Publication Cover
Applicable Analysis
An International Journal
Volume 102, 2023 - Issue 18
94
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Attractors for partially damped systems of binary mixtures of solids

, , &
Pages 5103-5122 | Received 22 Oct 2021, Accepted 12 Dec 2022, Published online: 29 Dec 2022
 

Abstract

This paper targets the long-time dynamics of a semilinear system modeling a binary mixture of solids with frictional dissipation mechanism acting only on the elastic equation and subjected to nonlinear source term. The coupling gives new contributions to the theory associated with nonlinear dynamics of partially damped semilinear systems of a binary mixture of solids. Using the quasi-stability methods, we prove the existence of a smooth finite-dimensional global attractor irrespective of the wave speeds of the system. Moreover, we establish the existence of exponential attractors.

2000 Mathematics Subject Classifications:

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Additional information

Funding

M. M. Freitas thanks the CNPq for financial support [grant number 313081/2021-2]. T. A. Apalara extends his appreciation to the University of Hafr Al-Batin (UHB) for the continuous support. A. J. A. Ramos thanks the CNPq for financial support [grant number 310729/2019-0].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,361.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.