An experimental study of loss sources in a fan operating with continuous inlet stagnation pressure distortion

The viability of boundary layer ingesting (BLI) engines for future aircraft propulsion is dependent on the ability to design robust, efficient engine fan systems for operation with continuously distorted inlet flow. A key step in this process is to develop an understanding of the specific mechanisms by which an inlet distortion affects the performance of a fan stage. In this paper, detailed full-annulus experimental measurements of the flow field within a low-speed fan stage operating with a continuous 60 deg inlet stagnation pressure distortion are presented. These results are used to describe the three-dimensional fluid mechanics governing the interaction between the fan and the distortion and to make a quantitative assessment of the impact on loss generation within the fan. A 5.3 percentage point reduction in stage total-to-total efficiency is observed as a result of the inlet distortion. The reduction in performance is shown to be dominated by increased loss generation in the rotor due to off-design incidence values at its leading edge, an effect that occurs throughout the annulus despite the localized nature of the inlet distortion. Increased loss in the stator row is also observed due to flow separations that are shown to be caused by whirl angle distortion at rotor exit. By addressing these losses, it should be possible to achieve improved efficiency in BLI fan systems. © 2013 by ASME.

Continuous asr for flexible incremental dialogue

Spoken dialogue systems provide a convenient way for users to interact with a machine using only speech. However, they often rely on a rigid turn taking regime in which a voice activity detection (VAD) module is used to determine when the user is speaking and decide when is an appropriate time for the system to respond. This paper investigates replacing the VAD and discrete utterance recogniser of a conventional turn-taking system with a continuously operating recogniser that is always listening, and using the recogniser 1-best path to guide turn taking. In this way, a flexible framework for incremental dialogue management is possible. Experimental results show that it is possible to remove the VAD component and successfully use the recogniser best path to identify user speech, with more robustness to noise, potentially smaller latency times, and a reduction in overall recognition error rate compared to using the conventional approach. © 2013 IEEE.

Kernelized log linear models for continuous speech recognition

Large margin criteria and discriminative models are two effective improvements for HMM-based speech recognition. This paper proposed a large margin trained log linear model with kernels for CSR. To avoid explicitly computing in the high dimensional feature space and to achieve the nonlinear decision boundaries, a kernel based training and decoding framework is proposed in this work. To make the system robust to noise a kernel adaptation scheme is also presented. Previous work in this area is extended in two directions. First, most kernels for CSR focus on measuring the similarity between two observation sequences. The proposed joint kernels defined a similarity between two observation-label sequence pairs on the sentence level. Second, this paper addresses how to efficiently employ kernels in large margin training and decoding with lattices. To the best of our knowledge, this is the first attempt at using large margin kernel-based log linear models for CSR. The model is evaluated on a noise corrupted continuous digit task: AURORA 2.0. © 2013 IEEE.

80 GSPS photonic analogue to digital conversion system using broadband continuous wave source

An 80 GSPS photonic ADC system is demonstrated, using broadband MLL and dispersive fibre to form a continuous waveform with time-wavelength mapping, and AWG to channelise. Tests are carried out for RF signals up to 10GHz. © 2005 Optical Society of America.