A phase field framework for capillary-induced fracture in unsaturated porous media: Drying-induced vs. hydraulic cracking

This manuscript introduces a unified mathematical framework to replicate both desiccation-induced and hydraulic fracturing in low-permeable unsaturated porous materials observed in experiments. The unsaturated porous medium is considered as a three-phase solid–liquid–gas effective medium of which each constituent occupies a fraction of the representative elementary volume. As such, an energy-minimization-based phase-field model (PFM) is formulated along with the Biot’s poroelasticity theory to replicate the sub-critical crack growth in the brittle regime. Unlike hydraulic fracturing where the excess pore liquid pressure plays an important role at the onset and propagation of cracks, desiccation cracks are mainly driven by deformation induced by water retention. Therefore, the wettability of the solid skeleton may affect the evolution of the capillary pressure (suction) and change the path-dependent responses of the porous media. This air–water–solid interaction may either hinder or enhance the cracking occurrence. This difference of capillary effect on crack growth during wetting and drying is replicated by introducing retention-sensitive degradation mechanisms in our phase field fracture approach. To replicate the hydraulic behaviors of the pore space inside the host matrix and that of the cracks, the path-dependent changes of the intrinsic permeability due to crack growth and porosity changes are introduced to model the flow conduit in open and closed cracks. Numerical examples of drying-induced and hydraulic fracturing demonstrate the capability of the proposed model to capture different fracture patterns, which qualitatively agrees with the fracture mechanisms of related experiments documented in the literature

From freezing-induced to injection-induced non-isothermal saturated porous media fracture

The focus of this contribution is laid on different aspects and instances related to porous media fracture under non-isothermal conditions. This includes the extreme case of fracturing due to pore-fluid freezing, where the micro-cryo-suction plays an important role in generating the required stresses for crack onset. This also includes studying the instances related to hydraulic fracturing and heat transfer under non-isothermal conditions. In all cases, the continuum mechanical modeling of the induced fractures is based on macroscopic porous media mechanics together with the phase-field method (PFM) for fracture modeling. For the micro-cryo-suction in saturated porous media, the water freezing is treated as a phase-change process. This is modeled using a different phase-field approach, in which the thermal energy derives the phase change and, thus, leads to the occurrence of micro-cryo-suction. Two numerical examples are presented to show the effectiveness of the proposed modeling frameworks

SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials

This paper examines the frame-invariance (and the lack thereof) exhibited in simulated anisotropic elasto-plastic responses generated from supervised machine learning of classical multi-layer and informed-graph-based neural networks, and proposes different remedies to fix this drawback. The inherent hierarchical relations among physical quantities and state variables in an elasto-plasticity model are first represented as informed, directed graphs, where three variations of the graph are tested. While feed-forward neural networks are used to train path-independent constitutive relations (e.g., elasticity), recurrent neural networks are used to replicate responses that depends on the deformation history, i.e. or path dependent. In dealing with the objectivity deficiency, we use the spectral form to represent tensors and, subsequently, three metrics, the Euclidean distance between the Euler Angles, the distance from the identity matrix, and geodesic on the unit sphere in Lie algebra, can be employed to constitute objective functions for the supervised machine learning. In this, the aim is to minimize the measured distance between the true and the predicted 3D rotation entities. Following this, we conduct numerical experiments on how these metrics, which are theoretically equivalent, may lead to differences in the efficiency of the supervised machine learning as well as the accuracy and robustness of the resultant models. Neural network models trained with tensors represented in component form for a given Cartesian coordinate system are used as a benchmark. Our numerical tests show that, even given the same amount of information and data, the quality of the anisotropic elasto-plasticity model is highly sensitive to the way tensors are represented and measured. The results reveal that using a loss function based on geodesic on the unit sphere in Lie algebra together with an informed, directed graph yield significantly more accurate rotation prediction than the other tested approaches

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A Review on Brittle Fracture Nanomechanics by All-Atom Simulations

Despite a wide range of current and potential applications, one primary concern of brittle materials is their sudden and swift collapse. This failure phenomenon exhibits an inability of the materials to sustain tension stresses in a predictable and reliable manner. However, advances in the field of fracture mechanics, especially at the nanoscale, have contributed to the understanding of the material response and failure nature to predict most of the potential dangers. In the following contribution, a comprehensive review is carried out on molecular dynamics (MD) simulations of brittle fracture, wherein the method provides new data and exciting insights into fracture mechanism that cannot be obtained easily from theories or experiments on other scales. In the present review, an abstract introduction to MD simulations, advantages, current limitations and their applications to a range of brittle fracture problems are presented. Additionally, a brief discussion highlights the theoretical background of the macroscopic techniques, such as Griffith’s criterion, crack tip opening displacement, J-integral and other criteria that can be linked to the fracture mechanical properties at the nanoscale. The main focus of the review is on the recent advances in fracture analysis of highly brittle materials, such as carbon nanotubes, graphene, silicon carbide, amorphous silica, calcium carbonate and silica aerogel at the nanoscale. These materials are presented here due to their extraordinary mechanical properties and a wide scope of applications. The underlying review grants a more extensive unravelling of the fracture behaviour and mechanical properties at the nanoscale of brittle materials