Matthias Adams, Georgios D. Stefanidis, and Tom Van Gerven of the Department of Chemical Engineering, KU Leuven, and the Department of Process Analysis and Plant Design, NTUA, have published a new article entitled: “Determining residence time distributions in oscillatory baffled reactors: A comparison between experiments and CFD-simulations.” The article appears in Chemical Engineering and Processing – Process Intensification and was made available online on 12 April 2025.
This paper investigates how well CFD simulations predict residence time distributions (RTDs) in oscillatory baffled reactors (OBRs)—a key process intensification technology. By testing four different modelling approaches (2D laminar, 2D turbulent, 3D laminar, 3D turbulent), the authors assessed predictive accuracy across a range of flow conditions. The standout finding: 3D laminar simulations best matched experimental data, even though 2D models are often recommended in literature for such tasks. This mismatch highlights the need for new modelling guidelines that differentiate between local flow descriptions and global performance metrics.
Mechanistically, the work underscores how alternating vortex formation during flow reversal drives enhanced radial mixing in OBRs. This vortex behaviour effectively transforms the reactor into a series of continuous stirred tank reactors (CSTRs), enabling near-plug-flow performance even under low Reynolds number conditions. Importantly, the decoupling of throughput (net flow) and mixing (oscillatory flow) offers significant control over reactor performance.
Reference:
Adams M., Stefanidis G.D., Van Gerven T. (2025). Determining residence time distributions in oscillatory baffled reactors: A comparison between experiments and CFD-simulations. Chemical Engineering and Processing – Process Intensification, Vol. 197, Article 110297. https://doi.org/10.1016/j.cep.2025.110297
Acknowledgements:
This research was supported by the SIM² KU Leuven research cluster and is published open access under the CC BY-NC-ND license.
