0563211 20230316105815.620221101235959.9 85127132123 000893681300059 10.1007/978-3-030-97549-4_59 9 s. P cav_un_epca*0556337978-3-030-97548-70302-9743515-523ChamSpringer2022LirkovI.MargenovS. Contact problems Tresca friction Semismooth* Newton method Finite elements Matlab implementation cav_un_auth*0319636 Gfrerer H. AT cav_un_auth*0101173 Outrata Jiří UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0292941 Valdman Jan UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2022/MTR/valdman-0563211.pdf GF19-29646L GA ČR CZ cav_un_auth*0385134 An equilibrium of a linear elastic body subject to loading and satisfying the friction and contact conditions can be described by a variational inequality of the second kind and the respective discrete model attains the form of a generalized equation. To its numerical solution we apply the semismooth* Newton method by Gfrerer and Outrata (2019) in which, in contrast to most available Newton-type methods for inclusions, one approximates not only the single-valued but also the multi-valued part. This is performed on the basis of limiting (Morduchovich) coderivative. In our case of the Tresca friction, the multi-valued part amounts to the subdifferential of a convex function generated by the friction and contact conditions. The full 3D discrete problem is then reduced to the contact boundary. Implementation details of the semismooth* Newton method are provided and numerical tests demonstrate its superlinear convergence and mesh independence. cav_un_auth*0429411 International Conference on Large-Scale Scientific Computing /13./ 20210607 20210611 Sozopol BG BA 10000 10100 10101 2023 PR RVO:67985556 https://hdl.handle.net/11104/0335249 S 3+4 Proceedings Paper Computer Science Interdisciplinary Applications|Computer Science Theory Methods|Operations Research Management Science|Mathematics Applied 499 0.249 24.53 1.2 80471 Q3 2022 85127132123 SCOPUS PUBMED 000893681300059 WOS cav_un_epca*0556337 Large-Scale Scientific Computing 978-3-030-97548-7 0302-9743 515 523 Cham Springer 2022 1. Lecture Notes in Computer Science 13127 Lirkov I. 340 Margenov S. 340