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Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 72, 2017 - Issue 10
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Original Articles

Estimation of slab surface radiative emissivities by solving an inverse coupled conduction, convection, and radiation problem

, , &
Pages 765-779 | Received 02 Aug 2017, Accepted 10 Oct 2017, Published online: 06 Dec 2017
 

ABSTRACT

Slab surface radiative emissivities severely affect the radiative heat transfer in a reheating furnace, as well as the slabs’ coupled conduction, convection, and radiation. Accurate evaluation of these parameters is of significance to ensure the high accuracy of the mathematical model for a reheating furnace, which is beneficial to the energy saving. However, it is difficult to directly and accurately measure these parameters. In this article, slab surface radiative emissivities in a reheating furnace are estimated by solving a nonlinear inverse problem, which is an inverse coupled conduction, convection, and radiation problem. An efficient and accurate gradient method, i.e., Levenberg–Marquardt algorithm, is applied to obtain the solution of the inverse problem. First, a finite difference method and the complex-variable-differentiation method are used for sensitivity analysis, and the inversion accuracy coupled with the efficiency is demonstrated. Then, effects of initial guesses, measurement errors, and measurement locations on estimated slab surface radiative emissivities are investigated in detail. Finally, conclusions are drawn based on the results and analysis.

Nomenclature

A=

area, m2

c=

mass specific heat, J/ (kg K)

d=

half depth of a slab, m

Eb=

blackbody emissive power, W/m2

F=

objective function

f=

nonlinear function

G=

gas

=

total radiative exchange area of G to S, m2

H=

imaginary part

h=

convective heat coefficient, W/(m2 K)

=

total radiative exchange area of G to W, m2

J=

sensitivity coefficients matrix

i, j=

no. of the inverted parameter

K=

total number of inverted parameters

k=

kth inverted parameter

M=

total number of measured temperatures

n=

power

P=

iteration number

S=

slab

=

total radiative exchange area of S to G, m2

=

total radiative exchange area of S to W, m2

T=

temperature, K

t=

temperature,°C

W=

wall

=

total radiative exchange area of W to G, m2

=

total radiative exchange area of W to S, m2

x=

vector of inverted parameters

Greek symbols=
α=

absorptivity

δ=

updated vector of inverted parameters

ε=

emissivity

ζ=

measurement error

η=

random number

μ=

the damping factor

ξ=

tolerance

ρ=

density, kg/ m3

φ=

view factor

Subscripts=
a=

air

b=

bottom

c=

convection

com=

combustion

exact=

exact

g=

medium/gas

r=

radiation

s=

surface

store=

stored

u=

upper

w=

wall

Superscripts=
*=

measured

Nomenclature

A=

area, m2

c=

mass specific heat, J/ (kg K)

d=

half depth of a slab, m

Eb=

blackbody emissive power, W/m2

F=

objective function

f=

nonlinear function

G=

gas

=

total radiative exchange area of G to S, m2

H=

imaginary part

h=

convective heat coefficient, W/(m2 K)

=

total radiative exchange area of G to W, m2

J=

sensitivity coefficients matrix

i, j=

no. of the inverted parameter

K=

total number of inverted parameters

k=

kth inverted parameter

M=

total number of measured temperatures

n=

power

P=

iteration number

S=

slab

=

total radiative exchange area of S to G, m2

=

total radiative exchange area of S to W, m2

T=

temperature, K

t=

temperature,°C

W=

wall

=

total radiative exchange area of W to G, m2

=

total radiative exchange area of W to S, m2

x=

vector of inverted parameters

Greek symbols=
α=

absorptivity

δ=

updated vector of inverted parameters

ε=

emissivity

ζ=

measurement error

η=

random number

μ=

the damping factor

ξ=

tolerance

ρ=

density, kg/ m3

φ=

view factor

Subscripts=
a=

air

b=

bottom

c=

convection

com=

combustion

exact=

exact

g=

medium/gas

r=

radiation

s=

surface

store=

stored

u=

upper

w=

wall

Superscripts=
*=

measured

Additional information

Funding

This work was supported by the National Nature Science Foundation of China [Grant Number 51576026] and China Postdoctoral Science Foundation [Grant Number 2016M601305].

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