Abstract
The paper deals with the experimental and numerical determination of mechanical fracture parameters of fine-grained composites based on the alkali-activated slag (AAS) at different ages of hardening. Two AAS composites, which differed only in the presence of shrinkage reducing admixture, were studied. The prismatic specimens with the nominal dimensions of 40 × 40 × 160 mm and initial central edge notch were subjected to fracture tests in a three-point bending configuration. The results of the fracture tests in the form load F versus deflection d diagrams were used as input data for the identification of parameters via the inverse analysis based on the artificial neural network whose aim is to transfer the fracture test response data to the desired material parameters. The modulus of elasticity, tensile strength, and fracture energy values were identified and subsequently compared with values obtained based on the direct fracture test evaluation using the effective crack model and work-of-fracture method.
Highlights
When modelling structures composed of quasi-brittle materials using non-linear fracture mechanics, one of the essential steps is to determine the values of material parameters, especially mechanical fracture parameters
This paper presents a methodology for the determination of mechanical fracture parameters of fine-grained composites
Determination of the mechanical fracture parameters of specimens made of fine-grained composite based on the alkali-activated slag with the addition of shrinkage reducing admixture was carried out at different ages of maturation
Summary
When modelling structures composed of quasi-brittle materials using non-linear fracture mechanics, one of the essential steps is to determine the values of material parameters, especially mechanical fracture parameters. Other reasons include assessing the quality of existing materials or the analysis of the behaviour of newly developed materials. The attention is paid to the resistance to crack initiation and propagation, rather than the maximum strength of the material. One venue for obtaining mechanical fracture parameters is to do it indirectly – based on a combination of fracture tests and inverse analysis [1, 2]. This paper presents a methodology for the determination of mechanical fracture parameters of fine-grained composites. Experimental data from three-point bending tests are used in the artificial neural network-based (ANN) inverse analysis method [3]
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