Generalized data reduction strategy for rocket engine applications
L. Michael Santi, John P. Butas · 36th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit · 2000
The process of calibrating component hardware characteristics based on system level test data is termed data reduction. Typical problems associated with conventional data reduction methods used in rocket engine diagnostics include numerical instability and the inability to access plausible hardware operating states. A new, robust data reduction strategy has been developed that addresses these problems. The new strategy, termed Generalized Data Reduction (GDR), was developed specifically for rocket engine applications. Although GDR employs a traditional linearization process to decouple data reduction from performance analysis, no artificial constraints are placed on the candidate hardware states. Stability is achieved through a systematic subset selection process that eliminates redundant parameters from the reduction process. The operating state solution is obtained by solving an equalityconstrained, weighted least squares problem. Detailed mathematical development and representative computational results based on initial GDR analyses of Fastrac engine mainstage operation are presented.