Data for: Experimental Analysis of Lifelines in a 15,000 L Bioreactor by Means of Lagrangian Sensor Particles

Version 1.0
Hofmann, Sebastian; Buntkiel, Lukas; Rautenbach, Ryan; Gaugler, Lena; Ma, Yifan; Haase, Ingrid; Fitschen, Jürgen; Wucherpfennig, Thomas; Reinecke, Sebastian; Hoffmann, Marko; Takors, Ralf; Hampel, Uwe; Schlüter, Michael, 2024, "Data for: Experimental Analysis of Lifelines in a 15,000 L Bioreactor by Means of Lagrangian Sensor Particles", https://doi.org/10.18419/DARUS-3768, DaRUS, V1
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Description

The DaRUS repository entails the raw files, result files and the MATLAB codes for the publication "Experimental Analysis of Lifelines in a 15,000 L Bioreactor by Means of Lagrangian Sensor Particles" in the journal "Chemical Engineering Research and Design".

This study employs Lagrangian Sensor Particles (LSPs) with a diameter of 40 mm equipped with a pressure sensor to investigate cell lifelines in a 15,000 L stirred tank reactor (STR) with three Elephant Ear impellers. The Stokes number of the LSPs is approx. 0.004 on a macro-scale. The vertical probability of presence, axial velocity profiles, circulation time distributions, and residence time distributions are quantified to analyze single-phase mixing heterogeneities, detect hydrodynamic compartments and conduct a Lagrangian regime analysis. Results reveal a similarly distributed probability of presence in the vertical reactor center but emphasize the LSP's sensitivity to fluctuating densities. Axial velocity distributions illustrate characteristic impeller-induced flow patterns, and circulation time distributions identify three compartments with comparatively shorter times in the axial center. Residence time distributions exhibit a similar compartmentalized profile. Moreover, the study estimates a potential oxygen deprivation zone for CHO cells in the upper compartment and demonstrates the LSP's efficacy in characterizing impeller systems. Contrary to literature, the ratio of examined global mixing times to circulation times is 1.0, highlighting macro-scale mixing. The research underscores that LSPs offer crucial insights into industrial-scale STRs, specifically for determining hydrodynamic compartments without having optical access. (2024-04-19)
Subject Engineering; Physics
Keyword Lagrangian Sensor Particle Tracking, Flow-Following Sensor Devices, Trajectories, Lagrangian Regime Analysis
Related Publication S. Hofmann, L. Buntkiel, R. Rautenbach, L. Gaugler, Y. Ma, I. Haase, J. Fitschen, T. Wucherpfennig, S. Reinecke, M. Hoffmann, R. Takors, U. Hampel, M. Schlüter, Experimental Analysis of Lifelines in a 15,000 L Bioreactor by Means of Lagrangian Sensor Particles, Chemical Engineering Research and Design (ChERD) (2024).doi: 10.1016/j.cherd.2024.04.015
Data Generation Analysis; Experiment
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f_circulation.m
code/Plain Text - 7.0 KB
Published Apr 23, 2024
47 Downloads
MD5: 70c6144a36572b4400b1a4296cb29b9a
This function calculates circulation time and related statistics based on provided data. It iterates through each LSP's height data to determine circulation time per plane. It then calculates weighted averages and errors for both individual planes and overall circulation time.
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f_clear_all_but.m
code/Plain Text - 2.3 KB
Published Apr 23, 2024
47 Downloads
MD5: d474161af009e6d2bc7f86c90e516667
This function helps clearing selected variables from the workspace and is utilized in the code. Version: 16.09.2009, (c) Roland Pfister
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f_compartment_determination.m
code/Plain Text - 9.6 KB
Published Apr 23, 2024
37 Downloads
MD5: 4c7fc321a50a9b4307c0753fe658abc7
The function calculates the edges of compartments in a system based on the provided circulation and residence time data. It utilizes the ischange function to detect changes in the data indicating compartment boundaries. The function handles data preprocessing, smoothing, and change detection to identify compartment edges. It also contains internal functions for neighbor analysis in the data.
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f_PDF_over_height.m
code/Plain Text - 4.1 KB
Published Apr 23, 2024
38 Downloads
MD5: a6d5f91e0406a638fa1f326ab71583ff
This function calculates the normalized sum-product average of the PDF over height, its associated error, and provides data for creating a shaded area in a plot to represent the uncertainty in the PDF over height. The function first normalizes the height data and bin spaces, and then computes the histogram for each column in the height matrix. It then calculates a weighted average of these histograms, taking into account the number of counts in each bin. The function also calculates the standard deviation and error associated with this weighted average, and prepares data for plotting a shaded area representing this uncertainty.
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f_PDF_v_ax.m
code/Plain Text - 8.5 KB
Published Apr 23, 2024
33 Downloads
MD5: 8168abc8baf648322264b754f2ef1f44
The f_PDF_v_ax function calculates the probability density function (PDF) for the axial velocity distribution with a weighted average. Here's a detailed overall description of the function: The function takes a matrix dh_dt as input, where each column represents axial velocity data from a different mote (sensor), and each row represents a different velocity measurement.
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f_read_data_HZDR.m
code/Plain Text - 13.7 KB
Published Apr 23, 2024
31 Downloads
MD5: d4b1da5e8c964427c33c82c86f0716e8
This function navigates directory structures to read raw data and metadata from XML files, processes the data for different reactor speeds (RPM), and provides raw and smoothed interpolated data arrays for further analysis. For this purpose it utilizes two local functions.
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f_regime_analysis.m
code/Plain Text - 5.8 KB
Published Apr 23, 2024
34 Downloads
MD5: 59658286eb756801d3a0e2fe7807eb51
This function performs regime analysis on LSP data to identify and analyze different flow regimes within a reactor, following a methodology similar to that used by Haringa et al. It processes compartment positions and types based on either circulation or residence time data, to calculate the Probability Density Function (PDF) of the regimes across different reactor heights.
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f_v_ax.m
code/Plain Text - 8.8 KB
Published Apr 23, 2024
29 Downloads
MD5: 72e0a125a24275493529ca35d7c122a7
This function calculates the distribution of vertical velocities (dh_dt) into respective bins based on height (h). It separates velocities into positive and negative components, computes their absolute values, and then calculates the weighted average of absolute, positive, and negative velocities for each bin. Additionally, it computes the uncertainty of the weighted averages. This function also provides counts of positive, negative, and absolute velocities for each bin, as well as shaded areas representing the uncertainty for the weighted averages.
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f_V_dot.m
code/Plain Text - 19.8 KB
Published Apr 23, 2024
19 Downloads
MD5: a06faf02a735a9d2738df578e8d3e134
This function computes various parameters related to fluid flow and reactor geometry, focusing on volume flow rates and residence times. This function provides two options for calculating volume flow rates and residence times in a reactor. The first option is less accurate but computationally simpler, while the second option offers more accuracy by considering boundary conditions and iteratively refining the calculations. The second option iterates through possible diameters for the inner zone, calculating the corresponding diameter for the outer zone based on mass balance assumptions. It then computes various parameters such as cross-sectional areas, volume flow rates, and residence times, taking uncertainties into account. The function also performs tests for mass conservation to ensure the accuracy of the calculations and provides shaded areas to visualize uncertainties in the results.
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main.m
code/Plain Text - 21.6 KB
Published Apr 23, 2024
29 Downloads
MD5: a16332e3fde17aedf2e9dfc85aee685f
This script conducts data processing and analysis for Lagrangian Sensor Particles (LSPs) in a 15 kL bioreactor. It sets initial conditions, computes various physical properties, and iterates over datasets corresponding to HZDR data. The script involves preprocessing, calculation of parameters. It also includes data selection, logging, visualization, and saving functionalities.
Preview "code/main.m"
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