Data for: Experimental Analysis of Lifelines in a 15,000 L Bioreactor by Means of Lagrangian Sensor Particles (doi:10.18419/darus-3768)

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Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
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Data for: Experimental Analysis of Lifelines in a 15,000 L Bioreactor by Means of Lagrangian Sensor Particles

doi:10.18419/darus-3768

DaRUS

2024-04-23

1

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

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

doi:10.18419/darus-3768

Hofmann, Sebastian (TU Hamburg (TUHH))

Buntkiel, Lukas (Helmholtz-Zentrum Dresden-Rossendorf)

Rautenbach, Ryan (TU Hamburg (TUHH))

Gaugler, Lena (University of Stuttgart)

Ma, Yifan (Helmholtz-Zentrum Dresden-Rossendorf)

Haase, Ingrid (TU Hamburg (TUHH))

Fitschen, Jürgen (Boehringer Ingelheim Pharma GmbH & Co KG Late Stage USP Development)

Wucherpfennig, Thomas (Boehringer Ingelheim Pharma GmbH & Co KG Late Stage USP Development)

Reinecke, Sebastian (Helmholtz-Zentrum Dresden-Rossendorf)

Hoffmann, Marko (TU Hamburg (TUHH))

Takors, Ralf (University of Stuttgart)

Hampel, Uwe (Helmholtz-Zentrum Dresden-Rossendorf)

Schlüter, Michael (TU Hamburg (TUHH))

DaRUS

Hofmann, Sebastian

Hoffmann, Marko

Schlüter, Michael

Hofmann, Sebastian

2023-11-06

https://doi.org/10.18419/darus-3768

Engineering, Physics, Lagrangian Sensor Particle Tracking, Flow-Following Sensor Devices, Trajectories, Lagrangian Regime Analysis

<p>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".</p> 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.

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).

10.1016/j.cherd.2024.04.015

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).

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f_circulation.m

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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.

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plot_graphs_HZDR_paper.m

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This script creates all plots utilized in the manuscript. Additionally it calculates mixing time correlations, dimensionless mixing times and correlating stirrer Reynolds numbers from former mixing time trials.

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St_Fl_number_estimation.m

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This script estimates first Stokes numbers and Flow numbers for a bioreactor system. It involves calculations for both liquid and solid phases under various operating conditions. The script includes the plotting of Figure 10 in the manuscript.

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xml2struct.m

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This function helps reading the xml file for evaluation in the code. Source: https://de.mathworks.com/matlabcentral/fileexchange/58700-xml2struct-with-bug-fix-and-added-features (November 2022)

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Versuch_2_SP_1_pressure_data.mat

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data_HZDR_all_0000lpm.mat

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circ_time_dist_per_plane.jpg

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circ_time_wo_gassing_HZDR.jpg

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Circulation Time Distribution over reactor height with uncertainty.

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Dimensionless mixing time n*t vs. stirrer Reynolds number

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Plot P/V vs. t_mix, t_circ and tau AND t_circ and tau vs. t_mix

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