LAUSR

Reduced Order Models (ROMs), also known as Reduced Basis Methods (RBMs), have received considerable attention in recent years for their ability to drastically reduce CFD cost, particularly when dealing with parametrised problems in a multi-query setting. This Special Issue gathers recent advances in ROM/RBM techniques for complex flow problems relevant to applications in mechanical and aerospace engineering, as well as medical and applied sciences. Manuscripts have been selected focusing onmethodological developments, with an emphasis on mathematical modelling and applications in areas such as nonlinear inverse problems, optimal flow control, shape optimisation and uncertainty quantification. Advanced developments are proposed to cover broader applications in multiphysics contexts, such as fluid-structure interaction problems and such coupled phenomena involving inviscid, viscous and thermal flows in the incompressible and compressible flow regimes. This Special Issue provides an ideal and timely context to highlight some state-of-the-art methodologies ready to be applied in industrial andmedical problems, including aeronautical, mechanical, naval, offshore, wind, sport, biomedical engineering and cardiovascular surgery, combining elements of high-performance computing and advanced ROM/RBM, real time computing, data management and visualisation. Kaveh and Habashi, by means of ROM, show how CFD costs can be drastically reduced. In addition, a more complete investigation of a continuous design space obtained by adding experimental fluid dynamics and flight fluid dynamics data leads to a better integration of physical testing and computational data. Pascarella and co-authors show how accurate solutions of unsteady flows during the design process of an aircraft can be a highly demanding task. RBMs are