The fracture energy of metal fibre reinforced ceramic composites (MFCs)

A model is presented for prediction of the fracture energy of ceramic-matrix composites containing dispersed metallic fibres. It is assumed that the work of fracture comes entirely from pull-out and/or plastic deformation of fibres bridging the crack plane. Comparisons are presented between these predictions and experimental measurements made on a commercially-available composite material of this type, containing stainless steel (304) fibres in a matrix predominantly comprising alumina and alumino-silicate phases. Good agreement is observed, and it's noted that there is scope for the fracture energy levels to be high (~20kJm-2). Higher toughness levels are both predicted and observed for coarser fibres, up to a practical limit for the fibre diameter of the order of 0.5mm. Other deductions are also made concerning strategies for optimisation of the toughness of this type of material. © 2010 Elsevier Ltd.

Structural optimization of lattice materials

Lattice materials are characterized at the microscopic level by a regular pattern of voids confined by walls. Recent rapid prototyping techniques allow their manufacturing from a wide range of solid materials, ensuring high degrees of accuracy and limited costs. The microstructure of lattice material permits to obtain macroscopic properties and structural performance, such as very high stiffness to weight ratios, highly anisotropy, high specific energy dissipation capability and an extended elastic range, which cannot be attained by uniform materials. Among several applications, lattice materials are of special interest for the design of morphing structures, energy absorbing components and hard tissue scaffold for biomedical prostheses. Their macroscopic mechanical properties can be finely tuned by properly selecting the lattice topology and the material of the walls. Nevertheless, since the number of the design parameters involved is very high, and their correlation to the final macroscopic properties of the material is quite complex, reliable and robust multiscale mechanics analysis and design optimization tools are a necessary aid for their practical application. In this paper, the optimization of lattice materials parameters is illustrated with reference to the design of a bracket subjected to a point load. Given the geometric shape and the boundary conditions of the component, the parameters of four selected topologies have been optimized to concurrently maximize the component stiffness and minimize its mass. Copyright © 2011 by ASME.

Numerical study of the shielding properties of macroscopic hybrid ferromagnetic/superconductor hollow cylinders

We study the magnetic shielding properties of hybrid ferromagnetic/ superconductor (F/S) structures consisting of two coaxial cylinders, with one of each material. We use an axisymmetric finite-element model in which the electrical properties of the superconducting tube are modeled by a nonlinear E-J power law with a magnetic-field-dependent critical current density whereas the magnetic properties of the ferromagnetic material take saturation into account. We study and compare the penetration of a uniform axial magnetic field in two cases: 1) a ferromagnetic tube placed inside a larger superconducting tube (Ferro-In configuration) and 2) a ferromagnetic tube placed outside the superconducting one (Ferro-Out configuration). In both cases, we assess how the ferromagnetic tube improves the shielding properties of the sole superconducting tube. The influence of the geometrical parameters of the ferromagnetic tube is also studied: It is shown that, upon an optimal choice of the geometrical parameters, the range of magnetic fields that are efficiently shielded by the high-temperature superconductor tube alone can be increased by a factor of up to 7 (2) in a Ferro-Out (Ferro-In) configuration. The optimal configuration uses a 1020 carbon steel with a thickness of 2 mm and a height that is half that of the superconducting cylinder (80 mm). © 2009 IEEE.

Characterization of the surface acoustic wave devices based on ZnO/nanocrystalline diamond structures

Nanocrystalline ZnO films with strong (0002) texture and fine grains were deposited onto ultra-nanocrystalline diamond (UNCD) layers on silicon using high target utilization sputtering technology. The unique characteristic of this sputtering technique allows room temperature growth of smooth ZnO films with a low roughness and low stress at high growth rates. Surface acoustic wave (SAW) devices were fabricated on ZnO/UNCD structure and exhibited good transmission signals with a low insertion loss and a strong side-lobe suppression for the Rayleigh mode SAW. Based on the optimization of the layered structure of the SAW device, a good performance with a coupling coefficient of 5.2% has been realized, promising for improving the microfluidic efficiency in droplet transportation comparing with that of the ZnO/Si SAW device. An optimized temperature coefficient of frequency of -23.4 ppm°C-1 was obtained for the SAW devices with the 2.72 μm-thick ZnO and 1.1 μm-thick UNCD film. Significant thermal effect due to the acoustic heating has been redcued which is related to the temperature stability of the ZnO/UNCD SAW device. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of the steering control behaviour of five test subjects following a randomly curving path in a driving simulator

The paper is concerned with the identification of theoretical preview steering controllers using data obtained from five test subjects in a fixed-base driving simulator. An understanding of human steering control behaviour is relevant to the design of autonomous and semi-autonomous vehicle controls. The driving task involved steering a linear vehicle along a randomly curving path. The theoretical steering controllers identified from the data were based on optimal linear preview control. A direct-identification method was used, and the steering controllers were identified so that the predicted steering angle matched as closely as possible the measured steering angle of the test subjects. It was found that identification of the driver's time delay and noise is necessary to avoid bias in identification of the controller parameters. Most subjects' steering behaviour was predicted well by a theoretical controller based on the lateral/yaw dynamics of the vehicle. There was some evidence that an inexperienced driver's steering action was better represented by a controller based on a simpler model of the vehicle dynamics, perhaps reflecting incomplete learning by the driver. Copyright © 2014 Inderscience Enterprises Ltd.

Vulnerability assessment of buildings subject to tunnel-induced settlements: the influence of orientation and position of the building

The assessment of settlement induced damage on buildings during the preliminary phase of tunnel excavation projects, is nowadays receiving greater attention. Analyses at different levels of detail are performed on the surface building in proximity to the tunnel, to evaluate the risk of structural damage and the need of mitigation measures. In this paper, the possibility to define a correlation between the main parameters that influence the structural response to settlement and the potential damage is investigated through numerical analysis. The adopted 3D finite element model allows to take into account important features that are neglected in more simplified approaches, like the soil-structure interaction, the nonlinear behaviour of the building, the three dimensional effect of the tunnelling induced settlement trough and the influence of openings in the structure. Aim of this approach is the development of an improved classification system taking into account the intrinsic vulnerability of the structure, which could have a relevant effect on the final damage assessment. Parametric analyses are performed, focusing on the effect of the orientation and the position of the structure with respect to the tunnel. The obtained results in terms of damage are compared with the Building Risk Assessment (BRA) procedure. This method was developed by Geodata Engineering (GDE) on the basis of empirical observations and building monitoring and applied during the construction of different metro lines in urban environment. The comparison shows a substantial agreement between the two procedures on the influence of the analysed parameters. The finite element analyses suggest a refinement of the BRA procedure for pure sagging conditions.

Influence of cluster-assembly parameters on the field emission properties of nanostructured carbon films

Supersonic cluster beam deposition has been used to produce films with different nanostructures by controlling the deposition parameters such as the film thickness, substrate temperature and cluster mass distribution. The field emission properties of cluster-assembled carbon films have been characterized and correlated to the evolution of the film nanostructure. Threshold fields ranging between 4 and 10 V/mum and saturation current densities as high as 0.7 mA have been measured for samples heated during deposition. A series of voltage ramps, i.e., a conditioning process, was found to initiate more stable and reproducible emission. It was found that the presence of graphitic particles (onions, nanotube embryos) in the films substantially enhances the field emission performance. Films patterned on a micrometer scale have been conditioned spot by spot by a ball-tip anode, showing that a relatively high emission site density can be achieved from the cluster-assembled material. (C) 2002 American Institute of Physics.

Uniform stability of a particle approximation of the optimal filter derivative

Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.