Abstract

Nodular cast iron is a Fe-C-Si metallic alloy whose microstructure consists of a matrix, composed in general of ferrite and pearlite, with graphite nodules embedded in it. Owing to its microscopical heterogeneity, the material response is governed by the properties, morphology and typology of the phases involved. This work reports on the evaluation of the elastic properties, i.e., Youngs modulus and Poissons ratio, of an equivalent homogeneous material that characterizes the macroscopic response of a nodular cast iron. Asymptotic homogenization is used to this end. This approach is applied to both 3D and 2D multiparticle cells simulated via the finite element method. Two different physically and geometrically-based criteria are considered to estimate the representative volume element (RVE), where the size of the RVE is found to be sensitive to the chosen criterion. The main microstructural features are obtained from a computational simulation of the solidification process of the material. The numerical predictions computed for the 3D and 2D cases are compared and discussed in terms of the resulting elastic properties. It is observed that the models employing 3D multiparticle cells require lower RVE sizes than the corresponding 2D models, where the latter present a stiffer elastic response.

Abstract

Cutting-edge methods in the computational analysis of structures have been developed over the last decades. Such modern tools are helpful to assess the safety of existing buildings. Multi-scale techniques have been proposed to combine the accuracy of micro- modelling and the computational efficiency of macro-modelling. Machine-learning tools have been utilized successfully to train specific models by feeding big source data from different fields, e.g. autonomous driving, face recognition, etc. This research proposes a continuous nonlinear material law that can reproduce data from micro-scale analysis. The proposed method is based on a machine-learning tool that links the two scales of the analysis by training a macro-model smeared damage constitutive law through benchmark data from numerical tests derived from micro-models.

Abstract

Among the numerous strategies available for suppressing/decreasing delamination of laminated composite materials, the current work is focused on the tufting process. A literature study is carried out to underscore the advantages of this technology over alternative manufacturing techniques.  The current paper presents with a mesomechanical composite modeling approach, based on a MMF (MicroMechanics of Failure) micromechanics scheme.  The type of composite material analyzed here is a conventional ply laminate tufted along its thickness.  In terms of mesomechanics, a new unit cell is described and formulated. In order to assess the accuracy of the current approach, three theory-experiment correlations studies have been carried out, the results obtained being quite accurate.