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.

Stall Warning by Blade Pressure Signature Analysis

At low mass flow rates, axial compressors suffer from flow instabilities leading to stall and surge. The inception process of these instabilities has been widely researched in the past---primarily with the aim of predicting or averting stall onset. In recent times, attention has shifted to conditions well before stall and has focused on the level of irregularity in the blade passing signature in the rotor tip region. In general, the irregularity increases in intensity as the flow rate through the compressor is reduced. Attempts have been made to develop stall warning/avoidance procedures based on the level of flow irregularity, but little effort has been made to characterize the irregularity itself, or to understand its underlying cause. Work on this project has revealed for the first time that the increase in irregularity in the blade passing signature is highly dependent on both tip-clearance size and eccentricity. In a compressor with small, uniform, tip-clearance, the increase in blade passing irregularity that accompanies a reduction in flow rate will be modest. If the tip-clearance is enlarged, however, there will be a sharp rise in irregularity at all circumferential locations. In a compressor with eccentric tip-clearance, the increase in irregularity will only occur in the part of the annulus where the tip-clearance is largest, regardless of the average clearance level. In this paper, some attention is also given to the question of whether the irregularity observed in the prestall flow field is due to random turbulence or to some form of coherent flow structure. Detailed flow measurements reveal that the latter is the case. From these findings, it is clear that a stall warning system based on blade passing signature irregularity would be difficult to implement in an aero-engine where tip-clearance size and eccentricity change during each flight cycle and over the life of the compressor. © 2013 American Society of Mechanical Engineers.

Numerical analysis of AC loss reduction in HTS superconducting coils using magnetic materials to divert flux

In this paper, the use of magnetic materials to divert flux in high-temperature superconductor superconducting coils and reduce transport ac loss is investigated. This particular technique is preferred over other techniques, such as striation, Roebel transposition, and twisted wires because it does not require modification to the conductor itself, which can be detrimental to the properties of the superconductor. The technique can also be implemented for existing coils. The analysis is carried out using a coil model based on the H formulation and implemented in comsol multiphysics. Both weakly and strongly magnetic materials are investigated, and it is shown that the use of such materials can divert flux and achieve a reduction in transport ac loss, which, in some cases, is quite significant. This analysis acts to provide a foundation for further optimization and experimental work in the future. © 2011 IEEE.

Evidence-informed development of engineering practical work: Effecting change through staff and student engagement

This paper discusses innovations in curriculum development in the Department of Engineering at the University of Cambridge as a participant in the Teaching for Learning Network (TFLN), a teaching and learning development initiative funded by the Cambridge-MIT Institute a pedagogic collaboration and brokerage network. A year-long research and development project investigated the practical experiences through which students traditionally explore engineering disciplines, apply and extend the knowledge gained in lectures and other settings, and begin to develop their professional expertise. The research project evaluated current practice in these sessions and developed an evidence-base to identify requirements for new activities, student support and staff development. The evidence collected included a novel student 'practice-value' survey highlighting effective practice and areas of concern, classroom observation of practicals, semi-structured interviews with staff, a student focus group and informal discussions with staff. Analysis of the data identified three potentially 'high-leverage' strategies for improvement: development of a more integrated teaching framework, within which practical work could be contextualised in relation to other learning; a more transparent and integrated conceptual framework where theory and practice were more closely linked; development of practical work more reflective of the complex problems facing professional engineers. This paper sets out key elements of the evidence collected and the changes that have been informed by this evidence and analysis, leading to the creation of a suite of integrated practical sessions carefully linked to other course elements and reinforcing central concepts in engineering, accompanied by a training and support programme for teaching staff.

Finite element analysis of compressor disc heat transfer using the transient conduction method with sparse boundary collocation points

Surface temperature measurements from two discs of a gas turbine compressor rig are used as boundary conditions for the transient conduction solution (inverse heat transfer analysis). The disc geometry is complex, and so the finite element method is used. There are often large radial temperature gradients on the discs, and the equations are therefore solved taking into account the dependence of thermal conductivity on temperature. The solution technique also makes use of a multigrid algorithm to reduce the solution time. This is particularly important since a large amount of data must be analyzed to obtain correlations of the heat transfer. The finite element grid is also used for a network analysis to calculate the radiant heat transfer in the cavity formed between the two compressor discs. The work discussed here proved particularly challenging as the disc temperatures were only measured at four different radial locations. Four methods of surface temperature interpolation are examined, together with their effect on the local heat fluxes. It is found that the choice of interpolation method depends on the available number of data points. Bessel interpolation gives the best results for four data points, whereas cubic splines are preferred when there are considerably more data points. The results from the analysis of the compressor rig data show that the heat transfer near the disc inner radius appears to be influenced by the central throughflow. However, for larger radii, the heat transfer from the discs and peripheral shroud is found to be consistent with that of a buoyancy-induced flow.

A Maximum-Likelihood Interpretation for Slow Feature Analysis

The brain extracts useful features from a maelstrom of sensory information, and a fundamental goal of theoretical neuroscience is to work out how it does so. One proposed feature extraction strategy is motivated by the observation that the meaning of sensory data, such as the identity of a moving visual object, is often more persistent than the activation of any single sensory receptor. This notion is embodied in the slow feature analysis (SFA) algorithm, which uses “slowness” as an heuristic by which to extract semantic information from multi-dimensional time-series. Here, we develop a probabilistic interpretation of this algorithm showing that inference and learning in the limiting case of a suitable probabilistic model yield exactly the results of SFA. Similar equivalences have proved useful in interpreting and extending comparable algorithms such as independent component analysis. For SFA, we use the equivalent probabilistic model as a conceptual spring-board, with which to motivate several novel extensions to the algorithm.

The vibro-acoustic analysis of built-up systems using a hybrid method with parametric and non-parametric uncertainties

An existing hybrid finite element (FE)/statistical energy analysis (SEA) approach to the analysis of the mid- and high frequency vibrations of a complex built-up system is extended here to a wider class of uncertainty modeling. In the original approach, the constituent parts of the system are considered to be either deterministic, and modeled using FE, or highly random, and modeled using SEA. A non-parametric model of randomness is employed in the SEA components, based on diffuse wave theory and the Gaussian Orthogonal Ensemble (GOE), and this enables the mean and variance of second order quantities such as vibrational energy and response cross-spectra to be predicted. In the present work the assumption that the FE components are deterministic is relaxed by the introduction of a parametric model of uncertainty in these components. The parametric uncertainty may be modeled either probabilistically, or by using a non-probabilistic approach such as interval analysis, and it is shown how these descriptions can be combined with the non-parametric uncertainty in the SEA subsystems to yield an overall assessment of the performance of the system. The method is illustrated by application to an example built-up plate system which has random properties, and benchmark comparisons are made with full Monte Carlo simulations. © 2012 Elsevier Ltd. All rights reserved.

When will a flame describing function approach to thermoacoustics work well?

In any thermoacoustic analysis, it is important not only to predict linear frequencies and growth rates, but also the amplitude and frequencies of any limit cycles. The Flame Describing Function (FDF) approach is a quasi-linear analysis which allows the prediction of both the linear and nonlinear behaviour of a thermoacoustic system. This means that one can predict linear growth rates and frequencies, and also the amplitudes and frequencies of any limit cycles. The FDF achieves this by assuming that the acoustics are linear and that the flame, which is the only nonlinear element in the thermoacoustic system, can be adequately described by considering only its response at the frequency at which it is forced. Therefore any harmonics generated by the flame's nonlinear response are not considered. This implies that these nonlinear harmonics are small or that they are sufficiently filtered out by the linear dynamics of the system (the low-pass filter assumption). In this paper, a flame model with a simple saturation nonlinearity is coupled to simple duct acoustics, and the success of the FDF in predicting limit cycles is studied over a range of flame positions and acoustic damping parameters. Although these two parameters affect only the linear acoustics and not the nonlinear flame dynamics, they determine the validity of the low-pass filter assumption made in applying the flame describing function approach. Their importance is highlighted by studying the level of success of an FDF-based analysis as they are varied. This is achieved by comparing the FDF's prediction of limit-cycle amplitudes to the amplitudes seen in time domain simulations.

On the relation of slow feature analysis and Laplacian eigenmaps

The past decade has seen a rise of interest in Laplacian eigenmaps (LEMs) for nonlinear dimensionality reduction. LEMs have been used in spectral clustering, in semisupervised learning, and for providing efficient state representations for reinforcement learning. Here, we show that LEMs are closely related to slow feature analysis (SFA), a biologically inspired, unsupervised learning algorithm originally designed for learning invariant visual representations. We show that SFA can be interpreted as a function approximation of LEMs, where the topological neighborhoods required for LEMs are implicitly defined by the temporal structure of the data. Based on this relation, we propose a generalization of SFA to arbitrary neighborhood relations and demonstrate its applicability for spectral clustering. Finally, we review previous work with the goal of providing a unifying view on SFA and LEMs. © 2011 Massachusetts Institute of Technology.

Nonlinear drillstring dynamics analysis

This paper studies the dynamical response of a rotary drilling system with a drag bit, using a lumped parameter model that takes into consideration the axial and torsional vibration modes of the bit. These vibrations are coupled through a bit-rock interaction law. At the bit-rock interface, the cutting process introduces a state-dependent delay, while the frictional process is responsible for discontinuous right-hand sides in the equations governing the motion of the bit. This complex system is characterized by a fast axial dynamics compared to the slow torsional dynamics. A dimensionless formulation exhibits a large parameter in the axial equation, enabling a two-time-scales analysis that uses a combination of averaging methods and a singular perturbation approach. An approximate model of the decoupled axial dynamics permits us to derive a pseudoanalytical expression of the solution of the axial equation. Its averaged behavior influences the slow torsional dynamics by generating an apparent velocity weakening friction law that has been proposed empirically in earlier work. The analytical expression of the solution of the axial dynamics is used to derive an approximate analytical expression of the velocity weakening friction law related to the physical parameters of the system. This expression can be used to provide recommendations on the operating parameters and the drillstring or the bit design in order to reduce the amplitude of the torsional vibrations. Moreover, it is an appropriate candidate model to replace empirical friction laws encountered in torsional models used for control. © 2009 Society for Industrial and Applied Mathematics.

Structural analysis of plate-type fuel assemblies and development of a non-destructive method to assess their integrity

This work is concerned with the structural behaviour and the integrity of parallel plate-type nuclear fuel assemblies. A plate-type assembly consists of several thin plates mounted in a box-like structure and is subjected to a coolant flow that can result in a considerable drag force. A finite element model of an assembly is presented to study the sensitivity of the natural frequencies to the stiffness of the plates' junctions. It is shown that the shift in the natural frequencies of the torsional modes can be used to check the global integrity of the fuel assembly while the local natural frequencies of the inner plates can be used to estimate the maximum drag force they can resist. Finally a non-destructive method is developed to assess the resistance of the inner plates to bear an applied load. Extensive computational and experimental results are presented to prove the applicability of the method presented. © 2013 Elsevier B.V. All rights reserved.

Axial discontinuity factors for the nodal diffusion analysis of high conversion BWR cores

High conversion LWRs concepts typically rely on a heterogeneous core configuration, where fissile zones are interspersed with fertile blanket zones in order to achieve a high conversion ratio. Modeling such a heterogeneous structure of these cores represents a significant challenge to the conventional reactor analysis methods. It was recently suggested to overcome such difficulties, in particular, for the case of axially heterogeneous reduced moderation BWRs, by introducing an additional set of discontinuity factors in axial direction at the interfaces between fissile and fertile fuel assembly zones. However, none of the existing nodal diffusion core simulators have the capability of accounting for discontinuity of homogeneous nodal fluxes in axial direction since the fuel composition of conventional LWRs is much more axially uniform. In this work, we modified the nodal diffusion code DYN3D by introducing such a capability. The new version of the code was tested on a series of reduced moderation BWR cases with Th-U233 and U-Pu-MA fuel. The library of few-group homogenized cross sections and the data required for the calculation of discontinuity factors were generated using the Monte Carlo transport code Serpent. The results obtained with the modified version of DYN3D were compared with the reference Monte Carlo solutions and were found to be in good agreement. The current analysis demonstrates that high conversion LWRs can in principle be modeled using existing nodal diffusion core simulators. © 2013 Elsevier Ltd. All rights reserved.

An investigation into numerical analysis alternatives for predicting reingestion in turbine disc rim cavities

Reliable means of predicting ingestion in cavities adjacent to the main gas path are increasingly being sought by engineers involved in the design of gas turbines. In this paper, analysis is to be presented that results from an extended research programme, MAGPI, sponsored by the EU and several leading gas turbine manufactures and universities. Extensive use is made of CFD modelling techniques to understand the aerodynamic behaviour of a turbine stator well cavity, focusing on the interaction of cooling air supply with the main annulus gas. The objective of the study has been to benchmark a number of CFD codes and numerical techniques covering RANS and URANS calculations with different turbulence models in order to assess the suitability of the standard settings used in the industry for calculating the mechanics of the flow travelling between cavities in a turbine through the main gas path. The modelling methods employed have been compared making use of experimental data gathered from a dedicated two-stage turbine rig, running at engine representative conditions. Extensive measurements are available for a range of flow conditions and alternative cooling arrangements. The limitations of the numerical methods in calculating the interaction of the cooling flow egress and the main stream gas, and subsequent ingestion into downstream cavities in the engine (i.e. re-ingestion), have been exposed. This has been done without losing sight of the validation of the CFD for its use for predicting heat transfer, which was the main objective of the partners of the MAGPI Work- Package 1 consortium. Copyright © 2012 by ASME.

First-principles energetics of water clusters and ice: a many-body analysis.

Standard forms of density-functional theory (DFT) have good predictive power for many materials, but are not yet fully satisfactory for cluster, solid, and liquid forms of water. Recent work has stressed the importance of DFT errors in describing dispersion, but we note that errors in other parts of the energy may also contribute. We obtain information about the nature of DFT errors by using a many-body separation of the total energy into its 1-body, 2-body, and beyond-2-body components to analyze the deficiencies of the popular PBE and BLYP approximations for the energetics of water clusters and ice structures. The errors of these approximations are computed by using accurate benchmark energies from the coupled-cluster technique of molecular quantum chemistry and from quantum Monte Carlo calculations. The systems studied are isomers of the water hexamer cluster, the crystal structures Ih, II, XV, and VIII of ice, and two clusters extracted from ice VIII. For the binding energies of these systems, we use the machine-learning technique of Gaussian Approximation Potentials to correct successively for 1-body and 2-body errors of the DFT approximations. We find that even after correction for these errors, substantial beyond-2-body errors remain. The characteristics of the 2-body and beyond-2-body errors of PBE are completely different from those of BLYP, but the errors of both approximations disfavor the close approach of non-hydrogen-bonded monomers. We note the possible relevance of our findings to the understanding of liquid water.

A framework for the analysis of thermal losses in reciprocating compressors and expanders

This article presents a framework that describes formally the underlying unsteady and conjugate heat transfer processes that are undergone in thermodynamic systems, along with results from its application to the characterization of thermodynamic losses due to irreversible heat transfer during reciprocating compression and expansion processes in a gas spring. Specifically, a heat transfer model is proposed that solves the one-dimensional unsteady heat conduction equation in the solid simultaneously with the first law in the gas phase, with an imposed heat transfer coefficient taken from suitable experiments in gas springs. Even at low volumetric compression ratios (of 2.5), notable effects of unsteady heat transfer to the solid walls are revealed, with thermally induced thermodynamic cycle (work) losses of up to 14% (relative to the work input/output in equivalent adiabatic and reversible compression/expansion processes) at intermediate Péclet numbers (i.e., normalized frequencies) when unfavorable solid and gas materials are selected, and closer to 10-12% for more common material choices. The contribution of the solid toward these values, through the conjugate variations attributed to the thickness of the cylinder wall, is about 8% and 2% points, respectively, showing a maximum at intermediate thicknesses. At higher compression ratios (of 6) a 19% worst-case loss is reported for common materials. These results suggest strongly that in designing high-efficiency reciprocating machines the full conjugate and unsteady problem must be considered and that the role of the solid in determining performance cannot, in general, be neglected. © 2014 Richard Mathie, Christos N. Markides, and Alexander J. White. Published with License by Taylor & Francis.