Towards Maneuvering Aeroelasticity—Progress in the Simulation of Large Fluid-Structure Interaction Problems

Abstract

Advanced multidisciplinary software tools enable the development of sophisticated models of fixed and rotary wing vehicles. Such comprehensive vehicle models account for the interactions between the structural and aerodynamic fields, often coupled with hydraulic and electromechanical subsystem models and with control laws (aero-servo-elasticity). With these models it is now possible to predict with a growing level of confidence a variety of phenomena that are of crucial importance in the design phase, including loads, performance, stability, vibratory response, handling qualities and flight mechanics characteristics of the vehicle.

The quick pace of the evolution of comprehensive vehicle models must be accompanied by a similar growth in the range of problems that can be addressed by simulation. In particular, it is clear that quite often the limiting factors that constrain the design are found in the maneuvering regime at the boundaries of the flight envelope. For example, a design engineer might be interested in flying a minimum time turn with a virtual model of a helicopter while not exceeding a maximum allowable load factor, in order to assess the vibratory characteristics of the machine in this extreme turn. Current aeroelastic simulation tools are not directly equipped to solve this class of problems, since in fact they all compute the dynamic response of the model under the action of assigned control inputs. Unfortunately, control inputs that will fly a given maneuver are in general not available, and must be computed.

In this paper we describe a methodology for maneuvering aeroelasticity that is applicable to arbitrarily complex vehicle models. The approach is based on model-based virtual pilots that, on the basis of a formal maneuver description, first plan the path of the vehicle throughout the maneuver and then track it by driving the vehicle model along it, as proposed in Reference [1]. Both planning and tracking pilots are based on adaptive reduced models of the system and have the ability to learn, and hence improve their driving performance, as they steer the vehicle. We illustrate the use of this emerging technology with the help of relevant examples in the area of rotorcraft technology.