458321 Advances in DEM Computing Which Improve Predictive Capability for Processes

Monday, November 14, 2016: 3:30 PM
Monterey I (Hotel Nikko San Francisco)
Howard Stamato1, Aditya Vanarase1, Preetanshu Pandey1, Rahul Bharadwaj2, Martin Hack3, Lucilla Almeida2 and Leon W Nogueira2, (1)Drug Product Science and Technology, Bristol-Myers Squibb, New Brunswick, NJ, (2)Rocky DEM, Inc., (3)L.B. Bohle, LLC

Prediction of process performance by DEM is limited by the number of particles which can practically be handled, modeling the particle shape by aggregating spheres, and post processing. New advances in software have now reduced computational time to allow models to capture a complete piece of full sized equipment and, with reasonable computing times, use a close approximation of particle shape. These advances, when coupled with effective post processing of the data show remarkable accuracy and detial matching the equipment performance and previously validated numerical techniques for predicting the performance. This presentation will discuss examples supporting the software capability.

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See more of this Session: CAST Rapid Fire Session: III
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