Research Tim Van Winckel

Abstract

Water scarcity is a major issue in Flanders. Up to 80% of our available water resources are utilized, meaning it is high time for integrative solutions that focus on water reuse, preferably decentralized. Source-separated grey water is the largest stream by volume and thus ideal candidate for decentralized domestic water reuse. Current state-of-the-art to achieve this is utilize a membrane biofilm reactor (MBR), which has the advantage of being compact. MBRs, however, have a high energy demand and maintenance, making them relatively expensive to maintain. TwinMemBio tackles these disadvantages by combining a membrane aeration biofilm reactor (MABR) with an MBR to create a system with low energy demand a decreased maintenance. TwinMemBio's unique control strategy makes it an excellent choice for places that require the highest standard for non-potable reuse while also requiring low energy and maintenance cost, making it an excellent choice for decentralized domestic source-separated water treatment and reuse.

Researcher(s)

• Promoter: Van Winckel Tim
• Co-promoter: Vlaeminck Siegfried

Research team(s)

• Sustainable Energy, Air and Water Technology (DuEL)

Project type(s)

• Research Project

Abstract

Flanders together with many other regions in Europa has suffered through one of its driest summers in history and this will unfortunately not be a singular event. To ensure sufficient water availability for all actors in the Flemish region (drinking water, agriculture, industry…), we need to significantly increase the resilience of our water management through optimization of existing infrastructures, stimulation of circular water practices and strategic investments in new infrastructure. However, water management is inherently a very complex subject touching many different actors and covering a large spatial scale. Building water resilience thus requires a decision making tool which is able to incorporate this complexity in order to support holistic decisions that can balance multiple objectives. However, bringing available data and modelling tools together over different scales and application domains to address high level technological or societal challenges is not possible with tools that are currently available. This project will use methodologies based on semantic web standards. More specifically, data standards, a ontology model and a dynamic knowledge graph will be developed as a way to encode and structure knowledge and as such create a standardized and holistic structure of the water domain. The knowledge graph will be dynamic so it can be continuously populated with new data (sensor data, design data, simulation data) and integration of predictive models and optimization algorithms will be foreseen within its structure allowing for the analysis of holistic scenarios to support decision making. Knowledge graphs can be built in a modular way creating a lot of flexibility for future developments/updates. Since they are based on standardized web semantics they can be easily queried (used to answer questions). Moreover their standardized form also allows coupling to other sectors (such as energy) for cross-domain decision making.

Researcher(s)

• Promoter: Vlaeminck Siegfried
• Co-promoter: Spiller Marc
• Co-promoter: Van Winckel Tim

Research team(s)

• Sustainable Energy, Air and Water Technology (DuEL)

Project type(s)

• Research Project

Abstract

Legionella is a bacterium that can affect many processes operating at higher temperature or functioning discontinuously. Monitoring of this bacterium is currently done primarily through microbiological tests such as plating. This project investigates whether Legionella can be detected using artificial intelligence to monitor existing processes more efficiently.

Researcher(s)

• Promoter: Vlaeminck Siegfried
• Co-promoter: Van Winckel Tim

Research team(s)

• Sustainable Energy, Air and Water Technology (DuEL)

Project type(s)

• Research Project