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RESEARCH PROGRAM

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Keywords
UNCERTAINTY AND VARIABILITY; VIBRATION AND VIBROACOUSTICS; PROBABILISTIC APPROACH; INTERVAL ALGEBRA; FUZZY ARITHMETIC; ADAPTATIVE CONTROL; VEHICHE COMPONENTS

Dynamic modeling and control of complex mechanical structures with uncertain parameters

Università degli Studi di Roma "La Sapienza"
Abstract
The purpose of the research proposed is threefold:
- to study of dynamic effects of complex structural models with uncertain parameters;
- to create dynamic models of complex structures that consist of elements which are difficult or even impossible to characterize for lack of information on their construction details and/or on the materials used;
- to control the dynamic response of systems with uncertain parameters.
All these items can be considered in the general topic "Modeling of uncertain systems", that is becoming a major interest in Industry and, especially, in the transportation sector. In fact, increasingly the interest of industry is not to address the design or validation of a single unit but instead to estimate how a set of such units behaves when assembled to form a complex system. Since any component differs from the others because of unavoidable variations due to working tolerances, enviromental conditions, material non-uniformities, etc., it is necessary to evaluate the way such variations affect the whole system. Moreover, some components are too complex to model and, thus, neither more powerful computers nor more specific information on the components' features can lead to a confident description of them, at least with the standard techniques (typically FE). On the other hand, such components often have a relevant role in the general behavior of the whole system (vibration and vibroacoustic), so that they require a particular >>>

Principal Investigator
Aldo SESTIERI Università degli Studi di ROMA "La Sapienza"
Research Objectives
The present project is aimed to provide a significant contribution to describe and control the dynamic behavior of complex structures affected by stochastic uncertainties and variability in the system parameters. The subject is very important for the transportation industry where many components, with uncertain characteristics, play a crucial role in the vibrational and vibroacoustic comfort of passengers.
In recent years the industry has paid increasing attention and devoted important efforts to the dynamic characterization of the vehicle and its components. In the low frequency range (specifically in the range where the wavelengths involved are comparable with the characteristic dimensions of the system considered), the finite element method (FEM) is the most common procedure and is used with increasing confidence, although an updating procedure is often necessary to obtain results comparable with the experimental data. The high frequency range, important in the analysis of vibroacoustic problems, is more and more addressed by the Statistical Energy Analysis (SEA) and/or alternative techniques that produce, in general, a response averaged in space and frequency (octave or third-octave bandwidths). However, excluding SEA whose explicit goal is that of solving the problem in statistical terms with reference to a population of similar systems, none of the other methods, either for low or high frequencies, address directly the modeling of components in presence of >>>

Timescale
24 months
National and international background
The dynamic characterization of complex systems is a problem that has not a simple solution and represents an open challenge for the research community. Several items contribute to such difficulty.
- Some vehicle components are difficult to model and, yet, play a significant role in the vibroacoustis characterization of vehicles: for example the seats, the dash-board, the internal trimmings, etc. are themselves complex systems each of which consists of a large number of different elements and different materials. The complexity of such systems precludes the analyst from the possibility of using standard models for their description. Moreover, even when appropriate models are developed to represent joints and particular elements, they introduce quite often systematic modeling errors, that are amplified by their respective number when assembling the whole system. A possible strategy to circumvent such difficulty is the development of robust models. A robust model should simplify considerably the dynamics of the considered system by reducing the information of the output. More precisely, one sacrifices the information related to the local details while keeping a global, but still significant, information on the system response. An example of this is represented by those methods describing only the average energy (in frequency, space or in statistical sense) of the subsystems that make up the system under consideration. The word "robust" is appropriate in that the >>>