(561d) New Insights into Local Residence Time Distributions of Twin Screw Elements Used in Hot Melt Extrusion Via Smoothed Particle Hydrodynamics Simulation

Hot Melt Extrusion (HME) is a continuous manufacturing process used in the pharmaceutical industry to produce drug products with a controlled release profile or with increased bioavailability. Due to the complex flow in Twin Screw Elements (TSE), some parts of the polymer melt reside longer in it then others. This effect is commonly described with Residence Time Distributions (RTD). The RTD can be investigated experimentally for entire Hot Melt Extrusion (HME) processes. However, when kinetic effects (e.g., product formation or degradation) play a role local RTDs are required and these are difficult to obtain experimentally.

Method

Here we show that the numerical simulation method Smoothed Particle Hydrodynamics (SPH) is suitable for determining local RTDs in silico. SPH is a lagrangian meshless fluid dynamics method and offers computational advantages for flow simulations with complex moving boundaries.[1–3]

Results

We compared our computed local RTDs with experimental results. Furthermore, we investigated a variety of geometrically different screw elements and how their local RTDs varied with screw speed, throughput and screw length. Computational tracer experiments were used to visualize the underlying flow mechanism leading to differences in the local RTD.

References

[1] Eitzlmayr A, Khinast J. Co-rotating twin-screw extruders: Detailed analysis of conveying elements based on smoothed particle hydrodynamics. Part 1: Hydrodynamics. Chem Eng Sci 2015. https://doi.org/10.1016/j.ces.2015.04.055.

[2] Eitzlmayr A, Khinast J. Co-rotating twin-screw extruders: Detailed analysis of conveying elements based on smoothed particle hydrodynamics. Part 2: Mixing. Chem Eng Sci 2015;134:880–6. https://doi.org/10.1016/j.ces.2015.05.035.

[3] Eitzlmayr A, Matic J, Khinast J. Analysis of Flow and Mixing in Screw Elements of Co-Rotating Twin-Screw Extruders via SPH. vol. 00. 2016. https://doi.org/10.1002/aic.