Teaching Assistant

Prof. dr. ir. Ingmar Nopens - Ghent University
Dr. ir. Jan Baetens - Ghent University

Research background

In filtration modelling, traditional resistance in series models to describe fouling behaviour do not have the predictive power to be useful in scenario analysis, since their empirical nature and typical overcalibration hampers validation in other parts of the operational space. Instead, a new modelling framework for describing membrane fouling is presented based on an integration of computational fluid dynamics and individual-based models. This framework, in relation to similar trends in biokinetic modelling, allows for knowledge build-up on filtration behaviour that can be used to construct simplified but realistic fouling models. The key element of the presented approach is modelling individual (microscopic) particle movement to understand (macroscopic) bulk behaviour.

Research objective

Within this research, I try to build a general framework that allows for a better mechanistic model to describe particle motion in filtration application. The model is modular in design, so that new equations and processes can be built in, depending on the operating conditions and feed characteristics.

Research methodology
  1. First, a computational fluid dynamic (CFD) model is set up to describe the fluid flow in tubular membranes
  2. This model is extended with a description of the force balance on particles in suspension
  3. A lab let-up is built to gather experimental data for calibration and validation
Key publications
Naessens, W., Maere, T., and Nopens, I. (2012). Critical review of membrane bioreactor models - Part 1: Biokinetic and filtration models. Bioresource Technology 122, 95-106.
Naessens, W., Maere, T., Ratkovich, N., Vedantam, S., and Nopens, I. (2012). Critical review of membrane bioreactor models, part 2: hydrodynamic and integrated models. Bioresource Technology 122, 107-118.
Naessens, W., Maere, T., Gilabert-Oriol, G., Garcia-Molina, V., and Nopens, I. (2017a). PCA as tool for intelligent ultrafiltration for reverse osmosis seawater desalination pretreatment. Desalination 419, 188-196.
Maere, T., Villez, K., Marsili-Libelli, S., Naessens, W., and Nopens, I. (2012a). Membrane bioreactor fouling behaviour assessment through principal component analysis and fuzzy clustering. Water Research 46, 6132-6142.