Predict Material Failure Research Articles

Spectroscopic Study of Strain, Oxidation, and Formation of Few-Layer Graphene at Steel Surfaces Tribologically Tested against MoS2 Films.

MoS2 not only has unique optoelectronic properties realizing photonic and semiconductor applications but also serves as a promising solid lubricant in tribological three-body contacts due to its advantageous friction and wear behavior. Its functionality is defined by elementary processes including strain, oxidation processes, and material mixing. However, these mechanisms were not elucidated for MoS2 having transferred from the MoS2 film synthesized at the main body to a steel counter body during tribological ball-on-disk tests. Using spatially and spectrally high-resolved Raman spectroscopy, we study the compressive and tensile strain within the MoS2 transfer material and analyze the oxidation of molybdenum, sulfur, and iron. In addition, we elaborate on the impact of transition metals modifying the MoS2 films on the strain distribution and oxidation processes. Decreasing intensities of the MoS2 Raman lines are accompanied with enhanced intensities of sulphur and molybdenum oxide Raman signatures which are particularly agglomerated at the edges of the tribological track. The formation of tribochemical oxides, including Mo4O11 in the Magnéli-phase, depends weakly on the type of modifying element, and an oxidation of a modification element itself is not detected. We also identified a tribologically induced formation of disordered few-layer graphene at counter-body surface areas which experienced weak thermo-mechanical tribological load. Our results characterize structural and chemical features of the MoS2 transfer material, thus predicting material failure at the microscopic level.

Study on the lower head failure in severe accidents Part II: Thermal-mechanical coupling behavior analysis on CAP1400 reactor lower head

Under severe accident conditions with core meltdown, large amounts of molten material relocate to the lower head at high temperatures. Significant thermal and mechanical loads may lead to failure of the reactor pressure vessel (RPV) lower head, spreading radioactive fission products. Lower head failure time and location are crucial for accident mitigation and consequence assessment. This study developed a thermodynamic failure analysis model for the lower head by investigating material failure mechanisms, coupling this into an Integrated Severe Accident Analysis code (ISAA), and conducting experimental validation and applied research. Part I mainly introduces the thermodynamic analysis module development, validation against OLHF experiments, and preliminary failure criteria analysis. Results indicate the model accurately predicts lower head failure behavior, and Larson-Miller life fraction and Hedl-Dorn parameter criteria accurately assess lower head integrity. Part II presents applied research after validation and preliminary analysis. Using the improved ISAA, melt pool behavior and lower head thermal–mechanical response were analyzed for a CAP1400 small break loss-of-coolant accident (SBLOCA), assuming multiple safety system failures. Results indicate the bottom of the lower head melt pool didn’t form a hard shell due to high heat release rate, only an oxide shell layer around the second layer. Decay heat from melt pool components cannot be dissipated, leading to lower head failure. Further External Reactor Vessel Cooling (ERVC) heat transfer model analysis and research are needed in ISAA. The two developed mechanical analysis models predict material failure at high temperatures, and the timing and location of lower head failure are consistent, at approximately 16,000 s at 25.38°±5.47° on the lower head. The predicted failure mode is similar to Part I validation, indicating both Larson-Miller life fraction and Hedl-Dorn parameter criteria provide consistent lower head integrity judgments.

A Multi-Yield-Surface Plasticity State-Based Peridynamics Model and its Applications to Simulations of Ice-Structure Interactions

Due to complex mesoscopic and the distinct macroscopic evolution characteristics of ice, especially for its brittle-to-ductile transition in dynamic response, it is still a challenging task to build an accurate ice constitutive model to predict ice loads during ship-ice collision. To address this, we incorporate the conventional multi-yield-surface plasticity model with the state-based peridynamics to simulate the stress and crack formation of ice under impact. Additionally, we take into account of the effects of inhomogeneous temperature distribution, strain rate, and pressure sensitivity. By doing so, we can successfully predict material failure of isotropic freshwater ice,iceberg ice, and columnar saline ice. Particularly, the proposed ice constitutive model is validated through several benchmark tests, and proved its applicability to model ice fragmentation under impacts, including drop tower tests and ballistic problems. Our results show that the proposed approach provides good computational performance to simulate ship-ice collision.

Deep language models for interpretative and predictive materials science

Machine learning (ML) has emerged as an indispensable methodology to describe, discover, and predict complex physical phenomena that efficiently help us learn underlying functional rules, especially in cases when conventional modeling approaches cannot be applied. While conventional feedforward neural networks are typically limited to performing tasks related to static patterns in data, recursive models can both work iteratively based on a changing input and discover complex dynamical relationships in the data. Deep language models can model flexible modalities of data and are capable of learning rich dynamical behaviors as they operate on discrete or continuous symbols that define the states of a physical system, yielding great potential toward end-to-end predictions. Similar to how words form a sentence, materials can be considered as a self-assembly of physically interacted building blocks, where the emerging functions of materials are analogous to the meaning of sentences. While discovering the fundamental relationships between building blocks and function emergence can be challenging, language models, such as recurrent neural networks and long-short term memory networks, and, in particular, attention models, such as the transformer architecture, can solve many such complex problems. Application areas of such models include protein folding, molecular property prediction, prediction of material failure of complex nonlinear architected materials, and also generative strategies for materials discovery. We outline challenges and opportunities, especially focusing on extending the deep-rooted kinship of humans with symbolism toward generalizable artificial intelligence (AI) systems using neuro-symbolic AI, and outline how tools such as ChatGPT and DALL·E can drive materials discovery.

A meshless method coupling peridynamics with corrective smoothed particle method for predicting material failure

In this paper, we developed a meshless framework that couples peridynamics (PD) and the corrective smoothed particle method (CSPM) to simulate the complex damage and fracturing process of structures. This framework retains the advantages of PD in simulating material failure, and solves the problem that PD cannot simulate structures with irregular grids, and it also reduces the interface effect. Furthermore, the coupled PD-CSPM overcomes the challenge that stress boundary cannot be directly applied on CSPM-based models. In addition, PD-CSPM is capable of eliminating the limitation of Poisson's ratio imposed by the bond-based PD method. By simulating the deformation and failure behaviors of structures, the performance of PD-CSPM is verified and validated by the experimental observation and the numerical results obtained using other methods (the classic finite element method (FEM), extended finite element method (XFEM), and phase field method). Using the developed method, we successfully simulated fracture and failure behaviors of structures with irregular grids.

Processes controlling helium bubble dynamics at varying temperatures in simulated radioactive materials

Alpha-radiation damage is known to degrade materials exposed to harsh radiation environments via swelling and embrittlement by nano-scale helium bubbles. How these bubbles grow under varying temperature is essential to understanding and predicting material failure and optimization. Using in situ X-ray scattering, we probed ≈1012 bubbles before, during and after annealing at different temperatures in He-implanted aluminum to reveal a critical growth activation temperature that depends strongly on the helium implantation conditions. An analysis of the data aided by our molecular dynamics simulations identifies multiple temperature-dependent bubble growth mechanisms above and below the critical growth activation temperature. Moreover, the irreversible bubble growth that occurs after annealing for ≈4 h was evaluated using dislocation dynamics and found to negligibly affect the yield strength but may affect subsequent bubble growth at temperature. These in situ results provide valuable insight into bubble growth never observed before and reveal, for the first time, bubble shrinkage after cooling.

Modeling tension-compression asymmetry and failure anisotropy in bending operations of a magnesium alloy

The deformation behavior of the magnesium sheet alloy AZ31 at room temperature is investigated using different standard and non-standard mechanical tests as well as respective finite-element simulations. In order to address the bendability, three-point bending tests were performed for different orientations of the sample with respect to the sheets axes of orthotropy. The elastic-plastic deformation was modeled using a two-yield-surface model, which is able to describe the evolving strength differential effect as well as the anisotropy of the material. For the prediction of material failure, a numerically efficient damage criterion based on transformation of strain rates is calibrated and applied. It is shown that this model is able to predict the observed edge failure of specimens with good accuracy.

Extended GTN model for predicting ductile fracture under a broad range of stress states

Continuous damage accumulation resulting from void nucleation, growth, and coalescence leads to the final ductile fracture. The Gurson–Tvergaard–Needleman (GTN) model and its extensions, which model these mechanisms, are famous coupled constitutive models for predicting material failure. In this study, the GTN model was extended by incorporating two different damage variables: void volume fraction and shear damage; this was done to describe damage accumulation and ductile fracture under a wide range of stress states from compression-dominated to tension-dominated ones. The shear damage was composed of the shear void nucleation related to secondary voids and shear deformation damage. In addition, the shear void nucleation and void closure effect resulting from compression deformation were introduced to model the change in void volume under different loading conditions. The Lode angle dependence function was updated to express the various stress states and competition mechanism between two damage variables. Furthermore, the effective damage and its incremental form was used to define the extent of damage accumulation and fracture initiation. Subsequently, the proposed model was implemented in finite element software through user subroutines, and three distinct experiments related to high, low, and negative stress triaxiality were performed to calibrate the model parameters by the inverse analysis method for 1045 steel and 2024-T351 aluminum alloy. The experimental results under proportional and path-changing loading conditions were used to analyze the damage evolution and validate the proposed model. The good agreement between the numerical prediction and experimental results for the displacement and location at fracture, indicates good predictive ability of formulated model under arbitrary loading conditions.

Analysis of the metal sheets formability at single point incremental forming process

Although research on incremental forming process began a few decades ago, it is still a process in development phase. Single point incremental forming is a simple process and the deformation of the sheet blank is done with the help of a punch that follows a known toolpath. In the case of this process, one important aspect is the prediction of material failure. To achieve this with the help of a finite element analysis, a series of experiments were performed to determine the forming limit diagram. In this paper, an attempt has been made to determine the forming limit diagram for the AA1050 aluminum alloy. The experiments were performed with the help of an industrial robot, KUKA KR 210-2, thus the part can be measured with an optical measuring instrument obtaining the major and minor strain from forming limit diagram.

Modelling and understanding edge glow effects on material failure resulting from artificial lightning strike

This paper examines the influence of edge glow effects (arcing of current from specimen side surfaces) on the prediction of material failure during an artificial lightning strike. A novel modelling approach is proposed to incorporate edge glow effects. Finite Element simulations are undertaken to examine modelling strategies and results compared against experimental data. Simulations also examine the influence of inter-ply properties, as together with edge glow modelling, these may be expected to impact the predicted current path through a test specimen. Unprotected carbon fibre/epoxy composite material and Society of Automotive Engineers (SAE) lightning test Waveform A are studied. Inter-ply thermal and electrical conductivities are modified either wholly or partly (by 50% or 100%) from a reference magnitude. Results reveal that changes to inter-ply contact can affect the damage area and depth predictions, varying damage area predictions by up to 22%. However, it is shown that edge glow effects produce an even more significant change in the prediction of thermal damage behaviour, reducing predicted damage areas, by up to 55%, and increasing damage depth by 14%.

Probabilistic characterization of the effect of transient stochastic loads on the fatigue-crack nucleation time

The rainflow counting algorithm for material fatigue is both simple to implement and extraordinarily successful for predicting material failure times. However, it neglects memory effects and time-ordering dependence, and therefore runs into difficulties dealing with highly intermittent or transient stochastic loads with heavy tailed distributions. Such loads appear frequently in a wide range of applications in ocean and mechanical engineering, such as wind turbines and offshore structures. In this work we employ the Serebrinsky–Ortiz cohesive envelope model for material fatigue to characterize the effects of load intermittency on the fatigue-crack nucleation time. We first formulate efficient numerical integration schemes, which allow for the direct characterization of the fatigue life in terms of any given load time-series. Subsequently, we consider the case of stochastic intermittent loads with given statistical characteristics. To overcome the need for expensive Monte-Carlo simulations, we formulate the fatigue life as an up-crossing problem of the coherent envelope. Assuming statistical independence for the large intermittent spikes and using probabilistic arguments we derive closed expressions for the up-crossing properties of the coherent envelope and obtain analytical approximations for the probability mass function of the failure time. The analytical expressions are derived directly in terms of the probability density function of the load, as well as the coherent envelope. We examine the accuracy of the analytical approximations and compare the predicted failure time with the standard rainflow algorithm for various loads. Finally, we use the analytical expressions to examine the robustness of the derived probability distribution for the failure time with respect to the coherent envelope geometrical properties.

An XFEM multilayered heaviside enrichment for fracture propagation with reduced enhanced degrees of freedom

SummaryThe development of advanced numerical techniques such as eXtended/Generalized Finite Elements Methods (XFEM/GFEM) has provided means for accurate prediction of material failure. However, the present theories mostly rely on a global formulation, where the system of equations is subject to progressive dimension increase with crack evolution. In this regard, an independent multilayered enrichment is proposed for the XFEM/GFEM family of methods where a few elements in close proximity are assigned to an enrichment layer independent of the remaining ones. The enhanced degrees of freedom can be condensed out at the layer level, which leads to system dimensions, sparsity, and bandness identical to those of the underlying finite elements. Nodal and elemental enrichment methods are shown to be particular limit cases of present approach. The robustness of the proposed approach is first demonstrated in element‐level examples. The use of only few adjacent elements in a group enrichment is shown to suffice for acceptable results while the order of the condition number of the final stiffness matrix resembles the underlying uncracked finite element counterpart. Finally, using several structural examples, the accuracy and robustness of the method is shown in terms of force–displacement response, stress fields, and traction continuity in nonlinear problems.

Determining failure properties of as-received and hydrided unirradiated Zircaloy-4 from ring compression tests

An integrated experimental and computational approach was developed to determine the plastic strain at fracture and to investigate the fracture energy of as-received and hydrided unirradiated Zircaloy-4 nuclear cladding tubes in the hoop direction at room temperature from ring compression testing (RCT). This work builds on previous methods in the literature that were developed to obtain the mechanical properties of nuclear cladding before fracture (Young’s modulus, yield stress, and strain-hardening parameters) from experimental RCT results and extends the characterization of this material class to include material failure properties. A ductile damage approach was developed and implemented in a validated finite element model to predict material failure, evaluate fracture energy, and quantify the plastic strain at fracture initiation. The hydrogen content of the Zircaloy-4 specimens was varied up to 610 wppm when the failure became brittle. As expected, increasing hydrogen content caused embrittlement of the Zircaloy-4 samples tested and the plastic strain at fracture and fracture energy to decrease

Thermal dissipation as both the strength and weakness of matter. A material failure prediction by monitoring creep.

In any domain involving some stressed solids, that is, from seismology to general engineering, the strength of matter is a paramount feature to understand. We here discuss the ability of a simple thermally activated sub-critical model, which includes the auto-induced thermal evolution of cracks tips, to predict the catastrophic failure of a vast range of materials. It is in particular shown that the intrinsic surface energy barrier, for breaking the atomic bonds of many solids, can be easily deduced from the slow creeping dynamics of a crack. This intrinsic barrier is however higher than the macroscopic load threshold at which brittle matter brutally fails, possibly as a result of thermal activation and of a thermal weakening mechanism. We propose a novel method to compute this macroscopic energy release rate of rupture, Ga, solely from monitoring slow creep, and we show that this reproduces the experimental values within 50% accuracy over twenty different materials, and over more than four decades of fracture energy.

Experimental and numerical analysis of PMMA impact fracture

The work presents experimental and numerical results on dynamic fracture of PMMA plates subjected to impact loading. The experimental tests were conducted using steel cylinder-shaped projectile accelerated using a gas gun. In order to evaluate performance of the tested specimens, residual impactor velocity was assessed using high-speed photography setup. Square-shaped PMMA specimens with three thicknesses were investigated using various projectile velocities. For all the three specimen types the ballistic limits were experimentally obtained. The conducted experiments were numerically simulated using finite element method with explicit time integration scheme and incubation time fracture model for the material failure prediction. Experiments with all three specimen configurations were successfully simulated using one parameter – incubation time, which was evaluated from existing experimental data on the dynamic fracture of PMMA. In addition to the simulations of the real experiments estimates on performance of a sample with a virtual geometry were made using the developed numerical approach.

An approximate method for the progressive failure analysis of a composite lattice rectangular plate

This paper defines in-plane displacement functions of a composite lattice rectangular plate, which is assumed to be a Kirchhoff-Love plate. It presents an approximate method based on the continuous model of conducting a progressive failure analysis for predicting material failure and post-failure behavior of the composite lattice rectangular plate with various boundary and load conditions. To define the approximate method, we use the Ritz method and Hashin’s failure criteria. The validity of the present method is verified by comparing the results of the finite element analysis. Finally, we perform parametric and sensitivity analyses to investigate the effects of the design parameters on the failure characteristics of the composite lattice rectangular plates based on the present method. The results allow a database to be obtained on the structural characteristics of composite lattice rectangular plates. Consequently, it is concluded that the present method is well suited to progressive failure analysis of composite lattice rectangular plates due to their relative simplicity and computational efficiency.

Numerical and experimental investigation of out-of-plane fiber waviness on the mechanical properties of composite materials

The limited capability to predict material failure in composite materials and specifically in wavy composite layers has led to high margins of safety for the design of composite structures. Thus, the full lightweight potential of this class of materials is left unused. To understand the complex failure behavior of composite materials containing out-of-plane fiber waviness under compressive and tensile loading, a non-linear 2D material model was implemented in ABAQUS and validated with extensive experimental test data from compression and tensile tests. Each test was recorded by a stereo camera system for digital image correlation to resolve damage initiation and propagation in detail. This study has shown excellent agreement of numerical simulations with experimental data. In a virtual testing approach various parameters, i.e. amplitude, wavelength and laminate thickness, have been studied. It was found that the failure mode changed from delamination to kink shear band formation with increasing laminate thickness. The wavelength has shown minor influences compared to amplitude and laminate thickness.

Workshop on Mathematical Challenges in Brittle Material Failure

The Army Research Office funded an invitation-only workshop entitled “Identifying Mathematical Challenges Associated with Failure of Brittle Materials” at the Johns Hopkins University, Maryland on May 20–21, 2019. The workshop brought together mathematicians, statisticians, and mechanics of materials researchers with diverse academic and research backgrounds to discuss the state-of-the-art in brittle material failure prediction and to identify new directions for future research. Three specific goals of the workshop were: (1) to identify the state-of-the-art for modeling failure of brittle materials (e.g., ceramics, glasses); (2) to discuss the major mathematical and statistical challenges experienced by academics and scientists studying brittle failure; and (3) to propose novel and unexplored research collaborations between mechanics researchers and mathematicians to address the identified challenges. By virtue of the Army Research Office’s interests and the expertise of participants, these three goals were broadly pursued within the context of understanding and predicting dynamic behavior of brittle materials. This document provides a summary of workshop presentations, discussions, and recommendations for future work (and research funding) that emerged from the workshop. The recommendations for future work are organized into four major thrusts: (i) defining robust quantities of interest; (ii) understanding and modeling variability and stochasticity; (iii) model parameter importance and calibration; and (iv) transitioning from discrete to continuum behaviors. For each thrust, specific future work discussed in the workshop is described in this article.

A Macroscopic Strength Criterion for Isotropic Metals Based on the Concept of Fracture Plane

Although the linear Mohr–Coulomb criterion is frequently applied to predict the failure of brittle materials such as cast iron, it can be used for ductile metals too. However, the criterion has some significant deficiencies which limit its predictive ability. In the present study, the underlying failure hypotheses of the linear Mohr–Coulomb criterion were thoroughly discussed. Based on Mohr’s physically meaningful concept of fracture plane, a macroscopic strength criterion was developed to explain the failure mechanism of isotropic metals. The failure function was expressed as a polynomial expansion in terms of the stresses acting on the fracture plane, and the quadratic approximation was employed to describe the non-linear behavior of the failure envelope. With an in-depth understanding of Mohr’s fracture plane concept, the failure angle was regarded as a generalized strength parameter in addition to the failure stress (i.e., the conventional basic strength). The undetermined coefficients of the non-linear failure function were calibrated by the strength parameters obtained from the common uniaxial tension and compression tests. Theoretical and experimental assessment for different types of isotropic metals validated the effectiveness of the proposed criterion in predicting material failure.

Graph theoretical approaches for the characterization of damage in hierarchical materials

We discuss the relevance of methods of graph theory for the study of damage in simple model materials described by the random fuse model. While such methods are not commonly used when dealing with regular random lattices, which mimic disordered but statistically homogeneous materials, they become relevant in materials with microstructures that exhibit complex multi-scale patterns. We specifically address the case of hierarchical materials, whose failure, due to an uncommon fracture mode, is not well described in terms of either damage percolation or crack nucleation-and-growth. We show that in these systems, incipient failure is accompanied by an increase in eigenvector localization and a drop in topological dimension. We propose these two novel indicators as possible candidates to monitor a system in the approach to failure. As such, they provide alternatives to monitoring changes in the precursory avalanche activity, which is often invoked as a candidate for failure prediction in materials which exhibit critical-like behavior at failure, but may not work in the context of hierarchical materials which exhibit scale-free avalanche statistics even very far from the critical load.