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Identification of Mechanical Fracture Parameters of Alkali-Activated Slag Based Composites During Specimens Ageing
Hana Simonova, Barbara Kucharczykova, Martin Lipowczan, David Lehky, Vlastimil Bilek Jr., Dalibor Kocab
Transactions of the VSB - Technical University of Ostrava, Civil Engineering Series
2019, Volume 19, Issue 2, Pages 59-64
Doi: 10.35181/tces-2019-0021
The aim of the paper is to present the results of the experiment focused on the development of the mechanical fracture characteristics of alkali-activated slag (AAS) based composites within the time interval from 3 days to 2 years of ageing. Two AAS composites, which differed only in the presence of shrinkage reducing admixture (SRA), were prepared for the purpose of experiments. The composites were prepared using ground granulated blast furnace slag activated by water-glass with silicate modulus of 2.0, standardized quartzite sand with the particle grain size distribution of 0−2 mm, and water. Commercially produced SRA was added into the second mixture in an amount of 2 % by weight of slag. The test specimens were not protected from drying during the whole time interval and were stored in the laboratory at an ambient temperature of 21 ± 2 °C and relative humidity of 60 ± 10 %. The prism specimens made of the above-mentioned composites with nominal dimensions of 40 × 40 × 160 mm with the initial central edge notch were subjected to the fracture tests in a three-point bending configuration. The load F and displacement d (deflection in the middle of the span length) were continuously recorded during the fracture tests. The obtained F−d diagrams and specimen dimensions were used as input data for identification of parameters via the inverse analysis based on the artificial neural network, which aim is to transfer the fracture test response data to the desired material parameters. In this paper, the modulus of elasticity, tensile strength, and fracture energy values were identified and subsequently compared with values obtained based on the fracture test evaluation using the effective crack model and work-of-fracture method.
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