Novel parametric reduced order model for aeroengine blade dynamics

Parametric Reduced-Order Models

We address the problem of propagating input uncertainties through a computational fluid dynamics model. Methods such as Monte Carlo simulation can require many thousands (or more) of computational fluid dynamics solves, rendering them prohibitively expensive for practical applications. This expense can be overcome with reduced-order models that preserve the essential flow dynamics. The specific...

Aeroengine Multi-Rotors Dynamics Optimization

Abstract Based on detail analyzed optimization model of rotor dynamics of aeroengine multi-rotors system, the sum of weight of normal distribution membership function of fuzzy theory was used to describe the distribution of multi-order critical rotor speeds versus multi in common used operating speeds, and then to formulate the optimal objective function. According to the design specification a...

Reduced-order computational model for low-frequency dynamics of automobiles

A reduced-order model is constructed to predict, for the lowfrequency range, the dynamical responses in the stiff parts of an automobile constituted of stiff and flexible parts. The vehicle has then many elastic modes in this range due to the presence of many flexible parts and equipments. A non-usual reduced-order model is introduced. The family of the elastic modes is not used and is replaced...

Parametric dependencies of aeroengine flutter for flutter clearance applications

This thesis describes the effects of operational parameters upon aeroengine flutter stability. The study is composed of three parts: theoretical development of relevant parameters, exploration of a computational model, and analysis of fully scaled test data. Results from these studies are used to develop a rational flutter clearance methodology-a test procedure to ensure flutter-free operation....

Improved Reduced Order Modeling Strategies for Coupled and Parametric Systems