A microstructural investigation of deformation in fine SiC particulate- and whisker-reinforced aluminium-matrix composites

Aluminium-based composites, reinforced with low volume fractions of whiskers and small particles, have been formed by a powder route. The materials have been tested in tension, and the microstructures examined using transmission electron microscopy. The whisker composites showed an improvement in flow stress over the particulate composites, and this was linked to an initially enhanced work-hardening rate in the whisker composites. The overall dislocation densities were estimated to be somewhat higher in the whisker composites than the particulate composites, but in the early stages of deformation the distribution was rather different, with deformation in the whisker material being far more localized and inhomogeneous. This factor, together with differences in the internal stress distribution in the materials, is used to explain the difference in mechanical properties.

Microstructure, strain fields and flow stress in deformed metal matrix composites

An experimental study of local orientations around whiskers in deformed metal matrix composites has been used to determine the strain gradients existing in the material following tensile deformation. These strain fields have been represented as arrays of geometrically necessary dislocations, and the material flow stress predicted using a standard dislocation hardening model. Whilst the correlation between this and the measured flow stress is reasonable, the experimentally determined strain gradients are lower by a factor of 5-10 than values obtained in previous estimates made using continuum plasticity finite element models. The local orientations around the whiskers contain a large amount of detailed information about the strain patterns in the material, and a novel approach is made to representing some of this information and to correlating it with microstructural observations. © 1998 Acta Metallurgica Inc. Published by Elsevier Science Ltd. All rights reserved.

Make or buy decision in the context of manufacturing strategy

This paper describes an approach to structuring the make or buy decision process, basing it firmly in the context of an overall manufacturing strategy. The work has been carried out jointly by the University of Cambridge Manufacturing Engineering Group and Lucas Industries. A review of the current state of ideas surrounding the linked issues of vertical integration and make or buy decisions is presented. Important features of the approach include identification of core manufacturing capabilities, assessment of the role of technology in manufacturing, the development of a cost model to support make or buy decisions and a review of the strategic implications of varying degrees of vertical integration.

Mechanical and magnetic properties of metal fibre networks, with and without a polymeric matrix

Bonded networks of metal fibres are highly porous, permeable materials, which often exhibit relatively high strength. Material of this type has been produced, using melt-extracted ferritic stainless steel fibres, and characterised in terms of fibre volume fraction, fibre segment (joint-to-joint) length and fibre orientation distribution. Young's moduli and yield stresses have been measured. The behaviour when subjected to a magnetic field has also been investigated. This causes macroscopic straining, as the individual fibres become magnetised and tend to align with the applied field. The modeling approach of Markaki and Clyne, recently developed for prediction of the mechanical and magneto-mechanical properties of such materials, is briefly summarised and comparisons are made with experimental data. The effects of filling the inter-fibre void with compliant (polymeric) matrices have also been explored. In general the modeling approach gives reliable predictions, particularly when the network architecture has been characterised using X-ray tomography. © 2005 Published by Elsevier Ltd.

Dispersion rheology of carbon nanotubes in a polymer matrix

We report on rheological properties of a dispersion of multiwalled carbon nanotubes in a viscous polymer matrix. Particular attention is paid to the process of nanotubes mixing and dispersion, which we monitor by the rheological signature of the composite. The response of the composite as a function of the dispersion mixing time and conditions indicates that a critical mixing time t* needs to be exceeded to achieve satisfactory dispersion of aggregates, this time being a function of nanotube concentration and the mixing shear stress. At shorter times of shear mixing t< t*, we find a number of nonequilibrium features characteristic of colloidal glass and jamming of clusters. A thoroughly dispersed nanocomposite, at t> t*, has several universal rheological features; at nanotube concentration above a characteristic value nc ∼2-3 wt. % the effective elastic gel network is formed, while the low-concentration composite remains a viscous liquid. We use this rheological approach to determine the effects of aging and reaggregation. © 2006 The American Physical Society.

Bayesian learning of noisy Markov decision processes

This work addresses the problem of estimating the optimal value function in a Markov Decision Process from observed state-action pairs. We adopt a Bayesian approach to inference, which allows both the model to be estimated and predictions about actions to be made in a unified framework, providing a principled approach to mimicry of a controller on the basis of observed data. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from theposterior distribution over the optimal value function. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.