An examination of the size effect in quasi-brittle materials using a bond-based peridynamic model
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Hobbs, M., Dodwell, T., Hattori, G., & Orr, J. (2022). An examination of the size effect in quasi-brittle materials using a bond-based peridynamic model. Engineering Structures https://doi.org/10.1016/j.engstruct.2022.114207
This paper examines the size effect in quasi-brittle materials using a three-dimensional bond-based peridynamic model. This is the first time that the capability of a peridynamic model to capture the size effect in quasi-brittle materials has been examined. Correctly reproducing the size effect is an essential check on the validity of any computational model and it is demonstrated that a bond-based peridynamic model can accurately capture the failure stress of geometrically identical structures over a range of sizes. A systematic examination of geometrically similar notched and unnotched beams provides new insights into the predictive capabilities of the model, and mode I and mixed-mode problems are considered to examine the generality of the model. The model is validated using published experimental data, and the predictive accuracy is equivalent, if not superior, to well-established numerical methods whilst offering several benefits that justify further research and development. This study provides evidence that the length scale in a peridynamic model is a numerical parameter and not a material property.
This work was funded by the UK Engineering and Physical Sciences Research Council (EPSRC), grant no. EP/L016095/1 - University of Cambridge Centre for Doctoral Training in Future Infrastructure and Built Environment, and grant no. EP/M020908/1 - Concrete Modelled using Random Elements. This work was performed using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/P020259/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). TD and MH are funded through a Turing AI Fellowship (2TAFFP\100007).
Engineering and Physical Sciences Research Council (EP/M020908/1)
Engineering and Physical Sciences Research Council (EP/L016095/1)
Engineering and Physical Sciences Research Council (EP/P020259/1)
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External DOI: https://doi.org/10.1016/j.engstruct.2022.114207
This record's URL: https://www.repository.cam.ac.uk/handle/1810/336353
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Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/