“…A considerable saving in computational effort can be made if, for the thousands of simulations required during an aircraft loads loop or for quantification of the effects of parameter uncertainties on the aeroelastic behaviour, a ROM is used in place of the high dimensional model. The ROM could thus be seen as a physics-based surrogate alternative to the data-fitting approaches, such as Kriging, Radial Basis Functions, Neural Networks or system identification proposed for the same purpose in [6], [7], [8]. Whereas a data-fit surrogate model, created in a black-box mode, maps an input/output relationship, a ROM embodies the underlying physics of the problem and, unlike the aforementioned methods, its validity is not limited to the conditions under which it was generated, but can be applied to simulate various initial conditions.…”