Abstract

In this work an anisotropic material model at finite strains with nonlinear mixed (isotropic and kinematic) hardening is used for the identification of the hardening parameters of sheet steel. The algorithmic system is thereby reduced to a single equation return mapping. For the identification, a cruciform specimen is loaded biaxially in an alternating shear test to provoke the kinematic hardening behavior and prevent the sheet from buckling. The material parameters are found through an optimization strategy by comparing the deformation field from the experiment to that from a finite element (FE) simulation. The resulting cost function is minimized by means of a gradient-based method.

Abstract

An optimization method to identify the material parameters of composite structures using an inverse method is proposed. This methodology compares experimental results with their numerical reproduction using the finite element method in order to obtain an estimation of the error between the results. This error estimation is then used by an evolutionary optimizer to determine, in an iterative process, the value of the material parameters which result in the best numerical fit. The novelty of the method is in the coupling between the simple genetic algorithm and the mixing theory used to numerically reproduce the composite behavior. The methodology proposed has been validated through a simple example which illustrates the exploitability of the method in relation to the modeling of damaged composite structures.

Abstract

Magnetorheological (MR) dampers have received special attention as semi-active devices for mitigation of structural vibrations. Because of the inherent nonlinearity of these devices, it is difficult to obtain a reasonable mathematical inverse model. This paper is concerned with two related concepts. On one hand, it presents a new inverse model of MR dampers based on the normalized Bouc–Wen model. On the other hand, it considers a hybrid seismic control system for building structures, which combines a class of passive nonlinear base isolator with a semi-active control system. In this application, the MR damper is used as a semi-active device in which the voltage is updated by a feedback control loop. The management of MR dampers is performed in a hierarchical way according to the desired control force, the actual force of the dampers and its capacity to react. The control is applied to a numerical three-dimensional benchmark problem which is used by the structural control community as a state-of-the-art model for numerical experiments of seismic control attenuation. The performance indices show that the proposed semi-active controller behaves satisfactorily.

Abstract

Magnetorheological (MR) dampers are devices that can be used for vibration reduction in structures. However, to use these devices in an effective way, a precise modeling is required. In this sense, in this paper we consider a modified parameter identification method of large-scale magnetorheological dampers which are represented using the normalized Bouc–Wen model. The main benefit of the proposed
identification algorithm is the accuracy of the parameter estimation. The validation of the parameter identification method has been carried out using a black box model of an MR damper in a smart base-isolated benchmark building. Magnetorheological dampers are used in this numerical platform both as isolation bearings as well as semi-active control devices.

Abstract

A modular computational framework for the identification of friction parameters in metal machining applications is presented. Numerical simulation of such processes using mesh-based techniques (usually) necessitates the re-meshing procedure, which is time-consuming and hard to parallelize. Therefore, the present framework synthesizes the advantages of mesh-free methods with GPU parallel computing, offering an efficient tool for the optimization procedures in thermomechanical modeling of cutting problems. The proposed approach employs an inverse method to determine the unknown coefficients of a temperature-dependent friction model in high-speed metal cutting. We found good agreement between the numerical results and experimental data through a quantitative-qualitative comparison.

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