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Quarterly of Applied Mathematics

Quarterly of Applied Mathematics

Online ISSN 1552-4485; Print ISSN 0033-569X

   
 
 

 

Construction of boundary conditions for hyperbolic relaxation approximations II: Jin-Xin relaxation model


Authors: Xiaxia Cao and Wen-An Yong
Journal: Quart. Appl. Math. 80 (2022), 787-816
MSC (2020): Primary 35L50
DOI: https://doi.org/10.1090/qam/1627
Published electronically: May 25, 2022
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Abstract: This is our second work in the series about constructing boundary conditions for hyperbolic relaxation approximations. The present work is concerned with the one-dimensional linearized Jin-Xin relaxation model, a convenient approximation of hyperbolic conservation laws, with non-characteristic boundaries. Assume that proper boundary conditions are given for the conservation laws. We construct boundary conditions for the relaxation model with the expectation that the resultant initial-boundary-value problems are approximations to the given conservation laws with the boundary conditions. The constructed boundary conditions are highly non-unique. Their satisfaction of the generalized Kreiss condition is analyzed. The compatibility with initial data is studied. Furthermore, by resorting to a formal asymptotic expansion, we prove the effectiveness of the approximations.


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Additional Information

Xiaxia Cao
Affiliation: Department of Mathematical Sciences, Tsinghua University, Beijing 100084, People’s Republic of China
ORCID: 0000-0002-7423-4454
Email: caoxx18@mails.tsinghua.edu.cn

Wen-An Yong
Affiliation: Department of Mathematical Sciences, Tsinghua University, Beijing 100084, People’s Republic of China —and—Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China
Email: wayong@tsinghua.edu.cn

Received by editor(s): March 12, 2022
Received by editor(s) in revised form: April 23, 2022
Published electronically: May 25, 2022
Additional Notes: This research was supported by National Natural Science Foundation of China (grant No. 12071246) and by National Key R&D Program of China (grant No. 2021YFA0719200)
Article copyright: © Copyright 2022 Brown University