Mathematical and Computational Modelling Across the Scales

Barcelona, Spain | 3-7 July, 2023

XX Jacques-Louis Lions Spanish-French School on Numerical Simulations in Physics & Engineering

Many problems in physics and engineering are characterised by phenomena involving different scales, both spatial and temporal. Accurate description and reliable simulation of such phenomena entail major challenges from the point of view of both mathematical modelling and computational science and engineering.

XX edition of the School is devoted to the challenges of “Mathematical and Computational Modelling Across the Scales”pertaining to physical problems involving micro-, meso-, macro- and multi-scale phenomena. The thematic focus is broad, encompassing contributions on modelling and numerical methods, for direct and inverse problems, with applications spanning from wave propagation to composite materials and complex fluids, from quantum mechanics to biological and building simulations.

The School is hosted by the Laboratori de Càlcul Numèric (LaCàN) at Universitat Politècnica de Catalunya and the International Centre for Numerical Methods in Engineering (CIMNE), under the auspices of the Sociedad Española de Matemática Aplicada (SEMA) and the Société de Mathématiques Appliquées et Industrielles (SMAI).

The School is addressed to PhD students and Postdoctoral fellows in applied mathematics and computational engineering, but it is open to any researcher interested in the field. The goal is to strengthen the long-time relation between the Spanish and the French applied mathematics communities, while broadening the boundaries to include international participants, as well as, computational scientists, physicists and engineers to foster trans-disciplinary discussion and cross-dissemination of ideas. For this purpose, the School is scheduled as a fully in-person event and the official language is English.

A poster session will be organised for young researchers to disseminate their work, offering a platform for discussion of current and new trends in the community. In this context, contributions involving industrial problems and emerging techniques in machine learning and artificial intelligence for data-intensive applications are particularly welcome.