Carbon Fiber Reinforced Polymer Samples 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.

High-Sensitivity Detection of Carbon Fiber-Reinforced Polymer Delamination Using a Novel Eddy Current Probe

The demand for non-destructive testing of carbon fiber-reinforced polymer (CFRP) is becoming increasingly pressing to ensure its safety and reliability across different fields of use. However, the complex structural characteristics and anisotropic bulk conductivity of CFRP make achieving high sensitivity in detecting internal defects such as delamination extremely challenging. To address this issue, a novel triple rectangular coil probe with high sensitivity developed for detecting delamination in CFRP is presented in this paper. A finite element model using COMSOL Multiphysics was developed for CFRP delamination eddy current testing with the designed probe. Based on this model, the probe parameters were determined through orthogonal experiments. By analyzing the eddy current distribution in CFRP samples, the scanning mode was defined. Following this, the detection voltage was evaluated for various delamination parameters, and the sensitivity of different probes was compared. Results indicate that, under the same excitation coil parameters, for a 5 mm delamination lateral dimension change, the single pancake and single rectangular coil probes exhibit sensitivities of 88.24% and 72.55%, respectively, compared with the designed probe. For a 0.5 mm delamination thickness change, their sensitivities are 49.04% and 56.69% of those of the designed probe. The designed probe meets the demand for high-sensitivity detection.

Simulating lightning effects on carbon fiber composite shielded with carbon nanotube sheets using numerical methods

The demand for lightweight aircraft structures has shifted from traditional metals like aluminum to composite materials such as carbon fiber reinforced polymers (CFRP) to achieve weight reduction. However, this transition has led to decreased lightning strike protection efficiency due to the dielectric nature of CFRP. To address this problem, two CFRP samples—one unprotected and the other shielded with carbon nanotube (CNT) sheets—were subjected to artificial lightning strike testing. The research employed a coupled thermal-electrical finite element analysis method to investigate the lightning strike's impact and damage mechanisms on both samples. The numerical results closely aligned with published experimental data, validating the simulation. Unprotected CFRP sustained damage through the thickness direction up to 8 composite plies and in-plane direction over a length of 110 mm. In contrast, the sample protected with CNT sheets exhibited damage limited to the surface of the first 4 plies, with in-plane damage reduced to 24 mm. Notably, the damage area in the CFRP protected with CNT sheets showed a substantial 78.1 % reduction compared to the unprotected CFRP sample. This suggests that CNT can enhance the electrical conductivity of CFRP when incorporated between interlayers in both in-plane and thickness directions. The study enhances understanding of CFRP damage behavior and failure modes under lightning strike conditions, emphasizing CNT sheets as an improved and viable lightning strike protection system for aerospace applications, warranting further investigation.

Mechanical Properties of Wooden Elements with 3D Printed Reinforcement from Polymers and Carbon.

The research presented in this article aimed to investigate the differences in mechanical properties between solid structural timber and the same reinforced element in three different ways. A three-point bending test was performed on wood elements reinforced with carbon-fiber-reinforced polymer (CFRP), 3D printed polycarbonate (3DPC) lamellas, and 3D printed polycarbonate with carbon fiber (3DPCCF) lamellas. In this comparison, the bending strength was large for CFRP samples, which have 8% higher performance than samples with 3DPCCF and 19% higher performance than samples with 3DPC. Conversely, when factoring in theoretical manufacturing costs, the performance of 3DPCCF is almost three times that of CFRP and 3DPC. In addition, 3D materials can be used for more complicated reinforcement shapes than those discussed in the paper.

Physical and mechanical properties of nano-modified polybenzoxazine nanocomposite laminates: Pre-flight tests before exposure to low Earth orbit

Polybenzoxazine (PBZ) formulations based on commercial components and modified with polyhedral oligomeric silsesquioxanes (POSS, 5 wt% and 10 wt%) have been scaled up for industrialisation, and their processing characteristics determined using thermal analysis and rheometry. The ultimate glass transition temperatures for the cured PBZ resins are increased by catalysis and by the incorporation of POSS. Carbon fibre reinforced polymer (CFRP) laminates (500 mm × 500 mm x 3 mm) were manufactured using resin transfer moulding and subjected to a suite of mechanical tests. The addition of 5 wt% POSS to the PBZ formulation leads to substantial improvements in both strength (tensile, flexural, short beam shear, and compression) and modulus (tensile, flexural, and compression). The CFRP specimens were subjected to a suite of pre-flight qualification tests prior to deployment in low Earth orbit. When the CFRP laminates were exposed to <1 × 10−5 mbar and 125 °C, the total mass loss recorded for each sample was <1 wt%. The introduction of POSS at both levels of incorporation improves erosion yield following exposure to high atomic oxygen flux and the ratio of solar absorptance (α) to emittance (ε) remained constant following simulated solar exposure. The outcome was that the three PBZ CFRP samples passed their pre-flight tests.

Thermomechanical Behavior and Microstructure Properties of Carbon Fiber Reinforced Polymer at Elevated Temperatures

Carbon fiber reinforced polymer (CFRP) has been extensively used in civil engineering for applications such as reinforcing and retrofitting various architectural materials. Therefore, understanding the degradation of CFRP under high temperatures is important. This study aims to investigate the thermomechanical and microstructural properties of CFRP plates at elevated temperatures up to 350 &lt;sup&gt;o&lt;/sup&gt;C. The platetype CFRP composites were subjected to temperatures of 50, 100, 150, 200, 250, 300, and 350 &lt;sup&gt;o&lt;/sup&gt;C, and then compared with pristine CFRP samples. X-ray diffraction analysis was conducted to examine the crystal structures of the carbon fibers and epoxy resin matrices in the CFRP. At temperatures higher than 150 &lt;sup&gt;o&lt;/sup&gt;C, the FWHM increased due to the degradation and softening of the resin matrix. Delamination and debonding between the matrix and fibers were observed in samples exposed to temperatures above 200 &lt;sup&gt;o&lt;/sup&gt;C. The maximum tensile strength of the CFRP plates exposed at 350 &lt;sup&gt;o&lt;/sup&gt;C significantly decreased to 0.605 GPa, a reduction of approximately 40% compared to the pristine sample. On the other hand, Young's modulus remained relatively unchanged across the different temperatures. This suggests that the polymer matrix degradation plays a crucial role in the mechanical properties of CFRP, as the matrix layers contribute significantly to the distribution of forces.

Cutting Parameter Optimization in Milling of Glass Fiber and Carbon Fiber Reinforced Composites to Reduce Cutting Force

Abstract Composite materials are often preferred in many engineering applications because of their lightness and high-strength properties. However, in addition to the advantages of composite materials, processing problems exist. The processing of fiber-reinforced composite materials is more complex than other metal materials. The forces that arise during milling cause undesirable results, such as tool wear and energy loss. In this study, the cutting parameter optimization was made by measuring the force during carbon fiber and glass fiber-reinforced epoxy matrix composites milling. Cutting velocity (90, 120, and 150 m/min) and feed per tooth (0.1, 0.15, and 0.2 mm/tooth) were selected as cutting parameters. Experiments were planned according to the Taguchi method with two parameters and three levels. Optimization of the parameters was evaluated using the signal/noise ratio approach. The effectiveness of parameters on results was determined by analysis of variance (ANOVA). Optimum levels were found as 120 m/min for cutting velocity and 0.1 mm/tooth for feed per tooth both glass fiber-reinforced polymer (GFRP) and carbon fiber-reinforced polymer (CFRP) composites. According to the ANOVA results, the contribution rates of the force parameters were 81.05 % for cutting velocity and 15.03 % for feed per tooth in GFRP composites. The contribution rates of the force parameters were 43.69 % for cutting velocity and 46.18 % for feed per tooth in CFRP composites. The surfaces of the milled samples were examined with an optical microscope to investigate the damage. It was observed that the surfaces of CFRP samples had a better surface quality than GFRP samples.

A reliability study on automated defect assessment in optical pulsed thermography

Nowadays, the reliability of data analysis and decision-making based on deep learning (DL) remains a primary concern in promoting DL technology for industrial non-destructive testing and evaluation (NDT&E). This study focuses on the quantitative assessment of the reliability of various automated data analysis techniques in NDT&E. To achieve this, optical pulsed thermography was employed to inspect three non-planar carbon-fiber-reinforced polymer (CFRP) samples, each containing embedded Teflon to simulate debonding defects. After applying thermographic signal reconstruction and first-order derivation processing to the raw thermal data, automated analysis was performed using three image-processing-based segmentation methods and three sequential-signal-based DL algorithms. Additionally, an experienced inspector manually analyzed the data for comparison purposes. Subsequently, the probability of detection and false positive analyses were conducted to quantitatively evaluate and compare the reliability of the automated and human-based evaluations. The comparison results demonstrated that optimal DL classification and advanced image-processing-based segmentation techniques could achieve performance levels close to that of human inspectors in defect detection, even for challenging non-planar CFRP samples.

Experimental investigation of nanosecond laser Machining of 3D printed carbon fiber reinforced polymer (CFRP) composite

Carbon fiber reinforced polymer (CFRP) composites are widely used in automotive and aerospace applications due to their high specific strengths, high fatigue and creep resistance, and excellent corrosion resistance. Additive manufacturing (AM) or 3D printing has opened new ways of manufacturing complex 3D parts using CFRP composites. As a result, researchers have gained interest in the machining or post-processing of 3D-printed CFRP composites. This study aims to investigate the feasibility of using a nanosecond laser for machining single craters or blind holes and slots on 3D printed CFRP samples and understand the effects of important process parameters on feature dimensions, (i.e., crater diameter, slot width, crater/hole depth, and slot depth), heat affected zone (HAZ), and surface quality of the machined features. A 1064 nm wavelength laser system with a focal length of 160 mm was used, whereas the number of pulses, laser energy level, and back-and-forth laser passes are varied. The heat-affected zone is found to be influenced by the laser energy level as compared to the number of pulses. It is found that for the same number of pulses, there is a clear sign of an increase in HAZ with the increase in laser energy level. With the increase in the number of pulses, the hole or slot edge becomes more defined and clearer, whereas the HAZ is mostly determined by the energy level. There is an accumulation of molten or removed materials at the edge of holes or slots causing jagged edges of machined features, which gradually diminishes when the edge becomes smoother for a higher number of pulses, or accumulated materials evaporate away at the higher setting of energy level. Finally, it is found that the nanosecond laser system is capable of machining quality holes and slots on the 3D-printed CFRP composite. To obtain features with well-defined profiles and minimal heat-affected zone, an understanding of the effects of laser process parameters is important.

A comparative experimental study of unidirectional CFRP high-speed milling in up and down milling with varied angles

Precision machining of Carbon Fiber Reinforced Polymer (CFRP) is challenging due to its high strength and anisotropic microstructure. This study proposes a specially designed cutting experiment method to understand the influence mechanism of cutting force and surface quality in CFRP high-speed cutting process. The study examines the influence of fiber cutting angle, up/down milling, and machining parameters on the side milling of regular 12-corner unidirectional CFRP samples. Cutting force and surface quality are evaluated to analyze the machining process. The results show that the cutting angle is a key factor influencing milling force and surface quality. For cutting along the fiber, force follows 60° > 30° > 90° > 0°, and against the fiber, it follows 90° > 180° > 150° > 120°. The 90° cutting angle provides optimal surface quality, and cutting against the fiber facilitates material removal. Up-milling can reduce cutting force by 15 %–20 % and surface roughness Sa by up to 25 % compared to down-milling, while improving tool durability. High-speed cutting can reduce surface roughness by at least 35 %. These findings can optimize CFRP machining processes and improve quality results.

Bond behaviour between CFRP, GFRP, and hybrid C-GFRP tubes and seawater sea sand concrete after exposure to elevated temperatures

The paper provides an overview of the current research on bond performance between fibre-reinforced polymer (FRP) tubes and SWSSC and investigates the bond strength of SWSSC-filled FRP tubes after exposure to different temperatures using push-out tests. A total of 27 samples, including glass FRP (GFRP), carbon FRP (CFRP), and glass-carbon hybrid FRP (HFRP) tubes, were tested to determine the effect of elevated up to 250 °C temperatures on the bond performance of the samples. It was observed that exposure to elevated temperatures increased the bond strength of all the tubes. The GFRP and CFRP tubes exhibited the strongest and weakest bond strengths, respectively. Since the inner layer of the HFRP tube was composed of CFRP, the bond strength of HFRP was found to be more similar to that of CFRP samples than GFRP samples. The study concluded that the bond strength of all the samples was predominantly influenced by the surface roughness of the inner tube rather than the fibre type.

Thickness effect on flexural strengths of laminar carbon fibre composites

The thickness dependence of flexural strengths of laminar carbon fibre reinforced polymer (CFRP) plates was investigated experimentally and analytically in this study. This thickness effect was linked to the ply thickness by a simple composite formula. Four different sample thicknesses of 1.48, 2.08, 2.48 and 2.96 mm were tested, and thickness dependent flexural strengths were evaluated by the Strength of Materials (SOM) formula and modelled by the simple composite formula containing the ply thickness. The ASTM standard D7264, recommending 4 mm thick CFRP samples, was justified analytically, i.e., the thickness effect is negligible if W≥ 4 mm for CFRP plates with typical ply thickness around 120–130μm. The intrinsic tensile strength, independent of the sample thickness, was deduced from all flexural tests by the composite formula, which compared well with the tensile strength from unidirectional tensile tests and the tensile strength estimated from notched flexural samples. The specimen and notch/crack size requirements in ASTM standards for the fracture toughness were also explained analytically.

Machine learning based models for defect detection in composites inspected by Barker coded thermography: A qualitative analysis

Machine learning and artificial intelligence have evolved as enablers for automation in various industrial applications. Barker-coded thermography is an active thermal non-destructive testing technique for examining subsurface features in industrial components. This article introduces supervised and unsupervised machine learning models for automatic defect detection in composite specimens inspected by the barker-coded stimulus. This work provides supervised and unsupervised machine learning methods to detect defects in composite specimens examined with a barker automatically coded stimulus. The suggested technology is tested using a carbon fiber-reinforced polymer sample with synthetically reproduced flat bottom hole flaws. The one-class Support vector machine is chosen for the unsupervised class of operation, whereas the supervised technique modifies the traditional Support Vector Machine (SVM). The qualitative comparison suggests that the unsupervised approach presents a less than 1% marginal difference in defect detection from its supervised counterpart.

Effect of EPD coated silanized graphene oxide on carbon fiber reinforced plastic: An emphasis on mechanical properties at cryogenic temperatures

The space industry is constantly exploring lightweight, high-strength materials, particularly carbon fiber reinforced polymer (CFRP) composites. Nonetheless, in some cryogenic space applications, neat CFRP fails miserably. Here, silane functionalized graphene oxide (SGO) was coated on the carbon fiber surface to modify its properties. SGO is deposited onto a PAN-based plain weave carbon fiber using the electrophoretic deposition (EPD) process. SGO coated carbon fiber, along with epoxy resin, was used to fabricate CFRP laminates. From mechanical studies of CFRP samples, tensile, flexural, and impact strength improved by 13.1 %, 26.6 %, and 3.9 %, respectively, at room temperature (RT). The improvements were 15.1 %, 35.3 %, and 13.5 %, respectively, at cryogenic temperatures (CT). FTIR studies confirmed the emergence of a flexible Si-O-Si bond, which is a key factor for improved strength. AFM and SEM analysis were conducted to investigate contact roughness improvement. Contact angle microscopy examined SGO-induced wettability of modified carbon fiber. Also, a fracture study showed that the failure mode of SGO-coated CFRP at CT had changed from interface failure to matrix failure.

Multi-Criteria Evaluation of the Failure of CFRP Laminates for Frames in the Automotive Industry.

Methods to predict the fracture of thin carbon fibre-reinforced polymers (CFRPs) under load are of great interest in the automotive industry. The manufacturing of composites involves a high risk of defect occurrence, and the identification of those that lead to failure increases the functional reliability and decreases costs. The performance of CFRPs can be significantly reduced in assembled structures containing stress concentrators. This paper presents a hybrid experimental-numerical method based on the Tsai-Hill criterion for behavior of thin CFRPs at complex loadings that can emphasize the threshold of stress by tracing the σ-τ envelope. Modified butterfly samples were made for shearing, traction, or shearing-with-traction tests in the weakened section by changing the angle of force application α. ANSYS simulations were used to determine the zones of maximum stress concentration. For thin CFRP samples tested with stacking sequences [0]8 and [(45/0)2]s, the main mechanical characteristics have been determined using a Dynamic Mechanical Analyzer (DMA) and ultrasound tests. A modified Arcan device (AD) was used to generate data in a biaxial stress state, leading to the characterization of the material as a whole. The generated failure envelope allows for the prediction of failure for other combinations of normal and shear stress, depending on the thickness of the laminations, the stacking order, the pretension of the fasteners, and the method used to produce the laminations. The experimental data using AD and the application of the Tsai-Hill criterion serve to the increase the safety of CFRP components.

Electroluminescent strain sensing on carbon fiber reinforced polymer

The present paper demonstrates an inexpensive and less labor-intensive machine vision-based strain and damage visualization technique compared to traditional carbon fiber reinforced polymer material inspection methods. This technique is used to characterize the fracture and failure properties upon progressive axial loading in textile carbon fiber reinforced polymer (CFRP) lamina with non-intrusive smart electroluminescent (EL) integration. The smart EL structure utilizes CFRP's unique conductive and piezoresistive properties to visualize deformation and cracks through brightness change. Two fiber orientations (±45° and 0°/90°) of twill-weave CFRP lamina are fabricated according to a modified ASTM D3039 for linear and fatigue loading in uniaxial mechanical tests to analyze both fiber and matrix-induced EL responses. The EL-strain visualization method is validated with standardized digital image correlation (DIC) utilizing the natural speckling pattern of the EL CFRP lamina. The axial EL-strain results for both static and cyclic loading highly agree with the strain extracted planar conventional DIC strain field on standard and damaged CFRP samples in terms of spatial resolution and sensitivity. This novel strain and damage visualization method aims to be a portable, low-cost, and real-time alternative to non-destructive testing methods commonly used in the composite industry. Instead of periodic checkups, EL architecture allows for real-time strain and damage visualization of composite structure. • Fabrication and tensile testing of strain sensing EL illuminating woven CFRP in [±45°] and [0°/90°] fiber orientations. • Visual damage and strain detection are achieved with EL CFRP structure. • Planar DIC strain fields produced on EL illuminating and conventional airbrushed patterns show strong correspondence. • Variations in piezoresistive and luminance response exhibit correlation with strain.

Experimental study of the damage behaviour of laminated CFRP composites subjected to impulse lightning current

Compared with traditional metal alloy materials, carbon fibre-reinforced polymer (CFRP) composites have many excellent advantages except for being vulnerable to lightning strike damage. This paper presents a study on the damage behaviour of CFRP laminates exposed to impulse lightning current. Measurement of near-field lightning mechanical impact on the CFRP laminates was achieved by a self-established device that effectively overcome the strong electromagnetic inference. The damage results assessed by non-destructive techniques showed that the damage degree was intensified by increasing current amplitude for CFRP samples, including apparent and bulk damage. For samples with different surface conditions, the presence of insulating epoxy resin layer dramatically exacerbated the lightning strike damage, while expanded copper foil protection mitigated the damage considerably. It was found from the mechanical impact measurement that there is a good proportional relationship between the maximum impact forces and the action integral calculated with their corresponding time for CFRP samples. CFRP coated with insulating layer subjected to stronger mechanical impact, which is almost twice as large as pristine CFRP did under the same current level. The mechanical force impacted on CFRP protected with expanded copper foil was comparable to that of unprotected CFRP. Through analysis, it was concluded that the significance of mechanical effects on the lightning damage behaviour of CFRP composite depends on the thermal effects and vice versa.

Effect of equienergetic low-velocity impact on CFRP with surface ice in low temperature arctic conditions

In this study, the impact response and damage mechanisms of carbon fiber reinforced polymer (CFRP) with and without surface ice are investigated under equal impact energy, but different impactor mass-velocity configurations. CFRP samples are subjected to low-velocity impact at 23 °C and −70 °C to understand composite behavior in cold Arctic environment. Results show that impactors with lower mass, but higher velocity create greater damage due to higher strain rate sensitivity. Moreover, different damage modes are detected by X-ray micro-computed tomography for various mass-velocity configurations. The presence of surface ice influences damage mechanisms of CFRP specimens by altering stress distribution on the impact face. This research provides an understanding of the dynamic behavior of CFRP when deployed in low-temperature icy conditions.

Spatio-Temporal 3-D Residual Networks for Simultaneous Detection and Depth Estimation of CFRP Subsurface Defects in Lock-In Thermography

Nondestructive thermography is a high-speed, low-cost, and safe solution for subsurface defects detection of carbon fiber reinforced polymer (CFRP) materials, providing essential quality control in aerospace, automobile, and sports industries. In this article, we build a reflective lock-in thermography system and construct a dataset that contains real-captured thermal image sequences of CFRP samples with various simulated internal defects under different excitation frequencies. Then, we present a novel 3-D convolutional neural network (CNN) model incorporating a combination of spatial and temporal convolutional filters and batch-size independent group normalization (GN) as a unified framework to process thermal image sequences captured by lock-in thermography for simultaneous subsurface defect detection and depth estimation. Finally, we define a multitask loss function to perform end-to-end training of both defect detection and depth estimation tasks based on the real-captured infrared sequences. Comparative experiments are carried out on CFRP specimens with artificial defects of various sizes/shapes and at different depths. Qualitative and quantitative results illustrate that our 3-D CNN model is capable of predicting accurate locations and depths of subsurface defects and performs favorably against the hand-crafted and CNN-based methods in lock-in thermography for individual defect detection and depth estimation tasks. The captured dataset and the source codes will be made publicly available.

Model of the Temperature Influence on Additively Manufactured Carbon Fibre Reinforced Polymer Samples with Embedded Fibre Bragg Grating Sensors.

This study investigates the thermo-mechanical behaviour of additively manufactured Carbon Fiber Reinforced Polymer (CFRP) with embedded Fibre Bragg Grating (FBG) sensors with respect to their feasibility for utilising them under thermal loading. This was conducted through the Finite Element Method (FEM) inside an ABAQUS environment. Numerical simulation was complemented by several experimental investigations in order to verify the computational results achieved for the specimens exposed to thermal loading. FBG sensors, incorporated into the material by embedding technique, were employed to measure the strains of the samples subjected to elevated temperatures. It was shown that the strains given by numerical simulation were in good agreement with the experimental investigation except for a few errors due to the defects created within the layers during Additive Manufacturing (AM) process. It was concluded that the embedding FBG sensors were capable of identifying thermo-mechanical strain accurately for 3D-printed composite structures. Therefore, the findings of this article could be further developed for other types of material and loading conditions.