The paper delivers an analytical model for prediction of peak force in concrete specimens loaded in bending (both notched and unnotched). The model is capable of predicting the statistics of the peak force of beams by computing the extreme values…
The paper delivers an analytical model for prediction of peak force in concrete specimens loaded in bending (both notched and unnotched). The model is capable of predicting the statistics of the peak force of beams by computing the extreme values of sliding averages of random strength field. Local strength of the specimen is modelled by a stationary isotropic random field with Gaussian distribution and squared-exponential autocorrelation function. The averaging operation represents the progressive loss in material integrity and the associated stress redistribution that takes place prior to reaching the peak load. Once the (linear) averaging process is performed analytically, the resulting random field of averaged strength is assumed to represent a series of representative volume elements (RVEs) and the global strength is found by solving for the minimum of such an effective strength field. All these operations can be written analytically and there are only four free parameters: the three dimensions of the averaging volume (RVE) and the length of the final weakest-link chain. The model is verified using detailed numerical computations of notched and unnotched concrete beamssimulated by mesoscale discrete simulations of concrete fracture performed with probabilistic distributions of model parameters. The numerical model represents material randomness both by random locations of the largest aggregates and by random fluctuations of material parameters via a homogeneous random field.