Failure Process Of Materials Research Articles

Bending properties and damage evolution of fiber-reinforced aeolian sand backfill materials

Backfilling is a promising measure for controlling surface subsidence in mined-out areas and disposing solid wastes from the mineral processing, there are increasing demands of enhanced toughness and anti-cracking properties of backfill materials to prolong the service life under the complex loads. In this study, polypropylene (PP) fibers were employed to improve performance of backfills, four-point bending and uniaxial compression tests were conducted to investigate the failure process and damage evolution of fiber-reinforced aeolian-sand backfill materials (FABs) using Digital Image Correlation (DIC) and Acoustic Emission (AE) techniques. The results show that the compressive strength tends to decrease with the increasing fiber volume fractions, while the four-point bending strength shows a tendency to increase initially and then decrease, and the optimum volume fraction of PP fiber is 0.6%. At the optimal fiber volume fraction, PP fibers with lengths of 3 mm and 9 mm resulted in a 65.25% and 81.62% increase in the four-point bending strength of FABs, respectively. As indicated by DIC measurements, PP fibers with a length of 9 mm were more effective in controlling the horizontal and vertical displacements of FABs under four-point bending loads than that of 3 mm, and the cracks developed more slowly at the same deflection. In addition, PP fibers with a length of 9 mm have stronger crack extension delay characteristics due to longer effective anchorage distance, as evidenced by more frequent acoustic emission ringing counts and higher cumulative ringing counts. The results of the study may provide a theoretical basis for the application of FABs materials in backfilling.

A self-consistent void-based rationale for hydrogen embrittlement

Solely based on the failure process of metallic materials containing voids, we propose a straightforward rationale for a self-consistent void-based hydrogen embrittlement (CVHE) predictive framework that effectively captures ductile failure, hydrogen-induced loss of ductility, and most importantly, the ductile-to-brittle transition. While the coupling effect of homogenously distributed secondary voids is well-documented, the rigor of our approach lies in the precise definition of an array of equally sized and spaced secondary voids nucleated aligning with the hydrogen embrittlement mechanisms HEDE, HELP and HESIV, in the ligament between primary voids. The CVHE model can quantitatively predict the full range of embrittlement; it naturally reveals the brittle inter-ligament decohesion associated with an intrinsic lower bound of ductility, when the secondary voids are sufficiently small. Counterintuitively, our results show that ductility reduction accelerates with a decrease in the secondary void volume fraction, and that smaller voids lead to greater embrittlement.

Data-driven bio-mimetic composite design: Direct prediction of stress–strain curves from structures using cGANs

Designing high-performance composites requires integrating tasks, including material selection, structural arrangement, and mechanical property characterization. Accurate prediction of composite mechanical properties requires a comprehensive understanding of their mechanical response, particularly the failure mechanisms under high deformations. As traditional computational methods struggle to exhaustively explore every composite configuration in the vast design space for optimal design search, machine learning offers rapid identification of optimal composite designs. This study presents a cGAN-based deep learning model for predicting stress–strain curves directly from composite structures using an image-to-vector approach. The model incorporates fully connected layers within a U-Net generator for stress–strain curve generation and utilizes a PatchGAN discriminator for realism assessment. This end-to-end mapping from structures to mechanical response effectively eliminates the need for extensive simulations and labor-intensive post-analyses. Phase-field simulations were conducted to model the material failure process, generating stress–strain curves for various composite structures used as ground truth data to train and test the surrogate model. This study incorporates various composite structures in the dataset, including random (RS), layered (LS), chessboard-like (CS), soft-scaffold (SS), and hard-scaffold (HS), enhancing the representation of design diversity. Despite being trained on a limited dataset (approximately 1.5% for each bio-mimetic structure and 10−72% for RS composites), the model achieves highly accurate predictions in stress–strain curves, with MAE loss converging to 0.01 for training and 0.05 for testing after 2 million iterations. High evaluation scores on training data (R2>0.997, MAPE <1.08%) and testing data (R2>0.946, MAPE <5.53%) demonstrate the model’s accuracy in predicting mechanical properties such as Young’s modulus, strength, and toughness across all composite structures. Overall, the study provides a proof of concept for using machine learning to simplify the design process, demonstrating its potential for solving inverse composite design problems.

Summary of Rock Damage Mechanics Classification

As an important means to study the mechanical properties and failure mechanism of rock materials and engineering mechanics, damage mechanics is often used to assist in the analysis of the failure process and mechanism of rock, metal, and other materials in the current research. In the use of damage mechanics to study the properties of rock materials and explore the deformation and failure law of rock, important research results have been achieved. The research methods of damage mechanics can be roughly divided into three types: statistical damage model, mesoscopic damage model, and continuous damage model. Based on the existing literature in hand, according to the division of damage mechanics research methods in the academic community, this paper collates and considers that the existing damage model construction can be summarized from the mechanical point of view. The pure theory is derived or fitted from the mathematical point of view. One of them is derived from the mechanism point of view, and the other is derived from the phenomenon point of view. The stress, strain, acoustic emission, and other data are analyzed and reconstructed, and both have advantages and disadvantages.

Strength-induced Peridynamic model for the dynamic failure of porous materials

Predicting the dynamic failure process of porous materials is a challenging task due to their complex structure. To minimize the use of time-consuming peridynamic (PD) models and to avoid surface effect issues in the dynamic failure of complex porous materials, this paper proposes a strength-induced PD model. The paper first presents the dynamic formula and relevant finite element discrete equation of the coupled PD and classical continuum mechanics (PD-CCM) model based on the Morphing method. The Morphing function is implemented to control the material parameters and enable the free transformation of PD and CCM models. Based on the coupled PD-CCM model, the strength-induced PD model is established to adaptively expand the PD subdomain in porous materials by controlling the Morphing function value through the strength state of the structure. This model enables the PD subdomain to appear automatically when the porous materials reach the critical stress state. The proposed model accurately predicts the location of crack initiation and path while minimizing computational costs and improving efficiency. Three two-dimensional numerical examples are used to verify the effectiveness, efficiency, and accuracy of the model. The results of the simulation suggest that the location where the crack initiates in the porous materials is strongly influenced by the amplitude of the dynamic load. Cracking is dependent on the pores and typically occurs through them.

Cross-scale deciphering thermal failure process of Ni-rich layered cathode

Ni-rich LiNixCoyMn1-x-yO2 (NCM) layered oxides are low-cost high-energy density cathode materials, but plagued by its poor thermal stability incurred safety concerns. The thermal failure process of the layered cathode is accompanied by heat generation and oxygen release, which drives the battery into thermal runaway (TR). Aiming to fully understand the TR process and the structure evolution, this work applies diverse characterization techniques onto a polycrystalline Ni-rich layered cathode (LiNi0.83Mn0.05Co0.12O2 (PCN83)) to comprehensively investigate its thermal failure process at multiple scales. From macro level, we validate that it is the cathode thermal failure that drives the battery from the heat accumulation stage into TR in adiabatic conditions. From micro level, transmission electron microscopy (TEM) verifies that the thermal failure of PCN83 starts from 150 °C, which is much lower than the TR temperature measured from macro level tests. We reveal that the PCN83 cathode experiences sequential phase transitions before the TR, where the phase transition mechanism is illustrated from the atomic scale and the pore evolution process is unraveled. In situ heating TEM further reveals that thermal failure is preferentially initiated from grain boundaries and defect regions. These findings provide an in-depth understanding of the whole thermal failure process of NMC-based layered cathode materials and sheds new lights on the rational design of Ni-rich cathode materials with improved thermal safety.

Effect of temperature and moisture composite environments on the mechanical properties and mechanisms of woven carbon fiber composites

AbstractTemperature and moisture are important environmental conditions governing the usage of carbon fiber‐reinforced plastics (CFRP). In this study, tensile, compression, and shear tests of woven CFRP composites were conducted in four composite environments: cold‐temperature dry state, room‐temperature dry state, elevated‐temperature dry state, and elevated‐temperature wet state. Fourier transform infrared (FTIR) spectroscopy was used to analyze the molecular composition and structure under these environments. The fracture morphology was also analyzed using scanning electron microscopy (SEM) to understand the deterioration mechanism of the material properties at the macro and micro scales. Finally, a two‐parameter Weibull statistical model was used to evaluate the scattering of the composites. The results demonstrate that the tensile, compressive, and shear properties of the material decrease under harsh conditions, and the degradation effect on the ultimate strength is much greater than that of the modulus. Cold‐temperature dry and elevated‐temperature wet conditions are particularly severe. Composite environments significantly affect the macroscopic failure process and ultimate failure mode of materials. In general, the temperature and humidity of the matrix system acts at the core of the deterioration mechanism of composites, affecting the properties of the fiber/matrix and orthogonal woven fiber interfaces, and eventually resulting in a loss of their constitutive strength and bearing capacity. The theoretical ultimate strength were consistent with the experimental values.Highlights Comprehensive mechanical property testing in multiple composite environments. Degradation mechanisms were revealed from multiscale morphology analysis. Scattering of composites were evaluated using statistical analyses. Cold temperature dry and elevated temperature wet were the worst states. Deterioration effect of environment on matrix and interface is the core failure mechanism.

Nonlinear effect of rigidity and correlated disorder on network fracture

Mechanical rigidity and disorder are two important parameters that influence the failure process of solid materials. We investigate the nonlinear mechanics under their coupled effect as well as the influence of disorder’s spatial correlation with 2-D network model. The strain–stress relations present strong nonlinearity and rigidity regain phenomenon when there is strong disorder and high rigidity. The correlation of disorder would weaken the effect and has a great influence on the peak stress, initial stiffness, and system toughness. The crossover of power-law exponents of avalanches is observed with consideration of disorder and the transitions in the cluster distribution induced by correlated disorder disappear as the system rigidity decrease. We conclude that although the disorder can be seen as a reduction of average coordinated number for small rupture thresholds system, the correlated disorder still has a great influence on the failure behaviors of heterogeneous materials.

Peridynamic model of ECC-concrete composite beam under impact loading

Engineering cement-based composite materials (ECC) are widely used for strengthening concrete structures and resisting impact loads. However, the impact failure process of materials involves the material discontinuity. To address this issue, this paper constructs a fully discrete model of ECC concrete composite beams under impact loads based on peridynamics (PD). In this model, the cement matrix is described using an exponential model, while the fibers are modeled using PD rods. The interaction between the fibers and the matrix is described based on the classical exponential friction attenuation model, while considering failure criteria based on strain rate effects. Finally, by employing the established model, the effects of impact velocity, fiber volume fraction, ECC layer thickness ratio, and fiber length on the impact performance of ECC concrete composite beams were investigated. Results showed that impact velocity affects the damage evolution and crack propagation mode of the composite beams by affecting the dynamic critical elongation of PD bonds. The fiber volume fraction, ECC layer thickness ratio, and fiber length all have important effects on the ductility and energy absorption capacity of composite beams.

Identification of Destruction Processes and Assessment of Deformations in Compressed Concrete Modified with Polypropylene Fibers Exposed to Fire Temperatures Using Acoustic Emission Signal Analysis, Numerical Analysis, and Digital Image Correlation.

This article presents the results of tests conducted to identify the failure process and evaluate the deformation of axially compressed concrete specimens modified with polypropylene fibers (PP). The test specimens were previously stored at ambient temperature and subjected to fire temperatures of 300 °C, 450 °C, and 600 °C. Acoustic emission (AE) signals were recorded during loading, along with force and strain measurements. The recorded AE signals were analyzed using the k-means clustering method. The compilation of the test results made it possible to determine the classes of signals characteristic of different stages of the material failure process and to indicate the differences in the failure mechanisms of specimens stored under ambient conditions and subjected to fire temperatures. Digital image correlation (DIC) measurements were conducted during the strength tests. A numerical model of the material (FEM) was also prepared, and a comparison of the obtained results was carried out.

Development of 1D bounding surface model for lattice spring model on predicting rock failure under cyclic loading

A sound interpretation of the deformation and failure of rock material subjected to cyclic loadings is of great importance when predicting the long-term stability of rock structures. The bounding surface model is generally utilized to depict the mechanical behaviour of rock subjected to cyclic loadings. In this work, a simplified 1D bounding surface model is developed into a 4D lattice spring model (4D-LSM) to predict rock failure under cyclic loading. To better represent the nonlinear behaviour of rock material, a microcrack model is also introduced in the simplified 1D bounding surface model, together with a macro strength criterion and a cohesive zone model to represent the failure process of the rock. GPU-based parallel computing is realized to accelerate the time-consuming numerical simulation. The numerical results indicate that the proposed model reproduces the deformation and failure process of rock material under different cyclic loading paths. Moreover, the fatigue life of the rock under different conditions is predicted, including different stress levels, confining stresses, and preexisting macro joints. These numerical results reveal that the simplified 1D bounding surface model not only satisfactorily describes the mechanical response of rock under cyclic loading (like in classical continuum-based constitutive models) but also shares the advantage of the discrete-based numerical model in modelling the fracture and failure processes of rock under cyclic loading. This approach could also be used in other discrete numerical models, such as the discrete element model (DEM).

Porous single crystals under triaxial creep loadings: A data-driven modelling approach

The evolution of porosity plays an important role during failure processes in metallic materials at room and elevated temperatures. Recent experiments showed that void growth and coalescence may lead to the creep rupture of single crystal materials, mainly through plastic flow. It is highly challenging to accurately model the combined effects of multiple controlling factors, such as crystal orientation, matrix hardening behaviour, void shape and stress state. In this work, a neural network surrogate model was constructed to predict the behaviour of single crystals containing voids under creep loadings. Training of the neural network model was performed using 3D micromechanical finite element simulation results. A detailed assessment was carried out to examine the interpolation ability of the neural network model with respect to the crystal orientation, stress triaxiality and Lode parameter, as well as its extrapolation ability. Within the interpolation range, the neural network predictions of the deformation behaviour and porosity evolution of porous single crystals agree well with the finite element results of test dataset. The characteristic quantities, including the effective steady state strain rate, critical time and effective strain for the onset of tertiary creep, were predicted within 20% error with respect to the micromechanical simulation results for most of cases considered. Finally, the extrapolation ability of the model in predicting deformation behaviour of porous single crystal is good for the stress triaxiality lower than 1/3. However, the prediction of deformation and void evolution is deteriorated for the stress triaxiality larger than the range of value used for the training.

Artificial neural network potentials for mechanics and fracture dynamics of two-dimensional crystals ** ** Notice: This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license

Understanding the mechanics and failure of materials at the nanoscale is critical for their engineering and applications. The accurate atomistic modeling of brittle failure with crack propagation in covalent crystals requires a quantum mechanics-based description of individual bond-breaking events. Artificial neural network potentials (NNPs) have emerged to overcome the traditional, physics-based modeling tradeoff between accuracy and accessible time and length scales. Previous studies have shown successful applications of NNPs for describing the structure and dynamics of molecular systems and amorphous or liquid phases of materials. However, their application to deformation and failure processes in materials is still uncommon. In this study, we discuss the apparent limitations of NNPs for the description of deformation and fracture under loadings and propose a way to generate and select training data for their employment in simulations of deformation and fracture simulations of crystals. We applied the proposed approach to 2D crystalline graphene, utilizing the density-functional tight-binding method for more efficient and extensive data generation in place of density functional theory. Then, we explored how the data selection affects the accuracy of the developed artificial NNPs. It revealed that NNP’s reliability should not only be measured based on the total energy and atomic force comparisons for reference structures but also utilize comparisons for physical properties, e.g. stress–strain curves and geometric deformation. In sharp contrast to popular reactive bond order potentials, our optimized NNP predicts straight crack propagation in graphene along both armchair and zigzag (ZZ) lattice directions, as well as higher fracture toughness of ZZ edge direction. Our study provides significant insight into crack propagation mechanisms on atomic scales and highlights strategies for NNP developments of broader materials.

A probabilistic constant amplitude life diagram modeling method for composite materials considering spatial mapping relation

AbstractConventional constant amplitude life diagrams (CLDs) model cannot reasonably describe mean stress effect and stochastic uncertainty present in the fatigue failure process of composite materials. To address this problem, taking the spatial mapping relationship between probabilistic S‐N curves and probabilistic CLD model as an entry point, a probabilistic CLD modeling method is proposed under the assumption of linear equations and the assumption of equiprobable quantile point between static strength distributions and fatigue life distributions. The p‐S‐N curve is established using fatigue test data from different load zones divided by different stress ratios.Subsequently, the p‐CLD model is derived through the spatial mapping relationship of the p‐S‐N curve. The method is validated by fatigue test data of glass fiber/polyester resin composites. The results indicate that the proposed method can offer an accurate description of the probabilistic behavior of composite materials.

Effect of Braid Angle on Crushing Performance of Double-Layer Carbon Fiber Composite Pipe

Three-dimensional braided composite materials have the advantages of high specific strength and good specific rigidity, they are widely used in various fields. With the help of the full-scale macrostructure model finite element analysis method to pre-test the mechanical properties of the axial compression, the simulation can observe the failure process, stress distribution and propagation form of the pipe, and study its failure mechanism. Then verify the correctness of the simulation through experiments. The conclusion is that the compressive performance of the material changes with the change in the braid angle. A smaller braiding angle can bear a larger load, but its material failure process is relatively rapid, and the load drop increases as the braiding angle decreases.

Micro-mechanical damage simulation of filament-wound composite with various winding angle under multi-axial loading

With the application of Filament Wound Composites (FWC) in the market, the general model for composites with different process parameters is urgently needed. In this paper, a generalized full-scale 3D finite element model (FEM) is established considering the fluctuation and lamination characteristics of FWC fiber arrangement. The Generalized Method of Cell (GMC) is embedded into the commercial FEM code of ANSYS as user-defined subroutine (UMAT) to obtain the micromechanics of the component materials and the macro-structural scale and the micro-structural scale are thus linked. For the damage analysis, three different failure criteria are used to explore the failure process of materials under different loads. The comparison of the predicted results with the experimental results shows that the simulation method can reflect the progressive damage of FWC under different loading conditions well. Furthermore, the effects of the winding angle on the mechanical properties of FWC under different loads are also investigated. The results show that the modulus and strength of the material decrease as the angle increases under pure tensile loading, and both the modulus and strength reach the maximum when the winding angle is 45 under torsional loading. Under tensile-torsional loading, the maximum strength value of the material is related to the tensile-torsional stress ratio.

Experimental-theoretical comparative analysis of PLA-based 3D lattice

Lattice materials are one of the most desirable and widely used materials due to the characteristics derived from their geometrical formation as opposed to their chemical composition. In this article, a lattice material has been designed and printed using polymer filament wire made of polylactic acid (PLA) and fused deposition modelling (FDM), followed by mechanical testing. In addition, tensile testing of the PLA printed samples has also been carried out to ascertain the tensile properties of the material in use, and the material has shown 38–40 MPa tensile strength with a Young’s modulus value of 1538 ± 120 MPa. The lattice was designed using 3D CAD software, and numerical results were obtained using the Autodesk Inventor simulation module. In addition to the experimental test, theoretical tests were also conducted, and the results were compared to the experimental results. With this methodology, the lattice material failure process can be comprehended. Along with the lattices, the PLA tensile test samples were also prepared and tested to check the feasibility of the PLA being used and ascertain the properties. In addition, it has been observed that after a specific load and deformation, the material’s resistance increases due to its increased density and repeated cell interference. The major purpose of the study is to explore the aspects and feasibility of the PLA printed lattice material with complex shapes and explore the application potential of such shapes.

Macroscopic Mechanical Properties of Brittle Materials with a 3D Internal Crack Based on Particle Flow Simulations

Pre-existing cracks significantly influence the macro-mechanical properties of rock. The macro-mechanical properties and crack propagation process of brittle materials with a 3D internal crack were investigated with PFC3D simulation in this paper. To determine the micro-parameters, the influence of micro-parameters on the macro-mechanical properties and ultimate failure mode was discussed. SJM’s parameters had little influence on the macro-mechanical properties and ultimate failure mode. Peak axial stress was changed greatly by strength parameters and friction coefficient, and the macro-elastic modulus was influenced greatly by Young’s modulus and changed slightly with other parameters. The failure mode changed gradually with all micro-parameters except Young’s modulus, which had a strong but irregular impact on it. The peak stress was 138 MPa in the simulation of the sample with a 3D internal crack, which agreed well with the experimental result (137 MPa). The crack propagation process can be divided into three stages: 17% of total crack was generated in the initial stage; 76% of the total crack was propagated when main failure surface coalesced; finally, the failure surface expanded downwards and caused the sample to be destroyed. Cracks initially appeared near the end of the lower major axis of the internal crack, which was in agreement with experimental results. The results demonstrated that PFC3D is a reliable method to simulate the failure process of brittle materials with internal cracks.

A new quasi-brittle damage model implemented under quasi-static condition using bond-based peridynamics theory for progressive failure

A novel quasi-brittle damage model implemented under quasistatic loading condition using bond-based peridynamics theory for progressive failure is proposed to better predict damage initiation and propagation in solid materials. Since peridynamics equation of motion was invented in dynamic configuration, this paper applies the adaptive dynamic relaxation equation to achieve steady-state in peridynamics formulation. To accurately characterise the progressive failure process in cohesive materials, we incorporate the dynamic equation with the novel damage model for quasi-brittle materials. Computational examples of 2D compressive and tensile problems using the proposed model are presented. This paper presents advancement by incorporating the adaptive dynamic equation approach into a new damage model for quasi-brittle materials. This amalgamation allows for a more accurate representation of the behavior of damaged materials, particularly in static or quasi-static loading situations, bringing the framework closer to reality. This research paves the way for the peridynamics formulation to be employed for a far broader class of loading condition behaviour than it is now able to.

An Ordinary State-Based Peridynamic Model of Unidirectional Carbon Fiber Reinforced Polymer Material in the Cutting Process

Due to the complexity of the composite structure, analyzing the material failure process of carbon fiber reinforced polymers (CFRP) is fairly difficult, particularly for the machining process. Peridynamic theory, a new branch of solid mechanics, is a useful tool for dealing with discontinuities. This study presents an ordinary state-based peridynamic (OSB-PD) model for unidirectional CFRP material in the cutting process. In this model, angle tolerance is used to overcome the fiber angle limitation in a classical OSB-PD laminate method, and the short-range force approach is utilized to simulate the contact of the cutting tool and workpiece. The effectiveness of the supplied models is validated by tension and cutting tests. Finally, it can be indicated that the OSB-PD model is capable of predicting machined surface damage and cutting force, based on the comparison of simulation and experimental data.