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Numerical Heat Transfer, Part B: Fundamentals
An International Journal of Computation and Methodology
Volume 73, 2018 - Issue 1
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Original Articles

Numerically solving twofold ill-posed inverse problems of heat equation by the adjoint Trefftz method

ORCID Icon, &
Pages 48-61 | Received 25 Oct 2017, Accepted 12 Dec 2017, Published online: 16 Jan 2018
 

ABSTRACT

The inverse problem endowing with multiple unknown functions gradually becomes an important topic in the field of numerical heat transfer, and one fundamental problem is how to use limited minimal data to solve the inverse problem. With this in mind, in the present article we search the solution of a general inverse heat conduction problem when two boundary data on the space-time boundary are missing and recover two unknown temperature functions with the help of a few extra measurements of temperature data polluted by random noise. This twofold ill-posed inverse heat conduction problem is more difficult than the backward heat conduction problem and the sideways heat conduction problem, both with one unknown function to be recovered. Based on a stable adjoint Trefftz method, we develop a global boundary integral equation method, which together with the compatibility conditions and some measured data can be used to retrieve two unknown temperature functions. Several numerical examples demonstrate that the present method is effective and stable, even for those of strongly ill-posed ones under quite large noises.

Nomenclature

A=

coefficient matrix in (Eq. 9)

b1=

:= ATe

aj, bj=

coefficients in Fourier series

ck=

coefficients in polynomial expansion

c=

n-dimensional vector of coefficients

D=

:= ATA

e=

the right-hand side in (Eq. 9)

f(x)=

initial temperature

g(t)=

right boundary temperature

=

boundary temperatures

h(x)=

final time temperature

=

heat operator

*=

adjoint heat operator

=

length of rod

m0=

the number of adjoint Trefftz functions

=

the number of coefficients

m3=

the number of measured data

n=

the number of total coefficients

nq=

the number of linear equations

s=

level of noise

t=

time

tf=

final time

ti=

u(x, t)=

temperature

vk(x, t)=

adjoint Trefftz functions

x=

space variable

xi=

:= iℓ∕(m3+1)

Greek symbols=
ε=

convergence criterion

Subscripts and superscripts=
i=

index

j=

index

k=

index

m=

index

T=

transpose

Γ=

boundary contour

Ω=

domain

Nomenclature

A=

coefficient matrix in (Eq. 9)

b1=

:= ATe

aj, bj=

coefficients in Fourier series

ck=

coefficients in polynomial expansion

c=

n-dimensional vector of coefficients

D=

:= ATA

e=

the right-hand side in (Eq. 9)

f(x)=

initial temperature

g(t)=

right boundary temperature

=

boundary temperatures

h(x)=

final time temperature

=

heat operator

*=

adjoint heat operator

=

length of rod

m0=

the number of adjoint Trefftz functions

=

the number of coefficients

m3=

the number of measured data

n=

the number of total coefficients

nq=

the number of linear equations

s=

level of noise

t=

time

tf=

final time

ti=

u(x, t)=

temperature

vk(x, t)=

adjoint Trefftz functions

x=

space variable

xi=

:= iℓ∕(m3+1)

Greek symbols=
ε=

convergence criterion

Subscripts and superscripts=
i=

index

j=

index

k=

index

m=

index

T=

transpose

Γ=

boundary contour

Ω=

domain

Additional information

Funding

The Thousand Talents Plan of China under the Grant Number A1211010 and the Fundamental Research Funds for the Central Universities under the Grant Number 2017B05714 for the financial support to the first author are highly appreciated. The Natural Science Foundation of Shandong Province of China under the Grant Number ZR2017BA003 and the Doctoral Research Foundation of Shandong University of Technology under the Grant Number 4041/416031 for the financial support to the second author are highly appreciated.

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