ANR RedLUM - Reduced order models under location uncertainty

The objectives of the RedLUM project are to develop and use mathematical and computational tools for real-time estimation and short-term prediction of 3D fluid flows, using limited computational resources. This will be made possible by coupling data, numerical simulations and parsimonious fluid flow measurements.

To achieve these ambitious goals, the dimensionality of the problems will be considerably reduced through the use of reduced-order data and models. The errors induced by the reduction in dimension will be quantified by a stochastic, physical and multi-scale parameterisation called ‘Models under positional uncertainty’. This quantification of uncertainty will enable simulation-measurement coupling via recent data assimilation algorithms.

The expected results will be scientific, methodological and software knowledge for the rapid, predictive and low-cost simulation of turbulent flows. A proof of concept will be carried out on real flows in a wind tunnel and then from the laboratory to the field on the control of micrometeorology in agriculture. The methodology developed could have practical applications in various industries in which rapid simulation of turbulent flows is used to make decisions or control systems, such as aeronautics, wind energy, water sports, ventilation and processes.

A multidisciplinary and complementary consortium will enable the fundamental and R&D aspects of the project to be tackled jointly. The mathematical and fluid mechanics aspects will be handled by INRAE, Inria and the Sant'Anna School of Advanced Studies (Italy). The R&D aspects will be carried out by SCALIAN DS for the numerical calculation-software component and by Weather Measures for the micrometeorology application in agriculture.

RedLUM is funded by the ANR as an Enterprise Collaborative Research Project (PRCE).
RedLUM is accredited by the Images & Réseaux and Vegepolys Valley competitiveness clusters.

Projet coordinateur RedLUM : dominique.heitz@inrae.fr
Scientific manager RedLUM : valentin.resseguier@inrae.fr