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To successfully guarantee the proper durability and serviceability of asphalt pavements, it is crucial to investigate asphalt mixtures’ performance and to design an accurate model to predict their mechanical behaviour. In Machine Learning, Artificial Neural Networks (ANNs) consist of a set of layered and interconnected artificial neurons capable of learning a complex function that maps the input to the target output. This study is specifically aimed at their implementation within the field of pavement engineering. The paper thoroughly discusses the development of an ANN-based methodology capable of predicting the stiffness modulus of an asphalt mixture (AM). The AM under investigation was prepared with spilite aggregate, a 50/70 penetration grade bitumen, and limestone filler. The volumetric properties of each specimen were first determined, and then the sequence of a 4-Point Bending Test was carried out under different conditions. Four testing temperatures (0, 10, 20, 30 °C) and eleven loading frequencies (0.1, 1, 2, 3, 5, 10, 15, 20, 30 and 50 Hz) were selected to investigate the asphalt mixture's mechanical behaviour. The resulting stiffness moduli represented the output of the designed neural model. Prediction accuracy was evaluated utilizing several goodness-of-fit metrics, and the results of this feasibility study proved to be very encouraging. They are certainly limited to the asphalt mixture under investigation. However, the high level of accuracy suggests that trained on a larger dataset, the developed methodology could allow the AMs’ mechanical behaviour to be predicted without the need to carry out the conventional tests that are usually expensive and time-consuming.

This paper discusses different aspects of analytical and numerical modelling of the buckling resistance of welded I-section columns subjected to axial compression. The section considered is of class 1 that implies no local buckling affecting the column performance. The proposed analytical formulation of the buckling resistance is based on the so-called Marchant-Rankine's-Murzewski approach (M-R-M approach). The model proposed is of a 2D type and is a simplification of the 3D one that has recently been presented by the authors. The parameters of equivalent stress-strain model of the postwelding steel are calibrated in two stages of the best fit approximation procedure and with use of numerical results of the finite element simulation of the buckling resistance. In the first stage, the postyielding inelastic tangent stiffness parameter ξE,eff is evaluated with fixed value of the first yield parameter ψeff= ψcom. A target of the second stage is to assign the best fit value of the first yield parameter ψeff and the imperfection factor n that allows for accounting the effect of geometric imperfections.

This paper analyzes the influence of geometrical and material imperfections on the buckling resistance of welded I-section columns subjected to axial compression through numerical and analytical models. The paper is divided into two parts. The first part recalls a FEM parametric study of members under compression taking into account different slenderness ratios, as well as different amplitudes of initial crookedness and different values of postwelding residual stresses. The formulation of analytical approach is the main issue of the second part of the paper. Analytical formulation of the buckling resistance is based on a statistical hypothesis of the minima value approach, called the Marchant-Rankine’s-Murzewski approach (M-R-M). Calibration of imperfection factors included in the analytical formulation is made using the results of FEM simulations performed in the first stage of research investigations.

In the presented paper the local instabilities occurring in compression test of perforated thin-walled bars of low slenderness are observed using digital image correlation system ARAMIS. The tested samples slenderness is so low, that from theoretical point of view we are dealing with compression tests of some perforated shells. The samples are made from typical low carbon steel, which has to be treated as elasto-plastic material. Because of that, the final geometry of the sample (after unloading) is also analysed giving a good data for calibration of the theory of elasto-plasticity for large deformations. In analysed cases the total strain values are not exceptionally large, while local rotation (and permanent deformations) have significant values.

In the paper two classes of poly-convex stored energy functions for transversally isotropic hyper-elastic materials have been proposed. Within these classes, a simplified model of hyper-elastic materials with an isotropic matrix reinforced with fibre family was derived and implemented in finite element software ABAQUS/Standard. The two numerical examples proving correctness of the implementation and showing its positive physical features are presented.

The paper deals with the problem of buckling resistance determination in case of perforated thin-walled elements. Depending on element slenderness the limit load in compression mode may be determined taking into account elastic (LBA analysis), elasto-plastic and plastic material properties (GMNA analysis). The limit load value is determined on the basis of thin-walled open section beam theory in case of elastic buckling and using Johnson-Ostenfeld approximation for elasto-plastic buckling. Obtained results are compared with finite element solutions derived using shell modelling and large deformation theory with Huber-Mises elasto-plasticity constitutive model without any geometrical imperfections. Some results of the carried out experiments are also shown.