to each of its variables: The higher order partial derivatives are defined recursively and include the mixed x,y derivatives: (1)     2 ) , ( ) , ( lim ) , ( 0 y x f y x f x y x f fx             2 ) , ( ) , ( lim ) , ( 0         y x f y x f y y x f fy     2 ) , ( ) , ( lim 0            y x f y x f x f y f f x x y x xy
  • 4. Math for CS Lecture 12 4 Partial Differential Equations Partial differential equation (PDE) is an equation containing an unknown function of two or more variables and its partial derivatives. Invention of PDE’s by Newton and Leibniz in 17th century mark the beginning of modern science. PDE’s arise in the physical problems, both in classical physics and quantum mechanics. Orbits of the planets or spaceships, flow of the liquid around a submarine or air around an airplane, electrical currents in the circuit or processor, and actually majority of the physics and engineering inspired problems are described by partial differential equations.
  • 5. Math for CS Lecture 12 5 Boundary Value Problem Consider the shape of the soap film stretched on approximately horizontal frame. Let z=h(x,y) be the description of the shape (height) of this film. The tension force, acting on the unit piece of the surface is proportional to And equals zero for an equilibrium solution. Let h(x(t),y(t))=g(t) be the parametric description of the frame. Thus, the following differential equation defines the shape of the soap film: This is the Laplace equation with Dirichlet boundary conditions. 2 2 2 2 y f x f        ) ( ) ( ), ( 0 2 2 2 2 t g t y t x f y f x f        Inside the region Along the Boundary
  • 6. Math for CS Lecture 12 6 Differential Operators In the differential equations, there are several derivatives that occur very often. For example the vector of first derivatives or gradient of the function: To clarify the notation of PDE’s and facilitate the calculations, the notation of differential operators was invented. Thus, nabla stands for gradient: The sum of second derivatives of f(x,y,z), formally obtained as the scalar product of two gradient operators is called a Laplacian:                 z f y f x f f , , (3)                 z y x , ,                                                          2 2 2 2 2 2 2 , , , , , z y x z y x z y x (2)
  • 7. Math for CS Lecture 12 7 Differential Operators 2 The divergence of a vector function (f1(x,y,z), f2(x,y,z), f3(x,y,z)) is the sum of its first derivatives, or a scalar product of the function with nabla: The rotor of a vector function (f1(x,y,z), f2(x,y,z), f3(x,y,z)) is the vector product of the function with nabla: Several identities can be derived for the operators of gradient, divergence, rotor and Laplacian.   z f y f x f f f            3 2 1 , div                                                  y f x f z f x f z f y f x f x f x f z y x k j i f f 1 2 1 3 2 3 3 2 1 , , ) ( ) ( ) ( rot (4) (5)
  • 8. Math for CS Lecture 12 8 Other Coordinate Systems We defined the differential operators in Euclidian coordinates. However, it is sometimes more convenient to use other systems, like spherical coordinates (r,φ,θ) for spherically symmetric problems or cylindrical (ρ,φ,z) for cylindrically symmetrical problems. Using the identities: ... ... 2 2 x f x f x r r f x f x f x f x f x r r f x f f x x x x x                                               Cylindrical coordinates
  • 9. Math for CS Lecture 12 9 Other Coordinate Systems We can obtain in cylindrical coordinates And in spherical: z f f f f f f f f z y x                          cos 1 sin sin 1 cos (2) Spherical coordinates                                            f r r f f r f r f r f f r f r f r f f z y x sin cos sin cos sin cos sin sin sin sin cos cos sin cos
  • 10. Math for CS Lecture 12 10 Laplacian in Cylindrical and Spherical systems We can obtain in cylindrical coordinates And in spherical: 2 2 2 2 2 2 2 1 1 z f f f f f                   2 2 2 2 2 2 2 sin 1 sin sin 1 1                                 f r f r r f r r r f (6) (7)
  • 11. Math for CS Lecture 12 11 1. The heat equation, describing the temperature in solid u(x,y,z,t) as a function of position (x,y,z) and time t: This equation is derived as follows: Consider a small square of size δ, shown on the figure. Its heat capacitance is δ2·q, where q is the heat capacitance per unit area. The heat flow inside this square is the difference of the flows through its four walls. The heat flow through each wall is: Example: The Heat Equation 2 / 0         x x u  y x x u W        2 / 0         x x u 2 / 0         y y u
  • 12. Math for CS Lecture 12 12 Here δ is the size of the square, µ is the heat conductivity of the body and is the temperature gradient. The change of the temperature of the body is the total thermal flow divided by its heat capacitance: the last expression is actually the definition of the second derivative, therefore: The Heat Equation 2 / 1 0          x x u F q y u y u q x u x u q F F F F t u y y x x                                             2 2 / 2 / 2 2 / 2 / 2 4 3 2 1 0 0 0 0            2 / 2 0          x x u F 2 / 3 0          y y u F 2 / 4 0          y y u F u q t u y u x u q t u                       2 2 2 2 (9) t u  
  • 13. Math for CS Lecture 12 13 Examples of Physical Equations 2. The vibrating string equation, describing the deviation y(x,t) of the taut string from its equilibrium y=0 position: The derivation of this equation is somewhat similar to the heat equation: we consider a small piece of the string; the force acting on this piece is ; it causes the acceleration of the piece which is . 3. The Schrödinger equation. This equation defines the wave function of the particle in the static field, and used, for example to calculate the electron orbits of the atoms.   2 2 2 ) (     m V E  2 2 2 2 2 x y a t y      2 2 x y k F    2 2 t y   (11) (10)
  • 14. Math for CS Lecture 12 14 Solution of the Heat Equation Consider again the Heat Equation: Let u=XT, where X(x) and T(t); then In the last equation the left part is function of t, while the right part is the function of x. Therefore, this equation can only be valid if both parts are constant, say –λ2. Then: We have chosen a negative constant in order to obtain a bounded solution. 2 2 x u c t u      X X T T c T X c T X         1 t c e T T c T 2 2        (12)
  • 15. Math for CS Lecture 12 15 Solution of the Heat Equation 2 Thus, the bounded solution of (12) is a linear combination of the functions from the parametric family the solution ax+b corresponds to λ=0. The specific solution of equation (12) with initial conditions f(0,x) and f(t,x1) f(t,x2) is found via decomposition of f(0,x) in the basis (13), satisfying f(t,x1) f(t,x2). x b x a X X X    sin cos 2         b ax x b x a e t c    ; ) sin cos ( 2      (13)
  • 16. Math for CS Lecture 12 16 Solution of the Heat Equation 3 Boundary and initial conditions restrict the family of these functions: The limitation of the domain to [-a,a] restricts the functions from a parametric family to a countable set of 2a periodic functions: The symmetry (odd or even) of the initial conditions further restricts the basis to sin(..) or cos(..). Similarly, the Dirichlet (constant value) or Neuman (zero derivative) boundary conditions restrict the basis to the functions, satisfying the conditions.                   ) sin cos ( 2 x a x n b x a x n a e t a n c     
  • 17. Math for CS Lecture 12 17 Example 1 Solve Given Solution The solution consists of functions: The condition u(0,t)=u(3,t)=0 is fulfilled by x x x x u t u t u    10 sin 2 8 sin 3 4 sin 5 ) 0 , ( 0 ) , 3 ( ) , 0 (      0 , 3 0 , 2 2 2         t x x u t u   b ax x b x a e t    ; ) sin cos ( 2 2      (14) (15)                  3 sin 2 3 2 x n e b t n n   (16)
  • 18. Math for CS Lecture 12 18 Example 1 We need only n=12, 24 and 30 in order to fit f(x,0). The solution is                  3 sin 2 3 2 x n e b t n n   x e x e x e t x f t t t       10 sin 2 8 sin 3 4 sin 5 ) , ( 2 2 2 200 128 32       (17)
  • 19. Math for CS Lecture 12 19 Solution of the String Equation The vibrating string equation Can be solved in the way similar to solution of the heat equation. Substituting into (14), we obtain       b ax t c b t c a x b x a     ; sin cos sin cos 2 2 1 1         (18) 2 2 2 2 2 x y c t y      XT y 
  • 20. Math for CS Lecture 12 20 Example 2 (1/3) The taut string equation is fixed at points x=-1 and x=1; f(-1,t)=f(1,t)=0; Its equation of motion is Initially it is pulled at the middle, so that Find out the motion of the string. Solution: The solution of (19) is comprised of the functions, obtaining zero values at x=-1 and x=1:                                   } , 0 { , sin cos sin 2 ) 1 2 ( 2 ) 1 2 ( 2 ) 1 2 ( cos 1 N m n t m b t m a x m a t n b t n a x n m m n n n       (19) 2 2 2 2 x y c t y                 1 0 , 1 0 1 , 1 ) 0 , ( x x x x x y (20)
  • 21. Math for CS Lecture 12 21 Example 2 (2/3) Solution (continued): Moreover, since the initial condition is symmetric, only the cos(…x) remains in the solution. The coefficients bn in (20) are zeros, since Therefore, the solution has the form (21)            1 0 , 1 0 1 , 1 ) 0 , ( x x x x x y 0 ) 0 , (    t x y t n x n a t x y n n   cos 2 ) 1 2 ( cos ) , ( 0      
  • 22. Math for CS Lecture 12 22 Example 2 (3/3) Where     dx n dx x n an       1 0 2 1 0 2 1 2 cos 2 ) 1 ( 2 1 2 cos 2  

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