About Us

At FLOW, we focus on ensuring access to sustainable energy for all, which is one of the sustainable development goals of the United Nations. We tackle this challenging mission through 3 research topics: circular energy, low emissions, and flexible energy systems.

Circular energy

The production and the use of energy needs to be encompassed in an holistic approach that aims at reducing the amount of waste energy in a cost-effective manner. We are dedicated to support the development of:

• Efficient wind power production;

• Optimal use of industrial and municipal waste, cost-effective valorisation of waste heat;

• Dynamic storage of heat coupled to combined heat & power production and local district heating;

• Integration of fuel-flexible bio-energy systems in the developing bio-based industry.

Low emissions

Pollutant emission reduction from transport and energy production is a crucial health issue. While zero-local-emissions technologies are evolving fast, they are not likely to entirely replace the existing, mature technologies in the near future. Although a dramatic decrease of the main sources of pollution has been observed in the last decades, further efforts must be carried out in order to reduce to acceptable levels the amount of harmful substances emitted in the atmosphere. This is why we work on the characterisation of the actual sources of NOx, SOx and particulate matter emissions in real conditions:

• real driving emissions from the transport sector;
• real emissions from stationary heat & power production, taking into account their flexible use as a support to intermittent energy sources;
• atmospheric flow simulation to predict propagation in cities.

Flexible energy systems

A flexible energy system that encompasses power, heat and transport is needed to allow for a high penetration rate of intermittent renewable energy sources like sun and wind. At FLOW, we work on the integration of these sources through studies and projects on:

• the flexible, cost-effective production of heat &power from sustainable, dispatchable energy sources like certified biomass and waste;
• the optimal production of electro-fuels for long term energy storage and further use for heat & power and transport.

The study of complex flows is typically done using numerical simulations that solve the governing equations. At FLOW, we have a broad experience in the simulations of steady and unsteady flows (uRANS and LES). We use the open source software OpenFOAM and the commercial package Ansys Fluent. Typical applications include the flow about horizontal and vertical axis wind turbines, oscillating aerofoils, wings, or bluff bodies, as well as atmospheric flows for the study of particle dispersion and wind resource assessment.

Unsteady and turbulent flow effects play a very important role in a wide range of applications: from the design of wind turbines, rotorcraft, to fixed-wing aeroplanes, to the study of turbulent atmospheric flows, turbine wakes, and particle dispersion in cities. We study these flows using both numerical simulations (CFD) and experiments in one of our four low-speed wind tunnels. One particular focus with respect to unsteady and turbulent flow phenomena is on the construction of accurate data-driven models that can be used for design optimisation or real-time flow control. Past efforts have proven the capability of our methods for a 2D circular cylinder oscillating transversely to the unperturbed flow. We are currently extending this functionality to include pitching and plunging aerofoils and wings.

Current state-of-the-art Computer-Aided Engineering (CAE) tools can only account for the uncertainties inherent to the processes in a very limited way, making the obtained global optima unreliable. The inclusion of an advanced and reliable uncertainty quantification in the CAE tools, coupled to an efficient methodology, would therefore be a major breakthrough for CAE, allowing industrial partners to design quicker and obtain better, cheaper and more robust (i.e. less uncertainty sensitive) products.

The primary objective of this research topic is to develop an efficient methodology for the optimization of industrial processes under uncertainty.  The methodology will enable to construct/achieve robust designs. The methodology will handle uncertainties in the model parameters, as well as uncertainties in the design variables. Hereby, the emphasis is on a large number of design variables and uncertainties. The inclusion of uncertainty quantification in the design cycle requires combining the exploration of the design space (optimization) with exploration of the stochastic space and the development and use of accurate and efficient surrogate models.

Such methodology offers following major opportunities:

1. better, more efficient, more performant products or processes
2. changing know-how from “alchemy” to “science”
3. resulting in more environmentally friendly processes
4. savings on R&D time and costs
5. reduced time-to-market path.

In practice, everything in aerodynamics is unsteady, turbulent, and nonlinear: from the wind that drives turbines and disperses particles throughout cities to the constantly changing flow around the blades of a helicopter or turbine rotor. For too long, unsteadiness, turbulence, and nonlinearity, have been treated as side-effects that are often neglected, more because of their complexity than their limited importance. Indeed, it is dangerous to reduce unsteady flows to averaged steady flows plus some marginal unsteadiness, to disregard turbulence as just negligible noise source, or to blindly trust the linearized-flow behaviour. Moreover, this oversimplification is unnecessary. With modern tools, aerodynamic unsteadiness, turbulence, and nonlinearity can be incorporated into design optimization, and even put to advantage via the active, closed-loop control of the flow.

Current and future developments include

1. the smart combination of data-driven modelling through nonlinear system identification techniques, with (multi-fidelity) physical modelling,
2. the use of such techniques for the prediction of time series of the wind speed with a given probability density function and autocorrelation function (something that is statistically impossible but what we believe can be approximated arbitrary well with our techniques), the input data will come from existing data and from wind measurements we perform ourselves,
3. the development of a cyber-fluid dynamics facility, in which a computer model is integrated into an experimental setup to artificially introduce extra dynamics that are not experimentally included,
4. an unsteady wind tunnel that can be combined with an oscillating model (aerofoil, cylinder) equipped with flow control actuators (plasma actuators, adaptive blowing, smart tabs and flaps) for the study of load alleviation and performance enhancement of wind turbines, helicopter rotors, and aeroelasticity in general,
5. the furthering of our work on small wind turbines (both in the field and in urban environments), in particular the effect of turbulence on the performance of these turbines, and the role that system identification can play in the mitigation of such undesirable effects.

The characterisation of the performance of energy systems in terms of efficiency and environmental impact is crucial for the validation of the static and dynamic models that we develop and for the quantification of the related uncertainties.  At FLOW, we work on both pilot-scale and full-scale measurements of the performances of windmills and heat & power production units, at small, medium and large scales. We combine conventional and advanced measurement techniques and we collaborate with industrial partners to ensure that our data-driven models are in line with reality, and ready for robust optimisation.