Non-linear analysis of the thermo-electro-mechanical behaviour of shear deformable FGM plates with piezoelectric actuators

This paper investigates the non-linear bending behaviour of functionally graded plates that are bonded with piezoelectric actuator layers and subjected to transverse loads and a temperature gradient based on Reddy's higher-order shear deformation plate theory. The von Karman-type geometric non-linearity, piezoelectric and thermal effects are included in mathematical formulations. The temperature change is due to a steady-state heat conduction through the plate thickness. The material properties are assumed to be graded in the thickness direction according to a power-law distribution in terms of the volume fractions of the constituents. The plate is clamped at two opposite edges, while the remaining edges can be free, simply supported or clamped. Differential quadrature approximation in the X-axis is employed to convert the partial differential governing equations and the associated boundary conditions into a set of ordinary differential equations. By choosing the appropriate functions as the displacement and stress functions on each nodal line and then applying the Galerkin procedure, a system of non-linear algebraic equations is obtained, from which the non-linear bending response of the plate is determined through a Picard iteration scheme. Numerical results for zirconia/aluminium rectangular plates are given in dimensionless graphical form. The effects of the applied actuator voltage, the volume fraction exponent, the temperature gradient, as well as the characteristics of the boundary conditions are also studied in detail. Copyright (C) 2004 John Wiley Sons, Ltd.

Reflections on the statistical analysis of personality and norms in war, peace, and prejudice: Are deviant minorities the problem?

The compelling quality of the Global Change simulation study (Altemeyer, 2003), in which high RWA (right-wing authoritarianism)/high SDO (social dominance orientation) individuals produced poor outcomes for the planet, rests on the inference that the link between high RWA/SDO scores and disaster in the simulation can be generalized to real environmental and social situations. However, we argue that studies of the Person × Situation interaction are biased to overestimate the role of the individual variability. When variables are operationalized, strongly normative items are excluded because they are skewed and kurtotic. This occurs both in the measurement of predictor constructs, such as RWA, and in the outcome constructs, such as prejudice and war. Analyses of normal linear statistics highlight personality variables such as RWA, which produce variance, and overlook the role of norms, which produce invariance. Where both normative and personality forces are operating, as in intergroup contexts, the linear analysis generates statistics for the sample that disproportionately reflect the behavior of the deviant, antinormative minority and direct attention away from the baseline, normative position. The implications of these findings for the link between high RWA and disaster are discussed.

Non-linear principal components analysis: an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia, Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore. three geographical areas with unique environmental characteristics could be identified. Copyright (c) 2005 John Wiley & Sons, Ltd.

Anisotropy-based robust performance analysis of finite horizon linear discrete time varying systems

We consider a problem of robust performance analysis of linear discrete time varying systems on a bounded time interval. The system is represented in the state-space form. It is driven by a random input disturbance with imprecisely known probability distribution; this distributional uncertainty is described in terms of entropy. The worst-case performance of the system is quantified by its a-anisotropic norm. Computing the anisotropic norm is reduced to solving a set of difference Riccati and Lyapunov equations and a special form equation.