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      • ED-FEM multi-scale computation procedure for localized failure

        Rukavina, Ivan,Ibrahimbegovic, Adnan,Do, Xuan Nam,Markovic, Damijan Techno-Press 2019 Coupled systems mechanics Vol.8 No.2

        In this paper, we present a 2D multi-scale coupling computation procedure for localized failure. When modeling the behavior of a structure by a multi-scale method, the macro-scale is used to describe the homogenized response of the structure, and the micro-scale to describe the details of the behavior on the smaller scale of the material where some inelastic mechanisms, like damage or plasticity, can be defined. The micro-scale mesh is defined for each multi-scale element in a way to fit entirely inside it. The two scales are coupled by imposing the constraint on the displacement field over their interface. An embedded discontinuity is implemented in the macro-scale element to capture the softening behavior happening on the micro-scale. The computation is performed using the operator split solution procedure on both scales.

      • Material model for load rate sensitivity

        Kozar, Ivica,Ibrahimbegovic, Adnan,Rukavina, Tea Techno-Press 2018 Coupled systems mechanics Vol.7 No.2

        This work presents a novel model for analysis of the loading rate influence onto structure response. The model is based on the principles of nonlinear system dynamics, i.e., consists of a system of nonlinear differential equations. In contrast to classical linearized models, this one comprises mass and loading as integral parts of the model. Application of the Kelvin and the Maxwell material models relates the novel formulation to the existing material formulations. All the analysis is performed on a proprietary computer program based on Wolfram Mathematica. This work can be considered as an extended proof of concept for the application of the nonlinear solid model in material response to dynamic loading.

      • Inverse model for pullout determination of steel fibers

        Kozar, Ivica,Malic, Neira Toric,Rukavina, Tea Techno-Press 2018 Coupled systems mechanics Vol.7 No.2

        Fiber-reinforced concrete (FRC) is a material with increasing application in civil engineering. Here it is assumed that the material consists of a great number of rather small fibers embedded into the concrete matrix. It would be advantageous to predict the mechanical properties of FRC using nondestructive testing; unfortunately, many testing methods for concrete are not applicable to FRC. In addition, design methods for FRC are either inaccurate or complicated. In three-point bending tests of FRC prisms, it has been observed that fiber reinforcement does not break but simply pulls out during specimen failure. Following that observation, this work is based on an assumption that the main components of a simple and rather accurate FRC model are mechanical properties of the concrete matrix and fiber pullout force. Properties of the concrete matrix could be determined from measurements on samples taken during concrete production, and fiber pullout force could be measured on samples with individual fibers embedded into concrete. However, there is no clear relationship between measurements on individual samples of concrete matrix with a single fiber and properties of the produced FRC. This work presents an inverse model for FRC that establishes a relation between parameters measured on individual material samples and properties of a structure made of the composite material. However, a deterministic relationship is clearly not possible since only a single beam specimen of 60 cm could easily contain over 100000 fibers. Our inverse model assumes that the probability density function of individual fiber properties is known, and that the global sample load-displacement curve is obtained from the experiment. Thus, each fiber is stochastically characterized and accordingly parameterized. A relationship between fiber parameters and global load-displacement response, the so-called forward model, is established. From the forward model, based on Levenberg-Marquardt procedure, the inverse model is formulated and successfully applied.

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