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** This approach to estimate CR and then CP will get you really close to the final answer.
** This approach to estimate CR and then CP will get you really close to the final answer.
** Now carry on with the rest of the steps in the notes. It's interesting how simply flipping what you guess first leads to much faster convergence.
** Now carry on with the rest of the steps in the notes. It's interesting how simply flipping what you guess first leads to much faster convergence.
** If you iterative and get a negative value for CP or CR, it simply means that you must decrease your guess for that term, since you obviously can't have a negative concentration.
** If you iterate and get a negative value for CP or CR, it simply means that you must decrease your guess for that term, since you obviously can't have a negative concentration.
* And a final hint: this question is much better to solve on a computer, with goal seek, than by hand. There is tremendous sensitivity to initial guesses, so solving by hand will take too long.
* And a final hint: this question is much better to solve on a computer, with goal seek, than by hand. There is tremendous sensitivity to initial guesses, so solving by hand will take too long.
* For question 2(B), part 3: by definition, optimization implies we have excess degrees of freedom, i.e. more unknowns than equations. You should get a system of 3 unknowns (including A1 and A2) and 2 equations. Set the 3rd unknown to various values (between its lower and upper bound), and solve for A1 and A2. Pick the solution that gives the optimum.
* For question 2(B), part 3: by definition, optimization implies we have excess degrees of freedom, i.e. more unknowns than equations. You should get a system of 3 unknowns (including A1 and A2) and 2 equations. Set the 3rd unknown to various values (between its lower and upper bound), and solve for A1 and A2. Pick the solution that gives the optimum.

Revision as of 17:20, 5 November 2012

Separation Processes: CHE 4M3


Administrative Class materials
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Announcements (previous ones)

  • Please note for assignment 4, question 5, you will require making an important correction to the membrane notes: slide 76: R=1CPCF
Some hints and an update for assignment 4, question 5:
  • The Asalt and Asolv terms are not the area of the membrane: they are the permeances of the salt and solvent respectively. This unfortunate notation is widely used though in most texts.
  • There is a correction, the feed concentration should be 2.5 g NaCl per liter in the feed (not 2.5 wt% NaCl). I apologize for wasting your time for those of you that have been iterating with negative concentrations.
  • And another hint. I found a way to solve question 5 that leads to faster convergence:
    • Specify CF and θ
    • Guess CR instead
    • Calculate CP from equation 5
    • If your calculated value of CP is negative or exceeds CF, then repeat your guess for CR, until you get a CP that lies between 0 and CF and double check also that the rejection coefficient from this CP is reasonable, around 90 to 99%.
    • This approach to estimate CR and then CP will get you really close to the final answer.
    • Now carry on with the rest of the steps in the notes. It's interesting how simply flipping what you guess first leads to much faster convergence.
    • If you iterate and get a negative value for CP or CR, it simply means that you must decrease your guess for that term, since you obviously can't have a negative concentration.
  • And a final hint: this question is much better to solve on a computer, with goal seek, than by hand. There is tremendous sensitivity to initial guesses, so solving by hand will take too long.
  • For question 2(B), part 3: by definition, optimization implies we have excess degrees of freedom, i.e. more unknowns than equations. You should get a system of 3 unknowns (including A1 and A2) and 2 equations. Set the 3rd unknown to various values (between its lower and upper bound), and solve for A1 and A2. Pick the solution that gives the optimum.


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