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1	$Phase-field modeling of ductile fracture$ $Phase-field modeling of ductile fracture$ Material Type: Article	Phase-field modeling of ductile fracture Computational mechanics, 2015-05, Vol.55 (5), p.1017-1040 [Peer Reviewed Journal] Springer-Verlag Berlin Heidelberg 2015 ;COPYRIGHT 2015 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-015-1151-4 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
2	Material Type: Article	Prediction of aerodynamic flow fields using convolutional neural networks Computational mechanics, 2019-08, Vol.64 (2), p.525-545 [Peer Reviewed Journal] Springer-Verlag GmbH Germany, part of Springer Nature 2019 ;COPYRIGHT 2019 Springer ;Copyright Springer Nature B.V. 2019 ;Computational Mechanics is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-019-01740-0 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
3	Material Type: Article	Diffusion–reaction compartmental models formulated in a continuum mechanics framework: application to COVID-19, mathematical analysis, and numerical study Computational mechanics, 2020-11, Vol.66 (5), p.1131-1152 [Peer Reviewed Journal] The Author(s) 2020 ;The Author(s) 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01888-0 ;PMID: 32836602 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
4	$A review on phase-field models of brittle fracture and a new fast hybrid formulation$ $A review on phase-field models of brittle fracture and a new fast hybrid formulation$ Material Type: Article	A review on phase-field models of brittle fracture and a new fast hybrid formulation Computational mechanics, 2015-02, Vol.55 (2), p.383-405 [Peer Reviewed Journal] Springer-Verlag Berlin Heidelberg 2014 ;COPYRIGHT 2015 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-014-1109-y Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
5	Material Type: Article	Machine learning for metal additive manufacturing: predicting temperature and melt pool fluid dynamics using physics-informed neural networks Computational mechanics, 2021-02, Vol.67 (2), p.619-635 [Peer Reviewed Journal] Springer-Verlag GmbH Germany, part of Springer Nature 2021 ;COPYRIGHT 2021 Springer ;Springer-Verlag GmbH Germany, part of Springer Nature 2021. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01952-9 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
6	Material Type: Article	Assessment of supervised machine learning methods for fluid flows Theoretical and computational fluid dynamics, 2020-08, Vol.34 (4), p.497-519 [Peer Reviewed Journal] Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;COPYRIGHT 2020 Springer ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 0935-4964 ;EISSN: 1432-2250 ;DOI: 10.1007/s00162-020-00518-y Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
7	Material Type: Article	Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies of various shapes Theoretical and computational fluid dynamics, 2020-08, Vol.34 (4), p.367-383 [Peer Reviewed Journal] Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;COPYRIGHT 2020 Springer ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 0935-4964 ;EISSN: 1432-2250 ;DOI: 10.1007/s00162-020-00528-w Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
8	Material Type: Article	Bayesian-based predictions of COVID-19 evolution in Texas using multispecies mixture-theoretic continuum models Computational mechanics, 2020-11, Vol.66 (5), p.1055-1068 [Peer Reviewed Journal] Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01889-z ;PMID: 32836598 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
9	Material Type: Article	A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites Computational mechanics, 2019-08, Vol.64 (2), p.307-321 [Peer Reviewed Journal] Springer-Verlag GmbH Germany, part of Springer Nature 2018 ;COPYRIGHT 2019 Springer ;Copyright Springer Nature B.V. 2019 ;Computational Mechanics is a copyright of Springer, (2018). All Rights Reserved. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-018-1643-0 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
10	$A Bayesian estimation method for variational phase-field fracture problems$ $A Bayesian estimation method for variational phase-field fracture problems$ Material Type: Article	A Bayesian estimation method for variational phase-field fracture problems Computational mechanics, 2020-10, Vol.66 (4), p.827-849 [Peer Reviewed Journal] The Author(s) 2020 ;The Author(s) 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01876-4 ;PMID: 33029034 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
11	$A comparative review of peridynamics and phase-field models for engineering fracture mechanics$ $A comparative review of peridynamics and phase-field models for engineering fracture mechanics$ Material Type: Article	A comparative review of peridynamics and phase-field models for engineering fracture mechanics Computational mechanics, 2022-06, Vol.69 (6), p.1259-1293 [Peer Reviewed Journal] The Author(s) 2022 ;COPYRIGHT 2022 Springer ;The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-022-02147-0 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
12	Material Type: Article	A computational library for multiscale modeling of material failure Computational mechanics, 2014-05, Vol.53 (5), p.1047-1071 [Peer Reviewed Journal] Springer-Verlag Berlin Heidelberg 2013 ;COPYRIGHT 2014 Springer ;Computational Mechanics is a copyright of Springer, (2013). All Rights Reserved. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-013-0948-2 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
13	Material Type: Article	Dynamic and fluid–structure interaction simulations of bioprosthetic heart valves using parametric design with T-splines and Fung-type material models Computational mechanics, 2015-06, Vol.55 (6), p.1211-1225 [Peer Reviewed Journal] Springer-Verlag Berlin Heidelberg 2015 ;COPYRIGHT 2015 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-015-1166-x ;PMID: 26392645 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
14	Material Type: Article	Data-driven non-linear elasticity: constitutive manifold construction and problem discretization Computational mechanics, 2017-11, Vol.60 (5), p.813-826 [Peer Reviewed Journal] Attribution ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-017-1440-1 Digital Resources/Online E-Resources View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
15	Material Type: Book	Fractional Order Signal Processing: Introductory Concepts and Applications The Author(s) 2012 ;ISSN: 2191-530X ;ISBN: 3642231160 ;ISBN: 9783642231162 ;EISSN: 2191-5318 ;EISBN: 9783642231179 ;EISBN: 3642231179 ;DOI: 10.1007/978-3-642-23117-9 ;OCLC: 757338273 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
16	Material Type: Article	De-biasing the dynamic mode decomposition for applied Koopman spectral analysis of noisy datasets Theoretical and computational fluid dynamics, 2017-08, Vol.31 (4), p.349-368 [Peer Reviewed Journal] Springer-Verlag Berlin Heidelberg 2017 ;COPYRIGHT 2017 Springer ;Theoretical and Computational Fluid Dynamics is a copyright of Springer, 2017. ;ISSN: 0935-4964 ;EISSN: 1432-2250 ;DOI: 10.1007/s00162-017-0432-2 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
17	Material Type: Article	A general phase-field model for fatigue failure in brittle and ductile solids Computational mechanics, 2021-05, Vol.67 (5), p.1431-1452 [Peer Reviewed Journal] The Author(s) 2021 ;COPYRIGHT 2021 Springer ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-021-01996-5 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
18	Material Type: Article	Is it safe to lift COVID-19 travel bans? The Newfoundland story Computational mechanics, 2020-11, Vol.66 (5), p.1081-1092 [Peer Reviewed Journal] Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01899-x ;PMID: 32904431 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
19	Material Type: Article	A splitting algorithm for dual monotone inclusions involving cocoercive operators Advances in computational mathematics, 2013-04, Vol.38 (3), p.667-681 [Peer Reviewed Journal] Springer Science+Business Media, LLC. 2011 ;ISSN: 1019-7168 ;EISSN: 1572-9044 ;DOI: 10.1007/s10444-011-9254-8 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
20	Material Type: Article	A physics-informed neural network technique based on a modified loss function for computational 2D and 3D solid mechanics Computational mechanics, 2023-03, Vol.71 (3), p.543-562 [Peer Reviewed Journal] The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;COPYRIGHT 2023 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-022-02252-0 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by

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Results 1 - 20 of 3,168 for All Library Resources

Springer-Verlag Berlin Heidelberg 2015 ;COPYRIGHT 2015 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-015-1151-4

Springer-Verlag GmbH Germany, part of Springer Nature 2019 ;COPYRIGHT 2019 Springer ;Copyright Springer Nature B.V. 2019 ;Computational Mechanics is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-019-01740-0

The Author(s) 2020 ;The Author(s) 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01888-0 ;PMID: 32836602

Springer-Verlag Berlin Heidelberg 2014 ;COPYRIGHT 2015 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-014-1109-y

Springer-Verlag GmbH Germany, part of Springer Nature 2021 ;COPYRIGHT 2021 Springer ;Springer-Verlag GmbH Germany, part of Springer Nature 2021. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01952-9

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;COPYRIGHT 2020 Springer ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 0935-4964 ;EISSN: 1432-2250 ;DOI: 10.1007/s00162-020-00518-y

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;COPYRIGHT 2020 Springer ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 0935-4964 ;EISSN: 1432-2250 ;DOI: 10.1007/s00162-020-00528-w

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01889-z ;PMID: 32836598

The Author(s) 2020 ;The Author(s) 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01876-4 ;PMID: 33029034

Springer-Verlag Berlin Heidelberg 2013 ;COPYRIGHT 2014 Springer ;Computational Mechanics is a copyright of Springer, (2013). All Rights Reserved. ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-013-0948-2

Springer-Verlag Berlin Heidelberg 2015 ;COPYRIGHT 2015 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-015-1166-x ;PMID: 26392645

Attribution ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-017-1440-1

The Author(s) 2012 ;ISSN: 2191-530X ;ISBN: 3642231160 ;ISBN: 9783642231162 ;EISSN: 2191-5318 ;EISBN: 9783642231179 ;EISBN: 3642231179 ;DOI: 10.1007/978-3-642-23117-9 ;OCLC: 757338273

Springer-Verlag Berlin Heidelberg 2017 ;COPYRIGHT 2017 Springer ;Theoretical and Computational Fluid Dynamics is a copyright of Springer, 2017. ;ISSN: 0935-4964 ;EISSN: 1432-2250 ;DOI: 10.1007/s00162-017-0432-2

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;COPYRIGHT 2020 Springer ;ISSN: 0178-7675 ;EISSN: 1432-0924 ;DOI: 10.1007/s00466-020-01899-x ;PMID: 32904431

Springer Science+Business Media, LLC. 2011 ;ISSN: 1019-7168 ;EISSN: 1572-9044 ;DOI: 10.1007/s10444-011-9254-8

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