PSI - Issue 37

Yulia Pirogova et al. / Procedia Structural Integrity 37 (2022) 1049–1056 Yulia Pirogova / Structural Integrity Procedia 00 (2021) 000 – 000

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Table 3. Values of the effective Young's modulus obtained during the FE analysis.

A p E , MPa

Elastic modulus derived from FE analysis,

Structure description

a=5 mm , N=4

1318.11

a=10 mm , N=32

1355.74

a=15 mm , N=84

1394.81

a=20 mm , N=195

1400.94

a=25 mm , N=368

1409.98

a=30 mm , N=663

1415.49

7. Conclusion In this paper the effect of voids shape on mechanical characteristics and morphological properties of heterogeneous structures was investigated. Additively manufactured heterogeneous samples made of polystyrene with disjoint pores of various shapes were studied. Multipoint statistical characteristics were used for analysis of the shape of inclusions in samples with different volume fractions. Also, the interrelation of such characteristics and elastic properties of heterogeneous media was investigated. It was revealed that the form of inclusions affects the correlation functions and effective elastic modulus of the porous samples. With an increase in the volume fraction of inclusions, the difference between the correlation functions obtained for different forms, as well as the value of the Young's modulus, decreases. It was also noted that the change in the spread between the maximum and minimum radii of spherical inclusions does not affect the value of the effective elastic modulus. For the considered RVE sample models with various size, the Young’s modulus converges to a certain value correspondingly to increasing of size of the samples, which allows to determine an optimal size for analysis. Acknowledgements The authors gratefully acknowledge financial support from the Government of the Russian Federation under the mega-grant program, contract no. 075-15-2021-578 of May 31, 2021, hosted by Perm National Research Polytechnic University. References Buryachenko, V.A., 2007. Micromehcanics of heterogenous materials, Micromechanics of Heterogeneous Materials. Springer US, Boston, MA. https://doi.org/10.1007/978-0-387-68485-7 Fullwood, D.T., Niezgoda, S.R., Adams, B.L., Kalidindi, S.R., 2010. Microstructure sensitive design for performance optimization. Prog. Mater. Sci. 55, 477 – 562. https://doi.org/10.1016/j.pmatsci.2009.08.002 Tashkinov, M.A., 2021. Multipoint stochastic approach to localization of microscale elastic behavior of random heterogeneous media. Comput. Struct. 249, 106474. https://doi.org/10.1016/j.compstruc.2020.106474 Tashkinov, M.A., 2014. Stochastic modelling of deformation process in elastoplastic composites with randomly located inclusions using high order correlation functions. PNRPU Mech. Bull. 2014, 163 – 185. https://doi.org/10.15593/perm.mech/2014.3.09 Torquato, S., 2002. Random Heterogeneous Materials, Computers and Mathematics with Applications. Zeman, J., Šejnoha, M., 2007. From random microstructures to representative volume elements. Model. S imul. Mater. Sci. Eng. 15, S325 – S335. https://doi.org/10.1088/0965-0393/15/4/S01