Parametric probabilistic analysis in the uncertain dynamics of magneto-electroelastic beams resting on elastic foundations
Abstract:
In this paper, the authors are concerned with uncertianty quantification of the dynamic behavior of magneto-electro-elastic (MEE) beams (both straight and curved) mounted on elastic foundations. The MEE beams are a type of composite structures that can be employed as imbedded subsystem in high performance aero spatial structures, control of motion and attenuation of vibrations, energy harvesting, etc. Although most of the research work related to the mechanics of MEE structures was done for dynamics and statics, it is remarkable the scarcity of papers analyzing the uncertainty propagation in the dynamics of a MEE structure, considering that many models have uncertainties related to their parameters (loads and/or material properties) and/or the hypotheses invoked to develop the model, among others. In order to perform studies about the uncertainty quantification of MEE beams, a beam model for curved beams is derived and employed as a mean basis or deterministic approach to the studies on stochastic modeling. Then, a probabilistic model is constructed, on the basis of the finite element formulation of the deterministic approach, by adopting random variables for the uncertain parameters selected. The probability density functions of the random variables are derived appealing to the Maximum Entropy Principle. Once the probabilistic model is constructed, the Monte Carlo method is used to perform simulations with independent random variables as uncertain parameters. Studies with several types of constitutive proportions are carried out in order to characterize the Magneto-elastic and/or piezoelectric coupling and response of the aforementioned MEE beams.
Año de publicación:
2015
Keywords:
- Elastic foundations
- MEE beams
- Uncertain dynamics
Fuente:
Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Ingeniería mecánica
- Matemáticas aplicadas
- Ingeniería mecánica
Áreas temáticas:
- Ingeniería y operaciones afines