Optimising the Rheology of Dense Granular Suspensions at the Particle Scale using Simulation and Machine Learning

Stefan Pantaleev, Lead Solutions Specialist at Altair presents at the 2024 ATCx DEM.

Achieving optimal dense suspension rheology is key to meeting product quality requirements in a wide range of industries, but the traditional optimization approach, which is heavily reliant on physical trial-and-error, is prohibitively time consuming and expensive. Virtual optimisation can lead to significant time and costs savings in this context.

In this talk we will present an efficient virtual optimization methodology that combines Discrete Element Method (DEM) simulation in Altair EDEM with machine learning and optimization algorithms in Altair HyperStudy to rapidly identify the optimal particle scale properties for a target suspension viscosity.