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Abstract

The paper presents the results of the noise propagation analysis in ship structures tested in a number of AHTS (Anchor Handling Tug Supply) vessels. Statistical Energy Analysis (SEA) based on numerical model developed specially for the purpose of this numerical investigation were conducted. This numerical model enabled the analysis of both the structural elements and the acoustic spaces. For the detailed studies 47 points fixed at various ship locations were selected. Prediction results with use of the numerical model were compared with the experimental results carried out in six identical AHTS vessels. Experimental studies were performed in accordance with the requirements of the International Maritime Organization (IMO) Resolution A.468 (XII). As a result one presented a comparison of the model analysis and experimental tests results.
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Authors and Affiliations

Grażyna Grelowska
Mateusz Weryk
Eugeniusz Kozaczka
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Abstract

The power injection method (PIM) is an experimental method used to identify the statistical energy analysis (SEA) parameters (called loss factors – LFs) of a vibroacoustic system. By definition, LFs are positive real numbers. However, it is not uncommon to obtain negative LFs during experiments, which is considered a measurement error. To date, a recently proposed method, called Monte Carlo filtering (MCF), of correcting negative coupling loss factors (CLFs) has been validated for systems that meet SEA assumptions. In this article, MCF was validated for point connections and in conditions where SEA assumptions are not met (systems with low modal overlap, non-conservative junctions, strong coupling). The effect of removing MCF bias on the results was also examined. During the experiments, it was observed that the bias is inversely proportional to the damping loss factor of the examined subsystems. The obtained results confirm that the PIM, combined with MCF, allows to determine non-negative SEA parameters in all considered cases.
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Authors and Affiliations

Paweł Nieradka
1 2
Andrzej Dobrucki
1

  1. Wrocław University of Science and Technology, Department of Acoustics, Multimedia and Signal Processing, Wroclaw, Poland
  2. KFB Acoustics, Acoustic Research and Innovation Center, Domasław, Poland

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