Transonic aeroelastic simulation for instability searches and uncertainty analysis

In this paper the use of eigenvalue stability analysis of very large dimension aeroelastic numerical models arising from the exploitation of computational fluid dynamics is reviewed. A formulation based on a block reduction of the system Jacobian proves powerful to allow various numerical algorithms to be exploited, including frequency domain solvers, reconstruction of a term describing the fluid–structure interaction from the sparse data which incurs the main computational cost, and sampling to place the expensive samples where they are most needed. The stability formulation also allows non-deterministic analysis to be carried out very efficiently through the use of an approximate Newton solver. Finally, the system eigenvectors are exploited to produce nonlinear and parameterised reduced order models for computing limit cycle responses. The performance of the methods is illustrated with results from a number of academic and large dimension aircraft test cases.

Reducing Uncertainty in Aeroelastic Flutter Boundaries Using Experimental Data

Flutter prediction as currently practiced is usually deterministic, with a single structural model used to represent an aircraft. By using interval analysis to take into account structural variability, recent work has demonstrated that small changes in the structure can lead to very large changes in the altitude at which
utter occurs (Marques, Badcock, et al., J. Aircraft, 2010). In this follow-up work we examine the same phenomenon using probabilistic collocation (PC), an uncertainty quantification technique which can eficiently propagate multivariate stochastic input through a simulation code,
in this case an eigenvalue-based fluid-structure stability code. The resulting analysis predicts the consequences of an uncertain structure on incidence of
utter in probabilistic terms { information that could be useful in planning
flight-tests and assessing the risk of structural failure. The uncertainty in
utter altitude is confirmed to be substantial. Assuming that the structural uncertainty represents a epistemic uncertainty regarding the
structure, it may be reduced with the availability of additional information { for example aeroelastic response data from a flight-test. Such data is used to update the structural uncertainty using Bayes' theorem. The consequent
utter uncertainty is significantly reduced across the entire Mach number range.