PRIN 2017 - 201752HKH8_004 - Tamellini Lorenzo (DIT.AD021.092)
Project areaMatematica Applicata (DIT.AD021)
Structure responsible for the research project
The objective of this research project is to design and analyze innovative numerical methods for the approximation of partial differential equations (PDEs) in computational sciences and engineering. The increasing complexity of realistic models and the evolution of the computational platforms and architectures are challenging the numerical analysis community to develop more efficient, effective, and innovative methods, able to incorporate uncertainty quantification, data analysis and high performance computing applications. Our research units share a consolidated expertise on advanced discretization schemes based on variational approaches, such as conforming and nonconforming finite elements (FEM), spectral and hp finite elements (hp-FEM), immersed methods, finite volumes (FV), as well as on reduced order methods (ROMs) that rely on the aforementioned schemes and on Uncertainty Quantification (UQ) methodologies.
Start date of activity
Partial Differential Equations, Reduced Order Models, Efficient and Acccurate Solvers
Last update: 09/12/2023