Loading...
4 results
Search Results
Now showing 1 - 4 of 4
- On the characterization of parametric uncertainty on FGM platesPublication . Damásio, Fábio R.; Silva, Tiago A. N.; Carvalho, Alda; Loja, AméliaComposite materials with their intrinsic tailor-made capabilities can be strong candidates to improve the mechanical performance of structures, either by partially or totally replacing other traditional materials. These easily tailored features can be thought not only in terms of the more often used fibre reinforced laminated composites but also in the context of particulate composites. In general, the mechanical performance of composite structures can be, intentionally or not, influenced through the manipulation of geometric properties, the selection of material’s phases and its disposition in the composite, as well as, the spatial distribution of reinforcement agents, such as fibres or particles. The uncertainty associated to all these diferente aspects can be considered as the main source of variability to the mechanical behaviour of a given structure. It is therefore important to characterize the relations between the geometric and material parameters and a set of some relevant structural responses. The quantification of uncertainty is often related to the experimental behaviour of a given structure, although it can also be assessed within the design perspective, where it is useful to understand and identify the parameters with a greater influence on the uncertainty associated to the model simulations. In the present work, one considers functionally graded plates, where different material and geometric characteristics are assumed to be uncertain. The mechanical behaviour of such plates is modelled using Lagrange- and Kriging-based finite element models, developed according to the assumptions of the first order shear deformation theory. A set of numerical results is presented and discussed in order to identify the most significant modelling parameters for the description of the output variability, in this case the maximum deflection.
- Assessing the influence of material and geometrical uncertainty on the mechanical behavior of functionally graded material platesPublication . Carvalho, Alda; Silva, Tiago; Loja, Amélia; Damásio, Fábio RaimundoComposite materials possessing a functional gradient are becoming strong candidates to enhance the performance of structures when severe operating conditions are a reality. These types of conditions may, for example, range from situations where a high thermal gradient is present to others where it is imperative to minimize abrupt stresses transitions between material interfaces. The manufacturing achievement of the gradients determined for a specific application may in practice face some limitations, which can be due, among other factors, to technological process constraints, eventual operating condition deterioration of production stages, or to nonconforming raw materials. Regardless of the origin of such limitations, the reality is that the uncertainty is always present to some extent; this is clearly reflected in the scattering of material and geometrical properties of these composites. The understanding that deterministic analyses are not enough to provide a complete prediction of the composite structures’ behavior emphasizes the crucial need to identify the effects that the variability in material and geometrical parameters will produce in the structural response.With the presentwork, one intends to study the influence of this variability in the static and free vibrations behavior of functionally graded plates. It is also an objective of this study to use regression models to predict these responses and to characterize the contribution of each model parameter to the explanation of the response variability. To this purpose, a set of numerical results is presented and discussed.
- A global optimization approach based on adaptive populationsPublication . Silva, Tiago A. N.; Loja, Amélia; Carvalho, Alda; Maia, Nuno M. M.; Barbosa, JoaquimThe solution of inverse problems based on experimental data is itself an important research issue. In this context and assuming that an experimental sample is available, rather than trying to find a specific deterministic solution for the inverse problem, one aims to determine the probabilistic distribution of the modelling parameters, based on the minimization of the dissimilarity between the empirical cumulative distribution function of an experimental solution and its simulation counterpart. The present paper presents na innovative framework, where Differential Evolution is extended in order to estimate not only an optimal set of modelling parameters, but to estimate their optimal probabilistic distributions. Additionally, the Adaptive Empirical Distributions optimization scheme is here introduced. Both schemes rely on the two samples Kolmogorov-Smirnov goodness-offit test in order to evaluate the resemblance between two empirical cumulative distribution functions. A numerical example is considered in order to assess the performance of the proposed strategies and validity of their solutions.
- Adaptive empirical distributions in the framework of inverse problemsPublication . Silva, Tiago; Loja, Amélia; Carvalho, Alda; Maia, Nuno. M.; Barbosa, JoaquimThis article presents an innovative framework regarding an inverse problem. One presents the extension of a global optimization algorithm to estimate not only an optimal set of modeling parameters, but also their optimal distributions. Regarding its characteristics, differential evolution algorithm is used to demonstrate this extension, although other population-based algorithms may be considered. The adaptive empirical distributions algorithm is here introduced for the same purpose. Both schemes rely on the minimization of the dissimilarity between the empirical cumulative distribution functions of two data sets, using a goodness-of-fit test to evaluate their resemblance.