In this article, we present a proposition of a model of the compressive behaviour of open- -cell aluminium with relation to the material apparent density. The research was based on experimental data from uniaxial compression tests conducted for two sample lots. These results were analysed with the use of neural networks in a specially designed algorithm. The main criterion for choosing a satisfactory approximation was mean absolute relative error MARE<5%. As a result of the analysis, the sought relation was extracted and is presented as a proposition of a new ANN model of the compressive stress-strain relationship for aluminium sponge.
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The paper presents compression test results of self-made open-cell aluminium which was produced by the investment casting method. Two groups of samples were studied: prototype samples containing some structural imperfections (apparent density 0.485 g/cm3 ) and regular samples without visible mistakes (apparent density 0.312 g/cm3 ). Performed experimental research covered quasi-static compression tests with one hysteresis loop. Based on experimental results, new measures to help material characterisation were proposed: instant and average loop secant gradients (E**inst.sec and E**av.inst.sec) and average linear loop gradient (E**av.lin).
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