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Numerical Heat Transfer, Part B: Fundamentals
An International Journal of Computation and Methodology
Volume 69, 2016 - Issue 4
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Original Articles

To recover heat source G(x) + H(t) by using the homogenized function and solving rectangular differencing equations

Pages 351-363 | Received 24 Jun 2015, Accepted 10 Sep 2015, Published online: 22 Mar 2016
 

ABSTRACT

For recovering an unknown heat source F(x, t) = G(x) + H(t) in the heat conduction equation, we develop a homogenized function method and the expansion methods by polynomials or eigenfunctions, which can solve the inverse heat source recovery problem by using collocation technique. Because the initial condition/boundary conditions/supplementary condition are satisfied automatically and a rectangular differencing technique is developed, a middle-scale linear system is sufficient to determine the expansion coefficients. After deriving a multiscale postconditioning matrix, the present methods converge very quickly, and are accurate and stable against large noise, as verified by numerical tests.

Nomenclature

A=

coefficient matrix in Eq. (26)

b=

right-hand side in Eq. (26)

b1=

:= AT b

B=

new coefficient matrix in Eq. (36)

cij=

coefficients in Pascal polynomial and eigenfunctions

ck=

vectorized of cij

c=

n-dimensional vector of coefficients

D=

:= AT A

f(x)=

initial temperature

F(x, t)=

heat source

g(x)=

final temperature

G(x)=

space-dependent heat source

H(t)=

time-dependent heat source

=

length of rod

m=

m − 1 the highest order of Pascal polynomial

m=

m × m terms of eigenfunctions

m1=

number of collocation points on a horizontal line

m2=

number of collocation points on a vertical line

n=

:= m(m + 1)/2 or m2

P=

postconditioning matrix in Eq. (35)

R(x)=

random function

R(i)=

random number

t=

time

tf=

final time

ti=

:= itf/m2

u(x, t)=

temperature

u(t)=

right-boundary temperature

u0(t)=

left-boundary temperature

v(x, t)=

:= u(x, t) − w(x, t)

w(x, t)=

homogenized function

x=

space variable

xi=

:= iℓ/m1

ϵ=

converegnce criterion

σ=

level of noise

Subscripts and superscripts=
i=

index

j=

index

k=

index

m=

index

T=

transpose

Nomenclature

A=

coefficient matrix in Eq. (26)

b=

right-hand side in Eq. (26)

b1=

:= AT b

B=

new coefficient matrix in Eq. (36)

cij=

coefficients in Pascal polynomial and eigenfunctions

ck=

vectorized of cij

c=

n-dimensional vector of coefficients

D=

:= AT A

f(x)=

initial temperature

F(x, t)=

heat source

g(x)=

final temperature

G(x)=

space-dependent heat source

H(t)=

time-dependent heat source

=

length of rod

m=

m − 1 the highest order of Pascal polynomial

m=

m × m terms of eigenfunctions

m1=

number of collocation points on a horizontal line

m2=

number of collocation points on a vertical line

n=

:= m(m + 1)/2 or m2

P=

postconditioning matrix in Eq. (35)

R(x)=

random function

R(i)=

random number

t=

time

tf=

final time

ti=

:= itf/m2

u(x, t)=

temperature

u(t)=

right-boundary temperature

u0(t)=

left-boundary temperature

v(x, t)=

:= u(x, t) − w(x, t)

w(x, t)=

homogenized function

x=

space variable

xi=

:= iℓ/m1

ϵ=

converegnce criterion

σ=

level of noise

Subscripts and superscripts=
i=

index

j=

index

k=

index

m=

index

T=

transpose

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