The Failure Prediction of Reinforced Composite Quasi-Brittle Structures by an Improved Version of the Extended Lumped Damage Approach

IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Daniel V. C. Teles, David L. N. F. Amorim, Edson D. Leonel
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引用次数: 0

Abstract

This study presents an improved version of the Extended Lumped Damage Mechanics (XLDM) formulation within a position-based approach of the Finite Element Method (FEM). In the XLDM, the strain field has been assessed from the elongations of numerical extensometers, which connect the finite element nodes. In addition, localisation bands positioned along the elements' boundaries depict the mechanical effects of material degradation. The position-based approach of FEM enables the accurate modelling of geometrically non-linear effects and its computational implementation is straightforward. In this approach, the equilibrium configuration has been evaluated in relation to the nodal positions instead of its displacements. Thus, one improvement proposed herein involves the coupling of the XLDM failure predictions within an exact geometrically non-linear framework. Besides, in this study, the XLDM has been further improved by incorporating the damage growth caused by compressive stresses. The non-linear formulation proposed herein enables the presence of reinforcements, which have been added by an embedded scheme and lead to another improvement in the XLDM context. Three applications demonstrate the accuracy of the proposed non-linear scheme, in which the numerical responses obtained by the proposed improved formulation have been compared to experimental results available in the literature.

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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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