Development of an Efficient Flutter and Limit Cycle Oscillation Predictive Tool

ABSTRACT: Several current fighter aircraft with external store configurations persistently encounter Limit Cycle Oscillation (LCO) problems. A fast and accurate aeroelastic prediction is required to identify the critical LCO configurations given the massive number of aircraft with store combinations short-time frame demanded by rapid military responses when facing todays ever-changing international situation. To meet this requirement, a LCO predictive tool based on the ZONA Euler Unsteady Solver (ZEUS) will be developed in Phase I. It will include a Message Passing Interface (MPI) implementation to drastically reduce the computational time of ZEUS. Since many studies have shown that the nonlinear aerodynamics alone is not sufficient to yield LCO, rather LCO is due to both nonlinear aerodynamics and Nonlinear Structural Damping (NSD), a generalized van der Pol NSD model will be incorporated into ZEUS to provide a LCO bounding mechanism in the post flutter flight conditions. The LCO predictive capability of ZEUS with MPI will be demonstrated through benchmark comparisons with flight test data. Prior to the end of Phase I, a prototypical ZEUS with MPI version will be installed in the users computational environment to ensure the compatibility between the ZEUS MPI and the users computational architecture. BENEFIT: LCO is a self-excited, sustained vibration of limited amplitude which can impact a pilots control authority over an aircraft, ride quality, and weapon aiming capability. It can also induce structural fatigue and, under certain circumstances, flutter. The LCO clearance of a modern fighter aircraft should be addressed for all possible store/weapon configurations. Given the drastic number of such configurations, this effort is a major engineering task in aircraft/store weapon compatibility certification. The outcome of Phase I will be a LCO predictive tool that can meet the requirement of computational efficiency to generate time-history response solutions for numerous flight conditions per day on conventional multi-processor computer platforms so that potentially dangerous configurations can be identified with confidence reducing the need for flight testing.