Fluid Agitation Studies for Drug Product Containers Using Computational Fluid Dynamics

<p>At Amgen, the Automated Vision Inspection (AVI) systems capture the movement of unwanted particles in Amgen's drug product containers. For quality inspection, the AVI system must detect these undesired particles using a high speed spin-stop agitation process. To better understand the fluid movements to swirl the particles away from the walls, Computational Fluid Dynamics (CFD) is used to analyze the nature of the two phase flow of air and a liquid solution.</p> <p>Several 2-D and 3-D models were developed using Fluent to create simulations of Amgen's drug product containers for a 1 mL syringe, 2.25 mL syringe, and a 5 mL cartridge. Fluid motion and potential bubble formations were studied within the liquid/gas domain inside the container by varying parameters such as viscosity, angular velocity, and surface tension. Experiments were conducted using Amgen's own equipment to capture the images of the spin-stop process and validate the models created in Fluent. Observations were made to see the effects of bubble formation or splashing during spin-down to rest.</p> <p>The numerical and experimental results showed favorable comparison when measuring the meniscus height or the surface profile between the air and liquid. Also, at high angular velocity and dynamic viscosity, the container experiences instabilities and bubble formations. These studies indicate that CFD can be used as an useful and important tool to study fluid movement during agitation and observe any undesirable results for quality inspection.</p>

Name thesis:degree_name

MS in Mechanical Engineering

Discipline thesis:degree_discipline

Mechanical Engineering

Year dc:date.available

2018

Author dc:creator

• Ichinose, Matthew Hiroki

Contributors dc:contributor

• Kim Shollenberger

• CFD
• Drug Manufacturing
• Computational Fluid Dynamics
• Spin-up
• Spin-down
• Fluid flow
• Applied Mechanics
• Computational Engineering
• Mechanical Engineering
• Process Control and Systems

Identifier

10.15368/theses.2018.144

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-3342