BE16. CRE1 – Residence Time Distribution (RTD)
One report per group must be submitted. Including:
Keep your report concise (!), because for every graph, every table and at the end of every paragraph that you submit, it must be clearly stated:
Furthermore, given prior experience, the reports will be checked for plagiarism. If a report or parts of it incurred in such practice, there may be grave consequences for the entire groups (those who shared and those who received)
In case you require more information on these rules, refer to Prof. Dr.-Ing. Frank Platte, responsible for this Practical Training.
QUESTIONS TO BE ADDRESSED
1. Calculate mean residence time (t̅), and b) the standard deviation (σ2).
Hints: You can find the equations in the lab protocol.
Please just write the result. The procedure will be checked on your submitted files.
2. Attach the following plots:
3. Answer and explain. The data that you were given corresponds to:
Hint: Using graphs to answer may help.
4. Attach a screenshot of the video "BE16 Lab 05 - Residence Time Distribution" showing the procedure (reactor + tracer with color) that was used to generate the data that you were given.
5. The data that you received was generated with a real reactor. Choose from Figure 3 of the Lab protocol the corresponding ideal impulse response E(t).
6. Compare your smoothed, normalized E(t)-curve with the following graph in terms of a) reactor used, and of b) data fluctuation. Please also explain the reason for the differences.
Hint: Paste the 2 plots side-by-side, and then proceed. The plot was sent to you.
7. Assume that the data that you received corresponds to a reactor which mean residence time at 50% of the pump capacity is 100 sec. By means of your calculated mean residence time (t̅), state and explain if the pump speed was lower, (almost) the same or higher than 50%
8. (If applicable) How did you derivate the F(t) curve to calculate E(t)?
If you used software such as Matlab, please name the software and find out how it calculates the derivative of a numerical function.
9. What does "smoothing" a curve mean? Why does it make sense smoothing your data?
10. What does "normalizing" a curve mean? Why does it make sense normalizing your data?
11. How did you numerically integrate (not the formula, but the concept) the E(t)-curve to calculate t̅?
If you used software such as Matlab, please name the software and find out how it integrates a numerical function
12. a) When mixing two aqueous solutions the temperature behaves like the electrical conductivity. That is, it will be proportional to the volumes of the mixed solutions. You need to prepare water at exactly 50°C. You can measure any volume, but there is no thermometer available. You know however that: a) Water boils at 100°C
b) Water is at 37°C when you put your finger in it and you feel warmth.
How many liters of (a) and (b) do you need to prepare x liters of water at 50°C?
(Please write down your calculations or model. The try-and-failure is also ok, but please write down the result of the different tries.
Do not forget to reference your answers in case you consulted material.
13. We are aware that there is much space for improvement. Give 3 examples of what could be improved, and suggest constructive solutions.
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