Accurate Roms for Industrial Applications

PI: Tomás Chacón Rebollo

co-PI: Macarena Gómez Mármol

Acronym: ARIA

Abstract: The project Accurate Roms for Industrial Applications aims at developing an array of mathematical methods for constructing predictive reduced-order models (ROMs) with guaranteed accuracy, robustness, reliability and efficiency for applications involving complex physical phenomena. New approaches to this challenge are proposed here with a focus on the Euler and Navier–Stokes equations of fluid flow, two of the most challenging continuum models with an extraordinary rich range of industrial applications. The mathematical modeling and solution of the Euler and Navier-Stokes equations is sometimes cited as the greatest challenge in continuum modeling of physical phenomena. This topic is selected as our principal focus because of its intrinsic importance, but also because the mathematical methods developed in addressing this very challenging task may well have an impact on other fields of knowledge. We plan to tackle these challenging objectives in this staff exchange program by combining the unique expertise of our extended research team whose members have made significant progress in ROM research during the past decade. This academic expertise is cross-fertilized by the exchange with knowledge intensive SMEs ans start up and well established industrial partners that will benefit from the scientific and technological results of the team and will challenge the solutions found with applications in real world problems. 
The University of Sevilla is one of its partners, in charge of Work Package 2: Reduced Order Models for incompressible turbulent and unsteady flows.

Source of Funding: H2020 Program. H2020-MSCA-RISE-2019, (H2020-872442)

Implied entities: University of Sevilla

Partners: INRIA (France), Optimad  (Italy), VirtualMech (Seville), Valorem (France),Poitecnico di Milano, ESTECO (Italy), Volkswagen (Germany), Nurea (France), IEFluids SISSA 

iMAT research line:    RL1: Modeling of Energy Systems     RL7: Numerical Analysis

Researchers:

Alejandro Bandera Moreno

Cristina Caravaca García

Tomás Chacón Rebollo

Soledad Fernández García

Macarena Gómez Mármol

Samuele Rubino