Analytical Model with Independent Control of Load–Displacement Curve Branches for Brittle Material Strength Prediction Using Pre-Peak Test Loads

Abstract

The relevance of problems related to the fracturing of engineering materials and structures will not decrease over time. Fracture mechanics methods continue to be developed, which, combined with numerical methods of computer modeling, are implemented in software packages. However, this is only one facet of the complex of actual problems related to modeling and analyzing the behavior of brittle materials. No less important are the problems of developing not only numerical, but also new analytical models. In this paper, analytical models of only one class are considered, the distinguishing feature of which is that they describe the full load–strain curve using only one equation. However, the determination of model parameters requires tests for which the destruction of the test object is necessary, which may be unacceptable if controlled destruction is technically impossible or economically unreasonable. At the same time, in practice, it is possible to obtain values of stresses and strains caused by loads smaller than the peak load. Pre-peak loads can be used to predict strength using numerical methods, but it is desirable to have a suitable analytical model to extend the capabilities and to reduce the cost of applied research. Such a model was not found in the known literature, which motivated this work, which aims to modify the analytical model to predict strength and the full load–displacement (or stress–strain) curve using only pre-peak loading. This study is based on the analysis of known data and synthesis using mathematical modeling and fracture mechanics. The input data for the model do not include the particle size distribution and other physical and mechanical properties of the components of the material under study. These properties may remain unknown, but their influence is taken into account indirectly according to the “black box” methodology. Restrictions of the scope of the model are defined. The simulation results are consistent with experiments known from the literature.