Résultats de recherche pour « fracture mechanics »

Physics-informed neural networks have been widely applied to solid mechanics problems. However, balancing the governing partial differential equations and boundary conditions remains challenging, particularly in fracture mechanics, where accurate predictions strongly depend on refined sampling near crack tips. To overcome these limitations, a Kolosov-Muskhelishvili informed neural network with Williams enrichment is developed in this study. Benefiting from the holomorphic representation, the governing equations are satisfied by construction, and only boundary points are required for training. Across a series of benchmark problems, the Kolosov-Muskhelishvili informed neural network shows excellent agreement with analytical and finite element method references, achieving average relative errors below 1\% and $R^2$ above 0.99 for both mode I and mode II loadings. Furthermore, three crack propagation criteria (maximum tangential stress, maximum energy release rate, and principle of local symmetry) are integrated into the framework using a transfer learning strategy to predict crack propagation directions. The predicted paths are nearly identical across all criteria, and the transfer learning strategy reduces the required training time by more than 70\%. Overall, the developed framework provides a unified, mesh-free, and physically consistent approach for accurate and efficient crack propagation analysis.

DEFORMATION OF ENGINEERING MATERIALS. Tensile Response of Materials. Elements of Dislocation Theory. Slip and Twinning in Crystalline Solids. Strengthening Mechanisms in Metals. High-Temperature Deformation Response of Crystalline Solids. Deformation Response of Engineering Plastics. FRACTURE MECHANICS OF ENGINEERING MATERIALS. Fracture: An Overview. Elements of Fracture Mechanics. Transition Temperature Approach to Fracture Control. Microstructural Aspects of Fracture Toughness. Environment-Assisted Cracking. Cyclic Stress and Strain Fatigue. Fatigue Crack Propagation. Analyses of Engineering Failures. Appendices. Indexes.

Linear Elastic Fracture Mechanics (LEFM) provides a consistent framework to evaluate quantitatively the energy flux released to the tip of a growing crack. Still, the way in which the crack selects its velocity in response to this energy flux remains far from completely understood. To uncover the underlying mechanisms, we experimentally studied damage and dissipation processes that develop during the dynamic failure of polymethylmethacrylate (PMMA), classically considered as the archetype of brittle amorphous materials. We evidenced a well-defined critical velocity along which failure switches from nominally-brittle to quasi-brittle, where crack propagation goes hand in hand with the nucleation and growth of microcracks. Via post-mortem analysis of the fracture surfaces, we were able to reconstruct the complete spatiotemporal microcracking dynamics with micrometer/nanosecond resolution. We demonstrated that the true local propagation speed of individual crack fronts is limited to a fairly low value, which can be much smaller than the apparent speed measured at the continuum-level scale. By coalescing with the main front, microcracks boost the macroscale velocity through an acceleration factor of geometrical origin. We discuss the key role of damage-related internal variables in the selection of macroscale fracture dynamics.

To this date the safety assessment of materials, used for example in the nuclear power sector, commonly relies on a fracture mechanical analysis utilizing macroscopic concepts, where a global load quantity K or J is compared to the materials fracture toughness curve. Part of the experimental effort involved in these concepts is dedicated to the quantitative analysis of fracture surfaces. Within the scope of this study a methodology for the semi-supervised training of deep learning models for fracture surface segmentation on a macroscopic level was established. Therefore, three distinct and unique datasets were created to analyze the influence of structural similarity on the segmentation capability. The structural similarity differs due to the assessed materials and specimen, as well as imaging-induced variance due to fluctuations in image acquisition in different laboratories. The datasets correspond to typical isolated laboratory conditions, complex real-world circumstances, and a curated subset of the two. We implemented a weak-to-strong consistency regularization for semi-supervised learning. On the heterogeneous dataset we were able to train robust and well-generalizing models that learned feature representations from images across different domains without observing a significant drop in prediction quality. Furthermore, our approach reduced the number of labeled images required for training by a factor of 6. To demonstrate the success of our method and the benefit of our approach for the fracture mechanics assessment, we utilized the models for initial crack size measurements with the area average method. For the laboratory setting, the deep learning assisted measurements proved to have the same quality as manual measurements. For models trained on the heterogeneous dataset, very good measurement accuracies with mean deviations smaller than 1 % could be achieved...

We propose a novel variational phase-field model for fracture and fatigue in pseudoelastic shape memory alloys (SMAs). The model, developed in a one-dimensional setting, builds upon the Auricchio-Petrini constitutive formulation for SMAs and couples damage evolution with phase transformation. We study analytically and numerically the homogeneous and localization responses of a bar under both monotonic and cyclic loading, and we investigate various macroscopic behaviors by tuning the constitutive parameters. A key feature of the model is the introduction of a transformation strain limit, beyond which the material is fully martensitic and behaves elastically. This leads to a distinctive behavior in which the region of localized damage widens, yielding a delay of fracture. The capability of the model to predict the fatigue performance is assessed by simulating the uniaxial response of Ni-Ti multi-wire samples under different loading conditions. The results show that the model discriminates between safe and critical loading scenarios, capturing the experimental trend of increased fatigue resistance with higher mean strain at a fixed strain amplitude. Ongoing efforts are aimed at further evaluating its reliability for quantitative fatigue life prediction.

This state-of-the-science publication on fracture test techniques for glass, ceramics, rocks, and cementitious composites is a compilation of 14 papers which were presented at the Eleventh National Symposium on Fracture Mechanics, which was held June 12-14,1978, at Virginia Polytechnic Institute and State University, Blacksburg, Va.These papers can be grouped into three categories: papers which relate to the theoretical and experimental details of test techniques; papers which describe the applications of these test techniques; and a paper which explains the use of fracture data in life time prediction of structural components.Although Griffith fracture theory was motivated by fracture of glass, its modern application to brittle materials is complicated by the unforgiving nature of such materials.Additional complication is introduced in the high temperature test environment of some structural ceramics.These unique test requirements promote the use of double torsion, notch bend, and short bar specimens which are discussed in detail by Fuller, Pletka, et al., Bansal, et al., and Barker.A unique ceramic fracture specimen which uses an indentation generated surface flaw in a bend specimen is discussed by Petrovic, et al., Marian and Evans.As for material characterization, dynamic fracture response of a birefringent polymer is discussed by Fourney, et al., and Mecholsky, et al., reported on ceramic fracture toughness obtained through fractographic analysis.Fracture toughness of alumina and Westerly granite are reported by Buresch and Schmidt, et al.The complex fracture behavior of cementitious composites is discussed by Naaman, et al.The last paper by Wiederhorn, et al, presents a fracture mechanics approach for improving the reliability of structural ceramics.As is the recent ASTM practice, this STP contains a thorough summary by the editor, S. W.

A new gradient-based formulation for predicting fracture in elastic-plastic solids is presented. Damage is captured by means of a phase field model that considers both the elastic and plastic works as driving forces for fracture. Material deformation is characterised by a mechanism-based strain gradient constitutive model. This non-local plastic-damage formulation is numerically implemented and used to simulate fracture in several paradigmatic boundary value problems. The case studies aim at shedding light into the role of the plastic and fracture length scales. It is found that the role of plastic strain gradients is two-fold. When dealing with sharp defects like cracks, plastic strain gradients elevate local stresses and facilitate fracture. However, in the presence of non-sharp defects failure is driven by the localisation of plastic flow, which is delayed due to the additional work hardening introduced by plastic strain gradients.

Proteins are the fundamental building blocks of a vast array of biological materials involved in critical functions of life, many of which are based on highly characteristic nanostructured arrangements of protein components that include collagen, alpha helices, or beta sheets. Bone, providing structure to our body, or spider silk, used for prey procurement, are examples of materials that have incredible elasticity, strength, and robustness unmatched by many synthetic materials. This is mainly attributed to their structural formation with molecular precision. We review recent advances in using large-scale atomistic and molecular modeling to elucidate the deformation and fracture mechanics of vimentin intermediate filaments (IFs), which are hierarchical self-assembled protein networks that provide structure and stability to eukaryotic cells. We compare the fracture and failure mechanisms of biological protein materials (BPMs) with those observed in brittle and ductile crystalline materials such as metals or ceramics. Our studies illustrate how atomistic-based multiscale modeling can be employed to provide a first principles based material description of deformation and fracture, linking nano- to macroscales.