Flutter is a complex oscillatory phenomenon that can destroy aircraft turbine blades and has historically been the cause of several plane accidents. In aerospace research, flutter generally refers to undesired and self-sustained vibrations in turbine blades that can readily grow out of control, destroying them along with the engine and even the aircraft’s wings.
Researchers have developed an approach that can be used for early detection of the onset of flutter, solving one of the main problems that has been holding back the design of lighter and more efficient turbines. The main idea behind the approach is that the turbine fan can be mathematically modeled as a complex network of interrelated oscillators and that flutter is ultimately the result of the progressive synchronization of more and more blades as a result of increased airflow going through the turbine.
Through experiments on a turbine test rig, the team found that before the onset of flutter, one particular blade begins to act as a “central hub” in the network and adjacent blades start to oscillate in sync with it. This “local” synchronization quickly expands and leads to the collective synchronization of all blades, resulting in potentially catastrophic flutter.
In this context, the network representation of the system demonstrated the applicability of two local and global measures as potential detectors of cascade flutter: the connecting strength between individual network nodes and the network’s synchronization parameter. The former is valid for specifying the dominant blades for the onset of cascade flutter. In contrast, the latter, which ranges from 0 to 1, is more suitable for determining a threshold for this onset.
The combined findings shed light on the complex phenomenon of flutter and contribute to the academic systemization of nonlinear problems in the field of aeronautical engineering and related nonlinear science. They could represent promising techniques for the early detection of flutter onset in the design state of blades.