Vortex Transport and Blade Interactions in High Pressure Turbines

This paper presents a study of the three-dimensional flow field within the blade rows of a high-pressure axial flow steam turbine stage. Half-delta wings were fixed to a rotating hub to simulate an upstream rotor passage vortex. The flow field is investigated in a Low-Speed Research Turbine using pneumatic and hot-wire probes downstream of the blade row. The paper examines the impact of the delta wing vortex transport on the performance of the downstream blade row. Steady and unsteady numerical simulations were performed using structured 3D Navier-Stokes solver to further understand the flow field. The loss measurements at the exit of the stator blade showed an increase in stagnation pressure loss due to the delta wing vortex transport. The increase in loss was 21% of the datum stator loss, demonstrating the importance of this vortex interaction. The transport of the stator viscous flow through the rotor blade row is also described. The rotor exit flow was affected by the interaction between the enhanced stator passage vortex and the rotor blade row. Flow underturning near the hub and overturning towards the mid-span was observed, contrary to the classical model of overturning near the hub and underturning towards the mid-span. The unsteady numerical simulation results were further analysed to identify the entropy producing regions in the unsteady flow field.

Self-organization of spinal reflexes involving homonymous, antagonist and synergistic interactions

Recent results in spinal research are challenging the historical view that the spinal reflexes are mostly hardwired and fixed behaviours. In previous work we have shown that three of the simplest spinal reflexes could be self-organised in an agonist-antagonist pair of muscles. The simplicity of these reflexes is given from the fact that they entail at most one interneuron mediating the connectivity between afferent inputs and efferent outputs. These reflexes are: the Myotatic, the Reciprocal Inibition and the Reverse Myotatic reflexes. In this paper we apply our framework to a simulated 2D leg model actuated by six muscles (mono- and bi-articular). Our results show that the framework is successful in learning most of the spinal reflex circuitry as well as the corresponding behaviour in the more complicated muscle arrangement. © 2012 Springer-Verlag.

Collective Cell Migration: Leadership, Invasion and Segregation

A number of biological processes, such as embryo development, cancer metastasis or wound healing, rely on cells moving in concert. The mechanisms leading to the emergence of coordinated motion remain however largely unexplored. Although biomolecular signalling is known to be involved in most occurrences of collective migration, the role of physical and mechanical interactions has only been recently investigated. In this paper, a versatile framework for cell motility is implemented in-silico in order to study the minimal requirements for the coordination of a group of epithelial cells. We find that cell motility and cell-cell mechanical interactions are sufficient to generate a broad array of behaviours commonly observed in vitro and in vivo. Cell streaming, sheet migration and susceptibility to leader cells are examples of behaviours spontaneously emerging from these simple assumptions, which might explain why collective effects are so ubiquitous in nature. This analysis provides also new insights into cancer metastasis and cell sorting, suggesting in particular that collective invasion might result from an emerging coordination in a system where single cells are mechanically unable to invade.

Single-gated multiple-mode power semiconductor devices

A new method has been used to design a power semiconductor device which combines IGBT switching and thyristor on-state characteristics. A single gate signal controls the switching and triggers the transitions between the IGBT and thyristor modes of operation. This paper discusses single-gated devices with multiple modes and aspects of their switching behaviour.

MCMC-based tracking and identification of leaders in groups

We present a novel framework for identifying and tracking dominant agents in groups. Our proposed approach relies on a causality detection scheme that is capable of ranking agents with respect to their contribution in shaping the system's collective behaviour based exclusively on the agents' observed trajectories. Further, the reasoning paradigm is made robust to multiple emissions and clutter by employing a class of recently introduced Markov chain Monte Carlo-based group tracking methods. Examples are provided that demonstrate the strong potential of the proposed scheme in identifying actual leaders in swarms of interacting agents and moving crowds. © 2011 IEEE.

Statistical parametric speech synthesis based on speaker and language factorization

An increasingly common scenario in building speech synthesis and recognition systems is training on inhomogeneous data. This paper proposes a new framework for estimating hidden Markov models on data containing both multiple speakers and multiple languages. The proposed framework, speaker and language factorization, attempts to factorize speaker-/language-specific characteristics in the data and then model them using separate transforms. Language-specific factors in the data are represented by transforms based on cluster mean interpolation with cluster-dependent decision trees. Acoustic variations caused by speaker characteristics are handled by transforms based on constrained maximum-likelihood linear regression. Experimental results on statistical parametric speech synthesis show that the proposed framework enables data from multiple speakers in different languages to be used to: train a synthesis system; synthesize speech in a language using speaker characteristics estimated in a different language; and adapt to a new language. © 2012 IEEE.

Ultrasonic imaging of 3D displacement vectors using a simulated 2D array and beamsteering.

Most quasi-static ultrasound elastography methods image only the axial strain, derived from displacements measured in the direction of ultrasound propagation. In other directions, the beam lacks high resolution phase information and displacement estimation is therefore less precise. However, these estimates can be improved by steering the ultrasound beam through multiple angles and combining displacements measured along the different beam directions. Previously, beamsteering has only considered the 2D case to improve the lateral displacement estimates. In this paper, we extend this to 3D using a simulated 2D array to steer both laterally and elevationally in order to estimate the full 3D displacement vector over a volume. The method is tested on simulated and phantom data using a simulated 6-10MHz array, and the precision of displacement estimation is measured with and without beamsteering. In simulations, we found a statistically significant improvement in the precision of lateral and elevational displacement estimates: lateral precision 35.69μm unsteered, 3.70μm steered; elevational precision 38.67μm unsteered, 3.64μm steered. Similar results were found in the phantom data: lateral precision 26.51μm unsteered, 5.78μm steered; elevational precision 28.92μm unsteered, 11.87μm steered. We conclude that volumetric 3D beamsteering improves the precision of lateral and elevational displacement estimates.