Damaged Areas Research Articles

A novel bidirectional LSTM network model for very high cycle random fatigue performance of CFRP composite thin plates

This study proposes a novel Double-layer Bidirectional Long Short-Term Memory (BiLSTM) neural network model, shorted as TDA-BiLSTM, which integrates Transfer learning and Attention mechanisms. The model aims to predict the fatigue life of carbon fiber reinforced polymer (CFRP) thin plate structures subjected to very high cycle random vibration fatigue loads. Distinct from conventional servo-hydraulic and ultrasonic fatigue testing methods, this research pioneers the use of a vibration table for very high cycle fatigue (VHCF) testing to fill the gap in the field. By training and validating data across various life ranges, the TDA-BiLSTM model demonstrates significant advantages in training speed and predicting accuracy. Its bidirectional structure and attention mechanism effectively capture complex patterns and long-term dependencies in sequence data. Experimental results indicate that the TDA-BiLSTM model achieves significantly lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) compared to Long Short-Term Memory (LSTM) and Long Short-Term Memory with Transfer learning (Tr-LSTM) models across different life ranges on the ε-N curve, indicating higher accuracy and stability in strain life prediction tasks. Additionally, an analysis of typical damage areas using Scanning Electron Microscopy (SEM) reveals the failure mechanisms of CFRP plates under very high cycle vibration fatigue loads.

Pest Control and Safety Management Monitoring in Outdoor Plantation Using Unmanned Aerial Vehicle Captured Images

The National Institute of Ecology in Seocheon, Chungcheongnam-do, exhibits and studies Korea’s diverse ecosystems to communicate the importance of biodiversity conservation to the general public. The site faces the challenge of preserving the natural environment while ensuring visitor convenience. This requires systematic data collection to quickly detect and respond to threats from pests and natural disasters. In this study, high-resolution orthoimages were acquired to monitor ecological changes using unmanned aerial vehicles. Images were captured through flights monthly from March to July 2024. Digital elevation models and orthoimages were generated to identify dead trees and assess areas of damage caused by heavy rainfall. The study covered an area of 998,655 m2, and the image resolution was 3.6 cm/pixel. The orthophotos were useful in identifying plant pest damage. They also helped evaluate damage caused by rain, showing that the total area of damage was 29,384 m2, mainly due to soil erosion. Furthermore, it is expected that the accumulation of such unmanned remote sensing image data can also be applied to the safety management of various natural conservation areas and public facilities.

Mussel-inspired polydopamine (PDA)-grafted 2D-Ti3C2 MXene nanosheets tailored ZnAl-layered double hydroxides (LDH); Toward designing a smart self-healing epoxy composite coating

The constant challenge of corrosion significantly compromises the durability and functionality of metal substrates, propelling the demand for advanced protective solutions. This study introduces a novel smart epoxy coating system modified with a three-component nanocomposite integrating polydopamine (PDA)-modified Ti3C2 MXene with ZnAl-layered double hydroxides (LDH), intercalated with phosphate (P) and glutamate (Gl) ions as corrosion inhibitors. The innovative approach leverages the synergistic impacts of barrier protection, ion exchangeability, and self-healing capabilities to offer superior anti-corrosion performance. In the solution phase, the EIS results revealed a notable increase in resistance values, with MPLG samples exhibiting a 2.45-fold and MPLP samples a 2.17-fold enhancement compared to the blank specimen after 96 h of immersion. Furthermore, the data obtained from EIS demonstrated a significant enhancement in the barrier effects of the epoxy coating upon the addition of MPLG and MPLP. This enhancement was evidenced by a significant increase in the impedance values, which were observed to be 103-fold higher following a prolonged immersion period of 140 days. The self-healing properties, confirmed through EIS, FE-SEM, and EDX/Mapping analyses, indicated the formation of a stable corrosion-protective layer over the damaged areas, thus providing active protection. Adhesion assessments further underscored the coatings' durability, with MPLG and MPLP samples demonstrating minimal delamination. Collectively, these findings emphasize the potential of the proposed PDA-modified MXene@ZnAl-LDH nanocomposite as a multifaceted solution to corrosion challenges, promising significant advancements in the longevity and reliability of coated metal surfaces.

COVID-19-Induced Changes in the Fibrin Network of Pulmonary and Renal Microthrombi

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection often causes coagulation disorders that affect highly vascularized organs, such as the lungs and kidneys. Objective The objective of this study was to report the histopathological findings of variations in the fibrin pattern of pulmonary and renal microthrombi in patients who died from SARS-CoV-2 infection. Methods Minimally invasive autopsies were performed on 40 patients to collect lung (n=40) and kidney (n=16) tissue samples. Histochemical and immunohistochemical staining techniques were used for histopathological analyses. Premortem laboratory data were obtained from the patients' electronic medical records. Results The lung tissue showed a patchy pattern, characterized by areas of both minimal and severe damage. The most significant histopathological finding was the detection of thrombi with fibrin structures organized into discrete star-shaped units, which were more frequently observed in areas with severe lung injury than in those with minimal lung injury (p = 0.012). Star-shaped fibrin structures were also observed in the renal glomerular capillaries. Immunohistochemical staining revealed the presence of platelets and the procoagulant proteins von Willebrand factor (VWF) and Factor VIII within the star-shaped fibrin thrombi. Patients with star-shaped fibrin thrombi had higher levels of the systemic inflammatory indicators C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio (NLR). Conclusion Our observations suggest that the inflammatory microenvironment resulting from SARS-CoV-2 infection may contribute to the formation of star-shaped fibrin units in the pulmonary and renal microthrombi.

Energy absorption characteristics of STF impregnated Kevlar fabric coating GFRP composite structure by projectile high-velocity impact

The new STF impregnated Kevlar fabric coated GFRP (glass fiber reinforced polymer) composite structure obtained by combining STF（shear thickening fluid） impregnated Kevlar fabric and GFRP can obtain strong energy absorption capacity with light weight compared with two separate structures, so it has strong impact resistance. In this paper, the experiments of STF impregnated Kevlar fabric, GFRP laminated plate and STF impregnated Kevlar fabric coating GFRP laminated structure were carried out, respectively. Based on reliable numerical simulation, the macroscopic damage and energy absorption characteristics of the same material in STF impregnated Kevlar fabric, GFRP laminated plate and STF impregnated Kevlar fabric coating GFRP laminated structure were analyzed. The results show that the GFRP laminate and the rear Kevlar fabric in the STF-impregnated Kevlar fabric coating GFRP laminate structure show a larger damage area than that of GFRP laminate and STF impregnated Kevlar fabric alone, and a larger deflection is generated during the process of impact. The increase of the number of layers of Kevlar fabric in the front and back of the laminate and the increase of the thickness of the laminate make the Kevlar fabric absorb more energy. If the energy absorption capacity of GFRP laminates is increased, the number of layers of the front Kevlar fabric can be reduced, the thickness of the laminates can be increased, and materials with greater strength can be added to the front ply of the laminates. However, increasing the thickness of GFRP laminates will reduce the lightweight requirements of laminated structures.

Study on the evolution characteristics of coal mass spalling during coal and gas outbursts

The process of coal and gas outbursts (called outbursts for short) are commonly accompanied by coal mass spalling and fragmentation, but the formation mechanism of spalling is still unclear. To clarify this mechanism, this research constructs multi-layered combined coal-rock mass model. Based on the stress wave propagation mechanism, it’s found that outbursts initially start from ‘weak layer’. Besides, there are two significant results by analyzing the process of unloading waves formed by sudden pressure relief of the excavation face. Firstly, in the axial direction, due to the internal impact of the coal mass during the unloading wave propagation, the load shock wave is formed. The tensile stress is formed on the surface of the coal mass, resulting in rapid damage to the coal mass and even multi-layered spalling. Secondly, in the radial plane, permanent standing surfaces will be formed when the unloading wave catches up with the plastic load wave. Under effect of the unloading wave, internal impact will occur a series of load shock wave, resulting in the formation of multi-layered spalling in the radial plane. In addition, the attenuation law of the load shock wave generated by the internal impact in multi-layered coal mass is also analyzed, results showed that the thickness of coal mass spalling formed far away from the free surface will increase. Finally, the three-dimensional dynamic damage path and the spindle shape damage area formation mechanism in coal mass under external dynamic load are analyzed, which provides a new idea for elucidating the outbursts mechanism.

Advancing structural health monitoring: Deep learning-enhanced quantitative analysis of damage in composite laminates using surface strain field

Composite materials have been widely used as critical components in aerospace applications due to their excellent performance characteristics. The real-time accurate identification and quantification of various types of damage within composite material structures pose a significant challenge. This study introduces an innovative damage detection method based on strain fields, which centrally employs deep learning techniques. Utilizing the Res-Mask R–CNN, this study accurately detects and categorizes various forms of damage within composite laminates, including open holes, subsurface holes, and delamination. Moreover, this method also enables precise localization and quantification of damaged areas. A series of experiments and simulations have validated the accuracy and robustness of the network model. Damage inversion experiments demonstrate that the area error of the damaged regions has been reduced to 7.4 %, and the positional error does not exceed 3.31 mm. In simulated scenarios, the shape context distance for complex damage contours does not exceed 0.21, indicating that the critical geometric features of the damage have been successfully preserved. This study provides an effective new approach for damage detection and real-time structural health monitoring of composite laminates.

Seismic analysis of asphalt concrete core rockfill dams considering the bimodulus effect

In China, with the extensive development of pumped storage power stations, asphalt concrete core rockfill dams have become the preferred dam type because of their good deformation adaptability and impermeability. In seismic-prone western regions of China, the seismic safety of asphalt concrete cores is particularly important. However, asphalt concrete materials used in hydraulic engineering exhibit significant differences in their tensile and compressive moduli under low-temperature conditions, which has not been considered in existing constitutive models. In this study, a dynamic constitutive model considering the bimodulus effect of asphalt concrete was developed on the basis of dynamic tension and compression tests. Using this model, the influence of the bimodulus characteristics on the dynamic response of the core was investigated. The results indicate that a bimodulus constitutive model can effectively simulate the stress‒strain relationship of asphalt concrete materials at low temperatures. Compared with the bimodulus model, the use of the monomodulus model for calculations results in a significant decrease in compressive stress and a substantial increase in tensile stress of the core. Specifically, using the tensile and compressive monomodulus models led to maximum reductions in tensile stress of 42.9 % and an increase by 336.8 %, respectively. Neglecting the bimodulus effect may lead to misjudgment of the damage area, so the bimodulus effect on the seismic safety of dam cores should not be ignored.

Research Progress on Treating Spinal Cord Injury by Modulating the Phenotype of Microglia.

Spinal cord injury (SCI) is a severe central nervous system disorder with no currently available effective treatment. Microglia are immune cells in the central nervous system that play crucial roles in the SCI occurrence, development, and recovery stages. They exhibit dynamic polarization over time and can switch between classical activation (M1) and alternative activation (M2) phenotypes to respond to environmental stimuli. The M1 phenotype is involved in initiating and sustaining inflammatory responses, while the M2 phenotype exerts anti-inflammatory effects and promotes tissue repair in damaged areas. Inhibiting M1 polarization and promoting M2 polarization have become hotspots in regulating neuroinflammation and treating SCI. This article provides a comprehensive review centered on modulating microglial polarization phenotypes for SCI treatment.

Study on visualization of impact damage characteristics of honey peaches based on finite element method.

The study of visualization of impact damage of fruit under different thicknesses of buffer materials can provide more efficient transportation and packaging solutions, and thus the economic losses caused by fruit damage can be reduced. Pearl cotton (EPE) is commonly used as a buffer material in the market, and the impact damage behavior of honey peaches under different thicknesses of EPE buffer material was studied by using the finite element method. Firstly, the damage area, maximum contact force and damage volume during the collision of honey peaches with EPE materials of different thicknesses (2, 4, and 6mm) were obtained by the single pendulum device, and then the Modulus of elasticity and Poisson's ratio of peach flesh were obtained by compression test. Finally, the finite element model of honey peach was built and the collision simulations were performed. The results of the study showed that the values of mechanical parameters of honey peach decreased with the increase of the thickness of the buffer material. When the collision angle was below 60°, the honey peaches were not damaged in the collision with the EPE material with a thickness of 4mm or more. By comparing the tested values with the simulated values, it was found that the errors of the damage area, damage volume and maximum contact force were less than 19.71%, 26.82%, and 25.88%, respectively. The study not only proves the possibility of the finite element method in the quantitative prediction of honey peaches damage but also provides rational support for the packaging design of honey peaches.

Repeated intrathecal injections of peripheral nerve-derived stem cell spheroids improve outcomes in a rat model of traumatic brain injury

BackgroundTraumatic brain injury (TBI) is a major cause of disability and mortality worldwide. However, existing treatments still face numerous clinical challenges. Building on our prior research showing peripheral nerve-derived stem cell (PNSC) spheroids with Schwann cell-like phenotypes can secrete neurotrophic factors to aid in neural tissue regeneration, we hypothesized that repeated intrathecal injections of PNSC spheroids would improve the delivery of neurotrophic factors, thereby facilitating the restoration of neurological function and brain tissue repair post-TBI.MethodsWe generated PNSC spheroids from human peripheral nerve tissue using suspension culture techniques. These spheroids were characterized using flow cytometry, immunofluorescence, and reverse-transcription polymerase chain reaction. The conditioned media were evaluated in SH-SY5Y and RAW264.7 cell lines to assess their effects on neurogenesis and inflammation. To simulate TBI, we established a controlled cortical impact (CCI) model in rats. The animals were administered intrathecal injections of PNSC spheroids on three occasions, with each injection spaced at a 3-day interval. Recovery of sensory and motor function was assessed using the modified neurological severity score (mNSS) and rotarod tests, while histological (hematoxylin and eosin, Luxol fast blue staining) and T2-weighted magnetic resonance imaging analyses, alongside immunofluorescence, were conducted to evaluate the recovery of neural structures and pathophysiology.ResultsPNSC spheroids expressed high levels of Schwann cell markers and neurotrophic factors, such as neurotrophin-3 and Ephrin B3. Their conditioned medium was found to promote neurite outgrowth, reduce reactive oxygen species-mediated cell death and inflammation, and influence M1-M2 macrophage polarization. In the CCI rat model, rats receiving repeated triple intrathecal injections of PNSC spheroids showed significant improvements in sensory and motor function, with considerable neural tissue recovery in damaged areas. Notably, this treatment promoted nerve regeneration, axon regrowth, and remyelination. It also reduced glial scar formation and inflammation, while encouraging angiogenesis.ConclusionOur findings suggest that repeated intrathecal injections of PNSC spheroids can significantly enhance neural recovery after TBI. This effect is mediated by the diverse neurotrophic factors secreted by PNSC spheroids. Thus, the strategy of combining therapeutic cell delivery with multiple intrathecal injections holds promise as a novel clinical treatment for TBI recovery.

Deep neural networks for automated damage classification in image-based visual data of reinforced concrete structures

Significant strides in deep learning for image recognition have expanded the potential of visual data in assessing damage to reinforced concrete (RC) structures. Our study proposes an automated technique, merging convolutional neural networks (CNNs) and fully convolutional networks (FCNs), to detect, classify, and segment building damage. These deep networks extract RC damage-related features from high-resolution smartphone images (3264 × 2448 pixels), categorized into two groups: damage (exposed reinforcement and spalled concrete) and undamaged area. With a labeled dataset of 2000 images, fine-tuning of network architecture and hyperparameters ensures effective training and testing. Remarkably, we achieve 98.75 % accuracy in damage classification and 95.98 % in segmentation, without overfitting. Both CNNs and FCNs play crucial roles in extracting features, showcasing the adaptability of deep learning. Our promising results validate the potential of these techniques for inspectors, providing an effective means to assess the severity of identified damage in image-based evaluations.

Lightning damage characteristics of Cf/SiC based on ultrasonic and multi‐nondestructive testing methods

AbstractAccording to the characteristics of the internal damage of the Cf/SiC composite material after the lightning strike, this article establishes a high‐energy ultrasonic excitation, reception, and high‐resolution ultrasonic testing model, achieving high‐energy and high‐resolution ultrasound C‐scan detection of Cf/SiC composite material samples after lightning strikes, and combining digital X‐ray and computed tomography methods for damage analysis. When the lightning energy is gradually increased, the lightning stratified damage will occur inside the sample, and the delamination damage area reaches the maximum value of 25182 mm2 at the lightning energy of S4. Subsequently, as the energy increases, significant needle‐like damage is generated at the needle‐stitched area inside the sample, and the area of delamination damage gradually decreases. When the energy continues to increase to the lightning strike energy of S6, as the energy increases, the number of needle‐like damage in the sample continues to grow, and penetrating injury appears at the needle suture site. At S8, the maximum number of needle‐like lightning damage occurred, with 53 damage points and a total volume of 256.86 mm3, respectively. Through comprehensive analysis, Cf/SiC has excellent resistance to lightning damage, but the needle‐stitched carbon fiber in the thickness direction significantly reduces its resistance to lightning penetration.

Road Damage Analysis using Surface Distress Index (SDI) and Its Handling on Provincial Road Babat - Jombang (STA 7+000 - 12+500)

The Babat - Jombang road is often traveled by highly loaded vehicles because there are large industries along this section. In addition, the road is damaged by weather and poor subgrade conditions. Thus, resulting in road damage that can interfere with user comfort. Therefore, road damage analysis research was conducted on Babat - Jombang Road (STA 7+000 - 12+500). Road damage analysis in this study using the SDI method. The SDI (Surface Distress Index) method is a road performance scale obtained from visual observations of road damage that occurs in the field. The SDI method is a method that produces an SDI value obtained from the percentage of crack area, crack width, number of holes per 100 m, and the depth of the ruts. From this research, the types of damage on Babat - Jombang Road (STA 7+000 - 12+500) are the hole damage area of 0.11%, longitudinal cracks of 12.05%, transverse cracks of 0.17%, edge cracks of 0.29%, crocodile skin cracks of 79, 66%, shoulder joint cracking by 0.0015%, ruts by 1.48%, bleeding by 1.1%, ravelling by 2.61%, surface layer flaking by 0.13%, patches by 0.26%, upheavel by 0.51%, shoving by 1.6%. Road condition assessment using SDI method shows 87.27% in good condition and 12.73% in moderate condition. Handling carried out is leveling, sealing, hot aggregate sprinkle, and patching holes.

Emergency safe havens

This paper describes how to find or create protective shelter in disaster zones. Federal Urban Search & Rescue (US&R) teams pre-stage directly in the path of on-coming hurricanes and floods, and these forward-positioned teams must seek out buildings and rooms that can survive these events. Safe havens are also needed for those civilians who can’t be evacuated, including the disabled and critically ill. Safe havens are also important in the aftermath of a disaster. Critical work continues for days or weeks at disaster zones, at places where buildings and infrastructure are severely damaged, and where hazards persist. Protected spaces are needed for ongoing humanitarian and medical care for survivors. Rescuers, law enforcement, and medical personnel also need safe interior spaces to eat and rehab. US&R teams and other first responders also seek out safe havens inside the “red zone”, the areas of intense damage and hazards where first responders must operate during rescue, fire-fighting, or HazMat mitigation. The authors describe how safe havens can be rapidly identified or created in disaster zones. This aspect of protective structures is of growing importance as the world population becomes more vulnerable to natural and man-made disasters.

Effect of geometric configurations and curvature angle of corrugated sandwich structures on impact behavior

AbstractThe aim of this study is to numerically investigate the low‐velocity impact behavior of carbon fiber reinforced orthogonal woven fabric composite sandwich structures with five different geometric configurations and four different curve angles. Low velocity impact simulations were performed in LS DYNA finite element program to investigate the effects of core configuration and curve angle on peak contact force, energy absorption efficiency and damage mode. A progressive damage analysis based on the combination of the Hashin damage criterion and the Cohesive Zone Model (CZM) with bilinear traction‐separation law was performed using the MAT‐54 (ENHANCED_COMPOSITE_DAMAGE) material model. Among the five different cores, Trapezoidal core has the highest peak force average of 2.9 kN while Triangular core sandwich structure has the lowest with 1.23 kN. Absorbed energy efficiency average was highest for rectangular core with 0.95 and lowest for sinusoidal core with 0.69. The specific absorbed energy value was highest for Triangular core with 0.312 J/g and lowest for Sinusoidal core with 0.178 J/g. The damage area on the structure increased with increasing curve angle. It was determined that the core structure and curve angle is an effective parameter on peak force and energy absorption efficiency.Highlights Impact behavior of sandwich composite structures was examined. The effects of core type and curve angles on peak force, energy absorption efficiency and specific absorption energy were investigated. Specific absorption energy rates were compared with studies in the literature.

Design of self-healing and anticorrosion epoxy coating with active multiple hydrogen bonds based on grafted polyetheramine

The healing of epoxy coatings in damaged areas significantly influences their service life and protection quality. Intrinsic self-healing coatings, which enable multiple healing cycles without the need for additional functional carriers, have emerged as a promising coating technology. Nevertheless, the cross-linked structure of thermoset epoxy coating system restricts the large-scale migration of molecular chains, posing a significant challenge to achieve intrinsic healing of resin without compromising its mechanical properties. In this study, we report a design scheme for epoxy coating with intrinsic self-healing properties based on active multiple hydrogen bonds. Grafting aminobenzothiazole at the end of polyetheramine D230 chain, the grafted polyetheramine (GD230) was synthesized and served as the auxiliary curing agent, whose accurate molecular structure has been confirmed by different characterizations. The self-healing coating with reversible dynamics network based on hydrogen bonds was prepared by crosslinking through epoxy resin and mixed curing agent of polyetheramine D230 and GD230. Various measurements have been adopted to evaluate the self healing and anticorrosion performance. Results showed that the functional coating with a ratio of 8:2 for D230 to GD230 has satisfied both performances on the steel substrate. After immersion in 3 wt% NaCl solution for 120 days, the impedance value of functional coating still remains about 1010 Ω cm2. After the coating was scratched and immersion for 96 h, the impedance value of functional coating increased by about two orders of magnitude compared to that in blank coating. Mechanical testing and theoretical calculations were used to support dynamic crosslinking model to reveal the self-healing mechanism.

Monitoring the leaf damage by the rice leafroller with deep learning and ultra-light UAV.

Rice leafroller is a serious threat to the production of rice. Monitoring the damage caused by rice leafroller is essential for effective pest management. Owing to limitations in collecting decent quality images and high-performing identification methods to recognize the damage, studies recommending fast and accurate identification of rice leafroller damage are rare. In this study, we employed an ultra-lightweight unmanned aerial vehicle (UAV) to eliminate the influence of the downwash flow field and obtain very high-resolution images of the damaged areas of the rice leafroller. We used deep learning technology and the segmentation model, Attention U-Net, to recognize the damaged area by the rice leafroller. Further, a method is presented to count the damaged patches from the segmented area. The result shows that Attention U-Net achieves high performance, with an F1 score of 0.908. Further analysis indicates that the deep learning model performs better than the traditional image classification method, Random Forest (RF). The traditional method of RF causes a lot of false alarms around the edge of leaves, and is sensitive to the changes in brightness. Validation based on the ground survey indicates that the UAV and deep learning-based method achieve a reasonable accuracy in identifying damage patches, with a coefficient of determination of 0.879. The spatial distribution of the damage is uneven, and the UAV-based image collecting method provides a dense and accurate method to recognize the damaged area. Overall, this study presents a vision to monitor the damage caused by the rice leafroller with ultra-light UAV efficiently. It would also contribute to effectively controlling and managing the hazardous rice leafroller. © 2024 Society of Chemical Industry.

Zr-based conversion film fabricated on cold rolled steel by separately providing zirconium and fluorine ions: Performance and mechanism study

Controlling the concentrations of Zr4+ and F− in traditional Zirconium (Zr)-based film-formation solution is challenging due to their dependence on the hydrolytic equilibrium of H2ZrF6. In this study, Zr-based films were prepared on cold rolled steel surface through the film-formation solution prepared by mixing Zr(NO3)4 and different amount of HF. The electrochemical results demonstrated that the Zr-based film prepared by Zr(NO3)4 and HF exhibited superior corrosion resistance compared to H2ZrF6. Under optimal film formation conditions, the protective efficiency of the prepared film reached 74.4 % which was higher than that of film fabricated in H2ZrF6. The electrochemical results concurrently demonstrated the self-reinforcing anti-corrosion performance of the prepared films. Scanning electron microscopy revealed that the Zr film, prepared in Zr(NO3)4 and HF, exhibited excellent corrosion resistance attributed to its high film density. The X-ray photoelectron spectroscopy and energy dispersive spectroscopic results indicated the presence of a fluoride layer on the surface of the Zr film. The F− ions can chelate with the corrosion products and selectively deposit onto the damaged areas of the film, thereby effectively contributing to the repair of the film layer. The results of density functional theory calculations demonstrated that Zr4+ readily forms Zr(OH)4 rather than ZrF62−. The present study offers an enhanced approach for regulating the properties of films prepared via H2ZrF6 by separately providing zirconium and fluorine ions.

Hybridization effect of Kevlar and glass fiber on carbon/epoxy composites to enhance the damage strength under low velocity impact. Part II: Numerical simulations

The research outlined in this paper extends the authors previous work to explore the impact resistance enhancement of CFRP composites through numerical simulations, focusing on the incorporation of a hybrid combination of Kevlar and glass fibers. Experimental drop weight low velocity impact and advanced NDT tests on CFRP and hybrid laminates were carried out in previous work. The current work focuses on the analysis of the dynamic behavior of hybrid composite subjected to LVI by numerical simulation methods. The numerical simulations have been validated with experiments and the damage area of numerical and experimental tests were compared. CFRP and hybrid laminates were modeled using Abaqus/Explicit FEA software to investigate the damage modes and mechanisms. The history curves of simulation results such as load/displacement-time etc. compared with experimental. Results show that incorporating 25% Kevlar fibers on the outer layer of the CFRP, denoted as [01K/06C/01K] resulted in a reduction of laminate deflection by 63.64%. Additionally, the stress distribution expanded over a larger area. A good concurrence between the simulation and experimental findings has been established, indicating that the modeling approach is suitable for conducting further parametric investigations.