DOFPro Team

Dew Your Bubbles Have Flash?

Overall
Composition
Subcooled
Liquid
Superheated
Vapor
\(2\text{–}\phi\)
Dew
Temperature
Dew
Composition
Bubble
Temperature
Bubble
Composition
Low Boiling
Azeotrope
Given all \(x_{i}\)’s and \(P\), calculate \(T\) and \(y_i\)’s
In general, an iterative solution is required. With a spreadsheet, the easiest method is to guess a temperature \(T_\mathrm{guess}\).
Calculate all of the vapor pressures from the Antoine equation, ?@eq-BP1,
\[ p_{i}^{*} = 10^{A_{i} - \frac{B_i}{T+C_i}}\ \ \ (i=1,2,3,.., N) \]
Then calculate the pressure from the guessed temperature
\[ P_\mathrm{guess} = \sum_{i=1}^{N} x_{i}p_{i}^{*} \tag{1}\]
Set up a cell to calculate the difference between the actual pressure and the guessed pressure, \(P_\mathrm{actual} - P_\mathrm{guess}\).
Have Goal Seek set the difference to 0 by varying \(T_\mathrm{guess}\).
\(T_\mathrm{guess}\) is now the correct temperature. You can calculate the \(y_i\)’s from Raoult’s law, ?@eq-DP2,
\[ y_{i} = \frac{x_{i}p_{i}^{*}}{P}\ \ \ (i=1,2,3,...,N) \]
Alternate Method: In a spreadsheet, guess a \(T\). For one component calculate \(p_{k}^{*}\) from Equation 3 and calculate \(p_{i}^{*}\) from the Antoine equation, ?@eq-BP1. Set a cell as the error between the two and goal seek to set that cell to \(0\) by varying \(T\).
Note: For a two-component system, if you are determining the \(y_i\)’s as a function of \(T\) at constant \(P\), you don’t need to iterate. Choose values of \(T\) between \(T_\mathrm{b1}\) and \(T_\mathrm{b2}\), and calculate the \(y_i\)’s using the Antoine equation, ?@eq-BP1 and Raoult’s law, ?@eq-DP2.
If you prefer programming to spreadsheets, begin by picking an arbitrary component, \(k\), then:
\[ P = p_{k}^{*} \sum_{i=1}^{N} x_{i} \frac{p_{i}^{*}}{p_{k}^{*}} \tag{2}\]
or
\[ p_{k}^{*} = \frac{P}{\sum\limits_{i=1}^{N} x_{i} \alpha_{ik}} \tag{3}\]
where the relative voltatility, \(\alpha_{ik}\), is defined as:
\[ \alpha_{ik} \equiv \frac{p_{i}^{*}}{p_{k}^{*}} \tag{4}\]
If the vapor pressures are related by the Antoine equation, ?@eq-BP1:
\[ \log_{10} p^* = A - \frac{B}{T + C} \]
then we can calculate,
\[ \log_{10}\alpha_{ik} = A_i - A_k - \frac{B_i}{T + C_i} + \frac{B_k}{T + C_k} \tag{5}\]
One can begin the iteration with an initial guess
\[ T_{0} = \sum_{i=1}^{N} x_{i}T_{i}^{*} \tag{6}\]
This \(T_{0}\) can be used to evaluate all of the \(\alpha_{ik}\)’s in Equation 4, which are then used in Equation 3 to calculate \(p_k^*\), from which a new value of \(T\) can be calculated from:
\[ T_1 = \frac{B_k} {A_{k} - \log_{10} p_{k}^{*} - C_{k}} \tag{7}\]
The iteration is repeated until \(T\) doesn’t change much from one iteration to the next. The Antoine equation, ?@eq-BP1 is then used to calculate all \(p_i^*\), then use Raoult’s law, ?@eq-DP2 to calculate the \(y_i\)’s.
Given all \(y_i\)’s and \(P\), calculate \(T\) and \(x_i\)’s.
In general, an iterative solution very similar to BUBL T is required. With a spreadsheet, the easiest method is to guess a temperature \(T_\mathrm{guess}\) .
Calculate all of the vapor pressures, \(p_i^*\)’s, from the Antoine equation, ?@eq-BP1
\[ P_{i}^{*} = 10 ^ {A - \frac{B_i}{T+C_i}}\ \ \ (i = 1, 2, 3, ..., N) \]
Then calculate the pressure from the guessed temperature using ?@eq-DP5,
\[ P_\mathrm{guess} = \frac{1}{\sum\limits_{i=1}^{N}\frac{y_i}{p_{i}^{*}}} \]
Set up a cell to calculate the difference between the actual pressure and the guessed pressure, \(P_\mathrm{actual} - P_\mathrm{guess}\).
Have Goal Seek set the difference to \(0\) by varying \(T_\mathrm{guess}\).
\(T_\mathrm{guess}\) is now the correct temperature. You can calculate the \(x_i\)’s from Raoult’s law, ?@eq-DP2,
\[ x_i = \frac{y_{i} P} {p_{i}^{*}}\ \ \ (i = 1,2,3, ..., N) \]
Alternate Method: As before, in a spreadsheet, guess a \(T\). For one component calculate \(p_{k}^{*}\) from Equation 9 and calculate \(p_{i}^{*}\) from the Antoine equation, ?@eq-BP1. Set a cell as the error between the two and goal seek to set that cell to 0 by varying \(T\).
If you prefer programming to spreadsheets, begin by picking an arbitrary component, \(k\), then:
\[ P = \frac{p_{k}^{*}}{\sum\limits_{i=1}^{N}y_{i}\frac{p_{k}^{*}}{p_{i}^{*}}} \tag{8}\]
or
\[ p_{k}^{*} = P \sum_{i=1}^{N} \frac{y_j}{\alpha_{ik}} \tag{9}\]
where the relative volatility, \(\alpha_{ki}\), is defined in Equation 4 and calculated using Equation 5.
The initial guess is:
\[ T_0 = \sum_{i=1}^{N} y_{i}T_{i}^{*} \tag{10}\]
This \(T_0\) can be used to evaluate all of the \(a_{ik}\)’s in Equation 4 which are then used in Equation 3 to calculate \(p_{k}^{*}\), from which a new value of \(T\) can be calculated from Equation 7:
\[ T_1 = \frac{B_k}{A_k - \log_{10} p_{k}^{*}} - C_k \]
After convergence we evaluate the \(x_i\)’s from Raoult’s law, ?@eq-DP2:
\[ x_i = \frac {y_{i}P}{p_{i}^{*}}\ \ \ (i = 1, 2, 3, ..., N) \]
Thanks for watching!
The previous in the series video is the link in the upper left. The next video in the series is the link the upper right. To learn more about Chemical and Thermal Processes, visit the website linked in the description.

