IWA Publishing in conjunction with the International Water Association’s Young Water Professionals is happy to announce a new initiative spotlighting the work of Young Water Professionals and showing how the work published in IWA Publishing Journals can be useful to those beginning their careers in the water sector.
Our third spotlight blog is on Bram De Jaegher, a PhD researcher at the BIOMATH research group of Ghent University and the Flemish Institute of Technological Research (VITO). Bram was selected for this blog post after attending a YWP Conference. You can connect with Bram on LinkedIn.
Bram had access to our entire journal portfolio for one month, and picked out some interesting papers to discuss, read his thoughts below! A big thank you to Bram for participating!
Models?!, Models?, Models!
I am Bram De Jaegher, a young water professional from Ghent, Belgium. As a PhD researcher at the BIOMATH research group of Ghent University and the Flemish Institute of Technological Research (VITO), my research is on the fouling of electrodialysis installations for the processing of bio-based process streams. The goal of this research project is to develop a model for the fouling behaviour of electrodialysis and using this model improve the fouling resilience of electrodialysis installations. I have a passion for modelling and am intrigued by fluid flow. So these research topics are a perfect fit. At conferences or meetings, I often get asked the questions: “Why modelling?!” and “But what can you actually do with these models?”. So, I would like to take the opportunity to answer both questions by highlighting some of my favourite models published in IWA Publishing journals while demonstrating what these models can do for the water industry.
“What is a model?”
A model is a mathematical description of a system which is often a real-life setup. There are many ways of constructing models but they are generally divided into two categories, mechanistic models and data-driven models. For the former, the system is translated into equations according to physical and chemical principles and is a solidification of knowledge. The latter, data-driven models, find patterns in data and do not include any prior-knowledge in the model. Machine learning (also known as artificial intelligence) is a very popular group of techniques to achieve this. Both approaches have different sets of advantages and disadvantages and are used for different purposes.
By rephrasing this question to: “Do you want a virtual, fully-automated, version of your experimental setup, pilot- or full-scale installation where you can perform billions of experiments while sipping your favourite beverage?” makes the answer pretty obvious as drinking is not allowed in most wet labs.
“But what can you actually do with these models?”
Mathematical models can fulfil a plethora of tasks in the water sector but for this blog post I’m going to highlight three prominent uses, 1) understanding, designing and improving systems, 2) control of processes, 3) risk management and decision-support tools.
The translation of a physical system into a set of equations generates insight and a better understanding of the process you are studying. Furthermore, such a model allows for virtual experimentation to explore improved designs and operation. this is illustrated by Amaral et al. (2017) where a model is constructed to better understand the underlying mechanism of aerators for biological water resource recovery facilities.
A model can predict the behaviour of a process in various conditions and the availability of a model can be a great asset to process control. Torfs et al. (2015) showed that by applying an advanced model for secondary settlers to control the operation of a water resource recovery facility one can greatly improve the robustness of these facilities during extreme rain events. As it is a challenge to ensure the performance of these water treatment plants in extreme conditions, this is a great example of the power of models. Models are not only useful in case something goes wrong but also to improve the performance and efficiency of a process. To that end, Bakker et al. (2013) developed a model-based controller to automate water utilities and improve the water quality and energy efficiency along with it.
The last, but not least of these applications is the use of mathematical models for risk management and decision-support systems. Due to climate change, the frequency of extreme weather events such as floods keeps increasing. To manage the risk for inhabitants of flood-prone areas and prioritise evacuation, it is crucial to accurately predict the extend flood events. Kirkpatrick & Olbert (2020) developed a model that maps the extent of coastal flooding due to climate change and helps manage the risk of flooding.
As you can see, the use of models in the water industry is widespread. And I hope by highlighting these four great research articles to have answered all your burning question on modelling and have sparked some interest in the science and art of mathematical modelling.
Bram De Jaegher
Bram.DeJaegher [at] UGent.be
Towards advanced aeration modelling: from blower to bubbles to bulk
Andreia Amaral, Oliver Schraa, Leiv Rieger, Sylvie Gillot, Yannick Fayolle, Giacomo Bellandi, Youri Amerlinck, Séverine T. F. C. Mortier, Riccardo Gori, Ramiro Neves and Ingmar Nopens
Water Science & Technology, (2017) 75 (3): 507–517.
Impact on sludge inventory and control strategies using the benchmark simulation model no. 1 with the Bürger-Diehl settler model
E. Torfs, T. Maere, R. Bürger, S. Diehl and I. Nopens
Water Science & Technology, (2015) 71 (10): 1524–1535.
Better water quality and higher energy efficiency by using model predictive flow control at water supply systems
M. Bakker, J. H. G. Vreeburg, L. J. Palmen, V. Sperber, G. Bakker and L. C. Rietveld
Journal of Water Supply: Research and Technology-Aqua, (2013) 62 (1): 1–13.
Modelling the effects of climate change on urban coastal-fluvial flooding
Jennifer Isabel Munro Kirkpatrick and Agnieszka Indiana Olbert
Journal of Water & Climate Change, January 2020.