Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  A stochastic nonlinear differential propagation model for underwater acoustic propagation: Theory and solution

Haiyang, Y., Haiyan, W., Zhichen, Z., Yong, X., Kurths, J. (2021): A stochastic nonlinear differential propagation model for underwater acoustic propagation: Theory and solution. - Chaos, Solitons and Fractals, 150, 111105.
https://doi.org/10.1016/j.chaos.2021.111105

Item is

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Haiyang, Yao1, Autor
Haiyan, Wang1, Autor
Zhichen, Zhang1, Autor
Yong, Xu1, Autor
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: The principle of underwater acoustic signal propagation is of vital importance to realize the “digital ocean”. However, underwater circumstances are becoming more complex and multi-factorial because of raising human activities, changing climate, to name a few. For this study, we formulate a mathematical model to describe the complex variation of underwater propagating acoustic signals, and the solving method are presented. Firstly, the perturb-coefficient nonlinear propagation equation is derived based on hydrodynamics and the adiabatic relation between pressure and density. Secondly, physical elements are divided into two types, intrinsic and extrinsic. The expression of the two types are combined with the perturb-coefficient nonlinear propagation equation by location and stochastic parameters to obtain the stochastic nonlinear differential propagation model. Thirdly, initial and boundary conditions are analyzed. The existence theorem for solutions is proved. Finally, the operator splitting procedure is proposed to obtain the solution of the model. Two simulations demonstrate that this model is effective and can be used in multiple circumstances.

Details

einblenden:
ausblenden:
Sprache(n):
 Datum: 2021-06-162021-06-162021-09
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.chaos.2021.111105
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Oceans
Research topic keyword: Weather
Model / method: Nonlinear Data Analysis
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Chaos, Solitons and Fractals
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 150 Artikelnummer: 111105 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/190702
Publisher: Elsevier