Projet GRAPES (Horizon 2020, appel à projets 2019)
Action : Doctoral Networks
Panel : Mathematics
Statut du projet : SIGNED

GRAPES aims at considerably advancing the state of the art in Mathematics, Computer-Aided Design, and Machine Learning in order to promote game changing approaches for generating, optimising, and learning 3D shapes, along with a multisectoral training for young researchers. Recent advances in the above domains have solved numerous tasks concerning multimedia and 2D data. However, automation of 3D geometry processing and analysis lags severely behind, despite their importance in science, technology and everyday life, and the well-understood underlying mathematical principles. The CAD industry, although well established for more than 20 years, urgently requires advanced methods and tools for addressing new challenges. The scientific goal of GRAPES is to bridge this gap based on a multidisciplinary consortium composed of leaders in their respective fields. Top-notch research is also instrumental in forming the new generation of European scientists and engineers. Their disciplines span the spectrum from Computational Mathematics, Numerical Analysis, and Algorithm Design, up to Geometric Modelling, Shape Optimisation, and Deep Learning. This allows the 15 PhD candidates to follow either a theoretical or an applied track and to gain knowledge from both research and innovation through a nexus of intersectoral secondments and Network-wide workshops. Horizontally, our results lead to open-source, prototype implementations, software integrated into commercial libraries as well as open benchmark datasets. These are indispensable for dissemination and training but also to promote innovation and technology transfer. Innovation relies on the active participation of SMEs, either as a beneficiary hosting an ESR or as associate partners hosting secondments. Concrete applications include simulation and fabrication, hydrodynamics and marine design, manufacturing and 3D printing, retrieval and mining, reconstruction and visualisation, urban planning and autonomous driving.

Mots clés : geometric computing, geometric processing, meshing, splines, isogeometric analysis, simulation, fluid dynamics, deep learning, retrieval, architectural design, algorithms, software, benchmarks

Participants :
- SINTEF (Norvège) — Partner, beneficiary, Recherche, subvention : 292342.32 €
- Geometry factory (France) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 274802.04 €
- Institut national de recherche en sciences et technologies du numérique (France) — Partner, beneficiary, Recherche, subvention : 593954.08 €
- Università della Svizzera italiana (Suisse) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 593806.24 €
- RWTH Aachen University (Allemagne) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 61301.19 €
- University of Barcelona (Espagne) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 501809.76 €
- Athena Research and Innovation Center In Information Communication & Knowledge Technologies (Grèce) — Coordinator, beneficiary, Recherche, subvention : 543805.97 €
- University of Strathclyde (Royaume-Uni) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 361280.63 €
- Johannes Kepler University of Linz (Autriche) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 264207.24 €
- University of Rome Tor Vergata (Italie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 261499.68 €
- Vilnius University (Lituanie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 223947.0 €