Mathematical modeling and noise-proof estimation of shock wave pulse parameters based on the results of an experiment in underwater explosions

The article deals with the construction of a mathematical model of the underwater shock wave pulse based on the results of the experiment and numerical and analytical scientific research. The results of the development and comparative analysis of various numerical methods for nonlinear estimation of...

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Published in:Vestnik Samarskogo gosudarstvennogo tehničeskogo universiteta. Seriâ Fiziko-matematičeskie nauki Vol. 25; no. 1; pp. 127 - 162
Main Authors: Vladimir E. Zoteev, Sergey Yu. Ganigin, Dmitry A. Demoretsky, Maksim V. Nenashev, Aleksey V. Gubinskiy
Format: Journal Article
Language:English
Russian
Published: Samara State Technical University 01.01.2021
Subjects:
generalized regression model
mathematical model
nonlinear regression analysis
root-mean-square estimation
statistical processing of experimental results
underwater shock wave pulse
ISSN:1991-8615, 2310-7081
Online Access:Get full text
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Summary:The article deals with the construction of a mathematical model of the underwater shock wave pulse based on the results of the experiment and numerical and analytical scientific research. The results of the development and comparative analysis of various numerical methods for nonlinear estimation of the parameters of this model are presented. A numerical method is proposed for estimating the pulse energy of a shock wave based on the experimental results in the form of an overpressure waveform both over an infinite period of time and at a given pulse duration. The results of testing the developed numerical methods for mathematical modeling of the underwater shock wave pulse when processing the results of the experiment at the explosion of model charge are presented. The reliability and efficiency of the computational algorithms and numerical methods of nonlinear estimation presented in this paper is confirmed by the results of numerical and analytical studies and mathematical models constructed on the basis of experimental data.
ISSN:1991-8615
2310-7081
DOI:10.14498/vsgtu1849