caa a22 4500 606166866 CHVBK 20210128100700.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s10665-014-9757-7 doi (NATIONALLICENCE)springer-10.1007/s10665-014-9757-7 Modelling of tear propagation and arrest in fibre-reinforced soft tissue subject to internal pressure [Elektronische Daten] [Lei Wang, Steven Roper, X. Luo, N. Hill] The prediction of soft-tissue failure may yield a better understanding of the pathogenesis of arterial dissection and help to advance diagnostic and therapeutic strategies for the treatment of this and other diseases and injuries involving the tearing of soft tissue, such as aortic dissection. In this paper, we present computational models of tear propagation in fibre-reinforced soft tissue undergoing finite deformation, modelled by a hyperelastic anisotropic constitutive law. We adopt the appropriate energy argument for anisotropic finite strain materials to determine whether a tear can propagate when subject to internal pressure loading. The energy release rate is evaluated with an efficient numerical scheme that makes use of adaptive tear lengths. As an illustration, we present the calculation of the energy release rate for a two-dimensional strip of tissue with a pre-existing tear of length $$a$$ a under internal pressure $$p$$ p and show the effect of fibre orientation. This calculation allows us to locate the potential bifurcation to tear propagation in the $$(a,p)$$ ( a , p ) plane. The numerical predictions are verified by analytical solutions for simpler cases. We have identified a scenario of tear arrest, which is observed clinically, when the surrounding connective tissues are accounted for. Finally, the limitations of the models and further directions for applications are discussed. Springer Science+Business Media Dordrecht, 2015 Arterial dissection nationallicence Energy release rate nationallicence Finite-element analysis nationallicence HGO model nationallicence Soft tissue nationallicence Tear propagation and arrest nationallicence Wang Lei School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut Roper Steven School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut Luo X. School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut Hill N. School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut Journal of Engineering Mathematics Springer Netherlands 95/1(2015-12-01), 249-265 0022-0833 95:1<249 2015 95 10665 https://doi.org/10.1007/s10665-014-9757-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10665-014-9757-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Lei School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut NATIONALLICENCE 700 1- Roper Steven School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut NATIONALLICENCE 700 1- Luo X. School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut NATIONALLICENCE 700 1- Hill N. School of Mathematics and Statistics, University of Glasgow, G12 8QW, Glasgow, UK aut NATIONALLICENCE 773 0- Journal of Engineering Mathematics Springer Netherlands 95/1(2015-12-01), 249-265 0022-0833 95:1<249 2015 95 10665