Thermoacoustic sensor for ultrasound power measurements and ultrasonic equipment calibration

1994 ◽  
Vol 20 (4) ◽  
pp. 367-373 ◽  
Author(s):  
B. Fay ◽  
M. Rinker ◽  
P.A. Lewin
Metrologia ◽  
2012 ◽  
Vol 49 (5) ◽  
pp. S271-S274 ◽  
Author(s):  
G Durando ◽  
C Guglielmone ◽  
C Musacchio

2017 ◽  
Vol 60 (4) ◽  
pp. 403-410 ◽  
Author(s):  
A. M. Enyakov ◽  
I. Kizlivskyi ◽  
S. I. Kuznetsov ◽  
V. P. Chalyi

2011 ◽  
Vol 279 ◽  
pp. 012013
Author(s):  
G Durando ◽  
C Guglielmone ◽  
C Musacchio

1985 ◽  
Vol 46 (C2) ◽  
pp. C2-303-C2-305
Author(s):  
R. S. Raymond ◽  
K. A. Brown ◽  
R. J. Bruni ◽  
P. R. Cameron ◽  
D. G. Crabb ◽  
...  

2020 ◽  
Vol 27 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Aleksandar Radonjić ◽  
Danijela Pjevčević ◽  
Vladislav Maraš

AbstractThis paper investigates the use of neural networks (NNs) for the problem of assigning push boats to barge convoys in inland waterway transportation (IWT). Push boat–barge convoy assignmentsare part of the daily decision-making process done by dispatchers in IWT companiesforwhich a decision support tool does not exist. The aim of this paper is to develop a Neural Network Ensemble (NNE) model that will be able to assist in push boat–barge convoy assignments based on the push boat power.The primary objective of this paper is to derive an NNE model for calculation of push boat Shaft Powers (SHPs) by using less than 100% of the experimental data available. The NNE model is applied to a real-world case of more than one shipping company from the Republic of Serbia, which is encountered on the Danube River. The solution obtained from the NNE model is compared toreal-world full-scale speed/power measurements carried out on Serbian push boats, as well as with the results obtained from the previous NNE model. It is found that the model is highly accurate, with scope for further improvements.


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