Fiber Reinforced Plastic Research Articles

Experimental Study on the Acceleration Amplification Ratio of Cable Terminations for Electric Power Facilities

Among national infrastructure facilities, electric power facilities are very important sites that must maintain their functions properly even during a natural disaster or during social crises. Therefore, seismic design is required when necessary for major electric power facilities that have a significant impact when damaged in the event of an earthquake. In electric power facilities, bushings are generally installed in devices or structures. Therefore, ground acceleration can be amplified through devices, such as transformers, or sub-structures. Among various electric power facilities, cable terminations are representative cantilever-type substation facilities consisting of a bushing, a sub-structure, and support insulators. The bushings of cable terminations are generally made of porcelain or fiber-reinforced plastic (FRP) materials, and they may have different dynamic characteristics. This study attempted to estimate the acceleration amplification ratio in the main positions of cable terminations considering the materials of bushings. For two cable terminations with different specifications and bushing materials, three-axis shake table tests were conducted in accordance with IEEE 693, which includes a seismic performance evaluation method for a power substation facility. The acceleration amplification ratios at the top of the bushing, mass center, and top of the support structure were estimated using the acceleration responses of each cable termination. They were then compared with the acceleration amplification factors presented in design standards. Consequently, the acceleration amplification ratio of cable termination with an FRP bushing was lower than that of the cable termination with a porcelain bushing.

The Effect of Modifiers on the Strength and Impact Toughness of Carbon Fiber Reinforced Plastics

This study utilized epoxy resin, three types of fabric (carbon fiber, glass fiber, and Kevlar), and two plasticizers – tricresyl phosphate (TCP) and oleic acid (OA) – to enhance the impact toughness of carbon fiber-reinforced plastics (CFRP). The polymer matrix used in the experiments was a hot-cured epoxy compound "Etal Inject-T" consisting of two components: A – epoxy resin and B – hardener, in a mass ratio of 100:49.9. For the fabrication of CFRP plates, both manual and vacuum molding techniques were employed. Combined reinforcement of carbon fiber was achieved using one of two types of fabrics: Ortex 360 glass fiber or Kevlar. Accordingly, two compositions were prepared for the experiments: carbon fiber/glass fiber and carbon fiber/Kevlar. Layer stacking in each composition was performed at ratios of 10:10 and 14:6, consisting of 20 layers in total. The greatest strengthening effect for CFRP in the case of carbon fiber/glass fiber was observed with a layer ratio of 14:6 and matrix modification using 10% TCP plasticizer. The strength of the CFRP increased from 425 to 451 MPa, and the impact toughness (α) improved from 192 to 280 kJ/m². A key feature of this technology is the achievement of high-performance dual-purpose CFRP. This enables the reduction of CFRP structures in aerospace applications by 3 to 5 times, while simultaneously enhancing resistance to impact loads.

Combining finite element analysis and reinforcement learning for optimal grip point planning of flexible components

Abstract Handling large flexible components is still a challenge in many industries. Examples include the handling of fibre-reinforced plastics or the assembly of industrial-scale electrolytic cells. Difficulties often arise in the design of suitable endeffectors. Inefficient gripping point design, i.e. the total number and positioning of grippers, can lead to increased stress and deflection of the component being handled. To counteract this, endeffectors are often oversized resulting in the use of more grippers than needed. Correspondingly, heavier moving masses imply longer handling times as well as higher energy consumption. This paper presents a process for planning and optimising gripping points for large flexible components. In addition to the shape of the component, actual dynamic loads of the handling path are also taken into account. The key element to the process is an optimisation algorithm based on reinforcement learning and trained using an finite element method (FEM) simulation. After computing a desirable starting configuration, the algorithm optimises the placement of gripper positions while aiming for a reduced total number. In addition, the optimisation has prescribed handling limits, such as physical and geometric constraints, that must not be exceeded. It was shown that the algorithm satisfactorily optimises the gripping points for dynamic loads for different materials and shapes. Furthermore, it has been shown that the computation of an initial configuration yields preferable results for simple components, yet requiring optimisation in the case of more complex shapes.

Assessment of occupational exposure to micro/nano particles generated from carbon fiber-reinforced plastic processing.

Carbon fiber-reinforced plastics (CFRP) are leading functional materials with superior strength and low mass density compared to metal. Our previous factory site analyses found that CFRP processing generates fibrous debris and fine micro/nano-sized particles of various shapes. The present interventional study was conducted at a factory located in Japan and evaluated debris consisting of various-sized particles generated during the industrial processing of CFRP, such as cutting, grinding, and turning of CFRP pipes, using real-time particle monitoring devices of the following: PM4 Digital Dust Monitor (DDM), handled Optical Particle Counter (OPC), Condensation Particle Counter (CPC), and Scanning Mobility Particle Sizer (SMPS). In addition, personal exposure of workers was evaluated using a novel wearable PM2.5-compatible device (P-sensor). First, we confirmed the presence of micro/nano particles in the dust generated during industrial processing of CFRP. Finer CFRP-generated particles were detected by the nanoparticle-compatible devices; CPC and SMPS, but not by OPC or DDM. The dynamic detection pattern of the P-sensor resembled that recorded by the nanoparticle-compatible devices. The novel wearable P-sensor can be used to measure finer particles generated by CFRP processing in occupational settings. Second, the exposure assessment was conducted twice and the levels of the micro/nano particles in the second survey were significantly (less than half) lower than that in the first survey. By avoiding immediate power-off of the exhaust system after operations, the scattering of particles was effectively reduced. Our results indicate that effective use of local exhaust ventilation system improves the workplace environment for particle exposure.

Dual-Modal Fusion PRI-SWT Model for Eddy Current Detection of Cracks, Delamination, and Impact Damage in Carbon Fiber-Reinforced Plastic Materials

Carbon fiber-reinforced plastic (CFRP) composites are prone to damage during both manufacturing and operational phases, making the classification and identification of defects critical for maintaining structural integrity. This paper presents a novel dual-modal feature classification approach for the eddy current detection of CFRP defects, utilizing a Parallel Real–Imaginary/Swin Transformer (PRI-SWT) model. Built using the Transformer architecture, the PRI-SWT model effectively integrates the real and imaginary components of sinusoidal voltage signals, demonstrating a significant performance improvement over traditional classification methods such as Support Vector Machine (SVM) and Vision Transformer (ViT). The proposed model achieved a classification accuracy exceeding 95%, highlighting its superior capability in terms of addressing the complexities of defect detection. Furthermore, the influence of key factors—including the real–imaginary fusion layer, the number of layers, the window shift size, and the model’s scale—on the classification performance of the PRI-SWT model was systematically evaluated.

Influence of stitching on the interlaminar fracture toughness energy – modes I and II – of unidirectional GFRP

Abstract The influence of stitching on the delamination resistance of unidirectional glass fiber-reinforced plastic laminates depends strongly on the loading mode. The application of a lock stitch with a stitch density of 3.4 cm−1 perpendicular to the fibers results in an increase of the interlaminar fracture toughness energy, mode I, G IC by a factor of 2.7 compared to an unstitched reference laminate. The Kevlar threads are pulled out of one half of the DCB specimen leaving large frayed fiber bundles sticking out of the other half. The same stitching, however, does not improve the interlaminar fracture toughness energy, mode II, G IIC. The Kevlar threads are not able to deform the surrounding matrix thereby expending additional energy. They fail directly at the mid-plane of the ENF specimens. An increased stitch density of 11.6 cm−1 can be expected to lead to a further significant increase in the G IC value. But the tight stitching pattern causes the bonded metal hinges to tear off. The force introduction would have to be changed to enable testing of corresponding DCB and subsequently ENF specimens.

Mechanical and thermal properties of microfibril /HDPE composite enhanced by nano-calcium carbonate

Natural fiber-reinforced plastic composites are powerful substitutes for traditional petroleum-based plastics. In order to promote the use of new composite, it is necessary to simplify the process, reduce the cost and meet the performance requirements. Herein, a nano-calcium carbonate (Nano-CaCO3)/ microfilament cellulose (MFC)/ high-density polyethylene (HDPE) composite was fabricated using a straightforward method, and the mechanical and thermal properties of the composite were tested by the relevant characterization. The test results show that a small amount of calcium carbonate can effectively co-strengthen with the main filler microfibril, and only 5 % of nano-calcium carbonate can increase the performance of the composite by 29 %, while its thermal stability and thermal decomposition performance were improved. The composites with superior properties would have potential applications in the field of structural and building, packaging and furniture.

Detection of matrix cracks in composite laminates using embedded fiber-optic distributed strain sensing

We used an optical frequency-domain reflectometry fiber Bragg grating (FBG) distributed strain measurement system to detect matrix cracks in carbon fiber-reinforced plastics. Load/unload tests were performed on cross-ply laminates under ambient-, high-, and low-temperature conditions using embedded 100mm gauge FBG sensors. We measured the strain distributed along the gauge and examined the crack initiation using optical microscopy and soft X-ray inspection. A peak appeared in the distributed strain corresponding to the occurrence of cracks. The strain distribution during crack initiation was calculated in each temperature range via finite element analysis and compared with the measurement results. We determined that the number and location of cracks can be determined by extracting the peaks from the distributed strain. However, the peaks in the distributed strain do not correspond to the occurrence of cracks that are close to each other, warranting a measurement method with a higher strain resolution.

Damage characterization of FRP embedded with different optical fibers under tensile load using acoustic emission and micrographic real-time inspection

Embedding optical fibers into fiber-reinforced plastics (FRPs) for composite health monitoring has attracted the interests of academia and industry recently though the impact of embedded optical fiber on FRP damage has not been clarified. In this study, the damage to the FRP structure caused by the embedded optical fibers was investigated. Five FRP samples incorporated with different types of optical fibers were subjected to tensile testing, and the crack initiation and propagation were in situ monitored using acoustic emission (AE) and micrographic inspection. After the AE signals were classified in terms of peak amplitude and peak frequency using K-means++ clustering, the damage progression from matrix cracking, fiber/matrix debonding, delamination, and fiber break were characterized. In-situ micrographic inspection clearly revealed the damage evolution around the embedded optical fiber. By correlating the stress-strain curves with the AE clustering and micrographic inspection results, it was verified that larger-diameter optical fibers reduce the modulus and ultimate strength of the FRP, while a good optical fiber/matrix interface mitigates these negative effects. The embedded optical fiber accelerated the crack propagation around it, leading to changes in the damage pattern. This phenomenon is the primary cause of FRP failure. Notably, polyimide-coated optical fibers with an outside diameter of 50 μm are ideal for embedded sensing as their incorporation into the matrix reduces the ultimate strength of FRP by only 1.8% with minimal impact on crack propagation.

Effect of Preheating Parameters on Extrusion Welding of High-Density Polyethylene Materials.

High-density polyethylene (HDPE) has emerged as a promising alternative to fiber-reinforced plastic (FRP) for small vessel manufacturing due to its durability, chemical resistance, lightweight properties, and recyclability. However, while thermoplastic polymers like HDPE have been extensively used in gas and water pipelines, their application in large, complex marine structures remains underexplored, particularly in terms of joining methods. Existing techniques, such as ultrasonic welding, laser welding, and friction stir welding, are unsuitable for large-scale HDPE components, where extrusion welding is more viable. This study focuses on evaluating the impact of key process parameters, such as the preheating temperature, hot air movement speed, and nozzle distance, on the welding performance of HDPE. By analyzing the influence of these variables on heat distribution during the extrusion welding process, we aim to conduct basic research to derive optimal conditions for achieving strong and reliable joints. The results highlight the critical importance of a uniform temperature distribution in preventing defects such as excessive melting or thermal degradation, which could compromise weld integrity. This research provides valuable insights into improving HDPE joining techniques, contributing to its broader adoption in the marine and manufacturing industries.

Computational Analysis of the Micromechanical Stress Field in Undamaged and Damaged Unidirectional Fiber-Reinforced Plastics Using a Modified Principal Component Analysis.

This study investigated the internal stress distribution of unidirectional fiber-reinforced plastics (UD-FRP) at the micro level using principal component analysis (PCA). The composite material was simulated using a representative volume element model together with the embedded cell approach. Two fundamental quasi-static load cases, transverse and longitudinal tensile deformation, were considered. The experimental results show that mechanical failure occurred at 2.15 ± 0.06% transverse tensile strain and at 1.52 ± 0.07% longitudinal tensile strain. Furthermore, the undamaged state and a combination of matrix and interface damage, as well as fiber breakage, were simulated. From the simulations, the octahedral shear stress and octahedral normal stress were computed at the integration points of the matrix elements, constituting what is known as the octahedral stress field. A modification on the PCA to obtain mesh-independent eigenvalues is presented and was used to investigate the effects of damage events on the octahedral stress field. The results indicate that each damage mechanism had a distinct signature in the redistribution of the stress field, characterized by specific changes in the eigenvalues and orientation of the principal component (θ1). Furthermore, the PCA suggests that the accumulation of matrix damage began to be relevant at the 1% strain, while fiber breakage began at an average longitudinal strain of 0.98 ± 0.12%. Additionally, it is shown that the first principal component served as an indicator of the predominant stress state of the stress field. This investigation suggests that the PCA can provide valuable insights regarding the complex damage mechanisms of UD-FRP that may not be captured by conventional mechanical analysis.

Fatigue life prediction of composite materials using strain distribution images and a deep convolution neural network

The damage process of composite materials, such as short fiber-reinforced plastics (SFRP), is complex. Therefore, it is necessary to accurately represent the damage process in fatigue life prediction. Herein, fatigue life prediction was conducted by combining the digital image correlation method, which is a non-destructive testing technique, with a convolutional neural network (CNN), using Xception as the network architecture. High prediction accuracy was obtained when training and testing were performed on the same SFRP specimens. In contrast, using different specimens for training and testing resulted in lower accuracy. This issue may be improved by increasing the number of specimens. The regions of interest in the model were visualized by Gradient-weighted Class Activation Mapping. Notably, the model indicated the breaking point as the region of interest from the early stages of the test. The breaking point was identified at an earlier stage by the CNN than by visual inspection, demonstrating the potential for a new method of damage observation.

Classification, Localization and Quantization of Eddy Current Detection Defects in CFRP Based on EDC-YOLO.

The accurate detection and quantification of defects is vital for the effectiveness of the eddy current nondestructive testing (ECNDT) of carbon fiber-reinforced plastic (CFRP) materials. This study investigates the identification and measurement of three common CFRP defects-cracks, delamination, and low-velocity impact damage-by employing the You Only Look Once (YOLO) model and an improved Eddy Current YOLO (EDC-YOLO) model. YOLO's limitations in detecting multi-scale features are addressed through the integration of Transformer-based self-attention mechanisms and deformable convolutional sub-modules, with additional global feature extraction via CBAM. By leveraging the Wise-IoU loss function, the model performance is further enhanced, leading to a 4.4% increase in the mAP50 for defect detection. EDC-YOLO proves to be effective for defect identification and quantification in industrial inspections, providing detailed insights, such as the correlation between the impact damage size and energy levels.

Strength characteristics analysis and unified model establishment of bonded, riveted, and adhesive-rivet hybrid CFRP joints

Carbon fiber-reinforced plastic (CFRP) bonded, riveted, and adhesive-rivet hybrid joints are among the weak parts of a structure. To study their strength characteristics and strength characterization methods, the key parameters of the CFRP constitutive model were obtained by constitutive tests, based on which finite element (FE) models of the three types of CFRP joints were established. The failure modes and F–D (load-displacement) curves of the CFRP joints were obtained through quasi-static tensile tests, and the accuracy of the FE models was verified. Based on the test results, the test strength models of the three types of CFRP joints were established, along with a unified model to characterize the joint strength; however, the strength models were affected by the joint parameters. Therefore, the influence of nine parameters on the joint strength were discussed, and the unified strength models of the three types of CFRP joints under each influencing parameter were established based on the initial strength model. The results showed that the unified strength models were highly correlated with R2 > 0.92. These results provide useful references for the strength check and parameter optimization of CFRP joints.

Smart carbon fiber reinforced plastic tubes with electromechanical structural health self-monitoring system

Carbon fiber-reinforced plastics (CFRPs), are utilized in the various mobilities owing to their superior specific structural rigidity. However, the studies for the structural health monitoring (SHM) of a tubular CFRP are relatively limited compared to its market share although it is directly related to the structural duties. Thus, this study investigated structural health self-monitoring (SHSm) of tubular CFRPs by monitoring their electrical resistances simultaneously. Multiple electrodes monitored electrical resistances of the CFRP tubes in terms of their mechanical deformation realizing condition-based SHM without any sensors. The proposed self-monitoring technology enabled not only local but also global deformation even after the mechanical fractures. Furthermore, the proposed self-monitoring method was comparatively analyzed and verified with corresponding mechanics and finite element analysis. Therefore, real-time SHSm technology for tubular CFRPs with various fiber stacking configurations was realised in this study covering all the deformation types over the whole structures.

Delamination and thrust force mitigation during drilling of unidirectional carbon fibre-reinforced plastic laminate using magnetorheological elastomer

Abstract In new improvements to the aviation industry, carbon fibre-reinforced plastic (CFRP) is a buoyant material due to its noteworthy and application-friendly properties. The behaviour of transversely isotropic CFRP, which prompts drilling-induced delamination, causes critical damage that leads to the rejection of the final product. The cause of the delamination damage is the thrust force generated by the drilling tool during the machining operation. The present work proposes an indigenous approach to suppress delamination significantly using magnetorheological elastomer (MRE). The thrust force generated by the drilling tool is recorded for varying magnetic field strengths. Delamination damage was computed using the MATLAB script. Meanwhile, specific focus was given to studying the interlaminar mechanics of a drilled hole through scanning electron microscopy. The results show that nearly 45% of the thrust force is reduced using this MRE at a maximum field strength of 0.4T compared to a conventional one. The results are further supported by a 22% and 30% smoothening of the delamination at the hole’s entry and exit, respectively. Thus, this approach helps to reduce delamination during drilling.

Acoustic Emission Energy Release Rate Model for Classification of Damage Development in Large Fiber Reinforced Plastic Composite Structures

Acoustic emission identification of fracture mechanisms in composite materials is of great importance for the practical assessment of the serviceability of aerospace structures, such as unmanned aerial vehicles, rocket motors, and others. Many scientific research studies conducted in recent decades have demonstrated the unique capabilities of the Acoustic Emission (AE) method to detect and identify different failure mechanisms, including fiber breakage, matrix cracking, and delaminations in fracture tests of composite specimens. However, testing large composite structures, in many cases, can be accompanied by multiple time-overlapped fracture events activated simultaneously, resulting in considerable difficulties in the classification and assessment of combined prolonged AE signals. In this work, we propose the Energy Release Rate (ERR) model for the classification of AE activity related to fiber-reinforced plastic (FRP) composite fracture. The model identifies accurately both micro-scopic and macro-scopic fracture mechanisms in large aerospace structures having complex composition of materials. The model is practically applied using several machine learning methods and provides a simple means to identify and discriminate typical fracture mechanisms and their combinations. Specifically, we describe ERR model, the choice of most informative AE parameters, the choice of suitable machine learning classification methods, their training and testing on FRP specimens, and validating the model in practical tests of large full-size FRP composite structures.

Behavior of laminated timber portal frames reinforced with fiber-reinforced plastic laminates under cyclic lateral load

This study aimed to enhance the structural performance of a drift joint with a slotted-in steel plate using laminated timber made from small- to medium-diameter timbers. An analysis was conducted to compare and evaluate the structural performance and seismic behavior of laminated timber portal frames reinforced with fiber-reinforced plastic (FRP) laminates, such as glass fiber cloth (GFC), glass fiber reinforced plastic sheet (GS), and carbon-reinforced plastic sheet (CS), under low amplitude cyclic lateral loads, in comparison to unreinforced portal frames (UR). The reinforced portal frame, strengthened by FRP laminates, exhibited higher resistance to strength and stiffness strength degradation due to cyclic loading-induced degradation at low drift angles compared to the unreinforced frame affected by heterogeneous timber. The reinforced portal frame, particularly the GFC and GS, exhibited energy dissipation rates 32% and 17% higher than UR, respectively, making them the most effective in vibration damping. FRP laminates mitigated fiber direction cleavage from drift pin holes. The average maximum moment and average yield moment of the reinforced portal frame increased by 18% and 21%, respectively, due to the alleviation of joint failure. Finally, CS significantly affected the maximum moment, while GFC significantly influenced the yield moment.

Prediction of tool wear and surface finish using ANFIS modelling during turning of Carbon Fiber Reinforced Plastic (CFRP) composites

Carbon fiber-reinforced plastics (CFRP) are widely used in various industries due to their high strength to weight ratio, corrosion resistance, durability, and excellent thermo-mechanical properties. The machining of CFRP composites has always been a challenge for the manufacturers. In this study, CNC turning operation with coated carbide tool is used to machine a specific CFRP and the relationship between the cutting parameters (Speed, Feed, Depth of Cut) and response parameters (Vibration, Surface Finish, Cutting Force and Tool Wear) are investigated. An adaptive-network-based fuzzy inference system (ANFIS) model with two multi-input–single-output (MISO) system has been developed to predict the tool wear and surface finish. Speed, feed, depth of cut, vibration and cutting force have been used as input parameters and tool wear and surface finish have been used as output parameters. Three sets of cutting parameter have been used to gather the data points for continuous turning of CFRP composite. The model merged fuzzy inference modeling with artificial neural network learning abilities, and a set of rules is constructed directly from experimental data. This model is capable of predicting the cutting tool wear and surface finish during turning of CFRP composite. The predicted tool wear and surface finish data are compared to the experimental results. The predicted data agreed well with the actual experimental data with 98.96 % accuracy for tool wear and 99.61 % accuracy for surface finish.

Growth performance of critically endangered Hypselobarbus pulchellus in biofloc system: Influence of carbon sources on immune response, enzyme and antioxidant activity

We investigated the effect of various carbon sources on the production performance of critically endangered Hypselobarbus pulchellus in biofloc system. The experimental setup comprised four biofloc treatment groups with various carbon sources (jaggery, tapioca, rice and corn flour) and a control group. Healthy early fry (0.0068 g) was randomly stocked at 100 individuals per m3 into 15 circular fibre reinforced plastic (FRP) tanks (1000 l) and raised for 90 days. All the tested carbon sources significantly influenced weight gain, weight gain (%) and specific growth rate (SGR), with the jaggery treatment displaying the best growth performance (p<0.05). Fingerling survival rates varied from 93 to 95.67% (p>0.05). Compared to the control, the biofloc groups had significantly lower concentrations of nitrogen compounds, specifically total ammonia nitrogen, nitrite and nitrate concentrations were significantly lowered (0.29, 0.35 and 1.32 mg l-1, respectively) in jaggery treatment (p<0.05). In addition, the treatment using jaggery had a higher amount of plankton biomass and an abundance of the Bacillariophyceae group (80%). All biofloc groups displayed enhanced immune and antioxidant activity compared to the control. The jaggery treatment had elevated levels of lysozyme activity than other treatments (p<0.05). Furthermore, fingerlings raised in BFT treatments had significantly higher amylase, protease and lipase activity (p<0.05). Overall, this study’s findings suggest that the addition of various carbon sources significantly improves the production performance, with jaggery as the best carbon source for critically endangered H. pulchellus fingerling production in biofloc system to ensure sustainability. Keywords: Antioxidant activity, Fingerling, Heterotrophic bacteria, Jaggery, Specific growth rate, Sustainability