Particle Image Velocimetry analysis in dynamic centrifuge tests

The Particle Image Velocimetry (PIV) technique is an image processing tool to obtain instantaneous velocity measurements during an experiment. The basic principle of PIV analysis is to divide the image into small patches and calculate the locations of the individual patches in consecutive images with the help of cross correlation functions. This paper focuses on the application of the PIV analysis in dynamic centrifuge tests on small scale tunnels in loose, dry sand. Digital images were captured during the application of the earthquake loading on tunnel models using a fast digital camera capable of taking digital images at 1000 frames per second at 1 Megapixel resolution. This paper discusses the effectiveness of the existing methods used to conduct PIV analyses on dynamic centrifuge tests. Results indicate that PIV analysis in dynamic testing requires special measures in order to obtain reasonable deformation data. Nevertheless, it was possible to obtain interesting mechanisms regarding the behaviour of the tunnels from PIV analyses. © 2010 Taylor & Francis Group, London.

Global nonlinear dynamics of thin aerofoil wakes

In the present investigation of thin aerofoil wakes we compare the global nonlinear dynamics, obtained by direct numerical simulations, to the associated local instability features, derived from linear stability analyses. A given configuration depends on two control parameters: the Reynolds number Re and the adverse pressure gradient m (with m < 0) prevailing at the aerofoil trailing edge. Global instability is found to occur for large enough Re and |m|; the naturally selected frequency is determined by the local absolute frequency prevailing at the trailing edge. © 2010 Springer Science+Business Media B.V.

Sparsity-Inducing Optimization Algorithm for the Extraction of Planar Structures in Noisy Point-Cloud Data

Most of the manual labor needed to create the geometric building information model (BIM) of an existing facility is spent converting raw point cloud data (PCD) to a BIM description. Automating this process would drastically reduce the modeling cost. Surface extraction from PCD is a fundamental step in this process. Compact modeling of redundant points in PCD as a set of planes leads to smaller file size and fast interactive visualization on cheap hardware. Traditional approaches for smooth surface reconstruction do not explicitly model the sparse scene structure or significantly exploit the redundancy. This paper proposes a method based on sparsity-inducing optimization to address the planar surface extraction problem. Through sparse optimization, points in PCD are segmented according to their embedded linear subspaces. Within each segmented part, plane models can be estimated. Experimental results on a typical noisy PCD demonstrate the effectiveness of the algorithm.

Transcription of multi-genre media archives using out-of-domain data

We describe our work on developing a speech recognition system for multi-genre media archives. The high diversity of the data makes this a challenging recognition task, which may benefit from systems trained on a combination of in-domain and out-of-domain data. Working with tandem HMMs, we present Multi-level Adaptive Networks (MLAN), a novel technique for incorporating information from out-of-domain posterior features using deep neural networks. We show that it provides a substantial reduction in WER over other systems, with relative WER reductions of 15% over a PLP baseline, 9% over in-domain tandem features and 8% over the best out-of-domain tandem features. © 2012 IEEE.

A hybrid surface tension seal for pneumatic and hydraulic microactuators

Recent research revealed that microactuators driven by pressurized fluids are able to generate high power and force densities at microscale. One of the main technological barriers in the development of these actuators is the fabrication low friction seals. This paper presents a novel scalable seal technology, which resists the actuation pressure relying on a combination of a clearance seal and a surface tension seal. This approach allows to seal pressures of more than 800 kPa without leakage. The seal is tested on an actuator with a bore of 0.8 mm2 and a length of 13 mm, which was able to generate forces up to 0.32 N. © 2008 Springer-Verlag.

Confidence in beliefs about pain predicts expectancy effects on pain perception and anticipatory processing in right anterior insula.

Psychological factors play a major role in exacerbating chronic pain. Effective self-management of pain is often hindered by inaccurate beliefs about the nature of pain which lead to a high degree of emotional reactivity. Probabilistic models of perception state that greater confidence (certainty) in beliefs increases their influence on perception and behavior. In this study, we treat confidence as a metacognitive process dissociable from the content of belief. We hypothesized that confidence is associated with anticipatory activation of areas of the pain matrix involved with top-down modulation of pain. Healthy volunteers rated their beliefs about the emotional distress that experimental pain would cause, and separately rated their level of confidence in this belief. Confidence predicted the influence of anticipation cues on experienced pain. We measured brain activity during anticipation of pain using high-density EEG and used electromagnetic tomography to determine neural substrates of this effect. Confidence correlated with activity in right anterior insula, posterior midcingulate and inferior parietal cortices during the anticipation of pain. Activity in the right anterior insula predicted a greater influence of anticipation cues on pain perception, whereas activity in right inferior parietal cortex predicted a decreased influence of anticipatory cues. The results support probabilistic models of pain perception and suggest that confidence in beliefs is an important determinant of expectancy effects on pain perception.

A framework for collecting inclusive design data for the UK population.

Successful inclusive product design requires knowledge about the capabilities, needs and aspirations of potential users and should cater for the different scenarios in which people will use products, systems and services. This should include: the individual at home; in the workplace; for businesses, and for products in these contexts. It needs to reflect the development of theory, tools and techniques as research moves on. And it must also to draw in wider psychological, social, and economic considerations in order to gain a more accurate understanding of users' interactions with products and technology. However, recent research suggests that although a number of national disability surveys have been carried out, no such knowledge currently exists as information to support the design of products, systems and services for heterogeneous users. This paper outlines the strategy behind specific inclusive design research that is aimed at creating the foundations for measuring inclusion in product designs. A key outcome of this future research will be specifying and operationalising capability, and psychological, social and economic context measures for inclusive design. This paper proposes a framework for capturing such information, describes an early pilot study, and makes recommendations for better practice.

Multi-frequency operation of a mems vibration energy harvester by accessing five orders of parametric resonance

The mechanical amplification effect of parametric resonance has the potential to outperform direct resonance by over an order of magnitude in terms of power output. However, the excitation must first overcome the damping-dependent initiation threshold amplitude prior to accessing this more profitable region. In addition to activating the principal (1st order) parametric resonance at twice the natural frequency ω0, higher orders of parametric resonance may be accessed when the excitation frequency is in the vicinity of 2ω0/n for integer n. Together with the passive design approaches previously developed to reduce the initiation threshold to access the principal parametric resonance, vacuum packaging (< 10 torr) is employed to further reduce the threshold and unveil the higher orders. A vacuum packaged MEMS electrostatic harvester (0.278 mm3) exhibited 4 and 5 parametric resonance peaks at room pressure and vacuum respectively when scanned up to 10 g. At 5.1 ms-2, a peak power output of 20.8 nW and 166 nW is recorded for direct and principal parametric resonance respectively at atmospheric pressure; while a peak power output of 60.9 nW and 324 nW is observed for the respective resonant peaks in vacuum. Additionally, unlike direct resonance, the operational frequency bandwidth of parametric resonance broadens with lower damping. © Published under licence by IOP Publishing Ltd.