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Stochastic generation of virtual air pores in granular materials

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Abstract

A computational method is described for the generation of virtual air pores with randomized features in granular materials. The method is based on the creation of a stack of two dimensional stochastically generated domains of packed virtual aggregate particles that are converted to three dimensions and made to intersected with one another. The three dimensional structure that is created is then sampled with an algorithm that detects the void space left between the intersected particles, which corresponds to the air void volume in real materials. This allows the generation of a map of the previously generated three dimensional model that can be used to analyse the topology of the void channels. The isotropy of the samples is here discussed and analysed. The air void size distribution in all the virtual samples generated in this study is described with the Weibull distribution and the goodness of fit is successfully evaluated with the Kolmogorov–Smirnov test. The specific surface of the virtual samples is also successfully compared to that of real samples. The results show that a stochastic approach to the generation of virtual granular materials based only on geometric principles is feasible and provides realistic results.

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Acknowledgments

The authors thank the University of Nottingham for the financial support provided for the Ph.D. of Andrea Chiarelli. The Ph.D. studies of the first author are funded by the University of Nottingham (A. García new lecturer’s award, no grant number).

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Authors and Affiliations

  1. Nottingham Transportation Engineering Centre (NTEC), Faculty of Engineering, The University of Nottingham, University Park, Nottingham, NG7 2RD, UK

    A. Chiarelli, A. R. Dawson & A. García

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  1. A. Chiarelli
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  2. A. R. Dawson
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  3. A. García
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Correspondence to A. Chiarelli.

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Chiarelli, A., Dawson, A.R. & García, A. Stochastic generation of virtual air pores in granular materials. Granular Matter 17, 617–627 (2015). https://doi.org/10.1007/s10035-015-0585-x

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