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Modelling and analysis of an endothermic reacting counter-current flow

Published online by Cambridge University Press:  29 September 2022

Ellen K. Luckins*
Affiliation:
Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
James M. Oliver
Affiliation:
Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
Colin P. Please
Affiliation:
Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
Benjamin M. Sloman
Affiliation:
Elkem ASA, Technology, Fiskaaveien 100, Kristiansand 4621, Norway
Robert A. Van Gorder
Affiliation:
Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin 9054, New Zealand
*
†Email address for correspondence: luckins@maths.ox.ac.uk

Abstract

We study the endothermic reaction and flow of a granular solid reactant, where energy for the reaction is provided by a counter-current flow of hot gases through the porous reactant bed. Research into reacting flows typically focusses on exothermic combustion processes. However, endothermic processes are common in the metallurgy industry, including the production of cement, silicon and rutile titanium dioxide. Several common features are observed in experimental and numerical studies of these processes, including critical temperatures of the reactant at which the chemical reaction begins, and regions of the reactor with uniform reactant temperature. Motivated specifically by the processes in a silicon furnace, we analyse a model of endothermic, reacting counter-current flow using the method of matched asymptotic expansions. Assuming the Péclet number in the solid is large, we explore the full range of values for the dimensionless inter-phase heat-transfer rate, finding six distinguished limits. In all limits, we find a diffusive boundary layer in which there is a fast chemical reaction rate due to the high temperatures, analogous to exothermic flame fronts. Outside this region, the counter-current flow is crucial to the chemical processes. For intermediate values of the heat-transfer rate, we find the same qualitative properties as those observed across the metallurgy industry, and we quantify the dependence of these properties on the flow rate and heat-transfer rate. In the limit of large heat-transfer coefficient, we derive the single-temperature limit, in which the solution structure is dependent on the direction of net heat flux through the domain.

Information

Type
JFM Papers
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1.Schematic of the dimensional model domain $x\in [s,x_0]$, with granular solid (grey) moving right-to-left as shown by the black arrows, surrounded by gas (pale yellow) flowing left-to-right as shown by the red arrows. The solid particles become smaller nearer to the free boundary $x=s(t)$, as solid mass is reacted away. The boundary conditions are shown at $x=s(t)$ and $x=x_0$.

Figure 1

Figure 2.Schematics of the different asymptotic solution structures (in steady state for cases D–F) for increasing $\mu$. In each case, the solutions, $T_s$ (red curves), $T_g$ (green curves) and $C$ (blue curves) are illustrated in the domain $x\in [s(t),1]$, with boundary layers and transition layers shown by the grey regions.

Figure 2

Figure 3.The variation of $\eta /A$ with $\delta \mu$, according to (3.2). The curve approaches the origin as $\delta \mu \rightarrow 0$, and becomes unbounded as $\delta \mu \rightarrow 1$.

Figure 3

Figure 4.Schematic of the solution structure in case A: $\mu =0$.

Figure 4

Table 1.Summary of the asymptotic regions of the domain, and the changes of variable in these regions, for case A: $\mu =0$.

Figure 5

Figure 5.Schematic of the solution structure in case B: $\mu =O(\eta _B)$.

Figure 6

Table 2.Summary of the asymptotic regions of the domain, and the changes of variable in these regions, for case B: $\mu =O(\eta _B)$.

Figure 7

Figure 6.Schematic of the solution structure in case C: $\mu =O(1)$.

Figure 8

Table 3.Summary of the asymptotic regions of the domain, and the changes of variable in these regions, for case C: $\mu =O(1)$.

Figure 9

Figure 7.Schematics of the steady-state solution structures in case D: $\mu =O(1)$. (a) Case Da, $KF_*<1$. (b) Case Db, $KF_*>1$.

Figure 10

Table 4.Summary of the asymptotic regions of the domain, and the changes of variable in these regions, for the steady-state cases D (a and b): $-\log (\eta _D)\ll \mu \ll \delta ^{-1}$.

Figure 11

Figure 8.Phase plane for the steady-state system (7.39a,b). Nullclines are in black and trajectories in blue. The green dashed curve is the line $\tau _g^{0}=\tau _g^{limit}(\tau _s^{0})$ given by (7.42). We take physically relevant values $\gamma =A=1$ and $KF_*=1$, so that $c_1=2$ and $c_2=5.44$.

Figure 12

Figure 9.Schematic diagrams illustrating the asymptotic solution structures, in steady state, for case E, where $\mu =O(\delta ^{-1})$. Time-dependent solutions may have these, or other structures. (a) Case Ea, with $Kf^{\infty }<1$. (b) Case Eb, with $Kf^{\infty }>1$.

Figure 13

Table 5.Summary of the notation in each asymptotic region in the cases Ea ($\mu =O(\delta ^{-1}$), $Kf^{\infty }<1$) and Eb ($\mu =O(\delta ^{-1}$), $Kf^{\infty }>1$), corresponding to the diagrams in figure 9.

Figure 14

Figure 10.Characteristic diagrams in the cases $V>0>U$ and $V<0< U$, for different sizes of $\dot {s}$. The red characteristics mark the boundaries between regions with the characteristics originating at different boundaries of the domain, or at the initial data. In general, we expect to have different dominant behaviour on either side of these bounding characteristics.

Figure 15

Figure 11.Schematic in a case where characteristics originate at both $x=1$ and $x=s(t)$ (with initial condition $T=T^{in}$ for $x>s$).

Figure 16

Figure 12.Schematic diagrams illustrating the asymptotic solution structures, in steady state, for case F $\mu \gg \delta ^{-1}$. (a) Case Fa: $\mu \gg \delta ^{-1}$, with $K(f_*+1-C_*)<1$. (b) Case Fb: $\mu \gg \delta ^{-1}$, with $K(f_*+1-C_*) >1$.

Figure 17

Table 6.Summary of the notation in each asymptotic region in the cases Fa ($\mu \gg \delta ^{-1}$, $K(f_*+1-C_*)<1$) and Fb ($\mu \gg \delta ^{-1}$, $K(f_*+1-C_*)>1$), corresponding to the diagrams in figure 12.

Figure 18

Figure 13.Numerical solutions of the region-I problem (10.1) for case A or B, taking parameter values $\gamma =1$, $A=1$, $C_*=0.2$ and $\rho =0.25$. (a) Variation of $\dot{s}_0$ with $s_0$. (b) Quasi-steady solutions.

Figure 19

Figure 14.Numerical solutions of (10.1) for case A or B, varying the parameter values $A$ (a,b) and $\gamma$ (c,d). Unless otherwise stated, we take parameter values $\gamma =1$, $A=1$, $C_*=0.2$ and $\rho =0.25$. (a) Variation of $\dot{s}_0$ with $s_0$, varying $A$. (b) Steady-state solutions, varying $A$. (c) Variation of $\dot{s}_0$ with $s_0$, varying $\gamma$. (d) Steady-state solutions, varying $\gamma$.

Figure 20

Figure 15.Numerical solutions of (10.1) for case C, varying the parameter values $f_*$ (a,b) and $\mu$ (c,d). Unless otherwise stated, we take parameter values $\gamma =1$, $A=1$, $C_*=0.2$, $\rho =0.25$, $K=0.66$, $f_*=1$ and $\mu =1$. (a) Steady-state solutions, varying $f_*$. (b) Steady-state solution parameters, varying $f_*$. (c) Steady-state solutions, varying $\mu$. (d) Steady-state solution parameters, varying $\mu$.

Figure 21

Figure 16.Steady-state numerical solutions of (10.1) for case D, varying $f_*$. The vertical black line in (b) at $f_*=C_*-1+1/K$ separates case Da (to the left) and case Db (to the right). We take the other parameter values $\gamma =1$, $A=1$, $C_*=0.2$, $\rho =0.25$ and $K=0.66$. (a) Steady-state solutions, varying $f_*$. (b) Steady-state solution parameters, varying $f_*$.

Figure 22

Figure 17.Steady-state numerical solutions of (10.8) for cases Ea and Eb, varying the parameter values $f_*$ (a,c) and $M$ (b,d). Unless otherwise stated, we take parameter values $\gamma =1$, $A=1$, $C_*=0.2$, $\rho =0.25$, $K=0.66$, $M=1$ and $f_*=0.3$ in case Ea, but $f_*=1.5$ in case Eb. (a) Steady states in case Ea, varying $f_*$. (b) Steady states in case Ea, varying $M$. (c) Steady states in case Eb, varying $f_*$. (d) Steady states in case Eb, varying $M$. (e) Steady-state $s_0$, varying $f_*$. ( f) Steady-state $s_0$, varying $M$.

Figure 23

Figure 18.Steady-state numerical solutions of (10.10) for cases Fa and Fb, varying the parameter $f_*$. We take the other parameter values $\gamma =1$, $A=1$, $C_*=0.2$, $\rho =0.25$, $K=0.66$. (a) Steady states in cases Fa and Fb, varying $f_*$. (b) Steady-state $s_0$, varying $f_*$.

Figure 24

Figure 19.Numerical steady-state solutions of (2.12) (dotted lines) and composite solutions as derived in §§ 4–7 (solid lines), with $T_s$ (red curves), $T_g$ (green curves) and $C$ (blue curves). The insets show the same solutions, near the free boundary $x=s$. In all cases we take $\delta =10^{-4}$, $A=\gamma =1$, $\rho =0.25$, $K=0.66$, $C_*=0.2$, $T^{in}=0.01$ and, unless otherwise stated, $f_*=1$. (a) Case A, $\mu =0$. (b) Case B, $\mu =\eta _B=0.09$. (c) Case C, $\mu =0.1$. (d) Case C, $\mu =1$. (e) Case Da, $\mu =25$, $f_*=0.3$. ( f) Case Db, $\mu =25$, $f_*=1.2$.

Figure 25

Figure 20.Numerical steady-state solutions of (2.12) (dotted lines) and composite solutions as derived in §§ 8–9 (solid lines), with $T_s$ (red curves), $T_g$ (green curves) and $C$ (blue curves). The insets show the same solutions, near the free boundary $x=s$. In all cases we take $\delta =10^{-4}$, $A=\gamma =1$, $\rho =0.25$, $K=0.66$, $C_*=0.2$ and $T^{in}=0.01$. (a) Case Ea, $\mu =\delta ^{-1}$, $f_*=0.3$. (b) Case Eb, $\mu =\delta ^{-1}$, $f_*=1.2$. (c) Case Fa, $\mu =10^{3}\delta ^{-1}$, $f_*=0.3$. (d) Case Fb, $\mu =10^{3}\delta ^{-1}$, $f_*=1.2$.