33 resultados para hybrid dynamical system


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When used correctly, Statistical Energy Analysis (SEA) can provide good predictions of high frequency vibration levels in built-up structures. Unfortunately, the assumptions that underlie SEA break down as the frequency of excitation is reduced, and the method does not yield accurate predictions at "medium" frequencies (and neither does the Finite Element Method, which is limited to low frequencies). A basic problem is that parts of the system have a short wavelength of deformation and meet the requirements of SEA, while other parts of the system do not - this is often referred to as the "mid-frequency" problem, and there is a broad class of mid-frequency vibration problems that are of great concern to industry. In this paper, a coupled deterministic-statistical approach referred to as the Hybrid Method (Shorter & Langley, 2004) is briefly described, and some results that demonstrate how the method overcomes the aforementioned difficulties are presented.

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Against a background of increasing energy demand and rising fuel prices, hybrid-electric propulsion systems (HEPS) have the potential to significantly reduce fuel consumption in the aviation industry, particularly in the lighter sectors. By taking advantage of both Electric Motor (EM) and Internal Combustion Engine (ICE), HEPS provide not only a benefit in fuel saving but also a reduction in take-off noise and the emission levels. This research considers the design and sizing process of a hybrid-electric propulsion system for a single-seat demonstrator aircraft, the experimental derivation of the ICE map and the EM parameters. In addition to the experimental data, a novel modeling approach including several linked desktop PC software packages is presented to analyze and optimize hybrid-electric technology for aircraft. Further to the analysis of a parallel hybrid-electric, mid-scale aircraft, this paper also presents a scaling approach for a 20 kg UAV and a 50 tonne inter-city airliner. At the smaller scale, two different mission profiles are analyzed: an ISR mission profile, where the simulation routine optimizes the component size of the hybrid-electric propulsion system with respect to fuel saving, and a maximum duration profile; where the flight endurance is determined as a function of payload weight. At the larger scale, the performance of a 50 tonne inter-city airliner is modeled, based on a hybrid-electric gas-turbine, assuming a range of electric boost powers and battery masses.

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This paper is concerned with the development of efficient algorithms for propagating parametric uncertainty within the context of the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) approach to the analysis of complex vibro-acoustic systems. This approach models the system as a combination of SEA subsystems and FE components; it is assumed that the FE components have fully deterministic properties, while the SEA subsystems have a high degree of randomness. The method has been recently generalised by allowing the FE components to possess parametric uncertainty, leading to two ensembles of uncertainty: a non-parametric one (SEA subsystems) and a parametric one (FE components). The SEA subsystems ensemble is dealt with analytically, while the effect of the additional FE components ensemble can be dealt with by Monte Carlo Simulations. However, this approach can be computationally intensive when applied to complex engineering systems having many uncertain parameters. Two different strategies are proposed: (i) the combination of the hybrid FE/SEA method with the First Order Reliability Method which allows the probability of the non-parametric ensemble average of a response variable exceeding a barrier to be calculated and (ii) the combination of the hybrid FE/SEA method with Laplace's method which allows the evaluation of the probability of a response variable exceeding a limit value. The proposed approaches are illustrated using two built-up plate systems with uncertain properties and the results are validated against direct integration, Monte Carlo simulations of the FE and of the hybrid FE/SEA models. © 2013 Elsevier Ltd.