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.
In this contribution an original concept of stochastic stability (P‐stability), formulated here to represent realistic stochastic nature of materials, is employed for stability analysis of material performance characteristics. Stochasticity in materials can be related, for example, to manufacturing processes, potential treatment of material, or properties of raw materials. On the other hand, performance characteristics, obtained through the novel fuzzy sets based multi‐scale methodology, are also of stochastic nature. The particular strength of this newly developed P‐stability, is its ability to analyse not only individual characteristics, but also multiple characteristics simultaneously. This methodology also allows to estimate and quantify an actual accuracy of obtained characteristics.
The role of the collective behavior of defect ensembles at the crack tip and the laws of fatigue crack propagation in aluminum-magnesium alloy AMg6 have been studied under conditions of symmetric tension-compression gigacycle loading at 20 kHz using ultrasonic fatigue testing machine Shimadzu USF2000. 3D New View 5010 interferometer profiler high resolution data of defect induced roughness in the crack process zone under fatigue crack path revealed the existence of two characteristic scales: the scale of the process zone and the correlation length that is the scale when the correlated behavior of defect induced roughness has started. A mathematical model allowing the assessment of fatigue resistance of functional metal material on the basis of the analysis of loading parameters and the resulting fracture surface is developed. Analyzing the image by means of the wavelet-analysis, the basis parameters of a destruction surface are allocated. Based on the analysis of the destruction surface characteristics and the corresponding loading parameters, the fatigue life of the functional material is evaluated. For the solution of the problem, the elements of the fuzzy sets theory are used.
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