Chapter 5: Isothermal Reactor Design: Conversion


Topics

  1. Algorithm for Isothermal Reactor Design
  2. Applications/Examples of CRE Algorithm
  3. Reversible Reactions
  4. ODE (Polymath) Solutions to CRE Problems
  5. General Guidelines for California Problems
  6. PBR with Pressure Drop
  7. Engineering Analysis

Algorithm for Isothermal Reactor Design

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For the $5^{th}$ edition $\frac{P}{P_o}$ equals $p$ i.e. $p = \frac{P}{P_o}$. In the $4^{th}$ and earlier editions $y = \frac{P}{P_o}$




  1. Mole Balance and Design Equation
  2. Rate Law
  3. Stoichiometry
  4. Combine
  5. Evaluate
    1. Graphically (Chapter 2 plots)
    2. Numerical (Quadrature Formulas Chapter 2 and appendices)
    3. Analytical (Integral Tables in Appendix)
    4. Software Packages (Appendix - Polymath)
Diagram illustrating the algorithm for isothermal reactors with a French menu analogy. It outlines the four key steps: 1) Mole Balances for PFR, CSTR, and Batch; 2) Rate Laws including equations for reaction rates; 3) Stoichiometry for flow and batch systems with constant or variable rates for liquids and gases; and 4) Combine the mole balance, rate law, and stoichiometry. Integrations for constant temperature and pressure result in an equation for reactor volume.

French Menu Analogy                                          



Example: The elementary liquid phase reaction

\(2A \rightarrow B\)

is carried out isothermally in a CSTR. Pure A enters at a volumetric flow rate of 25 dm3/s and at a concentration of 0.2 mol/dm3.

What CSTR volume is necessary to achieve a 90% conversion when k = 10 dm3/(mol*s)?


Mole Balance

\(V = \frac{F_{A0}X}{-r_A}\)


Rate Law

\(-r_A = kC_A^2\)


Stoichiometry

liquid phase (v = vo)

\(F_{A0} = v_0C_{A0}\)

\(F_A = vC_A = v_0C_A\)

\(C_A = \frac{F_A}{v} = \frac{F_A}{v_0} = \frac{F_{A0}(1 - X)}{v_0}\)

\(C_A = C_{A0}(1 - X)\)



Combine

\(V = \frac{v_0 C_{A0} X}{kC_{A0}^2 (1 - X)^2} = \frac{v_0 X}{kC_{A0} (1 - X)^2}\)


Evaluate

at X = 0.9,

\(V = \frac{25 \, \mathrm{dm^3/s} \cdot (0.90)}{\left(10 \, \mathrm{dm^3/(mol \cdot s)}\right) \cdot \left(0.2 \, \mathrm{mol/dm^3}\right) \cdot (1 - 0.9)^2}\)

V = 1125 dm3

Space Time

\(\tau = \frac{V}{v_o} = \frac{1125 \, \mathrm{dm^3}}{25 \, \mathrm{dm^3/s}} = 45 \, \mathrm{s}\)


Here are some links to example problems. You could also use these problems as self tests.

Critical Critical Thinking Questions for CSTR


Videos


The following humorous videos were made by Professor Lane's 2008 Chemical Reaction Engineering class at the University of Alabama, Tuscaloosa.



Applications/Examples of the CRE Algorithm

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Gas Phase Elementary Reaction

2A → B

Additional Information:

  • Only A is fed
  • P0 = 8.2 atm
  • T0 = 500 K
  • CA0 = 0.2 mol/dm3
  • k = 0.5 dm3/mol-s
  • vo = 2.5 dm3/s
Tip


Solve for X = 0.9

Applying the algorithm to the above reaction occurring in a Batch, CSTR, and PFR.


Batch CSTR PFR
Mole Balance:
\( t = N_{A0} \int_{0}^{X} \frac{dX}{-r_A} \)
Mole Balance:
\( V = \frac{F_{A0} X}{-r_A} \)
Mole Balance:
\( t = F_{A0} \int_{0}^{X} \frac{dX}{-r_A} \)
Rate Law:
\( -r_A = kC_A^2 \)
Gas: \( V = V_0 \)
(e.g., constant volume steel container)
Rate Law:
\( -r_A = kC_A^2 \)
Gas: \( T = T_0, P = P_0 \)
Rate Law:
\( -r_A = kC_A^2 \)
Gas: \( T = T_0, P = P_0 \)
Stoichiometry:

\( C_A = \frac{N_A}{V} = \frac{N_{A0}(1 - X)}{V_0} \)

\( C_A = C_{A0}(1 - X) \)

\( C_B = \frac{N_B}{V} = \frac{N_{A0} \left( + \frac{1}{2} X \right)}{V_0} \)

\( C_B = \frac{C_{A0} X}{2} \)

Stoichiometry:

\(\text{Per Mole of A:}\)

\(\text{A} \rightarrow \frac{\text{B}}{2}\)

\(\varepsilon = 1.0 \left( \frac{1}{2} - 1 \right) = -0.5\)

\(C_A = \frac{F_A}{\nu} = \frac{F_{A0}(1 - X)}{\nu_0(1 + \varepsilon X)}\)

\(C_A = C_{A0} \frac{(1 - X)}{(1 + \varepsilon X)}\)

\(C_B = \frac{F_B}{\nu} = \frac{F_{A0}\left(\frac{1}{2}X\right)}{\nu_0(1 + \varepsilon X)}\)

\(C_B = \frac{C_{A0}X}{2(1 + \varepsilon X)}\)

Stoichiometry:

\(\text{Per Mole of A:}\)

\(\text{A} \rightarrow \frac{\text{B}}{2}\)

\(\varepsilon = 1.0 \left( \frac{1}{2} - 1 \right) = -0.5\)

\(C_A = \frac{F_A}{\nu} = \frac{F_{A0}(1 - X)}{\nu_0(1 + \varepsilon X)}\)

\(C_A = C_{A0} \frac{(1 - X)}{(1 + \varepsilon X)}\)

\(C_B = \frac{F_B}{\nu} = \frac{F_{A0}\left(\frac{1}{2}X\right)}{\nu_0(1 + \varepsilon X)}\)

\(C_B = \frac{C_{A0}X}{2(1 + \varepsilon X)}\)

Combine:

\(t = \frac{1}{kC_{A0}} \int_{0}^{X} \left[\frac{1}{(1 - X)^2}\right] dX\)

Combine:

\(V = \frac{F_{A0} X (1 - 0.5X)^2}{kC_{A0}^2 (1 - X)^2}\)

Combine:

\(V = \frac{F_{A0}}{kC_{A0}^2} \int_{0}^{X} \frac{(1 - 0.5X)^2}{(1 - X)^2} \, dX\)

Integrate:

\(t = \frac{1}{kC_{A0}} \left[ \frac{X}{1 - X} \right]\)

Integrate:
Integrate:

\( V = \frac{F_{A0}}{kC_{A0}^2} \left( 2\epsilon(1+\epsilon)\ln(1-X) + \epsilon^2X + \frac{(1+\epsilon)^2X}{1-X} \right) \)

Evaluate:

\[ kC_{A0} = \left( 0.2 \, \frac{\text{dm}^3}{\text{mol} \cdot \text{s}} \right) \left( 0.5 \, \frac{\text{mol}}{\text{dm}^3} \right) = 0.1 \, \text{s}^{-1} \]

\[ kC_{A0} = 0.1 \, \text{sec}^{-1} \]

Evaluate:

\[ kC_{A0}^2 = 0.5 \, \frac{\text{dm}^3}{\text{mol} \cdot \text{s}} \left( 0.2 \, \frac{\text{mol}}{\text{dm}^3} \right)^2 = 0.02 \, \frac{\text{mol}}{\text{dm}^3 \cdot \text{s}} \]

\[ V = \frac{0.5 \, \frac{\text{mol}}{\text{s}} (0.9) \left(1 - 0.5(0.9)\right)^2}{0.02 \, \frac{\text{mol}}{\text{dm}^3 \cdot \text{s}} \left(1 - 0.9\right)^2} \]

Evaluate:

\[ F_{A0} = 0.5 \, \frac{\text{mol}}{\text{s}} \]

\[ kC_{A0}^2 = 0.02 \, \frac{\text{mol}}{\text{dm}^3 \cdot \text{s}} \]

\[ V = \frac{0.5 \, \frac{\text{mol}}{\text{s}} (0.9)}{0.02 \, \frac{\text{mol}}{\text{dm}^3 \cdot \text{s}}} \left( 2(-5)(1-5)\ln(1-0.9) + (-5)^2(0.9) + \frac{(1-5)^2(0.9)}{1-0.9} \right) \]

For X = 0.9:

\[ t = \left( \frac{1}{0.1 \, \text{s}^{-1}} \right) \left( \frac{0.9}{1-0.9} \right) \]

\[ t = 90 \, \text{sec} \]

For X = 0.9:
\( V = 680.6 \, \text{dm}^3 \)
\( \tau = \frac{V}{v_0} = 272.3 \, \text{s} \)
For X = 0.9:
\( V = 90.7 \, \text{dm}^3 \)
\( \tau = \frac{V}{v_0} = 36.3 \, \text{s} \)



Reversible Reactions

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To determine the conversion or reactor volume for reversible reactions, one must first calculate the maximum conversion that can be achieved at the isothermal reaction temperature, which is the equilibrium conversion. (See Example 3-8 in the text for additional coverage of equilibrium conversion in isothermal reactor design.)

Equilibrium Conversion, Xe

From Appendix C:

\( K_C = \frac{C_C^c C_D^d}{C_A^a C_B^b} \)


Example: Determine Xe for a PFR with no pressure drop, P = P0

Given that the system is gas phase and isothermal, determine the reactor volume when X = 0.8 Xe.

Reaction Additional Information

2A ⇌ B

  • CA0 = 0.2 mol/dm3
  • k = 2 dm3/mol-min
  • KC = 100 dm3/mol
  • FA0 = 5 mol/min

First calculate Xe:

\(K_C = \frac{X_e (1 + \epsilon X_e)}{2C_{A0} (1 - X_e)^2}\)

Xe = 0.89

X = 0.8Xe = 0.711




ODE (Polymath) Solutions to CRE Problems

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Algorithm Steps Polymath Equations
Mole Balance \( \frac{dX}{dV} = -\frac{r_A}{F_{A0}} \)
Rate Law \( r_A = -k \left( (C_A)^2 - \frac{C_B}{K_C} \right) \)
Stoichiometry \( C_A = \frac{C_{A0} (1 - X)}{1 + \epsilon X} \)
\( C_B = \frac{C_{A0} X}{2 (1 + \epsilon X)} \)
Parameter Evaluation \( \epsilon = -0.5 \), \( C_{A0} = 0.2 \, \text{mol/dm}^3 \), \( k = 2 \)
\( F_{A0} = 5 \), \( K_C = 100 \)
Initial and Final Values \( X_0 = 0 \), \( V_0 = 0 \), \( V_f = 500 \)

Polymath Screen Shots
Equations

Plot of X vs. V

Results in Tabular Form

A volume of 94 dm3 (rounding up from slightly more than 93 dm3) appears to be our answer.

\( V = 94 \, \text{dm}^3 \)




General Guidelines for California Problems

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Every state has an examination engineers must pass to become a registered professional engineer.  In the past there have typically been six problems in a three hour segment of the California Professional Engineers Exam. Consequently one should be able to work each problem in 30 minutes or less. Many of these problems involve an intermediate calculation to determine the final answer.

Some Hints:

  1. Group unknown parameters/values on the same side of the equation
    Example:
    [unknowns] = [knowns]
  2. Look for a Case 1 and a Case 2 (usually two data points) to make intermediate calculations
  3. Take ratios of Case 1 and Case 2 to cancel as many unknowns as possible
  4. Carry all symbols to the end of the manipulation before evaluating, UNLESS THEY ARE ZERO


PBR with Pressure Drop

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Note: Pressure drop does NOT affect liquid phase reactions

Sample Question:

Analyze the following second order gas phase reaction that occurs isothermally in a PBR: 

\( A \rightarrow B \)


Mole Balance

\( F_{A0} \frac{dX}{dW} = -r'_A \)

Must use the differential form of the mole balance to separate variables


Rate Law

Second order in A and irreversible:

\(-r'_A = kC_A^2\)


Stoichiometry
  

\(C_A = \frac{F_A}{\nu} = C_{A0} \frac{(1-X)}{(1+\epsilon X)} \frac{P \, T_0}{P_0 \, T}\)

Isothermal, T = T0

\(C_A = C_{A0} \frac{(1-X)}{(1+\epsilon X)} \frac{P}{P_0}\)


Combine
   

\(\frac{dX}{dW} = \frac{kC_{A0}^2}{F_{A0}} \frac{(1-X)^2}{(1+\epsilon X)^2} \left(\frac{P}{P_0}\right)^2\)

     

Need to find (P/P0) as a function of W (or V if you have a PFR).

Pressure Drop in Packed Bed Reactors


Ergun Equation

\( \frac{dP}{dz} = - \frac{G}{\rho g_c D_p} \left(\frac{1-\phi}{\phi^3}\right) \left[ \underbrace{\frac{150 (1-\phi) \mu}{D_p}}_{\text{laminar}} + \underbrace{1.75G}_{\text{turbulent}} \right] \)


Variable Gas Density

\( \rho = \rho_0 \frac{P}{P_0} \frac{T_0}{T} \frac{F_{T_0}}{F_T} \)


\( \frac{dP}{dz} = - \frac{G}{\rho_0 g_c D_p} \left( \frac{1-\phi}{\phi^3} \right) \left[ \frac{150 (1-\phi) \mu}{D_p} + 1.75G \right] \frac{P_0}{P} \frac{T}{T_0} \frac{F_T}{F_{T_0}} \)

let \( \beta_0 = \frac{G}{\rho_0 g_c D_p} \left( \frac{1-\phi}{\phi^3} \right) \left[ \frac{150 (1-\phi) \mu}{D_p} + 1.75G \right] \)


Catalyst Weight

\( W = zA_c \rho_b = zA_c (1-\phi) \rho_c \)

where \( \rho_b = \text{bulk density}, \quad \rho_c = \text{solid catalyst density}, \quad \phi = \text{porosity (void fraction)} \)

\( \frac{dP}{dW} = \frac{-\beta_0}{A_c (1-\phi) \rho_c} \frac{P_0}{P} \frac{T}{T_0} \frac{F_T}{F_{T_0}} \)


let \( \alpha = \frac{2\beta_0}{A_c (1-\phi) \rho_c P_0} \)

then \( \frac{dP}{dW} = -\frac{\alpha}{2} \frac{P_0}{P} \frac{T}{T_0} \frac{F_T}{F_{T_0}} \)

\( \frac{d\left(\frac{P}{P_0}\right)}{dW} = -\frac{\alpha}{2} \frac{T}{T_0} \frac{F_T}{F_{T_0}} \left(\frac{P}{P_0}\right) \)


English:
Español:
Svenska:

We will use this form for multiple reactions:

\(\frac{\frac{dp}{dW}}{\alpha} = -\frac{\frac{T}{T_o} \frac{F_T}{F_{T_o}}}{2p}\)

\(p = \frac{P}{P_o}\)


We will use this form for single reactions:

\(\frac{d(P/P_o)}{dW} = -\frac{\alpha}{2} \frac{1}{(P/P_o)} \frac{T}{T_o}(1+\epsilon X)\)


\(\frac{dp}{dW} = -\frac{\alpha}{2p} \frac{T}{T_o}(1+\epsilon X)\)

Isothermal Operation:

\(\frac{dp}{dW} = -\frac{\alpha}{2p}(1+\epsilon X)\)

Recall that:

\(\frac{dX}{dW} = \frac{kC_{A0}^2 (1-X)^2}{F_{A0} (1+\epsilon X)^2} p^2\)

Notice that:

\(\frac{dX}{dW} = f(X, P) \text{ and } \frac{dP}{dW} = f(X, P) \text{ or } \frac{dp}{dW} = f(p, X)\)

The two expressions are coupled ordinary differential equations. We can solve them simultaneously using an ODE solver such as Polymath. For the special case of isothermal operation and epsilon = 0, we can obtain an analytical solution.

Polymath will combine the mole balance, rate law and stoichiometry.


Analytical Solution \( A \to B \), [e], PFR with \( -r_A = kC_A^2 \)

\(\frac{dp}{dW} = -\frac{\alpha}{2p}(1+\epsilon X)\)

IF \( T = T_0 \) AND \( \epsilon = 0 \)

\( y = (1 - \alpha W)^{1/2} \)

CAUTION: Never use this form if \( \epsilon \neq 0 \)



For \( \epsilon = 0 \):

\( C_A = C_{A0}(1 - X)p = C_{A0}(1 - X)(1 - \alpha W)^{\frac{1}{2}} \)

Combine:

\( -r_A' = kC_A^2 = kC_{A0}^2(1 - X)^2(1 - \alpha W) \)

\( F_{A0} \frac{dX}{dW} = -r_A' \)

\( \frac{dX}{dW} = \frac{kC_{A0}^2}{F_{A0}}(1 - X)^2(1 - \alpha W) \)

Solve:

\( \frac{X}{1 - X} = \frac{kC_{A0}^2}{F_{A0}} \left[ W - \frac{\alpha W^2}{2} \right] \)


Could now solve for X given W, or for W given X.

For gas phase reactions, as the pressure drop increases, the concentration decreases, resulting in a decreased rate of reaction, hence a lower conversion when compared to a reactor without a pressure drop. 

Set of four graphs illustrating the effects of pressure drop on reactor performance: 
							1) Pressure (P) versus weight (W) showing P decreasing with W as P = P0(1 - αW)^1/2 for ε = 0; 
							2) Concentration of A (CA) versus W showing two curves, one with pressure drop (ΔP) and one without, where CA decreases more sharply with ΔP;
							3) Reaction rate (-rA) versus W demonstrating higher rates without ΔP compared to with ΔP, where -rA = kCA^2;
							4) Conversion (X) versus W with conversion increasing faster without ΔP compared to with ΔP. 

Here are some links to example problems dealing with packed bed reactors. You could also use these problems as self tests.


Analysis using Simulation Tools

Consider the following gas phase reaction carried out isothermally in a packed bed reactor containing 100 kg of catalyst. Pure A is fed at a rate of 2.5 mol/s and with $ {C_{A0} = 0.2 \frac{mol}{dm^3}} $, and $ {\alpha = 0.0162kg^{-1}} $.

\( 2A \rightarrow B \)

Mole Balance

$ {\frac{dX}{dW} = -r_A^{'} / F_{A0}} $

Rate Law

Elementary: $ {r_A^{'} = -kC_A^2} $

Stoichiometry

Gas with ${T = T_0}$

${A \rightarrow \frac{1}{2}B \\ C_A = \frac{F_A}{v} = \frac{C_{A0}(1-X)p}{1+\epsilon X} \\ \frac{dp}{dW} = -\alpha \frac{1+\epsilon X}{2p} \\ \epsilon = -1/2 \\ F_{A0} = 2.5 \\ C_{A0} = 0.2 \\ k = 5 \\ \alpha = 0.0162 \\ W_{final} = 100 \\ X(W = 0) = 0, p(W = 0) = 1 }$

The above equations can be easily combined with the help of simulation tools such as Polymath, Wolfram or Python.

Below is the result from Polymath

Table showing calculated values of DEQ variables, differential equations, and explicit equations: 
							1. Table includes variables (alpha, CA, CA0, epsilon, FA0, k, p, rA, W, X) with initial, minimal, maximal, and final values. Notable values: alpha=0.0162, CA0=0.2, epsilon=-0.5, FA0=2.5, k=5, p ranges from 1 to 0.1117136, rA from -0.2 to -7.563E-05, W from 0 to 100, and X from 0 to 0.9046661. 
							2. Differential equations: d(X)/d(W) = -rA/FA0 and d(p)/d(W) = -alpha/2/p*(1+epsilon*X).
							3. Explicit equations: CA0=0.2, epsilon=-0.5, CA = CA0*(1-X)*p/(1+epsilon*X), k=5, alpha=0.0162, FA0=2.5, and rA = -k*CA^2.

Graph titled 'Conversion and pressure drop Profile.' It shows X (conversion, blue line) and p (pressure drop, orange line) plotted against W (weight in kg). The X-axis ranges from 0 to 100. X starts at 0 and increases, leveling off near 1 as W increases. The pressure drop, p, starts at 1 and decreases sharply, approaching 0 as W increases. Both lines intersect at approximately W=30.

Here are links to Polymath, Wolfram, and Python code for the above example

Polymath Code
Wolfram Code
Python Code


Optimum Particle Diameter

\( A \rightarrow B \)

\( -r_A = kC_{A0}(1 - X)p, \, p = \frac{P}{P_0} \)

\( \frac{dp}{dW} = -\frac{\alpha}{2p}(1 + \epsilon X) \)

as \( \alpha \) increases the pressure drop increases

\( \alpha = \frac{2G}{A_c \rho_c P_0 \rho_0 D_P \phi^3} \left[ \frac{150(1 - \phi)\mu}{D_P} + 1.75G \right] \)

Laminar Flow, Fix \( P_0, \rho_0, \phi \)

\( \rho_0 = \frac{P_0 (\text{MW})}{RT_0} \)

\( \rho_0 P_0 \sim P_0^2 \)

\( \alpha \sim \frac{G}{A_C D_P^2 P_0^2} \)

\( \alpha_2 = \alpha_1 \left( \frac{G_2}{G_1} \right) \left( \frac{D_{P1}}{D_{P2}} \right)^2 \left( \frac{A_{C1}}{A_{C2}} \right) \left( \frac{P_{01}}{P_{02}} \right)^2 \)

If \( D_{P2} = 2D_{P1}, \, G_1 = G_2, \, A_{C1} = A_{C2} \)

\( \alpha_2 = \alpha_1 \left( \frac{1}{2} \right)^2 = \frac{\alpha_1}{4} \)

Graph showing conversion (X) versus weight (W). Two curves labeled α1 and α2 represent conversion profiles. α2 reaches a higher conversion level (X2) compared to α1, which levels off at a lower conversion (X1). Both curves asymptotically approach their respective values as W increases. Horizontal dashed lines represent X1 and X2, while vertical distances between the curves indicate differences in conversion.

Increasing the particle diameter descreases the pressure drop and increases the rate and conversion.

Scatter plot showing conversion (X) versus particle diameter (Dₚ). Two data points are marked on the plot. The x-axis represents particle diameter (Dₚ), and the y-axis represents conversion (X). The plot suggests a relationship between particle size and conversion.

However, there is a competing effect. The specific reaction rate decreases as the particle size increases, therefore so deos the conversion.

k ∼ 1/Dp

Graph showing conversion (X) versus reactor volume (V) for two cases. The first curve reaches a conversion level of X₁ with rate constant k₁(Dₚ₁), while the second curve reaches X₂ with rate constant k₂(Dₚ₂). The x-axis represents volume (V), and the y-axis represents conversion (X).

DP1 > DP2
k1 > k2

Higher k, higher conversion

Illustration of a diffusion and reaction system. On the left, a reactant with concentration Cₐ moves into a porous particle where it reaches the surface concentration Cₐₛ. The particle is shown with internal pores. On the right, a graph depicts the relationship between the rate constant (k) and particle diameter (Dₚ), showing an inverse relationship as k decreases with increasing Dₚ.

The larger the particle, the more time it takes the reactant to get in and out of the catalyst particle. For a given catalyst weight, there is a greater external surgace area for smaller particles than larger particles. Therefore, there are more entry ways into the catalyst particle.

Later on in the course, we will learn that effectiveness factor decreases as the particle size increases


Engineering Analysis - Critical Thinking and Creative Thinking

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We want to learn how the various parameters (particle diameter, porosity, etc.) affect the pressure drop and hence conversion. We need to know how to respond to "What if" questions, such as:

"If we double the particle size, decrease the porosity by a factor of 3, and double the pipe size, what will happen to D P and X?"

(See Critical Thinking in Preface Table P1 and P2 on pages xvi and xvii.  e.g., Questions the probe consenquences)

To answer these questions we need to see how a varies with these parameters.

\( \alpha = \frac{2G}{A_C \rho_0 \rho_c g_c D_P \phi^3 P_0} \left[ \frac{150 \mu (1 - \phi)}{D_P} + 1.75G \right] \)

Turbulent Flow                                    

\( \alpha \sim \frac{G^2}{A_c D_P P_0^2} \)

 

Compare Case 1 and Case 2:

For example, Case 1 might be our current situation and Case 2 might be the parameters we want to change to.

\( \boxed{\alpha_2 = \alpha_1 \left( \frac{G_2}{G_1} \right)^2 \left( \frac{A_{c1}}{A_{c2}} \right) \left( \frac{D_{P1}}{D_{P2}} \right) \left( \frac{P_{01}}{P_{02}} \right)^2} \)

For constant mass flow through the system, \( \dot{m} = \text{constant} \)

\( A + \frac{1}{2} B \rightarrow \frac{1}{2} C \)


Laminar Flow

\( \alpha \sim \frac{G}{A_c D_P^2}, \quad G = \frac{\dot{m}}{A_c} \)

\( \alpha_2 = \alpha_1 \left(\frac{D_{P1}}{D_{P2}}\right)^2 \left(\frac{A_{c1}}{A_{c2}}\right)^2 \)


Polymath Book Problem

The following is an example problem from the book. It is located on page 192 in Chapter 5. This is a problem done in polymath and the .pol file has been included for reference. The report and accompanying graphs generated in Polymath are also shown.

Table displaying calculated values of DEQ variables. It includes columns for Variable, Initial value, Minimal value, Maximal value, and Final value. Variables listed include alpha, Ca, Ca0, Cb, Cc, eps, Fa0, k, Kc, ra, thetaB, W, X, and y. Example values: alpha remains constant at 0.01, Ca ranges from 0.0007877 to 0.01, and X progresses to a final value of 0.3719772. Text showing Differential and Explicit equations. Differential equations include d(X)/d(W) = -ra / Fa0 and d(y)/d(W) = -alpha * (1 + eps * X) / (2 * y). Explicit equations include parameters such as Kc = 0.05, Ca0 = 0.01, eps = 0.33, and complex equations like Ca = Ca0 * (1 - X) / (1 + eps * X) * y and ra = -k * (Ca * Cb - (Cc ^ 3 / Kc)).

Graph showing the variation of concentrations Ca, Cb, and Cc against W. Ca (green) decreases steadily, Cb (brown) increases initially and then decreases, while Cc (cyan) increases throughout as W progresses.

Graph showing -ra versus W. The reaction rate (-ra) decreases exponentially with increasing W, starting at approximately 0.2 and approaching zero as W increases to its maximum value.

Graph showing y versus W. The variable y decreases gradually with increasing W, starting near 1.0 and steadily approaching 0 as W increases to its maximum value.

Here are more links to example problems dealing with packed bed reactors. Again, you could also use these problems as self tests.

 

* All chapter references are for the 1st Edition of the text Essentials of Chemical Reaction Engineering .

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