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Published September 2023 | Published
Journal Article

Data-driven breakage mechanics: Predicting the evolution of particle-size distribution in granular media


This paper presents a model-free data-driven framework for breakage mechanics. In contrast with continuum breakage mechanics, the de facto approach for the macroscopic analysis of crushable granular media, the present framework does not require the definition of constitutive models and phenomenological assumptions, relying on material behavior that is known only through empirical data. For this purpose, we revisit the recent developments in model-free data-driven computing for history-dependent materials and extend the main ideas to materials with particle breakage. A systematic construction of the modeling framework is presented, starting from the closed-form representation of continuum breakage mechanics and arriving at alternative model-free representations. The predictive ability of the data-driven framework is highlighted and contrasted with continuum breakage mechanics on different boundary value problems. Moreover, an application to a real experimental test in crushable sand is presented, where the data is furnished by high-fidelity grain-scale simulations, indicating that the proposed framework provides an accurate prediction of the mechanics of crushable materials including the state of comminution.

Copyright and License

© 2023 Elsevier.


Partial support for this research was provided by US ARO funding through the Multidisciplinary University Research Initiative (MURI) Grant No. W911NF-19-1-0245. This support is gratefully acknowledged.


Jacinto Ulloa: Conceptualization, Methodology, Investigation, Writing – original draft. Anna Gorgogianni: Conceptualization, Methodology. Konstantinos Karapiperis: Conceptualization, Methodology. Michael Ortiz: Conceptualization, Methodology. José E. Andrade: Conceptualization, Methodology, Funding acquisition.

Conflict of Interest

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.

Additional details

December 18, 2023
December 18, 2023