Noise propagation and equilibrium multiplicity

Author(s):  
Qingduo Zeng ◽  
Duxue Huang ◽  
Xu Teng
Keyword(s):  
1989 ◽  
Vol 40 (15) ◽  
pp. 10088-10099 ◽  
Author(s):  
T. Csiba ◽  
G. Kriza ◽  
A. Jánossy

Author(s):  
Roger L. Wayson ◽  
Kenneth Kaliski

Modeling road traffic noise levels without including the effects of meteorology may lead to substantial errors. In the United States, the required model is the Traffic Noise Model which does not include meteorology effects caused by refraction. In response, the Transportation Research Board sponsored NCHRP 25-52, Meteorological Effects on Roadway Noise, to collect highway noise data under different meteorological conditions, document the meteorological effects on roadway noise propagation under different atmospheric conditions, develop best practices, and provide guidance on how to: (a) quantify meteorological effects on roadway noise propagation; and (b) explain those effects to the public. The completed project at 16 barrier and no-barrier measurement positions adjacent to Interstate 17 (I-17) in Phoenix, Arizona provided the database which has enabled substantial developments in modeling. This report provides more recent information on the model development that can be directly applied by the noise analyst to include meteorological effects from simple look-up tables to more precise use of statistical equations.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1568
Author(s):  
Bernhard Wunsch ◽  
Stanislav Skibin ◽  
Ville Forsström ◽  
Ivica Stevanovic

EMC simulations are an indispensable tool to analyze EMC noise propagation in power converters and to assess the best filtering options. In this paper, we first show how to set up EMC simulations of power converters and then we demonstrate their use on the example of an industrial AC motor drive. Broadband models of key power converter components are reviewed and combined into a circuit model of the complete power converter setup enabling detailed EMC analysis. The approach is demonstrated by analyzing the conducted noise emissions of a 75 kW power converter driving a 45 kW motor. Based on the simulations, the critical impedances, the dominant noise propagation, and the most efficient filter component and location within the system are identified. For the analyzed system, maxima of EMC noise are caused by resonances of the long motor cable and can be accurately predicted as functions of type, length, and layout of the motor cable. The common-mode noise at the LISN is shown to have a dominant contribution caused by magnetic coupling between the noisy motor side and the AC input side of the drive. All the predictions are validated by measurements and highlight the benefit of simulation-based EMC analysis and filter design.


1990 ◽  
Vol 8 ◽  
pp. 169-176
Author(s):  
Yoshinori WATANABE ◽  
Tadaharu OZAKI ◽  
Takio YANAO
Keyword(s):  

2017 ◽  
Vol 12 (12) ◽  
pp. P12004-P12004 ◽  
Author(s):  
F. Arteche ◽  
C. Rivetta ◽  
M. Iglesias ◽  
I. Echeverria ◽  
A. Pradas ◽  
...  

2008 ◽  
Author(s):  
Rasika Fernando ◽  
Régis Marchiano ◽  
François Coulouvrat ◽  
Yann Druon ◽  
Bengt Enflo ◽  
...  

Fluids ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 19
Author(s):  
Emmanuele D’Andrea ◽  
Maurizio Arena ◽  
Massimo Viscardi ◽  
Tommaso Coppola

An increasing attention has recently been paid to the effect of the underwater noise field generated by ship activities on the marine environment. Although this problem is widely discussed in international treaties and conventions, it has not yet found a consolidated technical-scientific treatment capable of quantifying the level of underwater noise emissions produced by naval systems. As part of a national research collaboration, a novel code has been developed to predict noise propagation according to the Ray Tracing approach. Such optical geometry-based technique allows for calculating the Transmission Loss (TL) trend in its respective contributions: geometrical loss (due to the distance between the source and receiver), dissipation loss (due to the characteristics of the propagation environment), and reflection loss (due to the surfaces that delimit the field). The simulation requires as input parameters the source info as spatial position, frequency, and sound pressure level (SPL) as well as the sea properties like seabed depth, the speed of sound profile, the layers thickness the water column is divided into, the sea salinity, temperature, and pH. The simulation code provides the SPL spatial distribution useful as a fast industrial tool in the future studies addressed to identify the emission limits for the protection of marine wildlife.


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