Energy-based fracture mechanics of brittle lattice materials

Luan, Shengzhi; Chen, Enze; Gaitanaros, Stavros

doi:10.1016/j.jmps.2022.105093

Cited by 13 publications

(4 citation statements)

References 68 publications

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“…Mechanical properties. We consider the canonical mode-I fracture problem 7,29,41 , as shown in Fig. 2a, which involves a sample loaded vertically in tension.…”

Section: Resultsmentioning

confidence: 99%

Prediction and control of fracture paths in disordered architected materials using graph neural networks

Karapiperis

Kochmann

2023

Commun Eng

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Architected materials typically rely on regular periodic patterns to achieve improved mechanical properties such as stiffness or fracture toughness. Here we introduce a class of irregular cellular materials with engineered topological and geometrical disorder, which represents a shift from conventional designs. We first develop a graph learning model for predicting the fracture path in these architected materials. The model employs a graph convolution for spatial message passing and a gated recurrent unit architecture for temporal dependence. Once trained on data gleaned from experimentally validated elastoplastic beam finite element analyses, the learned model produces accurate predictions overcoming the need for expensive finite element calculations. We finally leverage the trained model in combination with a downstream optimization scheme to generate optimal architectures that maximize the crack path length and, hence, the associated fracture energy.

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“…Mechanical properties. We consider the canonical mode-I fracture problem 7,29,41 , as shown in Fig. 2a, which involves a sample loaded vertically in tension.…”

Section: Resultsmentioning

confidence: 99%

Prediction and control of fracture paths in disordered architected materials using graph neural networks

Karapiperis

Kochmann

2023

Commun Eng

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“…To quantify the effect of void geometry on damage tolerance, we first consider specimens with only one layer of voids (figure 2). As in previous work [33,34], the fracture energy can be calculated as the area under the load-displacement curve (note, the fracture energy used in this work is a structural property rather than a material property):…”

Section: Effect Of Void Length On Fracture Energymentioning

confidence: 99%

Improving structural damage tolerance and fracture energy via bamboo-inspired void patterns

Zhu,

Liu,

Hua

et al. 2024

Bioinspir. Biomim.

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Bamboo has a functionally-graded microstructure that endows it with a combination of desirable properties, such as high failure strain, high toughness, and a low density. As a result, bamboo has been widely used in load-bearing structures. In this work, we study the use of bamboo-inspired void patterns to geometrically improve the failure properties of structures made from brittle polymers. We perform finite element analysis and experiments on 3D-printed structures to quantify the effect of the shape and spatial distribution of voids on the fracture behavior. The introduction of periodic, uniformly distributed voids in notched bend specimens leads to a 15-fold increase in the fracture energy relative to solid specimens. Adding a gradient to the pattern of voids leads to a cumulative 55-fold improvement in the fracture energy. Mechanistically, the individual voids result in crack blunting, which suppresses crack initiation, while neighboring voids redistribute stresses throughout the sample to enable large deformation before failure.

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“…Cellular metamaterials, consisting of polyhedral topologies with struts (3,4), plates (5,6), or shells (7)(8)(9) as building blocks, are an important class of architected materials that has been the focus of a vast number of studies because of their unique mechanical, thermal, and acoustic properties, and their ubiquitous occurrence in nature (10). To date, a plethora of engineered architectures have been reported with desirable effective properties including high stiffness (11)(12)(13)(14), negative Poisson's ratio (15)(16)(17), phononic bandgaps (18,19), energy absorption (20)(21)(22), heat transfer (23), strength and resilience (24)(25)(26)(27)(28), toughness (29,30), and others. Rigorous design methodologies, such as topology optimization, have led to material systems with stiffness and strength that reach their individual theoretical bounds (12).…”

Section: Introductionmentioning

confidence: 99%

A data-driven framework for structure-property correlation in ordered and disordered cellular metamaterials

Luan,

Chen,

John

et al. 2023

Sci. Adv.

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Extracting the relation between microstructural features and resulting material properties is essential for advancing our fundamental knowledge on the mechanics of cellular metamaterials and to enable the design of novel material systems. Here, we present a unified framework that not only allows the prediction of macroscopic properties but, more importantly, also reveals their connection to key morphological characteristics, as identified by the integration of machine-learning models and interpretability algorithms. We establish the complex manner in which strut orientation can be critical in determining effective stiffness for certain microstructures and highlight cellular metamaterials with counterintuitive material behavior. We further provide a refined version of Maxwell’s criteria regarding the rigidity of frame structures and their connection to cellular metamaterials. By examining the shear moduli of these metamaterials, the mean cell compactness emerges as a key morphological feature. The generality of the proposed framework allows its extension to broader classes of architected materials as well as different properties of interest.

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Energy-based fracture mechanics of brittle lattice materials

Cited by 13 publications

References 68 publications

Prediction and control of fracture paths in disordered architected materials using graph neural networks

Prediction and control of fracture paths in disordered architected materials using graph neural networks

Improving structural damage tolerance and fracture energy via bamboo-inspired void patterns

A data-driven framework for structure-property correlation in ordered and disordered cellular metamaterials

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