Freeze-drying is a low-pressure, low-temperature condensation pumping process widely used in the manufacture of pharmaceuticals for removal of solvents by sublimation. The performance of a freeze-dryer condenser is largely dependent on the vapor and ice dynamics in the low-pressure environment. The main objective of this work is to develop a modeling and computational framework for analysis of vapor flow and ice dynamics in such freeze-dryer condensers. The direct Simulation Monte Carlo (DSMC) technique is applied to model the relevant physical processes that accompany the vapor flow in the condenser chamber. Low-temperature water vapor and nitrogen molecular model is applied in the DSMC solver SMILE to simulate the bulk vapor transport. The developing ice front on the coils of the condenser is tracked based on the steady state mass flux computed at the nodes of the DSMC surface mesh. Verification of ice accretion simulations has been done by comparison with the solution for analytical free-molecular flow over a circular cylinder. The developed model has also been validated with measurements of ice growth in a laboratory and production scale freeze-dryer using time-lapse imaging. To illustrate the application of the ice accretion algorithm in the area of bio-pharmaceutical freeze-drying, the current work discusses the effect of the condenser geometry and non-condensable gas on non-uniformity of mass flux in a laboratory scale and production scale freeze-dryer condenser. In addition, the simulations are used to predict the ice formation on the coils of the condenser. It was found that in the laboratory scale dryer, the presence of a duct connecting the product chamber and condenser increased non-uniformity by 65% at a sublimation rate of 5 g/hr. The measured ice thickness on the coils of the condenser was found to increase non-linearly. This non-linearity was captured within an accuracy of 1% compared to the measurements towards the end of a 24 hour cycle using an unsteady icing model while that using a steady model was within 14%. In the production dryer, while the steady model predicted the iced coil diameter within an accuracy of 2–5% with respect to the measurements, the unsteady model captured this within an accuracy of 1–6%. The DSMC simulations demonstrate that by augmenting its capabilities with the icing model, it is possible to predict the performance of a freeze-dryer condenser with any arbitrary design.

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