8,146 research outputs found

    Prediction of noise from serrated trailing edges

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    A new analytical model is developed for the prediction of noise from serrated trailing edges. The model generalizes Amiet’s trailing-edge noise theory to sawtooth trailing edges, resulting in a complicated partial differential equation. The equation is then solved by means of a Fourier expansion technique combined with an iterative procedure. The solution is validated through comparison with the finite element method for a variety of serrations at different Mach numbers. The results obtained using the new model predict noise reduction of up to 10 dB at 90∘^{\circ } above the trailing edge, which is more realistic than predictions based on Howe’s model and also more consistent with experimental observations. A thorough analytical and numerical analysis of the physical mechanism is carried out and suggests that the noise reduction due to serration originates primarily from interference effects near the trailing edge. A closer inspection of the proposed mathematical model has led to the development of two criteria for the effectiveness of the trailing-edge serrations, consistent but more general than those proposed by Howe. While experimental investigations often focus on noise reduction at 90∘^{\circ } above the trailing edge, the new analytical model shows that the destructive interference scattering effects due to the serrations cause significant noise reduction at large polar angles, near the leading edge. It has also been observed that serrations can significantly change the directivity characteristics of the aerofoil at high frequencies and even lead to noise increase at high Mach numbers.The first author (BL) wishes to gratefully acknowledge the financial support co-funded by the Cambridge Commonwealth European and International Trust and China Scholarship Council. The second author (MA) would like to acknowledge the financial support of the Royal Academy of Engineering. The third author (SS) wishes to gratefully acknowledge the support of the Royal Commission for the exhibition of 1851.This is the author accepted manuscript. The final version is available from Cambridge University Press via http://dx.doi.org/10.1017/jfm.2016.13

    Structure and electronic properties of the (3×3\sqrt{3}\times \sqrt{3})R30∘R30^{\circ} SnAu2_2/Au(111) surface alloy

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    We have investigated the atomic and electronic structure of the (3×3\sqrt{3}\times \sqrt{3})R30∘R30^{\circ} SnAu2_2/Au(111) surface alloy. Low energy electron diffraction and scanning tunneling microscopy measurements show that the native herringbone reconstruction of bare Au(111) surface remains intact after formation of a long range ordered (3×3\sqrt{3}\times \sqrt{3})R30∘R30^{\circ} SnAu2_22/Au(111) surface alloy. Angle-resolved photoemission and two-photon photoemission spectroscopy techniques reveal Rashba-type spin-split bands in the occupied valence band with comparable momentum space splitting as observed for the Au(111) surface state, but with a hole-like parabolic dispersion. Our experimental findings are compared with density functional theory (DFT) calculation that fully support our experimental findings. Taking advantage of the good agreement between our DFT calculations and the experimental results, we are able to extract that the occupied Sn-Au hybrid band is of (s, d)-orbital character while the unoccupied Sn-Au hybrid bands are of (p, d)-orbital character. Hence, we can conclude that the Rashba-type spin splitting of the hole-like Sn-Au hybrid surface state is caused by the significant mixing of Au d- to Sn s-states in conjunction with the strong atomic spin-orbit coupling of Au, i.e., of the substrate.Comment: Copyright: https://journals.aps.org/authors/transfer-of-copyright-agreement; All copyrights by AP

    Efficient Quantum Work Reservoirs at the Nanoscale

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    When reformulated as a resource theory, thermodynamics can analyze system behaviors in the single-shot regime. In this, the work required to implement state transitions is bounded by alpha-Renyi divergences and so differs in identifying efficient operations compared to stochastic thermodynamics. Thus, a detailed understanding of the difference between stochastic thermodynamics and resource-theoretic thermodynamics is needed. To this end, we study reversibility in the single-shot regime, generalizing the two-level work reservoirs used there to multi-level work reservoirs. This achieves reversibility in any transition in the single-shot regime. Building on this, we systematically explore multi-level work reservoirs in the nondissipation regime with and without catalysts. The resource-theoretic results show that two-level work reservoirs undershoot Landauer's bound, misleadingly implying energy dissipation during computation. In contrast, we demonstrate that multi-level work reservoirs achieve Landauer's bound and produce zero entropy.Comment: 17 pages, 5 figures, 6 tables; https://csc.ucdavis.edu/~cmg/compmech/pubs/eqwratn.ht

    MetaMax: Improved Open-Set Deep Neural Networks via Weibull Calibration

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    Open-set recognition refers to the problem in which classes that were not seen during training appear at inference time. This requires the ability to identify instances of novel classes while maintaining discriminative capability for closed-set classification. OpenMax was the first deep neural network-based approach to address open-set recognition by calibrating the predictive scores of a standard closed-set classification network. In this paper we present MetaMax, a more effective post-processing technique that improves upon contemporary methods by directly modeling class activation vectors. MetaMax removes the need for computing class mean activation vectors (MAVs) and distances between a query image and a class MAV as required in OpenMax. Experimental results show that MetaMax outperforms OpenMax and is comparable in performance to other state-of-the-art approaches.Comment: To be presented at the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshop on Dealing with Novelty in Open Worlds (DNOW
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