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    Wyświetlanie 1-3 z 3
    Tytuł:
    Shape Optimization of Two-layer Acoustical Hoods Using an Artificial Immune Method
    Autorzy:
    Chiu, M-C.
    Powiązania:
    https://bibliotekanauki.pl/articles/177732.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    multi-layer
    close-fitting acoustical hood
    artificial immune method
    Opis:
    Research on acoustical hoods used in industry has been widely discussed; however, the assessment of shape optimization on space-constrained close-fitting acoustic hoods by adjusting design parameters has been neglected. Moreover, the acoustical performance for a one-layer acoustic hood used in a high intensity environment seems to be insufficient. Therefore, an assessment of an optimally shaped acoustical hood with two layers will be proposed. In this paper, a numerical case for depressing the noise level of a piece of equipment by optimally designing a shaped two-layer close-fitting acoustic hood under a constrained space will be introduced. Furthermore, to optimally search for a better designed set for the multi-layer acoustical hood, an artificial immune method (AIM) has been adopted as well. Consequently, this paper provides a quick and effective method to reduce equipment noise by optimally designing a shaped multi- layer close-fitting acoustic hood via the AIM searching technique.
    Źródło:
    Archives of Acoustics; 2012, 37, 2; 181-188
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multi-Layer Perceptron Neural Network Utilizing Adaptive Best-Mass Gravitational Search Algorithm to Classify Sonar Dataset
    Autorzy:
    Mosavi, Mohammad Reza
    Khishe, Mohammad
    Naseri, Mohammad Jafar
    Parvizi, Gholam Reza
    Ayat, Mehdi
    Powiązania:
    https://bibliotekanauki.pl/articles/176971.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    MLP NN
    Multi-Layer Perceptron Neural Network
    ABGSA
    Adaptive Best Mass Gravitational Search Algorithm
    sonar
    classification
    Opis:
    In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed for classifying sonar targets and non-targets from the acoustic backscattered signals. Besides the capabilities of MLP NNs, it uses Back Propagation (BP) and Gradient Descent (GD) for training; therefore, MLP NNs face with not only impertinent classification accuracy but also getting stuck in local minima as well as lowconvergence speed. To lift defections, this study uses Adaptive Best Mass Gravitational Search Algorithm (ABGSA) to train MLP NN. This algorithm develops marginal disadvantage of the GSA using the bestcollected masses within iterations and expediting exploitation phase. To test the proposed classifier, this algorithm along with the GSA, GD, GA, PSO and compound method (PSOGSA) via three datasets in various dimensions will be assessed. Assessed metrics include convergence speed, fail probability in local minimum and classification accuracy. Finally, as a practical application assumed network classifies sonar dataset. This dataset consists of the backscattered echoes from six different objects: four targets and two non-targets. Results indicate that the new classifier proposes better output in terms of aforementioned criteria than whole proposed benchmarks.
    Źródło:
    Archives of Acoustics; 2019, 44, 1; 137-151
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Numerical Prediction of the Tonal Airborne Noise for a NACA 0012 Aerofoil at Moderate Reynolds Number Using a Transitional URANS Approach
    Autorzy:
    De Gennaro, M.
    Küehnelt, H.
    Zanon, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/178116.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    tonal airborne noise
    NACA 0012
    Laminar Boundary Layer-Vortex Shedding noise
    Ladder-like tonal structure of the acoustic spectrum
    multi-tonal structure of the acoustic spectrum
    Opis:
    Tonal airborne noise of aerofoils appears in a limited range of moderate Reynolds numbers and angles of attack. In these specific conditions, the aerofoil is characterised by a large region of laminar flow over the aerodynamic surface, typically resulting in two-dimensional laminar instabilities in the boundary layer, generating one or more acoustic tones. The numerical simulation of such phenomenon requires, beside an accurate prediction of the unsteady flow field, a proper modelling of the laminar to turbulent transition of the boundary layer, which generally imposes the use of highly CPU demanding approaches such as large eddy simulation (LES) or direct numerical simulation (DNS). This paper aims at presenting the results of numerical experiments for evaluating the capability of capturing the tonal airborne noise by using an advanced, yet low computationally demanding, unsteady Reynolds-averaged Navier-Stokes (URANS) turbulence model augmented with a transitional model to account for the laminar to turbulent transition. This approach, coupled with the Ffowcs Williams and Hawkings (FW-H) acoustic analogy, is adopted for predicting the far-field acoustic sound pressure of a NACA 0012 aerofoil with Reynolds number ranging from 0.39 · 106 to 1.09 · 106. The results show a main tone located approximately at 1.6–1.8 kHz for a Reynolds number equal to 0.62 · 106, increasing to 2.4 kHz at Reynolds number equal to 0.85 · 106 and 3.4 kHz at 1.09 · 106, while no main tones are observed at 0.39 · 106. The computed spectra confirm that the acoustic emission of the aerofoil is dominated by tonal structures and that the frequency of the main tone depends on the Reynolds number consistently with the ladder-like tonal structure suggested by Paterson et al. Moreover, in specific conditions, the acoustic spectra exhibit a multi-tonal structure visible in narrowband spectra, in line with the findings of Arbey and Bataille. The presented results demonstrate the capability of the numerical model of predicting the physics of the tonal airborne noise generation.
    Źródło:
    Archives of Acoustics; 2017, 42, 4; 653-675
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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