Fiber Reinforced Plastic Research Articles

Failure analysis of unidirectional FRP with fiber clusters under transverse pure shear

In nearly all the failure criteria for the FRP (fiber reinforced plastic), the fundamental strength of the FRP under uniaxial tensile, compressive and pure shear stress were utilized to construct appropriate mathematical function relationship with the multiaxial stress. Among them, the strength of the FRP under transverse pure shear stress was influenced by various factors and could not be directly obtained from tests. In this paper, transverse pure shear failure behavior of FRP was studied using finite element analysis based on RVE models, the RSE and HC algorithm were utilized to generate the FRP with different fiber distribution, mainly refers the different fiber clusters which was commonly experimentally observed. The bilinear cohesive model and extended linear Drucker Prager model were used to characterize the mechanical behavior of the interface and matrix respectively. Then, constraint of periodic boundary condition was applied for the RVE models. Difference on failure fracture behavior of FRP with different fiber distribution were identified and assessed under transverse pure shear stress, while the connection between stress triaxiality and initial damage equivalent plastic strain of the matrix was also altered. On this basis, the distinction of the maximum transverse pure shear stress, the crack resistance strength and the transverse shear strength was thoroughly discussed and identified, which provided a theoretic reference for the failure analysis of the FRP.

A study of machine learning object detection performance for phased array ultrasonic testing of carbon fibre reinforced plastics

The growing adoption of Carbon Fibre Reinforced Plastics (CFRPs) in the aerospace industry has resulted in a significant reliance on Non-Destructive Evaluation (NDE) to ensure the quality and integrity of these materials. The interpretation of large amounts of data acquired from automated robotic ultrasonic scanning by expert operators is often time consuming, tedious, and prone to human error creating a bottleneck in the manufacturing process. However, with ever growing trend of computing power and digitally stored NDE data, intelligent Machine Learning (ML) algorithms have been gaining more traction than before for NDE data analysis. In this study, the performance of ML object detection models, statistical methods for defect detection, and traditional amplitude thresholding approaches for defect detection in CFRPs were compared. A novel augmentation technique was used to enhance synthetically generated datasets used for ML model training. All approaches were tested on real data obtained from an experimental setup mimicking industrial conditions, with ML models showing improvement over amplitude thresholding and statistical thresholding techniques. The advantages and limitations of all methods are reported and discussed.

Some warning signs detected in coastal pelagic fisheries of the west coast of Sri Lanka: Declining trend of <em>Amblygaster sirm</em> suggesting the need for immediate management initiatives

Coastal fisheries, mainly characterized by small pelagic species, are significant on the west coast of Sri Lanka in terms of livelihood and food security. However, currently, the fishery has faced numerous challenges, particularly with the stock depletion allied with poor management practices. The present study was carried out using the time series data of 2001–2020 on the west coast of Sri Lanka representing four fisheries districts - Kalutara, Colombo, Negombo, and Chilaw - to explore the present status and the tendency of the fishery towards management considerations. The analysis was based on the outboard engine fiber-reinforced plastic boats (OFRP) with small meshed gillnets, which are the main boat gear combination that exists in the fishery. The recent five-year landings within the study period indicated that the highest average catch rates resulted in the onset of the southwest monsoon and extended until the end of the northeast monsoon. The catch rates of fishery exhibited greater inter-annual fluctuations during a two-decade period, with an average of 66.7 ± 17.3 kg per trip from 2011 to 2020. Over the past two decades, the Mean Trophic Level (MTL) of the coastal fish landings ranged from 3.13 to 3.62 and showed a declining trend with the forecast of 3.38 for 2022-2026. Moreover, the catch rates and the relative contribution of Amblygaster sirm, one of the main target species in the country, showed a declining trend over the past two decades while indicating the need for immediate management initiatives.

Multimodal 1D CNN for delamination prediction in CFRP drilling process with industrial robots

There is a growing demand for carbon fiber-reinforced plastics (CFRPs) in the aerospace and automotive industries. Consequently, the assembly and repair of CFRP components has garnered considerable attention. However, at industrial sites, there are potential difficulties in the CFRP drilling process. These challenges arise from the anisotropic properties of CFRP and the limitations of using an optical microscope to assess the quality of millions of drilled holes. Therefore, this study introduced an advanced indirect prediction method for the CFRP hole quality based on multisensor data. During the drilling process, data including force, torque, acceleration, voltage, current, sound, and images of the hole exits were acquired via a robotic machining system. The delamination factors, Fd and Fa, which quantify the quality of the hole, can be calculated from the hole images. Preprocessing was employed to segment the sensor data into discrete drilling trials and extract spectral features from the data. This paper proposed a multimodal one-dimensional convolutional neural network (1D CNN) that predicts delamination factors from time series multi-sensor data. A case study, using a test set of 100 trials, validated the proposed model. The performance of the proposed model was evaluated by the mean squared error (MSE) and inference time, yielding 8.42 ± 0.167 × 10−2 and 3.48 ± 0.192 s for Fd, and 6.1 ± 0.729 × 10−2 and 3.13 ± 0.098 s for Fa, respectively, across the entire test set with 100 trials. This result exceeds those of previous studies in terms of both the MSE value and inference time for multimodality, emphasizing the predictive accuracy and real-time operational capabilities of the proposed model in industrial settings. Furthermore, this approach provides practicality and flexibility, facilitating the easy integration or removal of sensors through data-driven preprocessing and a multimodal learning scheme.

Textile-based strain sensors for fiber-reinforced composites under tension, compression and bending

Abstract This research addresses the challenging task of monitoring the structural integrity of fiber-reinforced composite (FRC) components under complex loading conditions. Ensuring the safety and functionality of these components is critical but economically challenging. Therefore, this study presents an innovative approach using textile-based strain sensors that are cost-effective and structurally compatible with carbon fiber-reinforced plastic (CFRP) components. The investigation includes the systematic electromechanical characterization and comparison of four different sensor materials at the yarn and composite scale in various test scenarios. Cyclic tensile, compression, and bending tests of CFRP specimens are performed and show good reproducibility of sensor signals within the elastic range, with significant agreement observed with applied strain measurement methods, particularly in tensile tests. Although there are minor deviations in compression and bending evaluations, the signals are still meaningful for in-situ detection of complex loading patterns, crack initiation, and structural failure. The study demonstrates that the integration of textile-based sensor yarns allows for continuous structural health monitoring (SHM) of CFRP components under various loading scenarios, including tensile, bending, and especially compressive loads.

Fracture mechanism of carbon fiber-reinforced thermoplastic composite laminates under compression after impact

Thermoplastic carbon fiber-reinforced plastics (CFRPs) are increasingly utilized in the aerospace industry owing to their beneficial properties and enhanced formability relative to thermoset CFRPs. Despite the extensive use of these materials, studies focusing on compression after impact (CAI) tests with impact energies exceeding 20 J for thermoplastic CFRPs remain scarce. This study examines CAI tests on quasi-isotropic laminates of thermoplastic CFRP, subjected to a low-velocity impact energy of 27.04 J. For comparison, quasi-isotropic laminates of thermoset CFRP were subjected to a low-velocity impact energy of 36.5 J. These tests reveal that the CAI strength of both materials is comparable, notwithstanding the lower fiber volume fraction in the thermoplastic CFRP. Further, this research incorporates a finite element (FE) analysis to investigate the damage mechanisms in thermoplastic CFRP. The FE model, integrating interlaminar damage observed during the impact tests, accurately predicted the relationship between compressive stress and strain, correlating closely with the experimental outcomes. It was observed that both interlaminar and intralaminar damage propagation were constrained until the point of maximum compressive stress. Prior to reaching this maximum, a region of elevated compressive stress in the fiber direction was noted in the 0° layer near the non-impacted side. These findings indicate that the compressive stress in the fiber direction in the 0° layer adjacent to the non-impacted side is pivotal in dictating the final failure, which determines the CAI strength of thermoplastic CFRP laminates.

Temperature-dependent calibration and temperature compensation of elastic shape-memory alloy strain sensors for fiber-reinforced composite applications

Abstract Strain sensors for fiber-reinforced plastics require higher elasticity and fatigue resistance than conventional strain gauges. Elastic strain sensors made of shape-memory alloys (SMA) meet this requirement. Due to greater elasticity, other procedures are required for their calibration than those recommended in standards. This paper presents a calibration method for shape-memory strain sensors as a function of ambient temperature and methods for temperature compensation are investigated. SMA strain sensors are manufactured as sensor patches from wire and layers of glass fiber fleece infiltrated with epoxy resin. The patches are bonded to bending specimens made of glass-fiber plastic composites. The calibration of the SMA sensors is implemented by means of a 4-point bending test using a self-built test stand. This is designed for operation in a climate chamber. The results show successful proof of feasibility of temperature compensation. The variation of the sensor signal in the unloaded state in the temperature response is less than 0.4 mV/V. The gauge factor depends on the temperature and is compensated by means of a regression with temperature sensor data. In combination with a temperature sensor, an almost complete compensation of the temperature-dependent behaviour is possible. A procedure is realised for calibrating SMA sensors at larger strains.

Multi optimization in slot milling of CFRP composites through grey relational- based Taguchi analysis

Carbon fiber-reinforced plastic (CFRP) composite materials are challenging to machine due to their anisotropy and heterogeneity. Thus, the experimental study of milling CFRP composite material is very crucial. In the current study, based on Taguchi’s L9 orthogonal array, slot milling experiments were performed on CFRP composite samples to make a decision on a parametric optimization of multiple responses such as material removal rate (MRR), delamination factor (Fd) and surface roughness (Ra) using grey relational-based Taguchi analysis. The selected milling parameters are cutting speed (A), feed (B), and depth of cut (C). Based on Grey Relational Grade (GRG), Analysis of Variance (ANOVA) was used to determine the parameters' significant contributions and the parameters' optimal levels. The results showed, with a 95% confidence level, that all of the chosen cutting parameters have a substantial impact on all of the measured responses. Based on a confirmatory test performed under ideal milling conditions, MRR has been increased with an improvement of 31.25 %, Fd has been decreased with an improvement of 1.66% and Ra has been decreased with an improvement of 28.3%. These improvements in all measured responses are equivalent to an improvement of GRG by 3%.

Fiber-steered acoustic black hole beam with low cut-on frequency and high stiffness

This study proposes an acoustic black hole (ABH) beam with varying carbon fiber orientation and thickness for a low cut-on frequency and high stiffness. The proposed fiber-steered ABH beam contains a laminate with a varying fiber orientation as a junction between a tapered 90° laminate and uniform 0° laminate. The anisotropic viscoelastic properties of the carbon fiber-reinforced plastic were identified using dynamic mechanical analysis tests and a micromechanics model for fiber composites. An analytical model was developed to derive the solutions for the displacement field, cut-on frequency, and reflection coefficient. The analytical solutions demonstrated that varying the fiber orientation contributes to the decrease in the cut-on frequency and the reduction of the reflection coefficient while maintaining the stiffness of the host structure. Finite element method analyses were performed to investigate the frequency response of the fiber-steered ABH beam. The fiber-steered ABH beam exhibited lower resonance peaks than the uniform 0° laminate beam. The higher loss tangent of the 90° laminate compared to that of the 0° laminate improved the damping performance without an additional viscoelastic material layer. The frequency response calculated using the analytical solution agreed well with the numerical analysis results.

Cryogenic insulation performance of polyimide foam-filled fluted-core composite sandwich panels

Foam-filled composite sandwich structures have demonstrated superior thermal insulation performance, making them highly suitable for cryogenic tanks in launch vehicles. This study focused on the cryogenic insulation characteristics of carbon fiber-reinforced plastic (CFRP) fluted-core sandwich panels filled with polyimide foam. The fluted-core sandwich panel was simplified into a homogeneous multilayer plate to establish a one-dimensional heat transfer theoretical model. This model was used to predict steady-state temperature approximate solutions by linearizing the temperature-dependent thermal conductivity. The sandwich specimens were fabricated using an integrated forming co-cured method. Self-developed cryogenic insulation experiment and finite element simulations were conducted to acquire temperature distributions and validated the precision of the theoretical model. Results showed that the specimens achieved insulation temperature difference exceeding 143.05 °C, with effective thermal conductivity reaching 0.0326 W/(m·°C), significantly lower than that of CFRP. The temperature distributions along the thickness direction displayed a nonlinear increasing trend. The cryogenic thermal short effect was noticeable at the junction of the bottom facesheet and web. An analysis of geometric parameter influences revealed that increasing the short span, core height, or reducing web thickness could enhance thermal insulation characteristics with minimum effective thermal conductivity of 0.0276 W/(m·°C) and lead to a more uniform distribution of bottom temperatures with minimum temperature difference of 3.30 °C. These findings provide a foundational analysis for designing cryogenic insulation structures.

CO2 Emissions from Blade Waste Treatments under Wind Power Scenario in Japan from 2021 to 2100

Wind power generation has been introduced to reduce carbon emissions; however, recycling or recovering the waste of wind blades, which contain fibre-reinforced plastic, is difficult. Converting the recovered materials for secondary use is also difficult owing to the decreased strength and low material value. Many countries, including Japan, have not considered the future energy and CO2 emission scenarios, particularly CO2 emissions from wind blade waste. Based on these scenarios, Japan has planned to introduce large amounts of onshore/offshore wind power generation through 2050. Therefore, we aimed to evaluate quantitatively the total amount of waste and the global warming potential (GWP) from multiple blade waste treatment processes. Based on the average lifetime of blades (20–25 years), we found that the GWP of wind blade waste treatment in Japan may reach a maximum of 197.3–232.4 MtCO2eq by 2060–2065. Based on this lifetime, the wind blade treatment in 2050 accounted for 63.9–80.1% of the total greenhouse gas emissions in 2050. We also showed that the rise in CO2 emissions from the wind blade wastes would make up 82.5–93.6% of the potential reduction in the GWP, which is achievable by shifting from thermal to wind power generation.

High-Throughput Additive Manufacturing of Continuous Carbon Fiber-Reinforced Plastic by Multifilament.

Additive manufacturing (or 3D printing) of continuous carbon fiber-reinforced plastics with fused deposition modeling is a burgeoning manufacturing method because of its potential as a powerful approach to produce lightweight, high strength and complex parts without the need for a mold. Nevertheless, it cannot manufacture parts rapidly due to low throughput. This paper proposes a high-throughput additive manufacturing of continuous carbon fiber-reinforced plastics by multifilament with reference to fiber tape placement. Three filaments were fed and compaction printed simultaneously by a robotic manufacturing system. The coupled thermal-mechanical model of the filament deformation during printing was developed to eliminate the initial interval between the filaments and improved mechanical properties. Furthermore, the mathematical relationship between filament deformation and printing parameters consisting of printing temperature, printing speed and roller pressure was proposed using response surface methodology with the line width as the response. The tensile tests demonstrate that the tensile properties of printed parts are positively correlated with the line width, but not infinitely improved. The maximum tensile strength and tensile modulus are 503.4 MPa and 83.11 Gpa, respectively, which are better than those obtained by traditional methods. Void fraction and scanning electron microscope images also reveal that the appropriate line width achieved by the reasonable printing parameters contributes to the high-throughput multifilament additive manufacturing of continuous carbon fiber-reinforced plastics. The comparison results indicate that the high-throughput multifilament additive manufacturing proposed in this paper can effectively improve the speed of continuous carbon fiber-reinforced plastics additive manufacturing without degrading the mechanical performance.

Transforming GFRP into silicon carbide

Rice University researchers develop an energy-efficient method to upcycle glass fiber-reinforced plastic (GFRP).

Techno-Environmental Evaluation of Alkaline Treatment in Flax Reinforced Thermoplastics.

A combination of thermoplastics and natural fiber reinforcements is considered an ideal choice to mitigate environmental impacts and enhance recyclability or reusability. Chemical treatments are often employed to enhance the thermomechanical properties of natural fiber-reinforced plastics. Nevertheless, it is of paramount importance to assess the techno-economic impact of such chemical treatments and environmentally friendly materials for their implementation in mass productions on an industrial scale. In this work, high-density polyethylene is reinforced with sodium hydroxide (NaOH)-treated and untreated flax fibers to study its impact on mechanical and environmental properties. The composites treated with NaOH exhibited a 37% increase in tensile strength. However, life cycle assessment performed on the NaOH-treated samples showed that they had a global warming potential of 5.8 kg of CO2, a terrestrial acidification potential of 0.0269 kg of SO2, and a human carcinogenic toxicity of 0.031 kg of 1,4-DCB compared to the untreated samples. In summary, the techno-environmental analysis reveals a novel approach to identifying chemical treatments based on their technical and environmental effects.

Achieving strong interfacial bonding of CFRP and magnesium alloy by modifying magnesium alloy surface via alkaline etching with EDTA addition

The interfacial properties of fibre metal laminates are closely related to the surface microstructure of metals. Herein, a hitherto unreported honeycomb-like micro/nano-porous structure was successfully fabricated on an AZ31B Mg alloy surface by incorporation of ethylenediaminetetraacetic acid disodium (EDTA-2Na) into an alkaline solution and achieved excellent interfacial bonding property between AZ31B and carbon fibre-reinforced plastic. The addition of EDTA-2Na can promote the formation of etched pores. The growing nano-scale etched pores join together to produce micro-scale pores and ultimately lead to the formation of a micro/nano-porous structure. The 60 min etched AZ31B/carbon fibre-reinforced plastic laminate exhibits a bonding strength of 25.87 MPa, which is an increase of 350.7% compared to that of the untreated sample. The significant increase in bonding strength is mostly ascribed to composite mechanical interlocking by the micro/nano-porous structure and chemical bonding through the formation of MgCO3 and MgO1+X. In addition, the characteristics of micro-pores also affect the bonding strength.

Investigation on carbon fiber-reinforced polymer combined with graphene nanoparticles subjected to drilling operation using response surface methodology and non-dominated sorting genetic algorithm-II

In this article, drilling of carbon fiber-reinforced plastics combined with graphene nanoparticles is investigated. These nanocomposites have the potential to be used widely in different industrial applications such as electrical, biomedical and aerospace engineering due to their superior mechanical and thermal specifications. Nonetheless, to be assembled on different sets, drilling nanocomposites is required especially for rivets and joints. In drilling carbon fiber-reinforced polymers (CFRPs), delamination is one of the main challenges that should be minimized in order to enhance the produced hole quality. Besides, machining force is a chief factor to control the drilling-induced damages, especially delamination. This article evaluates the effects of machining parameters on machining force and delamination using response surface methodology experimental design and non-dominated sorting genetic algorithm-II (NSGA-II) multiobjective optimization methodology. Examining delamination is conducted in two parts including peel-up and push-down delamination which are the principal drawbacks in drilling of fiber-reinforced composites. Analysis of variance is also carried out in order to examine the effects of the machining parameters. In addition, predictive quadratic correlations are established by regression analysis. Eventually, multiobjective optimization was implemented by NSGA-II and the optimal values were obtained from pareto-optimal solution set aimed at enhancing the drilling process.

High Strain Rate Modeling of CFRP Composite Under Compressive Loading

An in-depth understanding of how carbon fiber-reinforced plastics (CFRP) respond to intense strain rates is essential, particularly in non-linear deformation and dynamic loading situations. The researchers undertook a computational study to examine the behavior of CFRP composites when exposed to high strain rates under compressive loading. Specifically, they employed Split Hopkinson Pressure Bar models for cohesive interfacial simulations, continuum shell analysis, and laminated composites oriented at 0° at a strain rate equivalent to 900 s-1. The Finite Element model utilized a custom Hashin damage model and a vectorized user material (VUMAT) sub-routine to identify degradation damage within the CFRP composite model. The quasi-isotropic composite demonstrated a significant enhancement in dynamic strength compared to static values, attributed to its intense sensitivity to strain. As confirmed by experimental test results, numerical simulations accurately predicted stress (σ)-strain (ε) and strain rate (ἐ) curves. Additionally, it was observed that the relationship between damage behavior varied depending on the element type used.

A Bio-Inspired Approach to Improve the Toughness of Brittle Bast Fibre-Reinforced Composites Using Cellulose Acetate Foils.

Bast fibre-reinforced plastics are characterised by good strength and stiffness but are often brittle due to the stiff and less ductile fibres. This study uses a biomimetic approach to improve impact strength. Based on the structure of the spicules of a deep-sea glass sponge, in which hard layers of bioglass alternate with soft layers of proteins, the toughness of kenaf/epoxy composites was significantly improved by a multilayer structure of kenaf and cellulose acetate (CA) foils as impact modifiers. Due to the alternating structure, cracks are deflected, and toughness is improved. One to five CA foils were stacked with kenaf layers and processed to composite plates with bio-based epoxy resin by compression moulding. Results have shown a significant improvement in toughness using CA foils due to increased crack propagation. The unnotched Charpy impact strength increased from 9.0 kJ/m2 of the pure kenaf/epoxy composite to 36.3 kJ/m2 for the sample containing five CA foils. The tensile and flexural strength ranged from 74 to 81 MPa and 112 to 125 MPa, respectively. The tensile modulus reached values between 9100 and 10,600 MPa, and the flexural modulus ranged between 7200 and 8100 MPa. The results demonstrate the successful implementation of an abstract transfer of biological role models to improve the toughness of brittle bast fibre-reinforced plastics.

Valorisation of Sub-Products from Pyrolysis of Carbon Fibre-Reinforced Plastic Waste: Catalytic Recovery of Chemicals from Liquid and Gas Phases.

Waste carbon fibre-reinforced plastics were recycled by pyrolysis followed by a thermo-catalytic treatment in order to achieve both fibre and resin recovery. The conventional pyrolysis of this waste produced unusable gas and hazardous liquid streams, which made necessary the treatment of the pyrolysis vapours. In this work, the vapours generated from pyrolysis were valorised thermochemically. The thermal treatment of the pyrolysis vapours was performed at 700 °C, 800 °C and 900 °C, and the catalytic treatment was tested at 700 °C and 800 °C with two Ni-based catalysts, one commercial and one homemade over a non-conventional olivine support. The catalysts were deeply characterised, and both had low surface area (99 m2/g and 4 m2/g, respectively) with low metal dispersion. The thermal treatment of the pyrolysis vapours at 900 °C produced high gas quantity (6.8 wt%) and quality (95.5 vol% syngas) along with lower liquid quantity (13.3 wt%) and low hazardous liquid (92.1 area% water). The Ni-olivine catalyst at the lowest temperature, 700 °C, allowed us to obtain good gas results (100% syngas), but the liquid was not as good (only 58.4 area% was water). On the other hand, the Ni commercial catalyst at 800 °C improved both the gas and liquid phases, producing 6.4 wt% of gas with 93 vol% of syngas and 13.6 wt% of liquid phase with a 97.5 area% of water. The main reaction mechanisms observed in the treatment of pyrolysis vapours were cracking, dry and wet reforming and the Boudouard reaction.

Non-linear frequency modulated thermal wave imaging for subsurface analysis

Thermographic analysis for subsurface non-destructive evaluation often encounters challenges in achieving better depth scanning and enhanced depth resolution. Usually, deeper depth analysis will be facilitated by the strength of the low-frequency components and the depth resolution on the frequency sweep of the stimulation, along with material properties in this active thermographic modality. Non-linear frequency modulation became prominent for subsurface analysis due to its ability to provide a band of frequencies with increased energy at low frequencies. This manuscript introduced novel Logarithmic frequency modulated stimulation for subsurface analysis and compared it with its well-established linear frequency counterpart. A quantitative analysis was performed using detectability and sizing of the defects. Experimental results demonstrate that the proposed modality offered an edge over the state of the art, as shown by the experimentation carried out over a carbon fibre-reinforced plastic specimen with embedded flat bottom holes.