Fast and accurate solution of computationally-demanding engineering problems is critical in daily industrial practice. Indeed, efficient strategies are needed to compute multiple queries of complex multi-physics and multi-disciplinary problems arising in parametric studies such as flow control, shape design and optimization, real-time monitoring of manufacturing processes and inverse analysis in medical imaging.
To contribute in these challenges the group exercises a comprehensive approach in the area of computational science and engineering, in order to develop new mathematical models and numerical methods to predict and quantify science and engineering problems. This implies combining concepts, methods and models of an interdisciplinary nature that include various disciplines such as mechanics, mathematics and computer science, among others.
An objective is to develop state-of-the-art computational engineering solutions for the efficient simulation of complex physical and industrial problems involving fluids, solids, electromagnetics and multi-physics phenomena. Consequently, research is articulated along different lines, spanning from high-order discretization techniques for the accurate description of complex features of the phenomena under analysis, to robust and efficient finite volume solvers for the simulation of large-scale problems and reduced order models to manage the computational burden of multiple queries studies. The above methodologies are then enhanced by certification procedures allowing to assess and control the accuracy of the numerical approximations and the uncertainty of models and data to devise credible and reliable simulations.
The group is also active in the development of open-source software and in the integration of innovative algorithms in existing open-source libraries.