Overview

This webinar presents an AI-augmented workflow that wraps an intelligent design-exploration layer around trusted mixing models, helping engineers search large design spaces with fewer manual iterations. Using a 2000-liter aerobic mammalian-cell bioreactor case study, we combine KaeMix mixing and kLa prediction with Oasis.AI small-data optimisation to vary impellers, sparging, and operating conditions under power, gas-dispersion, and shear constraints.

The session highlights how embedded optimisation can surface non-obvious, practical configurations that improve mass transfer while reducing energy and cell-damage risk.

Speaker

Richard D LaRoche, Founder and Director, Rwanika-LaRoche LLC

Richard is founder and director of Rwanika-LaRoche LLC, a consultancy focused on providing business development services for engineering software companies and developing cloud-based services that support fluid mixing and reactor design for the pharmaceutical and chemical process industries. He has over 30 years of experience commercialising and applying advanced engineering software (including CFD and DEM) to manufacturing and process-development problems.

Previously, he served as CEO/CTO of DEM Solutions (makers of EDEM, acquired by Altair Engineering in 2019), held leadership roles at ANSYS/Fluent spanning business development, consulting, and academic program management, and worked as a fluid flow and mixing expert at DuPont.

The material presented in this webinar has not been peer-reviewed. Any opinions are the presenter’s own and do not necessarily represent those of IChemE or the Fluid Mixing Processes Special Interest Group. The information is given in good faith but without any liability on the part of IChemE.

Time

12:00–13:00 GMT.

Software

The presentation will be delivered via Microsoft Teams. We recommend downloading the app from the Microsoft website, rather than using the web portal.