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kLa Calculation Mass Transfer Coefficient

20 vues (au cours des 30 derniers jours)
Parris
Parris le 31 Août 2023
We are looking to process KLa Value. The inputs are the form of three tags, DO, Condition Name, and step_name. The approach is to calculate after the expirment is completed. Inputing values in a PAT system, and data browsing those values to run calculation for KLa. Regression calculation of data when the inroduction of N2 20% into the process and or Air 80% introduction into the process. The idea is the trigger the calculation per the step in the process. I'm new to MatLab. Is there any literature around kLa formulas, utlizing Matlab modeling.
  2 commentaires
Torsten
Torsten le 31 Août 2023
Modifié(e) : Torsten le 31 Août 2023
We must at least know what your example data represent and how the kLA value can be derived from your 1st and 2nd column data.
Parris
Parris le 31 Août 2023
thx for the response.
The DO represents the dissolved oxygen concentration per 10 second increments. Per step in the process, the idea is capture KLa when we are introducing nitrogren then further when we are introducing air. The thought is to trigger based on timing of the step in the process to gather the timing.
Additonally, there will be a added column, with every value there is a associated gas used. That is either const Air = 100 or N2 =0. For this input, the approach is to get the Driving Force for starters with the available constants per row.
Something like In|DO*-DO| DO* being either Air or N2 Triggering on step naming N2 EVENT: DO =20% and then AIR EVENT: DO = 80%

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SANKALP DEV
SANKALP DEV le 4 Sep 2023
Hey Parris,
I understand you are trying to calculate KLa values based on dissolved oxygen concentration (DO) data collected at 10-second intervals, while introducing nitrogen and air during specific steps.
The following steps will assist you in accomplishing your objective,
  1. Load the data - You can use the “readtable” function to read data from a spreadsheet or CSV file.
  2. Use dot notations to extract relevant columns.
  3. Third step would be to filter data for N2 and air events.
  4. To calculate the driving force, you can utilize array indexing. Consider using the following lines of code to accomplish these steps:
% Filter data for N2 and air events
n2Index = strcmp(step_name, 'N2 EVENT');
airIndex = strcmp(step_name, 'AIR EVENT');
% Calculate driving force
drivingForce = abs(DO(airIndex) - DO(n2Index));
5. Now you have the appropriate data, you can proceed with your further calculations.
Please refer to the following MATLAB documentation for more details
  1. https://www.mathworks.com/help/matlab/matlab_prog/access-data-in-a-table.html?s_tid=srchtitle_site_search_1_in%20tables
  2. https://www.mathworks.com/help/matlab/ref/strcmp.html?s_tid=srchtitle_site_search_1_strcmp
Hope this helps,
Regards
Sankalp

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