Damage Of Carbon Fiber Reinforced Polymer Research Articles

Automated CFRP impact damage detection with statistical thermographic data and machine learning

The study is focused on the use of machine learning models for the automated detection of impact damage in carbon fiber reinforced polymer (CFRP) by flash-pulse thermographic testing. A new method for thermographic data pre-processing, which is based on statistical features, was proposed. Nine machine learning models for the automated detection of impact damage in CFRP samples were applied to the raw thermographic data, data pre-processed by the suggested method and data pre-processed by the widely used thermographic signal reconstruction (TSR) method. The machine learning models were tested to provide a binary classification of impact damage in CFRP. The results presented in this study show improved performance of the classification if the data are pre-processed by the proposed method. The best results were obtained by a Bagged tree ensemble trained with statistical features. The final balanced accuracy achieved for the Bagged trees model trained on 40 statistical features was 99.8 % which indicates a very good performance.

Numerical investigation on milling performance and damage response of UD-CFRP laminates

Carbon fiber-reinforced polymer (CFRP) is prone to machining defects, including burrs and tearing, during milling. These defects are closely associated with interface delamination while milling force plays a crucial role in their occurrence. In this paper, a nonlinear explicit finite element (FE) model is developed to predict the milling force and analyze the delamination damage occurring during the milling of unidirectional CFRP (UD-CFRP). The proposed FE model is validated through numerical comparison with experimental data for milling force. Moreover, a detailed study is conducted to examine the influences of spindle speed, feed rate and depth-of-cut on the side-milling performance and damage response of UD-CFRP. This study provides valuable insights into the effects of machining parameters on milling force and delamination damage in CFRP, thereby supporting the optimization of machining technology for this composite material system.

Axial compressive performance of RC columns strengthened with prestressed CFRP fabric and UHPC jacket with spiral stirrups

AbstractTo address the issue of easy shearing damage of Carbon Fiber Reinforced Polymer (CFRP) in enhancing the axial compressive performance of CFRP and Ultra‐High‐Performance Concrete (UHPC) strengthened concrete columns, two methods, prestressed CFRP and UHPC with spiral stirrups, were employed for composite strengthening of reinforced concrete (RC) columns. A total of one unstrengthened column and eight strengthened columns were designed and fabricated to validate the effectiveness of the proposed methods. The axial compressive performance and bearing capacity of each specimen were analyzed by considering parameters such as single or composite strengthening method, presence of spiral stirrups in UHPC, and application of pre‐stressed CFRP. The results show that, compared with any single strengthened specimen, the ultimate bearing capacity of the composite strengthened specimen is greater than the sum of the corresponding single strengthened specimens, and the bearing capacity of the prestressed CFRP with spiral stirrup UHPC composite strengthened specimen is the most significant, reaching 235.63%. By incorporating spiral stirrups in the UHPC jacket, the phenomenon of uneven fragmentation during the failure of the strengthened column is improved. This helps prevent premature shearing damage of CFRP and enhances the fracture strain and effective utilization of CFRP. Additionally, prestressed CFRP effectively restrains the lateral deformation and crack development of the core concrete in the UHPC jacket, fully utilizing the high compressive strength of UHPC. This further enhances the ultimate bearing capacity and ductility of the specimens. Based on the experimental phenomena and strain of each material, the failure mechanism of prestressed CFRP‐spiral reinforced UHPC composite‐strengthened columns is proposed. Finally, a unified bearing capacity calculation formula for single and composite strengthened columns is established, based on the theory of confined concrete strength and the assumption of strength increment superposition. The formula is validated with experimental results from relevant literature, showing small errors in the calculated results and indicating good applicability of the formula.

Analysis of the damage effects of carbon fiber composites under the mechanical impact loads of lightning based on a modified simulation calculation method

Mechanical effects contribute significantly to the multiphysical damage of carbon fiber-reinforced polymer (CFRP) composites induced by high-amplitude impulse lightning currents. In this paper, the mechanical impact loads (MILs) of lightning are decomposed into acoustic shock waves from arc channel expansion (AESW), electromagnetic force (EMF), and shockwave overpressure from surface explosion (SESW). A 3D finite element mechanical damage model of laminates was established based on the Hashin–Yeh initial creation and modified stiffness degradation matrix. The model was verified by comparison with pure mechanical impacts. The dynamic response and damage modes of laminates subjected to AESW, EMF, SESW, and MILs were studied and compared. The MILs are exponentially related to the current intensity. The damage effect of laminates under MILs is inversely related to the impact radius. The comparison shows that the effect of the EMF gradually exceeds that of the AESW as the current peak increases and its value is approximately twice that of the latter when the current peak Ip exceeds 165 kA. In contrast, SESW is the primary cause of the damage effect. Over 70 % of the deformation contribution to laminates under MILs comes from SESW (Ip = 165 kA). Furthermore, the strongest SESW is induced by the insufficient thermal conductivity of the CFRP laminates.

Impact damage assessment in laminated composites using acoustic emission and finite element methods

AbstractThis study aims to quantify impact damage in laminated composites using acoustic emission (AE) and to verify the AE results with finite element (FE) method. Carbon fiber reinforced polymer (CFRP) composite specimens were subjected to quasi‐static out‐of‐plane indentation loading. A procedure, including feature extraction, feature selection, data dimensionality reduction, and data clustering using an evolutionary algorithm, that is, differential evolution (DE) optimization algorithm, was proposed to identify and quantify different damage mechanisms using AE. The AE results showed that the dominant damages were matrix cracking and delamination. For the quantitative evaluation of the AE results, the indentation test was simulated using the FE method. A FE model based on cohesive zone modeling and continuum damage mechanics was implemented to predict interlaminar and intralaminar damages. The quantity of the damaged elements associated with the matrix cracking and delamination was consistent with the AE results. This study showed the applicability of the AE for impact damage identification and quantification in composite structures.Highlights Indentation damage in CFRP is experimentally quantified using the AE method. The DE algorithm is used to cluster the AE data. CZM and CDM are used to numerically model the damage. The AE clustering results are compared with the numerical results.

Damage formation and evolution mechanisms in drilling CFRP with prefabricated delamination defects: Simulation and experimentation

Delamination is a common defect in carbon fiber reinforced polymer (CFRP) during the molding process. Accurately understanding the formation and evolution mechanisms of drilling damage in CFRP with delamination defects is helpful for effectively suppressing drilling defects with delamination. In this study, a macro-micro finite element model (FEM) of CFRP with prefabricated delamination defects during drilling is established to simulate and analyze the damage formation and evolution behavior. The circular polytetrafluoroethylene (PTFE) films are employed to simulate the delamination defects in CFRP. These samples with different sizes of prefabricated delamination defects are prepared for the drilling experiments. The results show that the maximum errors of the thrust force and the exit damage factor between the simulation and experiments are 8.75% and 4.2% respectively, indicating good reliability of the simulation model. Under the condition of CFRP with delamination defects, as the size of the delamination defects increases, the maximum thrust force decreases, while the maximum delamination propagation length and exit damage increase. Compared to the case without delamination defects, when the delamination diameter is 7 mm, the delamination propagation percentage and the maximum stress in CFRP increase by 52.17% and 155.4% respectively, and the maximum increment of the exit delamination damage factor is 38%.

Fatigue damage monitoring of composite laminates based on acoustic emission and digital image correlation techniques

Timely and effective health evaluation of carbon fiber reinforced polymer (CFRP) structures under dynamic fatigue loading is one of the key issues of CFRP in practical engineering applications. This paper uses a combination of acoustic emission (AE) and digital image correlation (DIC) to study the fatigue behavior of CFRP open-hole laminated beams with different stacking sequences under pure tensile loading, and analyze the influence of different damage mechanisms on the ultimate fatigue failure of the specimens. Two parameters, AE hit rate and absolute AE energy, are used to characterize the stiffness degradation behavior of CFRP structures. The strain field distribution characteristics during the damage failure of specimens with different stacking sequences are discussed in association with DIC. Based on the data obtained by AE and DIC, the damage modes of two types of layered CFRP laminated beams are identified by combining principal component analysis (PCA) and the K-means++ algorithm. The clustering results are consistent with the microscopic image results of the fracture surface. The identified modes are employed to characterize the dynamic evolution of fatigue damage in CFRP, and the contribution of different damage modes to the ultimate fatigue failure of the specimens is analyzed using cumulative damage index (CDI) values.

Low-velocity impact response of self-piercing riveted carbon fiber reinforced polymer-AA6061T651 hybrid joints

Self-piercing riveting (SPR) is an effective method to join dissimilar materials, such as composite and aluminum alloy. In this paper, the dynamic loading response and the impact damage mechanism of carbon fiber reinforced polymer (CFRP) laminates and AA6061-T651 self-piercing riveting joints were investigated using the drop weight tests at energy levels between 7.5 J and 20 J at room temperature. The effect of diverse damage mechanisms on the impact resistance and quasi-static mechanical properties of the SPR joints were evaluated. The results showed that the low-velocity impact position has a great influence on the strength of SPR joints, and the strength of the joints is seriously decreased when impacted at the center of the rivet. There are two impact damage mechanisms. One was the internal damage of CFRP laminates and it was the dominant damage mechanism before the impact energy of 10 J. Another one is the plastic deformation of aluminum alloy when the impact energy was above 10 J. The composite damage played a leading role in the absorption of the impact energy. Moreover, the impacted joints present residual strengths of 83 % (5 J), 76 % (7.5 J), 71 % (10 J), 57 % (12.5 J), 51 % (15 J), 48 % (17.5 J), 38 % (20 J) of the non-impact SPR joints. The axial impact resistance was more sensitive to the plastic deformation of aluminum alloy, while the quasi-static mechanical properties were more sensitive to the internal damage of CFRP.

A New Electrical Resistance Measurement Method of Carbon Fiber-Reinforced Polymer Tubes Based on C⁴D Technique

This work introduces the capacitively coupled contactless conductivity detection ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{C}^{{4}}\text{D}$ </tex-math></inline-formula> ) technique into nondestructive testing (NDT) of carbon fiber-reinforced polymer (CFRP) and proposes a new resistance measurement method of CFRP tubes. The proposed method does not require direct contact between the electrodes and the carbon fiber. Therefore, the electrical resistance of CFRP can be measured without the treatments required by traditional electrical methods that may lead to surface or structural damage. The equivalent circuit model of the new method is established, and the challenges are analyzed. Simulation and experiment are conducted with woven fabric CFRP tubes to verify the feasibility of the proposed method, including the range of workable frequency, the effectiveness of the circuit model, and the capability of damage detection. Research results show that a relatively high working frequency is required to accurately measure the interested resistance and sense the resistance change. By selecting a workable frequency, the effectiveness of the circuit model is verified. Research results indicate that the stray capacitance between the electrodes has little effect on resistance measurement, and the capacitor–resistor–capacitor model is still applicable. Research results also verify the feasibility of the proposed method for damage detection. It is able to sense the resistance change resulted from the damage of CFRP, either the conductivity changes in simulation or actual cutting damage in experiment.

The research on laser welding-riveting hybrid bonding of titanium alloy and carbon fiber reinforced composites

The Ti-6Al-4V (TC4) and Carbon Fiber Reinforced Polymer (CFRP) were joined by welding-riveting hybrid bonding process. In order to reduce the thermal damage of CFRP in the process and obtain high-quality joints, the stepped rivet was used and a pulsed laser beam was used as the welding source. The maximum tensile shear load of 8.5 kN was obtained by varying the laser beam power. The weld joints were all in the form of 'button fracture', and the characteristics of joints failure are discussed in detail through tensile results combined with Digital Image Correlation (DIC) technology. Microscopic analysis by EPMA and SEM showed the bonding mechanism of the joint. The joint was sealed to improve the corrosion resistance, and it has better performance. In addition to the weld seams formed by the rivet and TC4 sheet and the mechanical bonding of the rivet, TC4 sheet and CFRP sheet, the mechanical interlocking phenomenon formed by the penetration of the molten CFRP into the assembly gap could reduce stress concentration and improve the mechanical properties of joints. It can also improve the structural integrity and sealability. Moreover, the molten CFRP and TC4 formed a 2 μm mixing layer, which also played a role in mechanical bonding process.

R-UNet Deep Learning-Based Damage Detection of CFRP With Electrical Impedance Tomography

Carbon fiber reinforced polymer (CFRP) with excellent properties is widely used in many fields. During the production process and service life of CFRP-related products, CFRP may suffer some damages which are difficult to be detected. Due to the electrical conductivity of CFRP, electrical impedance tomography (EIT) can be used to detect the damage in CFRP. However, the inverse problem of EIT is nonlinear and ill-conditioned and the reconstructed images based on EIT have low accuracy. In order to solve these problems, a R-UNet network with four modules (preliminary imaging module, backbone feature extraction module, enhanced feature extraction module, and prediction module) is proposed in the paper. Firstly, a shallow residual network is introduced to reconstruct the image. Then, the initial image is input into U-Net for backbone feature extraction and enhanced feature extraction. Finally, the image with fewer artifacts and clear edges is output. The network is trained with 12,600 simulated data. Four algorithms were compared with R-UNet. The simulation results showed that the R-UNet algorithm performed better than other algorithms in imaging quality. CC and SSIM were used as the indicators to evaluate the simulation results. The average CC and SSIM of R-UNet reached 0.93 and 0.95, respectively. In addition, an EIT experimental platform was established to verify R-UNet. The comparison of infrared thermal imaging results and experimental results of EIT indicated that R-UNet realized reliable detection results of CFRP damage.

Establishment of instantaneous milling force prediction model for multi-directional CFRP laminate

Carbon fiber reinforced polymer (CFRP) is widely used in the aerospace field due to its light weight and high strength. The CFRP milling process is prone to damage such as burrs and tears. The cutting force is closely related to the damage of CFRP and tool wear. In this paper, a back propagation (BP) neural network model of cutting force and edge force coefficients was established. The model considers the effects of instantaneous uncut chip thickness, fiber cutting angle, spindle speed, and axial depth of cut. The unidirectional CFRP laminate instantaneous milling model considering the cutting edge force was further established. The instantaneous milling force prediction model was extended to multi-directional CFRP laminates. And the relationship between the damage mechanism of CFRP and the instantaneous milling force was analyzed. Experiments have proved that the instantaneous milling force prediction model built in this paper has high accuracy.

Automatic Extraction of Material Defect Size by Infrared Image Sequence

A typical pulsed thermography procedure results in a sequence of infrared images that reflects the evolution of temperature over time. Many features of defects, such as shape, position, and size, are derived from single image by image processing. Hence, determining the key frame from the sequence is an important problem to be solved first. A maximum standard deviation of the sensitive region method was proposed, which can identify a reasonable image frame automatically from an infrared image sequence; then, a stratagem of image composition was applied for enhancing the detection of deep defects in the key frame. Blob analysis had been adopted to acquire general information of defects such as their distributions and total number of defects. A region of interest of the defect was automatically located by its key frame combined with blob analysis. The defect information was obtained through image segmentation techniques. To obtain a robustness of results, a method of two steps of detection was proposed. The specimen of polyvinyl chloride with two artificial defects at different depths as an example was used to demonstrate how to operate the proposed method for an accurate result. At last, the proposed method was successfully adopted to examine the damage of carbon fiber-reinforced polymer. A comparative study between the proposed method and several state-of-the-art ones shows that the former is accurate and reliable and may provide a more useful and reliable tool for quality assurance in the industrial and manufacturing sectors.

Using differential spread laser infrared thermography to detect delamination and impact damage in CFRP

In this paper, the feasibility of differential spread laser infrared thermography (DSLIT) to detect delamination and impact damage in carbon fiber reinforced polymer (CFRP) is investigated. The proposed method can significantly eliminate the influence of the uneven laser energy distribution and improve the detectability of laser infrared thermography. First, numerical simulation is carried out following the procedure of DSLIT to verify the feasibility of this method. Secondly, through experiments on the detection of defects both in practical aviation CFRP and common CFRP, the feasibility of DSLIT is confirmed. For the common CFRP, this technique has excellent performance: a defect at a depth of 2.5 mm was detected successfully, with the width-to-depth ratio reaches to 2.4. Comparatively speaking, the defect detection results for the aviation CFRP are not as good as those for the common CFRP. However, defects at a depth of 1.125 mm were detected, with the width-to-depth ratio reaching 2.67. In addition, defects caused by a low-velocity impact in practical aviation CFRP were successfully detected. Finally, the thermal data were processed by image processing methods such as sequence differential preprocessing (SDP), phase analysis (PA) and principal component analysis (PCA) to enhance the defect imaging results.

Damage analysis of carbon fiber composites exposed to combined lightning current components D and C

The damage properties of carbon fiber reinforced polymer (CFRP) laminates exposed to combined lightning components D and C were explored by standardized artificial lightning tests, and then evaluated by visual inspection and ultrasonic scan. To interpret the heating mechanism of CFRPs under the combined lightning components D and C, a mathematical model of lightning arc was involved in the finite element analysis, the results of which agreed well with experimental data. It was revealed that the component D controlled the in-plane damage area, while the sequential injection of component C aggravated the in-plane damage extent and tended to induce in-depth damage. The simulated results indicated that the resistive heating effect played a leading role in thermal damage of CFRPs during component D, whereas the damage occurred in component C was dominated by lightning arc heating effect.

Damage of Hygrothermally Conditioned Carbon Epoxy Composites under High-Velocity Impact.

The influence of hygrothermal aging on high-velocity impact damage of carbon fiber-reinforced polymer (CFRP) laminates is investigated. Composite laminate specimens were preconditioned in water at 70 °C. The laminates were subsequently impacted by flat-, sphere-, and cone- ended projectiles with velocities of 45, 68, and 86 m/s. The incident and residual velocities were collected during the impact test. The impact-induced damages were measured by ultrasonic C-scan, a digital microscope system, and a scanning electron microscope. The results show that the hygrothermally conditioned laminates offer a higher energy absorption during high-velocity impact. Due to the weakening of the interlaminar properties, the hygrothermally conditioned laminates are more susceptible to delamination failure, and shear-induced debonding dominates. The projected delamination area increases with the increment of impact velocity. The damaged region becomes close to a circular shape after hydrothermal conditioning, and close to a rhomboidal shape for the dry specimens.

Assessment of drilling-induced damage in CFRP under chilled air environment

ABSTRACTDrilling holes in carbon fiber-reinforced polymer (CFRP) laminates are more prone to incur damage during machining. Surface damage could be considerably minimized through the adoption of cryogenic assisted machining. The economic and safety implications associated with cryogenic technology necessitate the exploration of alternate technologies. In this research work, the effects of cutting velocity (100, 125, and 150 m/min) and feed rate (0.03, 0.06, and 0.09 mm/rev) on thrust force, surface roughness, delamination, and acoustic emissions are studied during the drilling of CFRP laminates under chilled air environment and compared with dry drilling. The output parameters are found to be much influenced by feed rate than cutting velocity. Under high feed rate and cutting velocity, the delamination factor, surface roughness, and acoustic emissions are, respectively, reduced by 13.2, 10.5, and 7.4% for the drilling performed under chilled air environment over dry condition. About 9.9% increased thrust force is observed for chilled air-assisted drilling under the identical machining condition.

Low-velocity impact damage characterization of carbon fiber reinforced polymer (CFRP) using infrared thermography

Carbon fiber reinforced polymer (CFRP) after low-velocity impact is detected using infrared thermography, and different damages in the impacted composites are analyzed in the thermal maps.The thermal conductivity under pulse stimulation, frictional heating and thermal conductivity under ultrasonic stimulation of CFRP containing low-velocity impact damage are simulated using numerical simulation method. Then, the specimens successively exposed to the low-velocity impact are respectively detected using the pulse infrared thermography and ultrasonic infrared thermography. Through the numerical simulation and experimental investigation, the results obtained show that the combination of the above two detection methods can greatly improve the capability for detecting and evaluating the impact damage in CFRP. Different damages correspond to different infrared thermal images. The delamination damage, matrix cracking and fiber breakage are characterized as the block-shape hot spot, line-shape hot spot, and “▪” shape hot spot respectively.

Real-time damage mechanisms assessment in CFRP samples via acoustic emission Lamb wave modal analysis

This paper proposes a very promising acquisition-analysis procedure to evaluate real-time damage in carbon fiber-reinforced polymer (CFRP) composite plates by means of the acoustic emission (AE) method. It shows how, by using appropriate acquisition frequency filters and very narrow time windows, it is possible to avoid reflection at boundaries and successfully split the A0 and S0 Lamb modes of the AE signals. After that, an appropriate algorithm —based on the comparison of strength of both modes in time and frequency domains— allows one to associate each AE event to a particular damage mechanism (delamination, fiber breaking and matrix micro-cracking). Experimental results from three point bending tests carried out on 22-layer CFRP samples, with delamination artificially induced by a Teflon film, clearly demonstrate the real-time evaluation of the induced delamination and the beginning and growth of new ones.