Reversible jump sampler for autoregressive time series

We use reversible jump Markov chain Monte Carlo (MCMC) methods to address the problem of model order uncertainty in autoregressive (AR) time series within a Bayesian framework. Efficient model jumping is achieved by proposing model space moves from the full conditional density for the AR parameters, which is obtained analytically. This is compared with an alternative method, for which the moves are cheaper to compute, in which proposals are made only for new parameters in each move. Results are presented for both synthetic and audio time series.

Bayesian inference for multidimensional NMR image reconstruction

Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

DEVELOPMENT OF THE WAVE CONTOURING RAFT.

The wave contouring raft system is the outcome of ideas initiated and developed by Sir Christopher Cockerell from 1972 onwards. His objective was to develop a wave energy device which is within the bounds of current technology. It should consist of simple, relatively small units, amenable to quantity production, which would enable a power generating system to be built up and commissioned in stages according to needs and production capability. This thinking led to the investigation of chains of pontoons, hinged together so that the passage of a wave down the chain causes the pontoons to oscillate relative to one another. Energy is extracted from the sea by applying a torque about the hinges to damp the motion. The work has involved extensive model testing in wave tanks and the building and testing of a 3-unit 1/10 scale power generating installation in the Solent, as well as design studies for a full size installation for Atlantic conditions.

Friction and material transfer in micro-scale sliding contact between aluminium alloy and steel

A ball-on-flat reciprocating micro-tribometer has been used to measure the friction coefficient between aluminium alloy strip and a steel ball. A relatively small ball and correspondingly low contact load is used to give a contact width of the order of 100μm, closer to asperity contact widths than generally found for this type of test. The effects of load, initial strip surface roughness, lubricants and boundary additives are investigated. It is found that the friction coefficient is significantly reduced by the addition of a lubricant. Observations of the wear tracks and ball surface show that the material transfer from aluminium to the ball is reduced in the presence of the lubricant. The initial friction coefficient is further reduced by the addition of a boundary additive, but the friction coefficient after 8 cycles is unchanged. Copyright © 2004 by Springer Science+Business Media, Inc.

Slip flow and heat transfer in microbearings with fractal surface topographies

The effects of random surface roughness on slip flow and heat transfer in microbearings are investigated. A three-dimensional random surface roughness model characterized by fractal geometry is used to describe the multiscale self-affine roughness, which is represented by the modified two-variable Weierstrass- Mandelbrot (W-M) functions, at micro-scale. Based on this fractal characterization, the roles of rarefaction and roughness on the thermal and flow properties in microbearings are predicted and evaluated using numerical analyses and simulations. The results show that the boundary conditions of velocity slip and temperature jump depend not only on the Knudsen number but also on the surface roughness. It is found that the effects of the gas rarefaction and surface roughness on flow behavior and heat transfer in the microbearing are strongly coupled. The negative influence of roughness on heat transfer found to be the Nusselt number reduction. In addition, the effects of temperature difference and relative roughness on the heat transfer in the bearing are also analyzed and discussed. © 2012 Elsevier Ltd. All rights reserved.

Turbine blade tip heat transfer in low speed and high speed flows

In this paper, high and low speed tip flows are investigated for a high-pressure turbine blade. Previous experimental data are used to validate a CFD code, which is then used to study the tip heat transfer in high and low speed cascades. The results show that at engine representative Mach numbers the tip flow is predominantly transonic. Thus, compared to the low speed tip flow, the heat transfer is affected by reductions in both the heat transfer coefficient and the recovery temperature. The high Mach numbers in the tip region (M>1.5) lead to large local variations in recovery temperature. Significant changes in the heat transfer coefficient are also observed. These are due to changes in the structure of the tip flow at high speed. At high speeds, the pressure side corner separation bubble reattachment occurs through supersonic acceleration which halves the length of the bubble when the tip gap exit Mach number is increased from 0.1 to 1.0. In addition, shock/boundary-layer interactions within the tip gap lead to large changes in the tip boundary-layer thickness. These effects give rise to significant differences in the heat-transfer coefficient within the tip region compared to the low-speed tip flow. Compared to the low speed tip flow, the high speed tip flow is much less dominated by turbulent dissipation and is thus less sensitive to the choice of turbulence model. These results clearly demonstrate that blade tip heat transfer is a strong function of Mach number, an important implication when considering the use of low speed experimental testing and associated CFD validation in engine blade tip design. Copyright © 2009 by ASME.

A reversible infinite HMM using normalised random measures

Copyright 2014 by the author(s). We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected we define a prior over random walks on graphs that results in a reversible Markov chain. The resulting prior over infinite transition matrices is closely related to the hierarchical Dirichlet process but enforces reversibility. A reinforcement scheme has recently been proposed with similar properties, but the de Finetti measure is not well characterised. We take the alternative approach of explicitly constructing the mixing measure, which allows more straightforward and efficient inference at the cost of no longer having a closed form predictive distribution. We use our process to construct a reversible infinite HMM which we apply to two real datasets, one from epigenomics and one ion channel recording.