Abstract

This paper presents the results of finite element simulations made on a bent pipe subjected to an in-plane variable cyclic displacement combined with internal pressure. Special emphasis is put on the capacity of the model to illustrate different failure modes depending on the internal pressure applied on the pipe. The results of the numerical analyses will be compared to experimental ones. The constitutive model used for the simulation of Ultra Low Cycle Fatigue (ULCF) loading and the hardening–softening law used are only briefly touched upon. The monotonic behavior of a large diameter pipe, as obtained from the constitutive model proposed, is also shown and compared to experimental results under two different loading conditions. The total axial load at failure for this case resulted in less than 10% error as compared to the experiments. Regarding the ULCF in-plane bending simulations conducted on a 16-in. 90º elbow, the results were in good agreement with the experimental test in terms of force–displacement hysteresis loops and total fatigue life of the specimen. An analysis of the dependence of the failure mode to the internal pressure applied has been conducted, showing that the formulation is capable of obtaining both habitual failure types.

Abstract

This paper presents a plastic-damage formulation and a new isotropic hardening law, based on the Barcelona plastic damage model initially proposed by Lubliner et al. (1989) [1], which is capable of predicting steel failure due to Ultra Low Cycle Fatigue (ULCF). This failure mechanism is obtained when the material is subjected to cyclic loads and breaks after applying a very low number of cycles, usually less than hundreds. The failure is driven by the plastic response of the material, and it is often predicted based on the plastic strains applied to it. The model proposed in this work has been formulated with the objective of predicting accurately the plastic behavior of the material, as well as its failure due to ULCF. This is achieved taking into account the fracture energy dissipated during the whole loading process. This approach allows the simulation of ULCF when it takes place due to regular cyclic loads or non-regular
cyclic loads, as it is the case of seismic loads. Several simulations are conducted in order to show the capabilities of the formulation to reproduce the mechanical response of steel when it is subjected to regular and non-regular cyclic loads. The formulation is validated comparing the numerical results with several experimental tests made o n X52 steel specimens. The agreement between the numerical and experimental results asses the validity of the proposed model to predict the plastic behavior of steel and its failure
due to Ultra Low Cycle Fatigue.

Abstract

Constitutive models have been utilized to study the mechanical behaviors of solid material. The formulation of constitutive relations is difficult and could be associated with limiting hypothesis. This work proposes neural network-based approaches to reproduce the complex nonlinear constitutive relations of solid materials including elastic behavior and plastic deformation. It is shown that the proposed history-based and internal variable-based strategies can represent exactly the von Mises elasto-plastic material model in uni-axial stress state. Furthermore, close investigation suggests that the internal variable-based approach is most suitable.

Abstract

The objective of this paper is to describe the numerical simulation of the transition zones in the multifunctional fuselage panel design to integrate a VHF (Very High Frequency) antenna. The panel is made of GLARE (Glass Laminate Aluminium Reinforced Epoxy) with a central window of GFRP (Glass Fibre Reinforced Polymer). The structural analyses of the transition GLARE/GFRP is presented along with its experimental validation. The numerical simulations showed a very high level of correlation with the experimental tests, both in the longitudinal load vs displacement curves and deformations captured with strain gauges and DIC (Digital Image Correlations).