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This paper introduces a new local plastic correction algorithm that is aimed at accelerating elasto-plastic finite element (FE) simulations for structural problems exhibiting localised plasticity (around e.g. notches, geometrical defects). The proposed method belongs to the category of generalised multi-axial Neuber-type methods, which process the results of an elastic prediction point-wise in order to calculate an approximation of the full elasto-plastic solution. The proposed algorithm relies on a rule of local proportionality, which, in the context of J2 plasticity, allows us to express the plastic plastic correction problem in terms of the amplitude of the full mechanical tensors only. This lightweight correction problem can be solved for numerically using a fully implicit time integrator that shares similarities with the radial return algorithm. The numerical capabilities of the proposed algorithm are demonstrated for a notched structure and a specimen containing a distribution of spherical pores, subjected to monotonic and cyclic loading. As a second point of innovation, we show that the proposed local plastic correction algorithm can be further accelerated by employing a sim

Over the last decade, fluvial plastics have been identified as major threat to aquatic environments and human health. In order to develop adequate mitigation strategies for plastic pollution, a fundamental process understanding of riverine plastic transport is of significant importance. In this context, the implementation of research findings into numerical simulation environments is anticipated to enhance modelling capabilities and to support a rigorous decision making. Recent experimental research has focused on the incipient motion of plastic particles, as well as on the effects of surface tension on plastic concentration profiles. While these investigations have advanced the state-of-the-art knowledge, current literature still displays a lack of basic insights into layer-specific plastic transport physics. In this study, first principles are applied to advance knowledge on free-surface detachment and bed entrainment of fluvial plastics. A novel relationship for the critical surface detachment velocity is derived, followed by the development of a framework that allows to relate plastic Shields parameters to those of natural sediments. Overall, it is anticipated that these develo

Crystal plasticity finite element simulations are frequently employed to predict the plastic anisotropy of polycrystalline metals based on their crystallographic texture. In age-hardenable aluminium alloys, however, the texture-induced plastic anisotropy is known to affect by precipitation. This paper presents a new modelling approach to incorporate this effect into crystal plasticity constitutive models. The approach focuses on the overall effect of precipitation, which is assumed to result in an additional directional dependency with respect to a global material orientation, superimposed with the texture-induced plastic anisotropy. This additional directional dependency is implemented into a conventional crystal plasticity constitutive model via a modified hardening law that introduces two new parameters, of which only one is treated as a free parameter. To demonstrate the applicability of the new modelling approach, it is applied to an age-hardenable AA6014-T4 aluminium alloy and compared against a state-of-the-art crystal plasticity constitutive model that considers only crystallographic texture. The results demonstrate that the new modelling approach significantly improves the

It was recently shown that vortex-like topological defects with negative winding number in the vibrational modes of a two-dimensional glass under quasistatic shear correlate strongly with plastic events, offering a promising route to predict them. However, many of these vortices, a number that actually grows quadratically with mode frequency, are entirely unrelated to plasticity and arise simply from the underlying plane-wave structure of the modes. This raises doubts about the fundamental relevance of such defects to plastic rearrangements and limits their predictive power. Here, we introduce a geometrical filter based on the Nye dislocation density that, when applied to the vibrational modes, removes these spurious defects and reveals the true plastic precursors. Using simulations of a two-dimensional model glass, we show that this filtered approach consistently outperforms the conventional vortex-based method, particularly at small strains and when focusing on genuine plastic stress drops, offering a more robust tool to predicting plasticity in glasses from their undeformed initial state.

In Reinforcement Learning (RL), enhancing sample efficiency is crucial, particularly in scenarios when data acquisition is costly and risky. In principle, off-policy RL algorithms can improve sample efficiency by allowing multiple updates per environment interaction. However, these multiple updates often lead the model to overfit to earlier interactions, which is referred to as the loss of plasticity. Our study investigates the underlying causes of this phenomenon by dividing plasticity into two aspects. Input plasticity, which denotes the model's adaptability to changing input data, and label plasticity, which denotes the model's adaptability to evolving input-output relationships. Synthetic experiments on the CIFAR-10 dataset reveal that finding smoother minima of loss landscape enhances input plasticity, whereas refined gradient propagation improves label plasticity. Leveraging these findings, we introduce the PLASTIC algorithm, which harmoniously combines techniques to address both concerns. With minimal architectural modifications, PLASTIC achieves competitive performance on benchmarks including Atari-100k and Deepmind Control Suite. This result emphasizes the importance of pr

A metric space is plastic if all its non-expansive bijections are isometries. We prove three main results: (1) every countable dense subspace of a normed space is not plastic, (2) every $k$-crowded separable metric space contains a plastic dense subspace, and (3) every strictly convex separable metric group contains a plastic dense subgroup.

Materials typically fail under complex stress states, essentially involving dilatational (volumetric) components that eventually lead to material decohesion/separation. It is therefore important to understand dilatational irreversible deformation -- i.e., dilatational plasticity -- en route to failure. In the context of glasses, much focus has been given to shear (volume-preserving) plasticity, both in terms of the stress states considered and the corresponding material response. Here, using a recently-developed methodology and extensive computer simulations, we shed basic light on the elementary processes mediating dilatational plasticity in glasses. We show that plastic instabilities, corresponding to singularities of the glass Hessian, generically feature both dilatational and shear irreversible strain components. The relative magnitude and statistics of the strain components depend both on the symmetry of the driving stress (e.g., shear vs.~hydrostatic tension) and on the cohesive (attractive) part of the interatomic interaction. We further show that the tensorial shear component of the plastic strain is generally non-planar and also extract the characteristic volume of plastic

Robust and credible material flow data are required to support the ongoing efforts to reconcile the economic and social benefits of plastics with their human and environmental health impacts. This study presents a global, but regionalized, life cycle material flow analysis (MFA) of all plastic polymers and applications for the period 1950-2020. It also illustrates how this dataset can be used to generate possible scenarios for the next 30 years. The historical account documents how the relentless growth of plastic production and use has consistently outpaced waste management systems worldwide and currently generates on the order of 60 Mt of mismanaged plastic waste annually. The scenarios show that robust interventions are needed to avoid annual plastic waste mismanagement from doubling by 2050.

A polycrystalline solid is modelled as an ensemble of random irregular polyhedra filling the entire space occupied by the solid body, leaving no voids or flaws between them. Adjacent grains can slide with a relative velocity proportional to the local shear stress resolved in the plane common to the two sliding grains, provided it exceeds a threshold. The local forces associated to the continuous grain shape accommodation for preserving matter continuity are assumed much weaker. The model can be solved analytically and for overcritical conditions gives two regimes of deformation, plastic and superplastic. The plastic regime, from yield to fracture, is dealt with. Applications to nickel superalloys and stainless steels give impressive agreement with experiment. Most work of the last century relies on postulating pre--existent cracks and voids to explain plastic deformation and fracture. The present model gives much better results.

In engineering crystal plasticity inelastic mechanisms correspond to tensorial zero-energy valleys in the space of macroscopic strains. The flat nature of such valleys is in contradiction with the fact that plastic slips, mimicking lattice-invariant shears, are inherently discrete. A reconciliation has recently been achieved in the mesoscopic tensorial model (MTM) of crystal plasticity, which introduces periodically modulated energy valleys while also capturing in a geometrically exact way the crystallographically-specific aspects of plastic slips. In this paper, we extend the MTM framework, which in its original form had the appearance of a discretized nonlinear elasticity theory, by explicitly introducing the concept of plastic deformation. The ensuing model contains a novel matrix-valued spin variable, representing the quantized plastic distortion, whose rate-independent evolution can be described by a discrete (quasi-)automaton. The proposed reformulation of the MTM leads to a considerable computational speedup associated with the use of a robust and efficient hybrid Gauss-Newton--Cauchy energy minimization algorithm. To illustrate the effectiveness of the new approach, we pres

The rheology of rocks transitions from a localized brittle behaviour to distributed plastic behaviour with increasing pressure and temperature. This brittle-plastic is empirically observed to occur when the material strength becomes lower than the confining stress, which is termed Goetze's criterion. Such a criterion works well for most silicates but is not universal for all materials. We aim to determine the microphysical controls and stress-strain behaviour of rocks in the brittle-plastic transition. We use a micro-mechanical approach due to Horii and Nemat-Nasser, and consider representative volume elements containing sliding wing-cracks and plastic zones. We find solutions for frictional slip, plastic deformation and crack opening at constant confining pressure, and obtain stress-strain evolution. We show that the brittle-plastic transition depends on the confining stress, fracture toughness and plastic yield stress but also critically on the friction coefficient on preexisting defects. Materials with low friction are expected to be more brittle, and experience transition to fully plastic flow at higher pressure than anticipated from Goetze's criterion. The overall success of G

Using molecular dynamics simulation, we study the plastic zone created during nanoindentation of a large CuZr glass system. The plastic zone consists of a core region, in which virtually every atom undergoes plastic rearrangement, and a tail, where the density distribution of the plastically active atoms decays to zero. Compared to crystalline substrates, the plastic zone in metallic glasses is significantly smaller than in crystals. The so-called plastic-zone size factor, which relates the radius of the plastic zone to the contact radius of the indenter with the substrate, assumes values around 1, while in crystals -- depending on the crystal structure -- values of 2--3 are common. The small plastic zone in metallic glasses is caused by the essentially homogeneous deformation in the amorphous matrix, while in crystals heterogeneous dislocations prevail, whose growth leads to a marked extension of the plastic zone.

How can we build agents that keep learning from experience, quickly and efficiently, after their initial training? Here we take inspiration from the main mechanism of learning in biological brains: synaptic plasticity, carefully tuned by evolution to produce efficient lifelong learning. We show that plasticity, just like connection weights, can be optimized by gradient descent in large (millions of parameters) recurrent networks with Hebbian plastic connections. First, recurrent plastic networks with more than two million parameters can be trained to memorize and reconstruct sets of novel, high-dimensional 1000+ pixels natural images not seen during training. Crucially, traditional non-plastic recurrent networks fail to solve this task. Furthermore, trained plastic networks can also solve generic meta-learning tasks such as the Omniglot task, with competitive results and little parameter overhead. Finally, in reinforcement learning settings, plastic networks outperform a non-plastic equivalent in a maze exploration task. We conclude that differentiable plasticity may provide a powerful novel approach to the learning-to-learn problem.

Irreversible plastic forming of B19$^\prime$ martensite of the NiTi shape memory alloy is discussed within the framework of continuum mechanics. It is suggested that the main mechanism arises from coupling between martensite reorientation and coordinated $[100](001)_{\rm M}$ dislocation slip. A heuristic model is proposed, showing that the ${(20\bar{1})_{\rm M}}$ deformation-twin bands, commonly observed in experiments, can be interpreted as a combination of dislocation-mediated kink bands, appearing due to strong plastic anisotropy, and reversible twinning of martensite. We introduce a term 'kwinking' for this combination of reversible twinning and irreversible plastic kinking. The model is subsequently formulated using the tools of nonlinear elasticity theory of martensite and crystal plasticity, introducing 'kwink interfaces' as planar, kinematically compatible interfaces between two differently plastically slipped variants of martensite. It is shown that the ${(20\bar{1})_{\rm M}}$ kwink bands may be understood as resultsing from energy minimization, and that their nucleation and growth and their pairing with $(100)_{\rm M}$ twins into specific patterns enables low-energy plast

Temporary plastic film barriers are widely used to separate occupied rooms from exterior renovation zones, yet their effect on indoor particulate exposure is poorly quantified. We monitored PM$_{2.5}$ in a Tampa, Florida, apartment for 48 days with a low-cost optical sensor (Temtop LKC-1000S+), spanning pre-barrier, barrier-on, and post-barrier periods. A quadratic baseline was fitted to "background" minutes devoid of identifiable indoor sources, allowing excess concentrations ($Δ$PM) to be partitioned into facade work, cooking, and passive accumulation without outdoor co-monitoring. The barrier prevented large construction spikes indoors but curtailed natural ventilation, doubling the mean baseline from 1.9 to 3.9 $μ$g m$^{-3}$. During this stage, passive build-up accounted for $45\,\%$ of the daily excess dose, with facade work and cooking contributing $31\,\%$ and $24\,\%$, respectively. Once the new window was installed and evening airing resumed, the baseline fell to 0.8 $μ$g m$^{-3}$, the lowest of the campaign. Our findings highlight the trade-off between dust shielding and background elevation and demonstrate that simple polynomial fitting bolsters low-cost IAQ diagnostics

Elastoplastic lattice models for the response of solids to deformation typically incorporate structure only implicitly via a local yield strain that is assigned to each site. However, the local yield strain can change in response to a nearby or even distant plastic event in the system. This interplay is key to understanding phenomena such as avalanches in which one plastic event can trigger another, leading to a cascade of events, but typically is neglected in elastoplastic models. To include the interplay one could calculate the local yield strain for a given particulate system and follow its evolution, but this is expensive and requires knowledge of particle interactions, which is often hard to extract from experiments. Instead, we introduce a structural quantity, "softness," obtained using machine learning to correlate with imminent plastic rearrangements. We show that softness also correlates with local yield strain. We incorporate softness to construct a "structuro-elasto-plasticity" model that reproduces particle simulation results quantitatively for several observable quantities, confirming that we capture the influence of the interplay of local structure, plasticity, and el

The compressive properties of metal-organic framework (MOF) crystals are not only crucial for their densification but also key in determining their performance in many applications. We herein investigated the mechanical responses of a classic crystalline MOF, HKUST-1 by using in situ compression tests. A serrated flow accompanied by the unique strain avalanches was found in individual and contacting crystals before their final flattening or fracture with splitting cracks. The plastic flow with serrations is ascribed to the dynamic phase mixing due to the progressive and irreversible local phase transition in HKUST-1 crystals, as revealed by molecular dynamics and finite element simulations. Such pressure-induced phase coexistence in HKUST-1 crystals also induces a significant loading-history dependence of their Young's modulus. The observation of plastic avalanches in HKUST-1 crystals here not only expands our current understanding of the plasticity of MOF crystals but also unveils a novel mechanism for the avalanches and plastic flow in crystal plasticity.

We present a novel approach to determine the constitutive properties of metals under large plastic strains and strain rates that otherwise are difficult to access using conventional materials testing methods. The approach exploits large-strain plastic flow past a sharp wedge, coupled with high-speed photography and image velocimetry to capture the underlying plastic flow dynamics. The inverse problem of estimating material parameters from the flow field is solved using an iterative optimization procedure that minimizes the gap between internal and external plastic work. A major advantage of the method is that it neither makes any assumptions about the flow nor requires computational simulations. To counter the problem of non-unique parameter estimates, we propose a parameterization scheme that takes advantage of the functional form of the constitutive model and reformulates the problem into a more tractable form to identify plasticity parameters uniquely. We present studies to illustrate the principle of the method with two materials with widely different plastic flow characteristics: copper (strain hardening) and a lead-free solder alloy (rate sensitive and deformation history dep

Ice plasticity has been thoroughly studied, owing to its importance in glaciers and ice sheets dynamics. In particular, its anisotropy (easy basal slip) has been suspected for a long time, then fully characterized 40 years ago. More recently emerged the interest of ice as a model material to study some fundamental aspects of crystalline plasticity. An example is the nature of plastic fluctuations and collective dislocation dynamics. 20 years ago, acoustic emission measurements performed during the deformation of ice single crystals revealed that plastic flow proceeds through intermittent dislocation avalanches, power law distributed in size and energy. This means that most of ice plasticity takes place through few, very large avalanches, thus qualifying associated plastic fluctuations as wild. This launched an intense research activity on plastic intermittency in the Material Science community. The interest of ice in this debate is reviewed, from a comparison with other crystalline materials. In this context, ice appears as an extreme case of plastic intermittency, characterized by scale-free fluctuations, complex space and time correlations as well as avalanche triggering. In othe