Internal Damage Research Articles

Fracture evolution characteristics of asphalt concrete using digital image correlation and acoustic emission techniques

The cracking damage of asphalt concrete significantly affects the service life of pavement. The objective of this research is to investigate fracture mechanisms of asphalt concrete by employing a synergistic approach combining digital image correlation (DIC) and acoustic emission (AE) techniques under three-point bending tests. Firstly, the crack tip opening displacement (CTOD) and the fracture process zone (FPZ) derived from DIC were utilized to classify fracture stages and describe the entire crack propagation process. Meanwhile, AE-related parameters were applied to detect the internal damage and fracture characteristics. Subsequently, the results from DIC and AE were utilized for comparative analysis to evaluate the cracking resistance of different materials. Finally, the fractal dimension and AE b-value were used to distinguish the characteristics of the critical damage conditions. The results indicated that both techniques are effective in classifying the fracture stage of asphalt concrete. DIC can visualize and analyze crack propagation processes and paths on concrete surfaces, especially at the stage of macrocrack initiation and propagation. AE allows for continuous monitoring and highly sensitive detection of early-stage damage inside concrete. The distinct advantages of DIC and AE result in different fracture stage identification results at the early stage, but consistent after the appearance of macrocracks. Based on the relationship between CTOD and AE cumulative count, a simple approach is proposed to directly evaluate the cracking resistance of different asphalt concretes. The formation of macrocracks in asphalt concrete can be reflected by a shift where the correlation dimension drops steeply to the minimum value, and a minimum inflection point in the AE b-value curve acts as a precursor of complete fracture. The research offers an in-depth insight of both surface deformation and internal damage, thus enhancing the understanding of crack growth behavior and fracture process in asphalt concrete.

Bridging the Gap: Correlating Ultrasonically Quantified BVID with the Compressive Strength of CFRP Composites

ABSTRACT Carbon fiber laminates are susceptible to impact damage due to the lack of fibers in the direction of impact. Often such damage can be difficult to find with visual assessment, prompting the need for detection via nondestructive testing techniques. This study quantifies the ultrasonically characterized impact damage diameters in 22 layered CFRP samples from 16 J, 18 J, 20 J, 22 J, and 24 J impact energies. These energies result in damage often defined as barely visible impact damage. This study utilizes x-ray computed tomography as a baseline to verify the results of the ultrasonic testing. Compression after impact test measurements are used in this study to find the ultimate compressive residual strength of the impacted carbon fiber laminates and to investigate the negative correlation between impact energy and residual mechanical properties of the damaged carbon fiber laminates. Many studies focus on the characterization of impact damage from various impact energies and setups via ultrasonic testing or, separately, the effect of the impact setups on the residual strength of the composite. This study strengthens the bridge between the barely visible impact damage quantified via ultrasonic testing and the residual compressive strength of the affected composite. Overall, this paper offers further insights into the relationship between internal damage size obtained using ultrasonic testing and correlates the characterized internal damage geometry to the resultant compressive strength reduction, providing a path for future studies in predictive modeling of the residual strength after impact.

Unsupervised machine learning classification for accelerating FE[formula omitted] multiscale fracture simulations

An approach is proposed to accelerate multiscale simulations of heterogeneous quasi-brittle materials exhibiting an anisotropic damage response. The present technique uses unsupervised machine learning classification based on k-means clustering to select integration points in the macro mesh within an FE2 strategy to track redundant micro nonlinear problems and to avoid unnecessary Representative Volume Element (RVE) calculations. More specifically, a classification vector including strains and internal damage variables is defined for each macro integration point. The macro internal damage variables are constructed using harmonic analysis of damage. At each step of the macro iterations, the integrations points are grouped into clusters and only one nonlinear problem is solved for each cluster. As a result, the computations are accelerated within an FE2 scheme by reducing the total number of RVE problems to be solved. The developed algorithm includes a macro regularization and an arc-length technique to capture macro snap-back due to the softening. Applications are proposed to simulate the response of different heterogeneous quasi-brittle materials with strong anisotropic responses. speed-up factors of the order of 12 to 15 can be achieved without the need to build a database, and without reduced-order modeling approximations at the micro level. Estimates of structural strength can be obtained with Speed-up factors between 45 and 85.

A Review of Experimentation Numerical Simulation of Low-Velocity Impact Performances and Damages of Fiber-Reinforced Composites

Fiber-reinforced composites (FRCs) are extensively utilized in various industries due to their lightweight and high-strength properties, making the understanding of their response to low-velocity impact (LVI) crucial for ensuring structural integrity, performance and invisible internal damages that can compromise performance and safety. This paper critically examines the current state of research on the low-velocity impact behavior of FRCs, focusing on both experimental and numerical simulation approaches. The review comprehensively surveys on characterizing and modeling the response of FRCs to low-velocity impacts leading to damages. The effects of parameters including composites preparation; impact mechanics; testing methods; induced damages including assessment methods; different performance parameters including impact energy, force, load, impact resistance; post-impact damages and their resistance; performance and damage affecting different factors; numerical and simulation modeling are discussed. Current challenges and future prospects regarding the subject matter is highlighted. The comprehensive analysis presented in this review goals to consolidate current knowledge, identify research gaps, and guide future endeavors in enhancing the understanding of low-velocity impact (LVI) behavior in fiber-reinforced composites (FRCs).

Physiological Responses to Acute Heat Stress in Rohu, Labeo rohita: Insights from Liver Proteomics.

Heat stress is a major problem in aquaculture species, causing changes in physiology such as decreased feed intake, growth rate, reproduction, and internal cellular damage, thereby affecting fish's health. The effects of an acute heat stress simulating a daily rise and fall in temperature on summer days were evaluated in the liver proteome of rohu (Labeo rohita) fingerlings in the present study. The fish maintained at 30°C were gradually exposed to a higher temperature of 36°C at an increment rate of 1°C per 1.5h, and after 3h at that temperature, it was gradually reduced to 30°C. The liver tissue samples were collected at 5 am, 5pm, and 5 am the next day from the exposed and control fish. Protein samples were prepared from the liver tissues, and the extracted proteins were compared using 2-dimensional (2D) gel electrophoresis (2DGE) and mass spectrometry (MS) using a MALDI-TOF/TOF mass spectrometer. A total of 44 differentially expressed protein spots were visualized in 2D gel analysis from heat stress exposed fish at three time points, out of which 21 proteins including one hypothetical protein could be identified by MS. The abundance of five selected differentially expressed proteins (DEPs) was validated using qPCR. The majority of DEPs were found to be involved primarily in lipid, protein and energy metabolism, immune system regulation, cytoskeletal stability, and ROS management. The findings of this study would help in the development of strategies to mitigate heat stress in L. rohita.

Understanding Structural Changes in Recycled Aggregate Concrete under Thermal Stress

Objective: This study investigates the influence of high-temperature treatment on the deformation properties and structural deformation of recycled aggregate concrete (RAC) in response to potential fire hazards in the construction industry. Methods: Standard-cured 28-day RAC specimens were subjected to microwave heating at 300 °C and 600 °C, with subsequent uniaxial compression tests utilizing a WDW-2000 machine and a VIC 3D strain measurement system to analyze strain data through digital image correlation (DIC) technology. Results: After treatment at 300 °C, recycled aggregate concrete (RAC) demonstrated superior mechanical properties to fresh concrete aggregates. This enhancement may be attributed to the more robust siloxane bonds (Si-O-Si) in the recycled materials. Conversely, exposure to 600 °C intensified internal structural damage, notably lowering the material’s elastic modulus and peak stress. DIC analysis highlighted the correlation among temperature, volumetric strain, and crack development patterns, with more extensive cracking at 600 °C. Conclusions: Moderate-temperature treatment enhances RAC’s structure and deformation properties, while high-temperature treatment diminishes its performance. These findings provide valuable insights for assessing building safety post-fire and the application of RAC, emphasizing its suitability at moderate temperatures and risks at high temperatures.

A recycled crushed rock sand mortar based on Talbot grading theory: Correlation of pore structure and mechanical properties

The use of crushed rock sand (CRS) as a substitute for natural sand is a necessary and feasible approach to address depletion of natural sand resources. This study investigated the effect of CRS aggregate gradation, based on Talbot grading theory, on pore structure and mechanical properties of mortar. 10 CRS mortars with different Talbot gradations were prepared, and quantitative relationships between Talbot gradation, pore characteristics (size distribution, fractal dimensions, and pore connectivity), acoustic emission (AE) characteristics, and compressive mechanical properties were analyzed using nuclear magnetic resonance (NMR) and AE techniques. The optimal Talbot index value was determined to be 0.4, based on the observed changes in pore structure and mechanical properties. Furthermore, the influence of Talbot index on internal damage process of CRS mortar was analyzed in conjunction with AE characteristics, and a prediction model for mortar strength was established based on porosity and AE cumulative counts. The correlation between pore structure, AE characteristics and mechanical properties of CRS mortar under Talbot grading was systematically investigated, which provides theoretical support for optimal design of CRS mortar materials. The application of Talbot grading theory in design of mortar is explored to provide a scientific basis for improvement of mortar engineering performance.

Seepage-stress coupling characteristics of initial damaged glass fiber reinforced concrete under different loading conditions

Different loading methods induce variations in the macroscopic performance of the specimens. In this investigation, experiments were conducted on glass fiber reinforced concrete subjected to varying degrees of damage. Initially, axial compression loading and unloading were performed, followed by continuous axial compression loading. The study elucidates the evolution of permeability and strength characteristics of specimens under these two loading regimes. The experimental results delineate the trend of permeability and its corresponding strength attributes under complex stress paths. It was observed that during the axial compression loading and unloading phases, the permeability of the specimens follows a negative exponential function. As axial pressure increases, internal pores within the specimens were compacted, leading to a reduction in seepage pathways and a significant decline in permeability. At different stages of axial compression (0–5 MPa, 5–15 MPa, 15–25 MPa), the rate of permeability reduction diminishes progressively, with minimal change observed in the high-stress stage. During the unloading phase, due to incomplete recovery of plastic deformation, permeability shows only a limited increase, with the maximum recovery rate being less than 40 %. During the initial phase of continuous axial compression loading, the permeability first diminishes, subsequently entering an elastic stage where it stabilizes. However, upon reaching the point of instability failure due to crack propagation, permeability increases sharply. Additionally, as the number of freeze-thaw cycles rises, the degree of internal damage within the specimen escalates, manifesting as an increase in both pore size and quantity. Notably, the initial permeability and peak strength exhibited opposing trends: after 40 freeze-thaw cycles, initial permeability increased by 36 %, while peak strength decreased by 22 %.

Microstructural evolution and micromechanical properties of asphalt due to chloride salt erosion: Insights from atomic force microscopy

To explore the impact of chloride salt erosion on the microstructure and micromechanical properties of asphalt, this study utilizes the atomic force microscopy (AFM) to examine the evolution of micromorphology, surface roughness, adhesion, and Young’s modulus of asphalt in dry conditions, under various chloride salt concentrations, and after different erosion times. The results indicate significant changes in the microtopography of the asphalt surface due to chloride salt erosion, characterized by the reorganization of nanoscale protrusions and white spots. This results in a decrease in their quantity and total area, while the average area increased, demonstrating a trend of phase dispersion and aggregation. Erosion increased the surface roughness of the asphalt and significantly altered its mechanical properties. Specifically, with an increase in chloride salt concentration, the average roughness (Ra) of asphalt, after one day of erosion relative to its dry state, increased by 7.99 %, 33.06 %, and 52.55 %, respectively. As the erosion time was extended, at a 2.5 % chloride salt concentration, the growth rate of Ra reached 33.06 %, 54.68 %, and 67.22 %, respectively. A declining trend in nano adhesion was observed, indicating internal structural damage and reduced durability, while Young’s modulus significantly increased, suggesting a densification of the asphalt matrix and enhanced rigidity.

Terahertz time-domain spectro-imaging and hyperspectral imagery to investigate a historical Longwy glazed ceramic

In this paper, we present the potential of Terahertz Time-Domain Imaging (THz-TDI) as a tool to perform non-invasive 3D analysis of an ancient enamel plate manufactured by Longwy Company in France. The THz data collected in the reflection mode were processed using noise filtering procedures and an advanced imaging approach. The results validate the capability to identify glaze layers and the thickness of ceramic materials. To characterize the nature of the pigments, we also use with X-ray images, visible near-infrared hyperspectral imaging spectroscopy, and p-XRF (portable X-ray fluorescence) to qualitatively and quantitively identify the materials used. The obtained information enables a better understanding of the decoration chromogens nature and, thus, to determine the color palette of the artists who produced such decorative object. We also establish the efficiency of a focus, Z-tracker, which enables to perform THz imaging on non-flat samples and to attenuate artifacts obtained with a short focus lens. Then, 3D images are extracted and generated, providing a real vision. We also report the evaluation of the internal damage state through the detection of fractures.

Novel joint algorithm for state-of-charge estimation of rechargeable batteries based on the back propagation neural network combining ultrasonic inspection method

State of Charge (SoC) is an essential indicator for energy storage distribution in lithium-ion batteries, which prevents overcharge and over-discharge of the battery by integrating it into the Battery Management System. Common estimation approaches are Extended Kalman Filtering (EKF), Coulomb counting, open-circuit-voltage (OCV), and neural networks (NN). While these methods are able to estimate SoC more accurately, they lack real-time monitoring capability for internal and external battery damage such as air bubbles and foreign objects. This study is the first to propose a novel joint algorithm for real-time monitoring of battery SoC and health with high accuracy, integrating ultrasonic non-destructive testing (NDT). The proposed algorithm predicts the battery overcharge based on the ultrasonic signal and reveals structural changes in commercial batteries during charging/discharging. Experimental results demonstrate that ultrasonic inspection cannot only enhance the SoC estimation accuracy of the backpropagation (BP) neural network, but also detects damaged conditions of the battery.

Thermomechanical and damage characterisation of short glass fibre reinforced polyamide 6 and impact-modified polyamide 6 composites

Polyamide 6 and its composites are widely used in engineering applications that are exposed to high strain rate deformation. This paper investigates the thermomechanical properties of two polyamide 6 composites, both reinforced with 30 wt% short glass fibres, and one of which additionally contains an impact modifier, to provide an understanding of the mechanical response over a wide range of strain rates and temperatures. Compression experiments were performed at rates between 2 and 3000 s−1, with high speed optical and infrared cameras to aid interpretation of the rate-dependent failure arising from the formation of adiabatic shear bands. Further high strain rate experiments were performed with ultra-fast X-ray phase-contrast imaging to provide in-situ internal damage evaluation. These data will improve the utilization of these composites and aid in development of advanced thermomechanical models.

Damage detection and localization in sealed spent nuclear fuel dry storage canisters using multi-task machine learning classifiers

Spent nuclear fuel (SNF) assemblies (FAs), composed of bundled radioactive fuel rods, are stored in stainless-steel canisters as an interim dry storage option until permanent storage solutions are available. Accidental damage to these canisters may occur during handling or transportation events. If such events occur, it is necessary to assess the integrity of FAs before long-term storage. Since the canisters are sealed shut and can only be opened in special handling facilities, non-destructive evaluation (NDE) is critical for detecting the FAs from the canister's exterior surface. In this study, two multi-task machine learning (ML) classifiers, a k-nearest neighbors (k-NN) and a convolutional neural network (CNN), are developed to simultaneously detect and localize internal FA damage. The classifiers were trained and tested on a dataset collected via experimental modal analysis on a 2/3-scale mock-up canister. The canister was excited from the bottom plate while accelerometers were also attached on the bottom plate at arbitrary locations to record the structural response. The differences in frequency response functions (FRFs) between an intact fully loaded canister basket (FLCB) system and the canister with simulated internal damage were calculated and used as input to the ML models. Results showed that both classifiers achieved high accuracy on the testing set. The k-NN classifier produced macro-F1 scores of 1.00 for the damage detection task and 0.996 for the localization task. The macro-F1 scores of the CNN were 0.991 for damage detection and 0.964 for damage localization. Additionally, dropout layers were added to the fully connected layers of the CNN to introduce model uncertainty. By testing the model 1,000 times, probability density functions (PDFs) were generated, and it was confirmed that the CNN produced confident predictions in both the damage detection and localization tasks. This multi-task ML method contributes to advancing NDE of SNF canisters and holds potential for field applications in inspecting actual SNF canisters.

Quantitative assessment of correlation between compressive strength degradation and microstructural crack information in mortar deteriorated by freeze-thaw cycles

Freeze-thaw cycle (FTC) deterioration poses significant durability challenges to concrete structures. However, the detailed quantitative relationship between FTC-induced internal damage pattern development and mechanical degradation remains underexplored, limiting the accuracy of FTC deterioration assessments. This study aims to provide a comprehensive analysis of microstructural damage progression and its quantitative relationship with mechanical degradation in mortar specimens throughout FTC process. Through establishing an experimental setup applied to specimens at two scales and facilitated by micro-computed tomography (micro-CT), this research concurrently evaluates the microstructural damage progression, mechanical degradation, and expansion of the specimens under various FTC severity levels. The quantification of multiple crack indices reveals a stronger correlation between compressive strength reduction and crack ingression than with increases in crack quantity or width. The findings further highlight the imperative to incorporate both expansion-induced damage and time-dependent fatigue damage in evaluating FTC deterioration, thus laying a foundation for refining FTC prediction models.

The Effect of Maltose on Structural, Physicochemical, and Digestive Properties of Lentil Starch under Electron Beam Irradiation.

This study investigated the effects of electron beam irradiation (EBI) on the structural, physicochemical, and functional properties of lentil starch with varying maltose content. EBI did not significantly disrupt the starch's surface structure or cause amorphization of starch and maltose crystals, but it significantly reduced the intensity of starch's XRD peaks. The presence of maltose intensified internal growth ring damage, leading to more cross-link and rearrangement between short chains, improving short-range ordering of lentil starch and enhancing starch's solubility and thermal stability. Additionally, adding maltose that EBI then treats can lead to an increased content of slowly digestible starch in samples.

Characterisation and Application of Bio-Inspired Hybrid Composite Sensors for Detecting Barely Visible Damage under Out-of-Plane Loadings.

Traditional inspection methods often fall short in detecting defects or damage in fibre-reinforced polymer (FRP) composite structures, which can compromise their performance and safety over time. A prime example is barely visible impact damage (BVID) caused by out-of-plane loadings such as indentation and low-velocity impact that can considerably reduce the residual strength. Therefore, developing advanced visual inspection techniques is essential for early detection of defects, enabling proactive maintenance and extending the lifespan of composite structures. This study explores the viability of using novel bio-inspired hybrid composite sensors for detecting BVID in laminated FRP composite structures. Drawing inspiration from the colour-changing mechanisms found in nature, hybrid composite sensors composed of thin-ply glass and carbon layers are designed and attached to the surface of laminated FRP composites exposed to transverse loading. A comprehensive experimental characterisation, including quasi-static indentation and low-velocity impact tests alongside non-destructive evaluations such as ultrasonic C-scan and visual inspection, is conducted to assess the sensors' efficacy in detecting BVID. Moreover, a comparison between the two transverse loading types, static indentation and low-velocity impact, is presented. The results suggest that integrating sensors into composite structures has a minimal effect on mechanical properties such as structural stiffness and energy absorption, while substantially improving damage visibility. Additionally, the influence of fibre orientation of the sensing layer on sensor performance is evaluated, and correlations between internal and surface damage are demonstrated.

On Low-Velocity Impact Response and Compression after Impact of Hybrid Woven Composite Laminates

This paper aims to study the low-velocity impact (LVI) response and compression after impact (CAI) performance of carbon/aramid hybrid woven composite laminates employed in marine structures subjected to different energy impacts. The study includes a detailed analysis of the typical LVI responses of hybrid woven composite laminates subjected to the impact with three different energies, as well as a comparative analysis of cracks and internal delamination damage within impact craters. Additionally, the influence of different impact energies on the residual compressive strength of hybrid woven composite laminate is investigated through CAI tests and a comparative analysis of internal delamination damage is also conducted. The results indicate that as the impact energy increases, the impact load and CAI strength show a decreasing trend, while impact displacement and impact dent show an increasing trend. The low-velocity impact tests revealed a range of failure modes observed in the hybrid woven composite laminates. Depending on the specific combination of fiber materials and their orientations, the laminates exhibited different failure mechanisms. Buckling failures were observed in the uppermost composite layers of laminates with intermediate modulus systems. In contrast, laminates with higher modulus systems showed early damage in the form of delamination within the top surface layers.

Strength characteristics of different stress spaces of red sandstone under loading and unloading tests

Red sandstone tests were conducted on the rock mechanics test system to clarify the strength and failure characteristics of red sandstone under triaxial loading and different unloading confining pressure rates. Strength change rules of the red sandstone in various stress spaces were analyzed. Results show that a large initial confining pressure indicates a long yield section and large axial strain. A small unloading confining pressure rate indicates a long yield section and large axial strain at failure under the identical initial confining pressure. The confining pressure reduction increases with the unloading confining pressure rate increasing when the red sandstone fails. The stress path of unloading confining pressure weakens the red sandstone cohesion and strengthens its internal friction angle. The general octahedral shear stress formula for judging whether the red sandstone fails under loading and different unloading rates was acquired on the basis of the octahedral shear stress characteristics of the red sandstone. In addition, a 3D empirical criterion for evaluating the red sandstone strength was constructed through the deviator plane function of Eekelen and the strength envelope curve on the meridian plane. A great initial confining pressure indicates serious internal damage of the red sandstone at failure under the identical unloading rate of confining pressure. A low unloading rate of confining pressure indicates internal serious damage of the red sandstone at failure when the initial confining pressure is the same. The analysis of macroscopic failure characteristics revealed that the stress path significantly influences the failure mechanism of the red sandstone. The results are instructive for determining the stability of underground engineering of the red sandstone.

Study on calculation model of deflection of prefabricated hole bulkhead under the action of internal explosion

In order to study the plastic deformation law of ship plate frames under the coupling action of internal explosion load and fragment, first, the calculation formula of plastic deformation deflection of the non-porous plate is derived through the law of conservation of energy. According to the numerical calculation results, the influence of the opening position and opening area of the target plate on the deflection gain of the target plate is further explored. The mathematical expression form of the opening area and opening position on the deflection gain of the prefabricated target plate is fitted, and then, the deflection calculation model of the prefabricated target plate is established. It can theoretically predict the deflection of the bulkhead under cabin explosion and has a certain application reference value for ship cabin anti-explosion design and internal explosion damage assessment.

Internal Damage Detection in Reinforced Concrete Member Using Ultrasonic Pulse Velocity Nondestructive Testing

Internal Damage Detection in Reinforced Concrete Member Using Ultrasonic Pulse Velocity Nondestructive Testing