Aircraft shape did not change so much from the 50s, but the innovations applied in all its parts during these decades changed completely the efficiency, maintenance and passengers comfort.
The new generation of aircraft designed in the last few years has lighter structures and new more powerful and efficient engines which guarantee better comfort and the possibility to head new longer routes. Unfortunately, all these improvements have a price, the new structures are more sensitive to vibration. During the flight tests were noticed unexpected vibrations in some structural components that were not taken into account during the design. The vibrational environments, harmful for aircraft, are usually generated by aeroelastic phenomena, which happen when the structures are excited by an unsteady aerodynamic load in a wide frequency range. These vibrations can impend on the general safety of the aircraft, reducing the fatigue life of the component that fails before as expected. In civil aviation, safety is the biggest task, it is vital that risk associated with aviation activities is reduced and controlled to an acceptable level. The current project will help to better predict the fatigue life of components and lead to safer maintenance of the aircraft and improve the general aircraft safety.
Airbus 330-900 during its first flight
To reach the project goal a probabilistic model verification and validation is being developed in order to predict the vibrational and nonlinearity behaviour of specific aircraft components. In fact, hidden nonlinearities in structures, that, in theory, are linear, are another big issue that generates unexpected vibration. Verification and validation is a tool for developing engineer predictions with quantified uncertainty. For expanding the tool is necessary to start by the easiest elements (unit problems) and after goes up through the components, subsystems and finally the complete aircraft. If in words it would seem simple, it is not trivial for several reasons.
The main issue is the uncertainty quantification: the uncertainty derives by the natural randomness that is presented in each hierarchy levels (elements, components, sub-systems) and for defining it correctly, it is necessary an in-depth study that is time-consuming and expensive, two aspects that the industries want to avoid. Moreover, not only the engineering predictions contain errors and uncertainties but also experimental results, used as a reference. It is not possible to say if the experiment outcomes are more correct than the computational results or the contrary.
Another big issue is how it is possible to propagate the uncertainties through the hierarchy levels. The second part of the project deals with this, a Bayesian Network will be built to quantify the uncertainty information at multiple levels of the system hierarchy, where the aircraft is the complete system, and propagate it in order to quantify the overall system prediction.
In summary, the project aims to define a probabilistic model verification and validation process for aircraft components typically affected by aeroelastic and nonlinear problems and relate them to the main system. The model is able to incorporate data from different sources and quantify uncertainties. In the end, the Bayesian network is developed to propagate uncertainties to multiple levels of the system hierarchy.