Cracking Events Research Articles

Fracture Behavior of a 2D Imine-Based Polymer.

2D polymers have emerged as a highly promising category of nanomaterials, owing to their exceptional properties. However, the understanding of their fracture behavior and failure mechanisms remains still limited, posing challenges to their durability in practical applications. This work presents an in-depth study of the fracture kinetics of a 2D polyimine film, utilizing in situ tensile testing within a transmission electron microscope (TEM). Employing meticulously optimized transferring and patterning techniques, an elastic strain of ≈6.5% is achieved, corresponding to an elastic modulus of (8.6 ± 2.5) GPa of polycrystalline 2D polyimine thin films. In step-by-step fractures, multiple cracking events uncover the initiation and development of side crack near the main crack tip which toughens the 2D film. Simultaneously captured strain evolution through digital image correlation (DIC) analysis and observation on the crack edge confirm the occurrence of transgranular fracture patterns apart from intergranular fracture. A preferred cleavage orientation in transgranular fracture is attributed to the difference in directional flexibility along distinct orientations, which is substantiated by density functional-based tight binding (DFTB) calculations. These findings construct a comprehensive understanding of intrinsic mechanical properties and fracture behavior of an imine-linked polymer and provide insights and implications for the rational design of 2D polymers.

Cyclic loading and unloading strain equations and damage evolution of gypsum specimens considering damping effects

This study aims to establish a strain instanton equation and damage factor evolution law for gypsum specimens by considering damping. First, damping energy is calculated based on the single-degree-of-freedom vibration model, and the instantaneous strain equation is obtained based on the stress balance equation. Second, the dissipation energy is divided into damping and damage energies, and a damage-factor correction algorithm is obtained. Third, cyclic loading and unloading tests were performed at different loading rates and stress amplitudes to verify the accuracy of the strain equation. Finally, the specimens’ magnitude curves and crack characteristics were monitored using moment–tensor acoustic emission simulations. The factors influencing the damping energy and strain equations, energy and damage evolution laws of the specimens, and damage patterns of the specimens at different loading rates were analysed. The results show that the instantaneous strain equation and the modified damage factor considering the damping effect can effectively reflect the deformation law and damage state of the specimens. In contrast, the damage to the specimens in the lower limit of the variable stress experiment was lower than that in the lower limit of the constant stress experiment. As the loading rate increases, the damage energy density of the specimen decreases, and the damage factor within a single cycle gradually decreases. As the loading rate increases, the number of crack events in the model increases significantly, size becomes more uniform, and sequentially exhibits dense and sparse distribution patterns, percentage of shear cracks decreases significantly, number of mixed cracks increases significantly, brittle behaviour of the specimen becomes obvious, and a complete damage state is attained known as the ‘crushed’ state. This study provides a theoretical reference for damage assessments of viscoelastic–plastic materials subjected to perturbing loads.

The failure evolution of hydraulic asphalt concrete under different tensile fatigue loading

The fracture and damage evolution patterns of hydraulic asphalt concrete (HAC) under cyclic tensile loading determine the performance of asphalt concrete impermeable structures in embankment dams under seismic loading. Therefore, in this study, the whole fatigue tensile damage process of HAC under different loading conditions was studied with the help of acoustic emission (AE) technique. The results indicated that the fatigue behaviors of the HAC and AE signals follow the same evolutionary pattern, experiencing the initial deformation stage, the stability stage, the acceleration stage, and the failure stage. The b value, obtained from the least square fit between AE event number and magnitude, decreases to its lowest point upon specimen failure, and this decrease corresponds to a sudden increase in the peak frequency of the AE. The parametric analysis of relative amplitude-average frequency values classified for different cracking modes revealed that the tensile cracking dominates during the fatigue damage process, while the proportion of shear cracking events increases during the failure stage. Moreover, the peak value of the proportion of shear cracking events appears within the range near the point of failure, making it a useful indicator for providing critical warnings of HAC fatigue damage.

Event identification in acoustic emission from wire breaks in pre-stressing/post-tensioning cables

Steel tendons commonly used in pre-stressed/post-tensioned concrete structural systems can lose cross-section due to corrosion, eventually leading to acoustic emission (AE) events when the stress exceeds the breaking strength of the wires that make up the tendons. Reliable differentiation of wire break AE events from traffic or grout crack events is critical for monitoring large structures, even where the distance between sensors may produce highly attenuated signals. In this paper, the Fuzzy c-means clustering algorithm was employed to differentiate AEs released from breaking wires of steel tendons from a database of 13464 AEs, including wire breaks, environmental and grout crack AEs. Wire breaks and grout crack AEs were collected from axial loading tests of grouted tendons in which the load increased until a wire broke. Environmental acoustic signals were collected from a bridge. Then all the collected AEs were gathered in a database and post-processed to simulate attenuation of up to 20 m from source to sensor. To optimize the speed and reliability of the Fuzzy c-means clustering algorithm, a non-dominated sorting genetic algorithm-II (NSGA-II) was used to find the minimum number of acoustic features needed. The NSGA-II algorithm started with 201 possible acoustic features and found 12 combinations of features that resulted in more than 80% wire break detection accuracy. In contrast, less than 3% of grout cracks and 0% of environmental signals were detected as wire breaks. The proposed method is suitable for deployment in a large sensor network and has sufficiently low-computational requirements for at-the-sensor processing, eliminating the need to send high-frequency sampled data outside the sensor node.

Wavelet entropy-based damage characterization and material phase differentiation in concrete using acoustic emissions

Damage evolution in concrete is a complex phenomenon involving micro-cracks that originate from different material phases (mortar matrix, ITZ and aggregate), and culminate into a major crack. The information about the individual damaged material phases can provide major insights into the global failure behaviour, cracking path, and fracture processes. The evolution of damage, damage mechanisms and the material phase of origin of micro-cracks is highly influenced by the type of concrete (Normal and high strength). In order to investigate the evolution of damage in concrete of varying strength, notched beam specimens with different water-to-cement ratios have been prepared and tested under CMOD control. The evolution and growth of damage have been continuously monitored during testing through acoustic emission techniques. Based on acoustic emission results, it has been demonstrated that the damage progression in concrete can be better described as a function of the wavelet entropy of the AE events occurring during the entire loading duration, and therefore, an analytical model for the damage evolution has been proposed. The study reveals that, under the high-strength category, the level of deterioration reduces as the w/c ratio rises, while in normal-strength concrete, a reverse trend is observed. Furthermore, a novel approach has been proposed that utilizes wavelet entropy and amplitude to differentiate amongst various damaged material phases with the help of an unsupervised clustering algorithm. Normal-strength concrete with a w/c ratio of 0.4 has been used to demonstrate the proposed methodology and has been validated with the help of experiments performed on the mortar and the parent stone of aggregate. A higher occurrence of mode-I cracks compared to mode-II cracks across all material phases has been observed for the specimen. Additionally, ITZ and aggregate exhibit a greater proportion of tensile and shear cracking events than the matrix phase. In the end, a deep learning convolutional neural network (CNN) model is devised utilizing labelled scalogram images of the AE waveforms to discriminate between the various damaged material phases. A 10-fold training cross-validation of the dataset has been carried out to achieve a stable performance. The deep learning model performs well in discriminating the damaged material phases with high training, validation, and testing accuracy.

Electrospun nanofiber interleaving through double infusion method to induce pseudo‐ductile damage resistance response in carbon/epoxy composites

AbstractCarbon composites are susceptible to invisible damage development such as matrix cracking, fiber kinking, and interfacial debonding upon external transverse loading. These incipient damages may interact to evolve into life‐limiting delamination propagating both in in‐plane and transverse directions. This study addressed that by interleaving carbon/epoxy composites with electrospun nylon 6 nanofibers adopting a double infusion method. Damage resistance results showed that the optimum nanofiber areal weight (17.35 g/m2) offered a 27% improvement in specific total toughness. The emergence of pseudo‐ductility substantially enhanced the plastic toughness (46.15%) of interleaved composites. The load required for initial matrix cracking was 65.49% higher, and number of matrix cracking events was suppressed by 84.11% at the optimum areal weight of interleave. Fractography revealed frequent interlaminar crossings and delamination crack bridging as two major toughness mechanisms. Both the external damage area and delaminated area increased with increment in nanofiber areal weight.Highlights Electrospun nanofibre interleaved carbon/epoxy composites were fabricated through a double infusion method to characterize damage resistance. Acoustic data of matrix cracking was rationalized to show the effectiveness of nanofiber interleaves in suppressing this damage type. Microstructural factors and mechanisms contributing to the improved toughness of optimally interleaved composites were identified. External damage/delaminated areas of interleaved composites were correlated with nanofiber areal weights.

Damage Detection combining Modal Analysis and Acoustic Emission in Concrete Structures

To ensure the structural stability of large infrastructure systems like concrete bridges, a range of measurement techniques are needed to identify and detect various types of damage or decay, including rebar corrosion, cracking, tendon failure, or alkali-silica reactions.In an experimental study, a progressively increasing point load was applied at the centre of a flipped-T-shaped concrete sample, inducing a reduction in mechanical stiffness. During the loading process, structural deformation and acoustic emission resulting from concrete crack formation were measured. Between the load steps, the unloaded structure was excited with an impulse hammer for a modal analysis. Therefore, accelerometers were attached at 24 sensor locations.At first, we assess the suitability of the individual methods in detecting, localizing and quantifying possible damage. As a second step we show correlations in the number and intensity of identified crack events, the change in eigenfrequencies of correlating mode shapes of the specimen and the size and location of optically identified cracks on the concrete surface.We conclude that the combination of different methods increases the reliability and quality of damage detection and localisation required for real-world application.

Stress distribution variations during nanoindentation failure of hard coatings on silicon substrates

Regarding quality inspection of technologically important nanocomposite hard coatings based on Ti, B, Si, C, and N and bioceramics such as hydroxyapatite that are used in small-scale high-precision devices and bio-implants, it is essential to study the failure mechanisms associated with nanoindentation, such as fracture, delamination, and chipping. The stress imposed by the indenter can affect the fracture morphology and the interfacial fracture energy, depending on indenter shape, substrate type, crystallographic properties, pre-existing flaws, internal micro-cracks, and pre-strain. Reported here are finite-element-based fracture studies that provide insights into the different cracking mechanisms related to the aforementioned failure process, showing that the fracture morphology is affected by the interaction of different cracking events. The interfacial fracture energy, toughness, and residual stress are calculated using existing models with minor adjustments, and it is found that increasing the indenter sharpness improves the shear stress distribution, making the coating more prone to separation. Depending on the prevailing type of stress, the stress distribution beneath the depression results in either crack formation or a dislocation pile-up leading to strain hardening. Different forms of resistances resulting from the indentation process are found to affect the tip–sample conduction, and because of its stronger induced plasticity than that of a Berkovich indenter tip, a sharper cube-corner tip produces more resistance.

Marine and lacustrine ice fracture detection

Ice fracturing has been extensively studied and modeled. With increased interest in ice mechanics and fracturing in recent years in climate science, fisheries, and for cultural impacts, detecting and classifying fracturing events has become an important problem to consider. Fractures primarily occur due to stress relief within an ice sheet during temperature shifts and ice movement. These events create mechanical waves within the sheet that couple into the water column which can then be detected as pressure and particle velocity fluctuations. Machine learning algorithms will be used to detect and classify ice cracking events though their acoustic signature. Different models will be compared to one another for effectiveness and accuracy. Data will be shown from several different locations, including Northern Alaska and the Great Lakes.

Static and fatigue cracking of thick carbon/glass hybrid composite laminates with complex wrinkle defects

This study presents an experimental investigation of cracking behavior of thick carbon/glass fiber hybrid composite laminates with manufacturing-induced ply wrinkles. Both pure glass fiber and glass/carbon fiber hybrid epoxy composite laminates are tested under static and cyclic tension. Stress–strain responses of the specimens under static tension are recorded and the failure sequences are identified. The cyclic loading is applied to the specimens under tension–tension fatigue. The stiffness degradation of the specimens is measured and the cracking events during the fatigue test are identified. The study shows that the glass/carbon fiber epoxy composite laminates first crack at a lower stress level than the pure glass ones despite their higher extension stiffness. The first cracking in the hybrid laminates occurs at the interface between different glass fiber layers while the first cracking in the pure glass laminates occurs between the rich region and the adjacent glass fiber layer in the wrinkled region. Under fatigue loading, the first cracking in hybrid laminates occurs within the carbon fiber layer while the one in the pure glass laminates occurs within the unidirectional glass fiber layer. This study also proposes a novel yet simple image difference analysis method, that by only using optical images of the specimens under fatigue loading, can accurately and efficiently pinpoint the stiffness drops at different fatigue cycles. This study provides new experimental insights into the failure of glass/carbon hybrid laminates toward a more damage-tolerant design.

Flexural toughness of extruded fiber-reinforced mortar with preferentially aligned fibers

This study explored the flexural toughness properties of polyvinyl alcohol (PVA) fiber-reinforced concrete (FRC) using a modified ASTM C1609 third-point bending test, and it established a comparative study between two methods of casting: traditional casting and pump-driven extrusion. The primary hypothesis posited that the extrusion process would promote fiber alignment parallel to the tensile stresses, thereby enhancing the flexural performance of the concrete. The study corroborated previous research findings that introducing fibers enhances the ductility and post-peak performance of the concrete. Moreover, this research introduced a unique observation that strategic fiber alignment through extrusion could serve to further enhance the concrete's flexural performance. The research employed digital image correlation to capture the full displacement field during testing, facilitating an examination of the crack propagation process and strain localization. The findings showed that the extrusion-based casting method improved the residual strengths by an average of 39% and 87% compared to conventional cast method for the 0.5% and 1% fiber volume specimens, respectively. Additionally, the base of the extruded specimens exhibited a greater incidence of crack initiation and displayed enhanced energy absorption through multiple cracking events. These observations underscore the concept that fiber alignment, when facilitated by extrusion, plays a significant role in influencing crack propagation and, consequently, in improving the flexural properties of the composite material.

Self-healing of transverse crack damage in carbon fiber composites

Laminated fiber-reinforced composites are susceptible to transverse cracking at relatively low stresses. These cracks cause a reduction in stiffness and can lead to premature and dangerous failure modes. Here, we investigate the self-healing efficiency of carbon fiber composites in isolated transverse crack events. The composites contain solvent-filled microcapsules in an epoxy matrix toughened with 20 wt% of thermoplastic poly(bisphenol A-co-epichlorohydrin) (PBAE). Self-healing is triggered upon release of the encapsulated solvent and subsequent transport of dissolved thermoplastic into the damaged volumes. Following solvent evaporation, redistributed thermoplastic re-bonds the crack faces to heal the damage. To evaluate self-healing efficiency, we develop a new protocol which leverages digital image correlation (DIC) to compare the stress required to open and re-open a transverse crack before and after healing. Self-healing is evaluated after 2, 4, and 6 days and compared to control specimens that are healed thermally. We report a self-healing efficiency of up to 57% after 6 days with just 1 vol% microcapsule concentration in a high glass transition temperature (179 °C) carbon fiber-reinforced composite.

Arrival-Time Detection With Multiscale Wavelet Analysis and Source Location of Acoustic Emission in Rock

In order to overcome the difficulties of traditional arrival time-picking techniques applied to Acoustic Emission (AE) events with low signal-to-noise ratio (SNR) and complex waveforms, this work proposed a new time-picking method. It combines the advantage of the wavelet transform technique, the ratio of Short-Term Average to Long Term Average (STA/LTA) method, and the Akaike Information Criterion (AIC), which is called the Wavelet-STA/LTA-AIC (WSA) picker. This work assessed the performance of picking arrival times of the WSA picker by locating the AE events from pencil-lead breaking on the marble panel (artificial sources) and tensile cracking sources on the granite. For all experiment results, the proposed WSA picker shows less location error compared with the AIC picker, regardless of geometry and source type. For location results of the pencil-lead breaking events on the marble panel, the average location errors are 1.4cm (AIC picker) and 0.6cm (WSA picker). For location results of the tensile cracking events on granite, the WSA picker is more concentrated in the region of the fracture surface and has fewer wrong-locating points at the specimen edge when compared with the AIC picker. It demonstrates that the proposed WSA picker can improve the accuracy and capability of AE location and be a viable method for arrival-time picking.

A machine learning model for predicting progressive crack extension based on experimental data obtained using DCPD measurement technique

A series of low cycle fatigue loading experiments were performed, using Inconel 718 (IN718) superalloy, to produce time history data using Direct Current Potential Drop (DCPD) approach at a range of temperatures and it was used to train a Bidirectional Long-Short Term Memory Neural Network (BiLSTM) model. The experimental investigations were conducted to understand the statistical nature of crack jumps during the fatigue loading. The BiLSTM model was trained on high sampling rate experimental data from crack initiation up through the Paris regime. For a single sample, the trained machine learning model was able to predict future crack events based on prior crack jumps in the time history. The model was able to predict the progressive crack extension at intermediate temperatures and stress intensities that lie between experimental conditions. The BiLSTM model demonstrated the potential to be used as a tool for future investigation into fundamental mechanisms such as high-temperature oxidation at the crack tips.

Hindered thermal warping triggers tensile cracking in the cores of compressed columns of a fire-loaded tunnel segment structure: Efficiency and accuracy of beam theory prediction, compared to FEM

The nonlinear Finite Element Method (FEM) is the current gold standard for the thermo-mechanical analysis of reinforced concrete structures. As an alternative, this paper is devoted to a model reduction strategy which reduces the CPU time by a factor of 500. This strategy combines Fourier series-based solutions for the thermal conduction problem, and thermo-elastic Timoshenko beam theory. Temperature histories known to be relevant for fire accidents enter series solutions quantifying the conduction of heat into a closed cell frame consisting of slabs, walls, and columns. Corresponding temperature profiles are translated into thermal eigenstrains. The latter are represented as the sum of three portions: (i) their cross-sectional averages (called thermal eigenstretches); (ii) their cross-sectional moments (called thermal eigencurvatures); and (iii) the remaining eigenstrain distributions (called eigenwarping). The latter portion is hindered at the cross-sectional scale, giving rise to non-linearly distributed self-equilibrated thermal stresses. The eigenstretches and eigencurvatures, in turn, are constrained at the scale of the frame structure. Together with external mechanical loads, they enter the exact solutions of thermo-elastic Timoshenko beam theory with equivalent cross-sections accounting for the different material properties of concrete and steel. Axial normal stresses, quantified from beam-theory-related normal forces and bending moments, are superimposed with the hindered-warping-induced stresses. These stresses agree well with corresponding results obtained by the nonlinear FEM. As regards the load carrying behavior of the columns, excessive thermal tensile strains at the periphery of the columns trigger, in the core of the columns, large tensile stresses which even exceed the strength of concrete. Respective cracking events are considered through reduced effective columnar cross-sections. Right after initiation of cracking, around 12min after the start of the heating process, the cracks propagate for some 30sec quite rapidly, and very much slower thereafter. If the initial cross-sections of the columns are increased, more pronounced hindered thermal warping, together with less quickly evolving compressive forces, results in earlier cracking. Overall, it is concluded that tensile cracking is the key material non-linearity, at least during the first 30min of the fire test, with maximum temperatures up to 300°C.

Ni/SiO2 catalysts for polyolefin deconstruction via the divergent hydrogenolysis mechanism

Noble metal-based hydrogenolysis is emerging as a key chemical deconstruction technology of polyolefins into valuable products. Still, the catalyst cost and availability are significant barriers to handling the large volume of plastics. Cheap earth-abundant metals have been deemed inactive for polyolefin hydrogenolysis. Herein, we report that Ni/SiO2 is active in deconstructing low-density polyethylene to n-alkanes (C6-C35) at mild conditions (300 °C, 30 bar H2) with maximum liquid yields of 65 wt%. We expose a new mechanism of long-alkane hydrogenolysis that encompasses chain location-dependent single and multiple C-C bond cracking events and rationalizes product selectivity and molecular weight dependence. Ni/SiO2 catalysts are reusable and can handle multiple plastics producing feedstock-dependent products (i.e., n-alkanes, iso-alkanes, cyclics, aromatics, etc.). The findings broaden the scope of viable catalysts polyolefin hydrogenolysis and unleash the potential to manage the volume of plastic waste.

Discrete Element Modelling of Cold Crushing Tests Considering Various Interface Property Distributions in Ordinary Refractory Ceramics.

The microstructures and local properties of ordinary refractory ceramic materials are heterogeneous and play a role in the fracture behavior of ordinary refractory ceramic materials. It is important to consider them in numerical modeling. Herein, the discrete element (DE) method was applied to determine the influences of heterogeneity of ordinary refractory ceramic materials by applying statistically distributed interface properties (uniform, Weibull), as opposed to constant interface properties, among the elements. Uniaxial cold crushing tests were performed as a case study. A reasonable loading strain rate for receiving quasi-static loading conditions and computation efficiency was evaluated. The loading wall displacement was recorded to present the stress-strain curves of cold crushing tests. Furthermore, the effects of the interface property distributions on the load/displacement curve, fracture energy, cold crushing strength, and fracture events were investigated. The results reveal that the DE method is a promising method for visualizing and quantifying the post-peak fracture process and crack events in ordinary refractory ceramics. Different interface property distributions contribute to significant variances in the load/displacement curve shape and fracture pattern. The heterogeneity of ordinary refractory ceramics can be further determined by comparing the experimental curves and fracture propagation along with an inverse identification approach.

Adaptive finite element method for hybrid phase-field modeling of three-dimensional cracks

Phase-field modeling of cracks in three dimensions (3D) is challenging due to expensive computational efforts caused by inefficient solution of non-linear governing equations as well as the requirement of extremely fine mesh for crack resolution. In this paper, a combination technique aiming at these two issues is presented. Firstly, a hybrid phase-field model is implemented in 3D with a simple and robust one-pass staggered solution scheme, yielding a linear system of governing equations which can be solved efficiently. Secondly, adaptive mesh refinement using the predictor-corrector algorithm is developed such that this hybrid model can be solved with minimal number of nodes. Numerical results show that computational cost of 3D phase-field modeling is dramatically reduced and complex crack events including initiation, mixed mode propagation, non-planar extension and twisting can be efficiently modeled with preferable robustness. Perfect agreement between numerical and experimental results on crack paths and application of the proposed method to the fracture of complicated engineering structures are demonstrated.

Multiscale modeling of hydrogenolysis of ethane and propane on Ru(0001): Implications for plastics recycling

Plastic waste presents an environmental threat. Chemical recycling via hydrogenolysis can convert plastic waste into waxes, lubricants, and fuels. Among catalysts, Ru stands out for its superior activity and selectivity. The chemistry of light alkane hydrogenolysis can help understanding plastics deconstruction. We perform first-principles calculations, develop descriptor-based relations, and conduct microkinetic modeling and analysis on ethane and propane. Predictions are in excellent agreement with experimental data. We identify a similar cracking pattern for both hydrocarbons entailing a deeply dehydrogenated species with the removal of four hydrogen atoms: CHCH* +* → 2CH* for ethane and CH3CCH* +2 * → CH3C* + CH* for propane. We find that the rate-determining step is the C-C cracking for ethane and the first dehydrogenation from the terminal carbon (CH3CH2CH3*+* → CH3CH2CH2*+H*) for propane. The vinyl species CH2CH* produced from propane cracking is responsible for whether a single or multiple cracking events occur and effectively controls the selectivity. Specifically, ethane formation in propane hydrogenolysis is suppressed at elevated temperatures due to over-cracking via multiple (two here) cracking events being preferred over hydrogenation and desorption of ethane from the catalyst. Our workflow and models provide a baseline for future studies on heavier hydrocarbons. Insights into recent experimental studies of polyethylene over Ru-based catalysts are discussed.

Chemical Recycling of Polystyrene to Valuable Chemicals via Selective Acid-Catalyzed Aerobic Oxidation under Visible Light.

Chemical recycling is one of the most promising technologies that could contribute to circular economy targets by providing solutions to plastic waste; however, it is still at an early stage of development. In this work, we describe the first light-driven, acid-catalyzed protocol for chemical recycling of polystyrene waste to valuable chemicals under 1 bar of O2. Requiring no photosensitizers and only mild reaction conditions, the protocol is operationally simple and has also been demonstrated in a flow system. Electron paramagnetic resonance (EPR) investigations and density functional theory (DFT) calculations indicate that singlet oxygen is involved as the reactive oxygen species in this degradation process, which abstracts a hydrogen atom from a tertiary C–H bond, leading to hydroperoxidation and subsequent C–C bond cracking events via a radical process. Notably, our study indicates that an adduct of polystyrene and an acid catalyst might be formed in situ, which could act as a photosensitizer to initiate the formation of singlet oxygen. In addition, the oxidized polystyrene polymer may play a role in the production of singlet oxygen under light.