Aerospace Research Projects

Nonlinear Dynamics Control Via Forescasting:

Increasing the structural flexibility of wings allows more aerodynamic and weight-efficient airframes. However, this might lead to aeroelastic instabilities, which aggravate the aircraft's performance, and, in the worst-case scenario, can cause the failure of the structure.

Among these phenomena, flutter arises from the coupling between a fluid and a structure. This instability creates self-excited vibrations also referred to as called limit cycle oscillations (LCO) that increase the fatigue of the structure and limit the flight envelope. To date, several passive methods have been suggested to overcome and control these oscillations. Several include nonlinear energy sinks (NES), defined by a pure nonlinear spring in a tuned mass damper. Recent studies have shown that the energy of the main system can be irreversibly transferred to the NES and dissipated through damping. This nonlinear elastic approach for the flap control surface was recently introduced to create a flap-NES that reduces the LCO amplitude and delays flutter speed. 

The goal of this research is to design an online adaptive control surface NES to control the post-flutter LCOs as they change with flying varying conditions. However, choosing parameters to achieve optimal flutter mitigation requires a knowledge of the bifurcation diagram. Recently, a novel data-driven technique, called the bifurcation forecasting method, has been introduced to construct the bifurcation diagram of nonlinear systems using a limited number of system measurements in the pre-bifurcation regime.

This method is used and developed in this study as an alternative to the traditional approaches to speed up the optimization process. This approach significantly speeds up the optimization process and is based on the critical slowing down (CSD) phenomenon observed in nonlinear aeroelastic systems as they approach a Hopf (flutter) instability.
 

Data-Driven Reduced-Order Modeling:

Reduced-order models to predict mistuned blisk dynamics have traditionally been physics-based, often using a combination of one or more projections based on unique cyclic-symmetric systems. However, data-driven methods have seen increased interest with the advent of improved computational resources and their ability to leverage both computational and experimental data. In our group, we have created and currently are developing novel data-driven methods that combine analytical modeling methods with machine-learning paradigms for predicting mistuning blisk dynamics like that seen during operation. 

The physics-based methods our group has previously developed for linear and nonlinear systems, as well as the data-driven reduced-order models we have developed pave the way not only for predicting mistuned blisk dynamics, but more generally to model structural systems as a whole. 

Model Parameter Identification:

Manufactured blisks include unavoidable small variations from their nominal properties, thus forming a mistuned system. This type of phenomenon can cause significant difficult to predict vibration response amplifications that can result in high-cycle fatigue failure of the blisk. Additionally, many reduced-order models treat mistuning as a variation in natural frequencies for one or more modes of an isolated blade. For bladed disks with inserted blades, one can measure the natural frequencies of manufactured blades directly. However, this is not possible with integrally bladed disks (blisks), which are becoming more prevalent in newer and next-generation engines. 

Thus, our group has developed methods to identify mistuning in blisks. Specifically, we have developed methods that combines both experimental and computational techniques to identify mistuning in as-manufactured blisks. This includes data-driven methods based on machine learning and developed data curation techniques and methods based on coupling coefficients, among others. 

Novel Dampening Concepts:

Due to their low inherent damping, blisks can experience high amplitude vibrations subject to operational loading. This has motivated the development of nonlinear damping mechanisms for blisks specifically. Our group has pioneered the development of dampers based on resonant vibration absorbers (RVAs) used to mitigate vibrations of structures through energy transfer and absorption. Our group develops techniques to enhance response reduction by designing RVA-based dampers that can further dissipate energy through both friction and impact contacts. We have extended the application of RVA concepts to a turbomachinery blisks. Concretely, using the concept of an RVA with only friction contacts, our group has developed friction-enhanced tuned ring dampers that are placed in the disk region of a blisk and significantly reduces the blisk vibration amplitudes through energy absorption and dissipation. Our work seeks to predict, identify, and experimentally verify the nonlinear dynamics of representative sub-systems and full-blisk models with RVA-based damping mechanisms.