  In this paper, a new take on the concept of an active subspace for reducing
the dimension of the design parameter space in a multidisciplinary analysis and
optimization (MDAO) problem is proposed. The new approach is intertwined with
the concepts of adaptive parameter sampling, projection-based model order
reduction, and a database of linear, projection-based reduced-order models
equipped with interpolation on matrix manifolds, in order to construct an
efficient computational framework for MDAO. The framework is fully developed
for MDAO problems with linearized fluid-structure interaction constraints. It
is applied to the aeroelastic tailoring, under flutter constraints, of two
different flight systems: a flexible configuration of NASA's Common Research
Model; and NASA's Aeroelastic Research Wing #2 (ARW-2). The obtained results
illustrate the feasibility of the computational framework for realistic MDAO
problems and highlight the benefits of the new approach for constructing an
active subspace in both terms of solution optimality and wall-clock time
reduction
