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A machine learning based sensitivity analysis of the GTN da..:
Paermentier, Benoît
;
Debruyne, Dimitri
;
Talemi, Reza
International Journal of Fracture. 227 (2021) 1 - p. 111-132 , 2021
Link:
https://doi.org/10.1007/s10704-020-00499-3
RT Journal T1
A machine learning based sensitivity analysis of the GTN damage parameters for dynamic fracture propagation in X70 pipeline steel
UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_s10704-020-00499-3&Exemplar=1&LAN=DE A1 Paermentier, Benoît A1 Debruyne, Dimitri A1 Talemi, Reza PB Springer Science and Business Media LLC YR 2021 SN 0376-9429 SN 1573-2673 JF International Journal of Fracture VO 227 IS 1 SP 111 OP 132 LK http://dx.doi.org/https://doi.org/10.1007/s10704-020-00499-3 DO https://doi.org/10.1007/s10704-020-00499-3 SF ELIB - SuUB Bremen
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