Numerical simulation and optimization of the multi-stage air/gas supply system in a coke oven battery with 7.1 m coking chambers

ABSTRACT

3-D numerical simulations based on diffusion combustion technology were employed to optimize the multi-stage air/gas supply system in a coke oven battery with 7.1 m coking chambers. In the heating flues, the Eddy-Dissipation Concept (EDC) model and the ideal gas model were utilized to numerically investigate diffusion combustion. What is more, the radiation between the flue gas and the silicon brick was calculated using the Discrete Ordinates (DO) model. After validating the reliability of the model with field-measured data, insights into the temperature field and gas flow in the heating flue, and heat flux distribution over the heating wall were obtained. To characterize the vertical heating uniformity, an index of the standard deviation of the heat flux over the vertical heating walls was proposed. By optimizing the multi-stage air/gas supply design of heating flues, the vertical heating uniformity was improved by 60% according to the index values. The approach developed in this work can be a useful tool for the design of large-capacity coke oven batteries at different scales.

KEYWORDS:

• Coke oven
• CFD
• staged gas supply
• heating flue
• vertical heating uniformity

Disclosure statement

In accordance with Taylor & Francis policy and Hongyuan Wei’s ethical obligation as a researcher, Hongyuan Wei is reporting that he received funding from Sinosteel Equipment & Engineering Co., Ltd. that may be affected by the research reported in the enclosed paper. Hongyuan Wei has disclosed those interests fully to Taylor & Francis, and he has in place an approved plan for managing any potential conflicts arising from that involvement.

Nomenclature

$\mathit{a}$	=	absorption coefficient (${\mathrm{m}}^{-1}$)
$\mathit{f}$	=	volume fraction of fine scales in the EDC model
${\mathbf{F}}_{\mathrm{s}}$	=	force vector (N)
$\mathit{h}$	=	thermal enthalpy ($\mathrm{J}\cdot \mathrm{k}{\mathrm{g}}^{-1}\cdot {\mathrm{K}}^{-1}$)
$\mathit{I}$	=	radiation intensity (cd)
${\mathbf{J}}_j$	=	diffusion flux of species j
$\mathit{k}$	=	rate constant
$\mathit{n}$	=	refractive index
$\mathit{p}$	=	the static pressure (Pa)
$p^{\ast }$	=	the sum of the partial pressures of all absorbing gases (Pa)
$\mathit{R}$	=	gas-law constant ($\mathrm{J}\cdot \mathrm{mo}{\mathrm{l}}^{-1}\cdot {\mathrm{K}}^{-1}$)
$R_j$	=	source term of species j due to chemical reaction ($\mathrm{kg}\cdot {\mathrm{m}}^{-3}\cdot {\mathrm{s}}^{-1}$)
$\vec{r}$	=	position vector
$\mathit{s}$	=	path length (m)
$\vec{s}$	=	direction vector
${\vec{s}}^{\prime }$	=	scattering direction vector
$S_h$	=	heat source term ($\mathrm{J}\cdot {\mathrm{m}}^{-3}\cdot {\mathrm{s}}^{-1}$)
$\mathit{t}$	=	time (s)
$\mathit{T}$	=	temperature (K)
$\mathbf{u}$	=	velocity vector ($\mathrm{m}\cdot {\mathrm{s}}^{-1}$)
$Y_j$	=	mass fraction of species j
$Y_j^{\ast }$	=	the fine-scale species mass fraction in the EDC model
Greek Letters	=
$\mathit{\epsilon }$	=	emissivity
${\kappa }_j$	=	absorption coefficient of the $j^{\mathit{th}}$ gray gas
$\mathit{\lambda }$	=	thermal conductivity ($\mathrm{W}\cdot {\mathrm{m}}^{-1}\cdot {\mathrm{K}}^{-1}$)
$\mathit{\mu }$	=	dynamic viscosity ($\mathrm{Pa}\cdot \mathrm{s}$)
$\mathit{\rho }$	=	density ($\mathrm{k}\mathit{g}\cdot {\mathrm{m}}^{-3}$)
$\mathit{\sigma }$	=	Stefan Boltzmann constant ($5.672\times {10}^{-8}\mathrm{W}\cdot {\mathrm{m}}^{-2}\cdot {\mathrm{K}}^{-4}$)
${\sigma }_s$	=	scattering coefficient (${\mathrm{m}}^{-1}$)
$\mathrm{\Phi }$	=	phase function
${\mathrm{\Omega }}^{\prime }$	=	solid angle
Subscripts	=
eff	=	effective
f	=	forward reaction
j	=	species j
r	=	reverse reaction

Additional information

Funding

This work was supported by Sinosteel Equipment & Engineering Co., Ltd. under Grant No. 006220206.