Discrete dislocation plasticity analysis of crack-tip fields in polycrystalline materials

Small scale yielding around a mode I crack is analysed using polycrystalline discrete dislocation plasticity. Plane strain analyses are carried out with the dislocations all of edge character and modelled as line singularities in a linear elastic material. The lattice resistance to dislocation motion, nucleation, interaction with obstacles and annihilation are incorporated through a set of constitutive rules. Grain boundaries are modelled as impenetrable to dislocations. The polycrystalline material is taken to consist of two types of square grains, one of which has a bcc-like orientation and the other an fcc-like orientation. For both orientations there are three active slip systems. Alternating rows, alternating columns and a checker-board-like arrangement of the grains is used to construct the polycrystalline materials. Consistent with the increasing yield strength of the polycrystalline material with decreasing grain size, the calculations predict a decrease in both the plastic zone size and the crack-tip opening displacement for a given applied mode I stress intensity factor. Furthermore, slip-band and kink-band formation is inhibited by all grain arrangements and, with decreasing grain size, the stress and strain distributions more closely resemble the HRR fields with the crack-tip opening approximately inversely proportional to the yield strength of the polycrystalline materials. The calculations predict a reduction in fracture toughness with decreasing grain size associated with the grain boundaries acting as effective barriers to dislocation motion.

A packaging technique for silicon MEMS strain sensors on steel

A packaging technique suited to applying MEMS strain sensors realized on a silicon chip to a steel flat surface is described. The method is based on adhesive bonding of the silicon chip rear surface on steel using two types of glue normally used for standard piezoresistive strain sensors (Mbond200/ 600), using direct wire bonding of the chip to a Printed Circuit Board, also fixed on steel. In order to protect the sensor from the external environment, and to improve the MEMS performance, the silicon chip is encapsulated with a metal cap hermetically sealed-off under vacuum condition with a vacuum adhesive in which the bonding wires are also protected from possible damage. In order to evaluate the mechanical coupling of the silicon chip with the bar and thestress transfer extent to the silicon surface, commercial strain sensors have been applied on the chip glued on a steel bar in alaboratory setup able to generate strain by inflection, yielding a stress transfer around 70% from steel to silicon. © 2008 IEEE.

Passive control of combustion instability in a low emissions aeroderivative gas turbine

This paper describes the conceptual ideas, the theoretical validation, the laboratory testing and the field trials of a recently patented fuel-air mixing device for use in high-pressure ratio, low emissions, gaseous-fueled gas turbines. By making the fuel-air mixing process insensitive to pressure fluctuations in the combustion chamber, it is possible to avoid the common problem of positive feedback between mixture strength and the unsteady combustion process. More specifically, a mixing duct has been designed such that fuel-air ratio fluctuations over a wide range of frequencies can be damped out by passive design means. By scaling the design in such a way that the range of damped frequencies covers the frequency spectrum of the acoustic modes in the combustor, the instability mechanism can be removed. After systematic development, this design philosophy was successfully applied to a 35:1 pressure ratio aeroderivative gas turbine yielding very low noise levels and very competitive NOx and CO measurements. The development of the new premixer is described from conceptual origins through analytic and CFD evaluation to laboratory testing and final field trials. Also included in this paper are comments about the practical issues of mixing, flashback resistance and autoignition.

A novel method for rapid comparative quantitative analysis of nuclear fuel cycles

One of the greatest obstacles facing the nuclear industry is that of sustainability, both in terms of the finite reserves of uranium ore and the production of highly radiotoxic spent fuel which presents proliferation and environmental hazards. Alternative nuclear technologies have been suggested as a means of delivering enhanced sustainability with proposals including fast reactors, the use of thorium fuel and tiered fuel cycles. The debate as to which is the most appropriate technology continues, with each fuel system and reactor type delivering specific advantages and disadvantages which can be difficult to compare fairly. This paper demonstrates a framework of performance metrics which, coupled with a first-order lumped reactor model to determine nuclide population balances, can be used to quantify the aforementioned pros and cons for a range of different fuel and reactor combinations. The framework includes metrics such as fuel efficiency, spent fuel toxicity and proliferation resistance, and relative cycle performance is analysed through parallel coordinate plots, yielding a quantitative comparison of disparate cycles. © 2011 Elsevier Ltd. All rights reserved.

Improving reverberant VTS for hands-free robust speech recognition

Model-based approaches to handling additive background noise and channel distortion, such as Vector Taylor Series (VTS), have been intensively studied and extended in a number of ways. In previous work, VTS has been extended to handle both reverberant and background noise, yielding the Reverberant VTS (RVTS) scheme. In this work, rather than assuming the observation vector is generated by the reverberation of a sequence of background noise corrupted speech vectors, as in RVTS, the observation vector is modelled as a superposition of the background noise and the reverberation of clean speech. This yields a new compensation scheme RVTS Joint (RVTSJ), which allows an easy formulation for joint estimation of both additive and reverberation noise parameters. These two compensation schemes were evaluated and compared on a simulated reverberant noise corrupted AURORA4 task. Both yielded large gains over VTS baseline system, with RVTSJ outperforming the previous RVTS scheme. © 2011 IEEE.

Tailoring the morphology of carbon nanotube assemblies using microgradients in the catalyst thickness

In addition to the structural control of individual carbon nanotubes (CNTs), the morphological control of their assemblies is crucial to realize miniaturized CNT devices. Microgradients in the thickness of catalyst are used to enrich the variety of available self-organized morphologies of CNTs. Microtrenches were fabricated in gate/spacer/cathode trilayers using a conventional self-aligned top-down process and catalyst exhibiting a microgradient in its thickness was formed on the cathode by sputter deposition through gate slits. CNTs, including single-walled CNTs, of up to 1μm in length were grown within 5-15 s by chemical vapor deposition. The tendency of thin CNTs to aggregate caused interactions between CNTs with different growth rates, yielding various morphologies dependent on the thickness of the catalyst. The field emission properties of several types of CNT assemblies were evaluated. The ability to produce CNTs with tailored morphologies by engineering the spatial distribution of catalysts will enhance their performance in devices. © 2011 The Japan Society of Applied Physics.

Phrase-based statistical language generation using graphical models and active learning

Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to inform the generation decision process. Both approaches rely on the existence of a handcrafted generator, which limits their scalability to new domains. This paper presents BAGEL, a statistical language generator which uses dynamic Bayesian networks to learn from semantically-aligned data produced by 42 untrained annotators. A human evaluation shows that BAGEL can generate natural and informative utterances from unseen inputs in the information presentation domain. Additionally, generation performance on sparse datasets is improved significantly by using certainty-based active learning, yielding ratings close to the human gold standard with a fraction of the data. © 2010 Association for Computational Linguistics.

The effect of remodelling and contractility of the actin cytoskeleton on the shear resistance of single cells: a computational and experimental investigation.

The biomechanisms that govern the response of chondrocytes to mechanical stimuli are poorly understood. In this study, a series of in vitro tests are performed, in which single chondrocytes are subjected to shear deformation by a horizontally moving probe. Dramatically different probe force-indentation curves are obtained for untreated cells and for cells in which the actin cytoskeleton has been disrupted. Untreated cells exhibit a rapid increase in force upon probe contact followed by yielding behaviour. Cells in which the contractile actin cytoskeleton was removed exhibit a linear force-indentation response. In order to investigate the mechanisms underlying this behaviour, a three-dimensional active modelling framework incorporating stress fibre (SF) remodelling and contractility is used to simulate the in vitro tests. Simulations reveal that the characteristic force-indentation curve observed for untreated chondrocytes occurs as a result of two factors: (i) yielding of SFs due to stretching of the cytoplasm near the probe and (ii) dissociation of SFs due to reduced cytoplasm tension at the front of the cell. In contrast, a passive hyperelastic model predicts a linear force-indentation curve similar to that observed for cells in which the actin cytoskeleton has been disrupted. This combined modelling-experimental study offers a novel insight into the role of the active contractility and remodelling of the actin cytoskeleton in the response of chondrocytes to mechanical loading.

Factor analysis based VTS discriminative adaptive training

Vector Taylor Series (VTS) model based compensation is a powerful approach for noise robust speech recognition. An important extension to this approach is VTS adaptive training (VAT), which allows canonical models to be estimated on diverse noise-degraded training data. These canonical model can be estimated using EM-based approaches, allowing simple extensions to discriminative VAT (DVAT). However to ensure a diagonal corrupted speech covariance matrix the Jacobian (loading matrix) relating the noise and clean speech is diagonalised. In this work an approach for yielding optimal diagonal loading matrices based on minimising the expected KL-divergence between the diagonal loading matrix and "correct" distributions is proposed. The performance of DVAT using the standard and optimal diagonalisation was evaluated on both in-car collected data and the Aurora4 task. © 2012 IEEE.

Lyapunov theory for zeno stability

Zeno behavior is a dynamic phenomenon unique to hybrid systems in which an infinite number of discrete transitions occurs in a finite amount of time. This behavior commonly arises in mechanical systems undergoing impacts and optimal control problems, but its characterization for general hybrid systems is not completely understood. The goal of this paper is to develop a stability theory for Zeno hybrid systems that parallels classical Lyapunov theory; that is, we present Lyapunov-like sufficient conditions for Zeno behavior obtained by mapping solutions of complex hybrid systems to solutions of simpler Zeno hybrid systems defined on the first quadrant of the plane. These conditions are applied to Lagrangian hybrid systems, which model mechanical systems undergoing impacts, yielding simple sufficient conditions for Zeno behavior. Finally, the results are applied to robotic bipedal walking. © 2012 IEEE.

The effect of floor heat source area on the induced airflow in a room

We examine the role of heat source geometry in determining rates of airflow and thermal stratification in natural displacement ventilation flows. We modify existing models to account for heat sources of finite (non-zero) area, such as formed by a sun patch warming the floor of a room. Our model allows for predictions of the steady stratification and ventilation flow rates that develop in a room due to a circular heat source at floor level. We compare our theoretical predictions with predictions for the limiting cases of a point source of heat (yielding a stratified interior), and a uniformly heated floor (yielding a mixed interior). Our theory shows a smooth transition between these two limits, which themselves result in extremes of ventilation, as the ratio of the heat source radius to the room height increases. Our model for the transition from displacement to mixing ventilation is compared to previous work and demonstrates that the transition can occur for smaller sources than previously thought, particularly for rooms with large floor area compared to ceiling height. © 2009 Elsevier Ltd.

Large-eddy simulation of complex geometry jets

Computations are made for chevron and coflowing jet nozzles. The latter has a bypass ratio of 6:1. Also, unlike the chevron nozzle, the core flow is heated, making the inlet conditions reminiscent of those for a real engine. A large-eddy resolving approach is used with circa 12 × 10 6 cell meshes. Because the codes being used tend toward being dissipative the subgrid scale model is abandoned, giving what can be termed numerical large-eddy simulation. To overcome near-wall modeling problems a hybrid numerical large-eddy simulation-Reynolds-averaged Navier-Stokes related method is used. For y + ≤ 60 a Reynolds-averaged Navier-Stokes model is used. Blending between the two regions makes use of the differential Hamilton-Jabobi equation, an extension of the eikonal equation. For both nozzles, results show encouraging agreement with measurements of other workers. The eikonal equation is also used for ray tracing to explore the effect of the mean flow on acoustic ray trajectories, thus yielding a coherent solution strategy. © 2011 by Cambridge University.

Large eddy simulation of a hot, high speed coflowing jet

Computations are made of a short cowl coflowing jet nozzle with a bypass ratio 8 : 1. The core flow is heated, making the inlet conditions reminiscent of those for a real engine. A large eddy resolving approach is used with a 12 × 106 cell mesh. Since the code being used tends towards being dissipative the sub-grid scale (SGS) model is abandoned giving what can be termed Numerical Large Eddy Simulation (NLES). To overcome near wall modelling problems a hybrid NLES-RANS (Reynolds Averaged Navier-Stokes) related method is used. For y+ ≤ 60 a κ-l model is used. Blending between the two regions makes use of the differential Hamilton-Jabobi (HJ) equation, an extension of the eikonal equation. Results show encouraging agreement with existing measurements of other workers. The eikonal equation is also used for acoustic ray tracing to explore the effect of the mean flow on acoustic ray trajectories, thus yielding a coherent solution strategy. Copyright © 2011 by ASME.

Modelling and control of nonlinear systems using Gaussian processes with partial model information

Gaussian processes are gaining increasing popularity among the control community, in particular for the modelling of discrete time state space systems. However, it has not been clear how to incorporate model information, in the form of known state relationships, when using a Gaussian process as a predictive model. An obvious example of known prior information is position and velocity related states. Incorporation of such information would be beneficial both computationally and for faster dynamics learning. This paper introduces a method of achieving this, yielding faster dynamics learning and a reduction in computational effort from O(Dn2) to O((D - F)n2) in the prediction stage for a system with D states, F known state relationships and n observations. The effectiveness of the method is demonstrated through its inclusion in the PILCO learning algorithm with application to the swing-up and balance of a torque-limited pendulum and the balancing of a robotic unicycle in simulation. © 2012 IEEE.

Nature of the electronic band gap in lanthanide oxides

Accurate electronic structures of the technologically important lanthanide/rare-earth sesquioxides (Ln2O3, with Ln=La, ⋯,Lu) and CeO2 have been calculated using hybrid density functionals HSE03, HSE06, and screened exchange (sX-LDA). We find that these density functional methods describe the strongly correlated Ln f electrons as well as the recent G0W0@LDA+U results, generally yielding the correct band gaps and trends across the Ln period. For HSE, the band gap between O 2p states and lanthanide 5d states is nearly independent of the lanthanide, while the minimum gap varies as filled or empty Ln 4f states come into this gap. sX-LDA predicts the unoccupied 4f levels at higher energies, which leads to a better agreement with experiments for Sm2O 3, Eu2O3, and Yb2O3. © 2013 American Physical Society.