Consider a tablet coating operation where the objective is to minimize the coating variability. Experimental optimization of such a process is costly and time consuming. Virtual troubleshooting and process optimization in Rocky can be far more feasible.
With the Compute Particle Visibility script introduced in Rocky 4.3, the ability to predict coating variability has become far more powerful than ever before. The users can now get:
A much more accurate estimate of the coating mass deposited on tablets
An estimate of the coating variability between tablets (inter-particle) but also within a tablet (intra-particle)
How it works
The user steps needed to use the Compute Particle Visibility script are the following:
Set up the Rocky case and run the simulation as before.
Set the 3D View window as seen by the spray nozzle(s) to get the spray zone. This can be easily done by setting the camera view using a simple script.
Run the Compute Particle Visibility script.
Rocky would track the time spent by each face of every particle within the spray zone and report it as “visibility”. This naturally takes into account instantaneous particle orientation and total or partial occlusion of the underlying particle layers, thus greatly enhancing the accuracy.
In the animation below we can see how the coating variability, both inter- and intra-particle, can be predicted using the Compute Particle Visibility script.
Utility of the Compute Particle Visibility script (Ray Tracing tool)
1. Inter-Particle Coating Variability: As seen in the video, Rocky provides the users with cumulative visibility data for every particle, i.e. the sum of the visibility of all the faces of the particle. This is directly related to the coating mass received by every particle.
The user can obtain the bulk average and standard deviation for visibility to obtain the coefficient of variation (CoV) estimate for inter-particle coating variability. Change of CoV with time can be used to predict the time needed to achieve target coating with a given process and compare different mixing configurations.
2. Intra-particle Coating Variability: Rocky would also provide the average cumulative visibility data for every face of a representative particle. As the video above highlights, the user can see if there’s any bias in the coating mass distribution over the tablet surface.
Applications Engineer, Rocky DEM
Dr. Saurabh Sarkar is an Applications Engineer for the Rocky DEM Business Unit. Prior to joining ESSS, Dr. Sarkar worked as an Adjunct Faculty at Rutgers University and an on-site Consultant at Sunovion Pharmaceuticals where he supported drug formulation and process development activities. He obtained his Ph.D. in Pharmaceutics from the University of Connecticut where his focus was understanding and optimization of different pharmaceutical unit operations using DEM and CFD tools in projects with multiple industrial and government collaborators. He is a Senior Member of the AIChE and serves as an expert reviewer for several journals.