Ryan Rautenbach, M.Sc.


Eißendorfer Str. 38

Building O, Room 1.013

21073 Hamburg

Phone +49 40 30601 - 3614

Mail Ryan Rautenbach


Research

As part of the Multiphase Flows in Bioreactors group, the research of Ryan Rautenbach focuses on the characterisation and understanding of scale-up and scale-down in bioreactors, both within the group and through the CHOLife+ subproject of the DFG Priority Program SPP2170 "InterZell".

The CHOLife+ initiative aims to achieve full spatiotemporal resolution for bioreactor characterisation across scales—from laboratory-scale 3 L systems to industrially relevant 15,000 L reactors. Central to this work is the investigation of mixing heterogeneities, flow behaviour, and multiscale mixing phenomena using Lagrangian Sensor Particles (LSPs) and Lattice Boltzmann Large Eddy Simulations (LB-LES). This includes the detailed analysis of particle lifelines to determine their impact on CHO cell cultivation performance.

A key element of the research is improving the reproducibility and robustness of LES simulations, ensuring that computational predictions remain reliable across scales and operating conditions. This also extends to exploring multiphase flow operation, reflecting the complexities of true industrial fermentation environments where gas–liquid interactions significantly influence mixing, transport, and residence time distributions.

The work further involves mapping and fully characterising stirred-tank reactors (STRs) and their spatiotemporal gradients, including detailed distributions of flow structures and residence times of cells and molecules based on Lagrangian lifelines.

Experimental and numerical insights are leveraged to advance the design and operation of single multi-compartment bioreactors (SMCBs) used as scale-down models at the University of Stuttgart. These systems replicate essential hydrodynamic and environmental features of large-scale industrial reactors under controlled laboratory conditions.

By integrating sensor-based measurements (LSPs), LB-LES simulations, and complementary diagnostic methods, this research provides a multi-faceted and mechanistic understanding of bioreactor performance. This includes transport and mixing efficiency, compartmentalisation, and the dynamic trajectories experienced by cells in realistic single- and multiphase environments.

 

Awards
  • Recipient of the 3rd presentation prize at 8th BioProScale Symposium in Berlin, Germany, in 2024 for the presentation on Resolved Particle Lattice-Boltzmann Large Eddy Simulation in a 15,000 L Bioreactor to mimic Lagrangian Sensor Particles; announcement post and other recipients can be found here.
  • Recipient of the Poster Award at the FSP BioProTech Workshop (TUHH) for his work on the Reproducibility of GPU-Based Large Eddy Simulations for Mixing in Stirred Tank Reactors.
Presentations

Oral Presentations

  • Rautenbach, R.; Hofmann, S.; Buntkiel, L.; Barczyk, J.; Reinecke, S.; Hoffmann, M.; Takors, R.; Hampel, U.; Schlüter, M. "Resolved Particle Lattice-Boltzmann Large Eddy Simulation in a 15,000 L Bioreactor to Mimic Lagrangian Sensor Particles." 8th BioProScale Symposium, Berlin, Germany, 2024
  • Rautenbach, R.; Hofmann, S.; Buntkiel, L.; Barczyk, J.; Reinecke, S.; Hoffmann, M.; Takors, R.; Hampel, U.; Schlüter, M. "Simulation of Lagrangian Sensor Particles as Resolved Particles in an Industrial Bioreactor through Lattice-Boltzmann Large Eddy Simulations." 28th International Symposium on Chemical Reaction Engineering (ISCRE 28), Turku, Finland, 2024
  • Rautenbach, R.; Haringa, C.; Brorens, P.; Maldonado de León, H.; Hoffmann, M.; Schlüter, M. "Reproducibility of Large Eddy Simulations for Mixing in Stirred Tank Reactors." 5th International Conference on Multiphase Flow and Porous Media (MMPE), Matsue, Japan, 8-11 September 2025

Poster Presentations

  • Rautenbach, R.; Barczyk, J.; Hoffmann, M.; Takors, R.; Schlüter, M. "Experimental and Numerical Fluid Dynamic Characterisation of an Industrial Sized Multiphase Bioreactor for Scale-Down Studies." DECHEMA Jahrestagung Mischen und Mehrphasenströmungen 2025, Hamburg, Germany
  • Rautenbach, R.; Maldonado de León, H.; Brorens, P.; Haringa, C.; Hoffmann, M.; Schlüter, M. "Reproducibility of Numerical Simulations - How Reliably Can We Predict Mixing Processes?" DECHEMA Jahrestagung Mischen und Mehrphasenströmungen 2025, Hamburg, Germany 
Education

Undergraduate and Graduate Teaching Assistant

  • Einführung in CAD (WS 2023/24, WS 2024/25)

  • Computational Fluid Dynamics in Process Engineering (SS 2024)

  • Fluid Mechanics II (SS 2025)

  • Transport Processes (WS 2025/26)


 

Supervised Theses

 

  • Experimental Study on the Influence of Counter-Current Dual Impellers in Unbaffle Stirred Tank Reactors - Sayaka Takagi, Project Thesis (2026)
  • Development of a Novel Method for the Visualisation of Local Oxygen Depletion in Gas–Liquid Reactors - Anna-Katharina Zörner, Bachelor’s Thesis (2025)
  • Lagrangian Trajectory Comparison between Flow-Tracers and Inertial Particles by Means of 4D-PTV - Mustafa Salli, Master’s Thesis (2024)
  • Measurement of Gas Hold-Up in a 30 L Stirred Tank Reactor - Gautama Halim, Bachelor’s Thesis (2024)
  • Documentation & Refinement of the 4D Particle Tracking Velocimetry Setup in the 3 L Stirred Tank Reactor  - Mustafa Salli, Project Thesis (2024)

Publications

[192190]
Title: Reproducibility of GPU-based Large Eddy Simulations for mixing in stirred tank reactors.
Written by: Rautenbach, R.; Maldonado de León, H.; Brorens, P.; Schlüter, M.; Haringa, C.;
in: <em>Computers and Chemical Engineering</em>. March (2026).
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DOI: 10.1016/j.compchemeng.2026.109615
URL: https://doi.org/10.1016/j.compchemeng.2026.109615
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[pdf] [www]

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Abstract: CFD simulations are widely used to quantify the mixing performance of stirred tanks for various applications in chemical engineering and biotechnology. Due to advances in GPU computing, these simulations increasingly employ Large Eddy Simulation (LES), which explicitly resolves the dynamics of large-scale turbulence. Although such simulations are fully deterministic and therefore theoretically reproducible, small numerical variations induced by round-off errors, floating-point arithmetic, and differences in the distribution and ordering of operations in parallel computing lead to separation of trajectories, resulting in run-to-run variability in predicted mixing times. This work investigates the impact of repeated simulations on the mixing-time distribution observed in a 30 L stirred tank reactor using two commercial CFD packages. The results demonstrate that numerical variability is of comparable magnitude to the experimental spread, highlighting the necessity to treat LES-derived metrics as statistical ensembles rather than deterministic values.