Carrara, P. and De Lorenzis, L. and Stainier, L. and Ortiz, M. (2020) Data-driven fracture mechanics. Computer Methods in Applied Mechanics and Engineering, 372 . Art. No. 113390. ISSN 0045-7825. https://resolver.caltech.edu/CaltechAUTHORS:20200910-100202726
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Abstract
We present a new data-driven paradigm for variational brittle fracture mechanics. The fracture-related material modeling assumptions are removed and the governing equations stemming from variational principles are combined with a set of discrete data points, leading to a model-free data-driven method of solution. The solution at a given load step is identified as the point within the data set that best satisfies either the Kuhn–Tucker conditions stemming from the variational fracture problem or global minimization of a suitable energy functional, leading to data-driven counterparts of both the local and the global minimization approaches of variational fracture mechanics. Both formulations are tested on different test configurations with and without noise and for Griffith and R-curve type fracture behavior.
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| Additional Information: | © 2020 Elsevier B.V. Received 20 May 2020, Revised 17 August 2020, Accepted 18 August 2020, Available online 7 September 2020. P. Carrara gratefully acknowledges the financial support of the German Research Foundation (DFG) through the Fellowship Grant CA 2359/1. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. | ||||||
| Group: | GALCIT | ||||||
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| Subject Keywords: | Data-driven computational mechanics; Fracture mechanics; Model-free; Numerical modeling | ||||||
| Record Number: | CaltechAUTHORS:20200910-100202726 | ||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20200910-100202726 | ||||||
| Official Citation: | P. Carrara, L. De Lorenzis, L. Stainier, M. Ortiz, Data-driven fracture mechanics, Computer Methods in Applied Mechanics and Engineering, Volume 372, 2020, 113390, ISSN 0045-7825, https://doi.org/10.1016/j.cma.2020.113390. (http://www.sciencedirect.com/science/article/pii/S0045782520305752) | ||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
| ID Code: | 105308 | ||||||
| Collection: | CaltechAUTHORS | ||||||
| Deposited By: | Tony Diaz | ||||||
| Deposited On: | 10 Sep 2020 18:17 | ||||||
| Last Modified: | 10 Sep 2020 18:17 |
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