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Vibration problems, which occur more frequently in high power to weight machines, often lead to costly down time, subsequent redesign, and, in some instances, catastrophic failure. A disproportionate number of vibration problems in rotating machinery can be attributed to highly pre-swirled fluid entering tight clearance locations such as seals and fluid bearings. The relationship between high fluid pre-swirl and undesirable vibration issues is clear. Machines with high levels of fluid pre-swirl are more susceptible to instabilities and vibration problems. A top priority in rotor dynamic design, therefore, is to develop devices to minimize the level of fluid pre-swirl entering tight clearance locations. The RVR was designed to condition the flow prior to entering the seal (or axial flow fluid-film bearing) so that the flow through the annular clearance is at a minimum purely axial. While conventional swirl brakes have only been shown to reduce pre-swirl by up to 30%, the RVR can actually reverse the direction of the swirl, so that circumferential fluid velocity flows in a direction counter to shaft rotation. Thus, a classic detriment to rotating machinery has now become an asset to ameliorate vibration issues through the RVR. The RVR is axially efficient, typically increasing the axial length of a smooth annular seal on the order of 10-12%. The RVR has been extensively tested and is now in use at NASA.

Proprotors on tiltrotor aircraft have complex aeroelastic properties, experiencing torsion, bending, and chord movement vibrational modes, in addition to whirl flutter dynamic instabilities. These dynamics can be stabilized by high-frequency swashplate adjustments to alter the incidence angle between the swashplate and the rotor shaft (cyclic control) and blade pitch (collective control). To make these high-speed adjustments while minimizing control inputs, generalized predictive control (GPC) algorithms predict future outputs based on previous system behavior. However, these algorithms are limited by the fact that tiltrotor systems can substantially change in orientation and airspeed during a normal flight regime, breaking system continuity for predictive modeling. NASA’s Advanced GPC (AGPC) is a self-adaptive algorithm that overcomes these limitations by identifying system changes and adapting its predictive behavior as flight conditions change. If system vibration conditions deteriorate below a set threshold for a set time interval, the AGPC will incrementally update its model parameters to improve damping response. AGPC has shown significant performance enhancements over conventional GPC algorithms in comparative simulations based on an analytical model of NASA’s TiltRotor Aeroelastic Stability Testbed (TRAST). Research for Hardware-In-the-Loop testing and flight vehicle deployment is ongoing, and hover data show improved vibration reduction and stability performance using AGPC over other methods. The example presented here is an application to tiltrotor aircraft for envelope expansion and vibration reduction. However, AGPC can be employed on many dynamic systems.