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Methodology to estimate the minimum number of experiments and key microstructural parameters in macroscopic strength properties evaluation
Author(s) -
Gitman I. M.,
Gitman M. B.,
Stolbov V. Yu.,
Batin S. E.,
Boyarshinov D. A.
Publication year - 2019
Publication title -
zamm ‐ journal of applied mathematics and mechanics / zeitschrift für angewandte mathematik und mechanik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 51
eISSN - 1521-4001
pISSN - 0044-2267
DOI - 10.1002/zamm.201800259
Subject(s) - experimental data , macro , materials science , position (finance) , key (lock) , computer science , biological system , mathematics , statistics , computer security , finance , economics , programming language , biology
A novel methodology, based on the theory of fuzzy sets, to obtain materials with pre‐defined sets of strength properties has been analysed from the position of identifying the necessary and sufficient number of experiments needed to predict these macro characteristics and establishing which micro parameters significantly influence the macroscale results. The procedure to estimate, with a user‐defined degree of accuracy, the minimum number of experiments and significant micro parameters has been tested and verified using experimental data, obtained from digital images of material microsections under different heat treatment conditions while analysing strength properties of reinforcing steel. The results confirm the possibility of using the developed methodologies for the performance properties evaluation of materials based on the minimum number of experiments and identification of the key grain‐phase parameters.