An advanced electrodialysis process model in the Julia ecosystem
07-25, 16:45–16:55 (US/Eastern), Elm A

Electrodialysis, a prominent technology in the production of drinking water from seawater is modelled using the Julia ecosystem. A framework of partial differential equations and neural networks is solved to model the fouling of this process and to optimise its design and operation.


Electrodialysis is a separation technology that uses electric fields and ion-exchange membranes to separate charged components from solutions. Electrodialysis is a highly efficient technology with prominent applications in the production of drinking water from seawater and the recovery and upgrading of various bio-based resources.

The majority of physical and electrochemical phenomena are well understood and can be described by mechanistic models. The complex and intricate interplay of various phenomena that occur at the surface of the ion-exchange membranes add an incredible amount of complexity and a mechanistic description is often too difficult. The Julia ecosystem provides a unique opportunity to couple differential equation solvers with machine learning techniques such as neural networks as a hybrid approach to model these kind of systems. Automatic differentation facilitates the optimisation procedure and is interesting from an engineering point of view.


Co-authors

Ingmar Nopens

A PhD student at Ghent University and VITO currently working on developing models for electrochemical processes. As a bio-science engineer that loves mathematical modelling, I transform real-life systems into virtual systems and have experience in computational fluid dynamics, machine learning and bioprocess technology.