Deep neural operators, such as DeepONet, have changed the paradigm in high-
dimensional nonlinear regression, paving the way for significant generalization and speed …

Surrogate modelling is a popular approach for reducing the number of high fidelity
simulations required within an engineering design optimization. Multi-fidelity surrogate …

Deep neural operators, such as DeepONets, have changed the paradigm in high-
dimensional nonlinear regression from function regression to (differential) operator …

OPTIMIZATION has become an important element in the design and development of modern
civil airliners. It is the continual goal of aircraft designers to improve performance, reducing …

C= fluctuation correlation matrix CD= drag coefficient CL= lift coefficient F= matrix of
snapshot fluctuations l= design variable lower bounds M= no. of snapshots n= no. of sample …

In the aviation field great interest is growing in passengers transportation at hypersonic
speed. This requires, however, careful study of the enabling technologies necessary for the …

In aerodynamic optimization, global optimization methods such as genetic algorithms are
preferred in many cases because of their advantage on reaching global optimum. However …

An optimization design method for a supercritical wing is developed in this paper based on a
pressure distribution transformation between the airfoil and wing. This transformation takes …

The subject of this work is numerical shape optimization in fluid mechanics, based on
isogeometric analysis. The generic goal is to design the shape of a 2-dimensional flow …

Panel methods are frequently applied to aerodynamic shape optimization problems due to
their fast turnaround time and ability to model arbitrary geometries. Despite being …