Fluids and Slender Structures
Innovative Solutions for Complex Geometries and Advanced Material Applications
Fluids and Slender Structures
Fluid-structure interaction in hydroelectric turbines
Fluid-structure interaction (FSI) is ubiquitous in industrial applications and in natural systems. At LM2, we seek to develop new modelling approaches for FSI phenomena arising in hydroelectric turbines. With the energetic transition under way in our society, hydraulic energy is being relied upon to balance the energy grid to compensate increasing fluctuations in demand and production from wind and solar energy. This implies more starts and stops and more vibrations of the turbine components. Turbine manufacturers and operators need better faster models to predict various FSI phenomena affecting vanes and runner blades such as vortex-induced vibrations; flow-added damping; and rotor-stator interaction. We collaborate with industrial and academic partners to develop and validate such models.
Fluid-structure interaction in nature
Wind buffets trees. Waves pound seaweeds. Plants, algae and corals live in constantly moving fluid, whether air or water. In response to the loads associated with fluid motion, these organisms bend and twist, often with great amplitude. They go with the flow. This strategy arising from evolution is very different from that favoured by engineers when designing structures and it gives rise to large amplitude phenomena not encountered in man-made systems. At LM2, we seek to understand how plants adapt to strong winds, through studying idealized synthetic systems. Similary, we work with biologists and ecologist to understand how soft corals make use of vortex-induced vibrations to capture more food. This works seeks first to understand the natural world we live in, but it also serves as a source of inspiration for biomimetics.
Digital twin technology
Together with industrial partners, LM2 works to develop the tools to build Digital Twins. Such a digital twin will combine live sensor data with physics-based modeling through artificial intelligence to achieve real-time simulation of a real piece of equipment. It will allow predicting failures, optimising maintenance schedules, and simulate scenarios of usage and wear of the equipment. We develop new methods based on Physics-Informed Neural Networks (PINNs) as well as different reduced-order modelling techniques to build a digital twin from the ground up. We also operate experiments such as a pipe conveying fluid and a vertical axis rotating machine to test our digital twin technologies
Experiments and Simulations
We make use of various experimental tools such as a closed-loop wind tunnel, 6-axes load cells, universal material testing machines, a laser cutting machine, microfabrication and 3d printing facilities. Various theoretical modelling tools such as custom-coded solvers for beam and shell dynamics have been developed, but commercial finite element and CFD codes are also frequently used. We develop codes based on Physics Informed Neural Networks, Proper Generalised Decomposition, Kalman Filters, and others.
Active Projects
Spiderweb-inspired, transparent, impact-absorbing composite
Flutter limit to drag reduction by reconfiguration
Past Projects
Kirigami-inspired parachutes: Programming the reconfiguration of flexible disks
Related News
LM2 at CANCOM 2024
