Carbon Fiber Composite Structures Research Articles

Design, fabrication and vibration characteristics of a novel composite auxetic structure embedded with resonators

With the rapid development of shipbuilding and aerospace industries, the mechanical performance requirements for structures are becoming increasingly demanding. Conventional vibration reduction structures cannot meet the requirements for lightweight, high load capacity, low frequency and broadband vibration reduction. Therefore, it is necessary to consider new structural topologies and material systems. Inspired by the lightweight and high strength characteristics of composite materials, the negative Poisson's ratio characteristics and the locally resonating phononic crystal, the carbon fiber composite auxetic structure embedded with resonators is proposed. Embedded resonators within composite auxetic structures can be strategically positioned to introduce gaps, thereby enhancing the vibration damping performance. The basic auxetic structure is prepared by simpler methods including molding and bonding, and the outer shell of resonator is made by 3D printing technology. The method enables the design of appropriate outer shell based on various cavity types within the structure, ensuring a stable connection between resonators and the structure itself. The range of the band gap can be predicted based on the negative effective mass. Vibration behavior and band gap characteristics of the structure are proved through vibration experiments and numerical simulations. It is revealed that the structure can generate local resonant band gaps at lower frequencies. Meanwhile, the coupling relationship between the auxetic structure and the resonator makes an impact to the band gap range. Therefore, the proposed structure can meet the required multi-functional integrated performance requirements. Furthermore, the parametric analysis is carried out, and the relevant conclusions can provide theoretical guidance for designing porous composite structures with effective low-broadband vibration reduction capabilities.

Investigation of the Mechanical Properties of Composite Honeycomb Sandwich Panels after Fatigue in Hygrothermal Environments.

Since carbon fibre composite sandwich structures have high specific strength and specific modulus, which can meet the requirements for the development of aircraft technology, more and more extensive attention has been paid to their residual mechanical properties after subjecting them to fatigue loading in hygrothermal environments. In this paper, the compression and shear characteristics of carbon fibre-reinforced epoxy composite honeycomb sandwich wall panels after fatigue in hygrothermal environments are investigated through experiments. The experimental results show that under compressive loading, the load required for the buckling of composite honeycomb sandwich wall panels after fatigue loading in hygrothermal environments decreases by 25.9% and the damage load decreases by 10.5% compared to those at room temperature. Under shear loading, the load required for buckling to occur is reduced by 26.2% and the breaking load by 12.2% compared to those at room temperature.

Ultrasonic guided wave-based probabilistic diagnostic imaging method with Single-Path-Scattering sparse reconstruction for Multi-Damage detection in composite structures

Plate-like carbon fiber composite structures are essential for equipment such as spacecraft and rail vehicles. These structures are exposed to long-term cyclic loads and harsh environmental conditions, leading to damage of unknown location and quantity. Ultrasonic guided wave (UGW) detection technology shows promise for evaluating the structural performance of composite structures due to its advantages of high precision, high speed, and real-time capabilities. However, multi-damage scattering sources interfere with and superimpose the received signals when multiple damages coincide. This interference can lead to artifacts in probability imaging methods that rely on features such as amplitude and time of flight (TOF). This paper proposes a single-path-scattering sparse reconstruction-based probabilistic diagnostic imaging (SSR-PDI) method. Firstly, a Lamb dictionary with time shift is constructed. Each actuator-receiver path is treated as a target signal, enabling the approximate separation and extraction of multiple scattering waves from different damages. It mitigates the “curse of dimensionality” associated with the sparse reconstruction (SR) method. Secondly, a new ring-shaped damage probability distribution is proposed based on the sparse representation matrix’s time mapping and amplitude weighting. The experimental results demonstrate that the SSR-PDI method effectively mitigates issues related to multi-damage detection, specifically false negatives/positives and localization errors arising from the superposition of scattering sources.

Experimental study on compression properties of composite aluminum honeycomb sandwich structures

AbstractThe mechanical properties of the carbon fiber and glass fiber composite honeycomb sandwich structure were studied through compression experiments. The influence of different aluminum honeycomb edge lengths, upper and lower panel thickness, aluminum honeycomb thickness, and loading speed on the compression failure load of carbon fiber composite laminates sandwich structure is analyzed. The influence of different aluminum honeycomb edge lengths and thicknesses on the compression failure load of glass fiber composite laminates sandwich structure was studied. The results show that the thickness of the panel has a significant effect on the failure load of the carbon fiber composite laminate sandwich structure, and the loading speed has a significant effect on the failure load of the carbon fiber composite laminate sandwich structure. The greater the loading speed, the greater the value of the failure load. The edge length and thickness of the aluminum honeycomb have a certain effect on the damage load of the carbon fiber composite laminates sandwich structure, but the influence on the mechanical properties of the glass fiber composite laminates sandwich structure is much greater.Highlights The compression performance of composite sandwich structures was experimentally studied. The influence of composite panel thickness was studied. The influence of aluminum honeycomb edge length and thickness was studied. The influence of loading speed was studied.

Development of a Prototype Drone through Carbon Fiber Composite Structures and Additive Manufacturing Techniques

Development of a Prototype Drone through Carbon Fiber Composite Structures and Additive Manufacturing Techniques

Framework for the Generation of 3D Fiber Composite Structures from 2D Observations

Synthetic generation of realistic materials for testing of process–structure–property (PSP) relationships in computational materials science has gained significant traction over the past two decades. Generation tools continue to lag in some aspects of realism, leading to uncertainty and errors in simulating material response. The experimental collection of information to guide generation of 3D synthetic structures remains costly, time consuming, and challenging. These challenges are compounded by limitations of stereology, which permits estimation of 3D microstructural statistics from 2D observations under restrictive assumptions on constituent morphologies and size distributions and can be difficult to apply to microstructure metrics like constituent orientation distribution and clustering. This work seeks to overcome these challenges by introducing a framework for learning probable 3D microstructure statistics by minimizing the loss determined by matching statistics obtained from 2D observations via synthetic microstructure generation software (e.g. Dream.3D) and stereological principles. This framework is applied to short carbon fiber composite structures printed from an additive manufacturing process, Direct Ink Writing, with the hope that the framework could generalize to other particulate structures as well as allow for simulation and design of materials structure.

Study on bearing capacity and damage mode of carbon fiber composite J-type structures in oilfield completion tool connections

Carbon fiber composite structures have a broad application prospect in oilfield completion tool module connection. However, the material failure mechanism is still unclear. In this paper, the mechanical properties and failure mode of T700/7901 composite J-type structure are investigated from experimental and finite element perspectives. Firstly, the load-carrying and failure properties of the structure were analyzed through typical mechanical property experiments such as tensile, bending, and compression, and the fiber, matrix damage, and delamination damage are the main reasons for the failure of the mechanical properties of the material. Secondly, a numerical model of the progressive damage ontological relationship of the composite material was established, and the accuracy of the model was verified by combining the experimental results. Based on the above study, this paper proposes the failure mechanism and optimization of composite J-type, which provides useful guidance for the design of fiber composite structures for oilfield completion tool types in the future.

High‐velocity impact resistance of the carbon fiber composite grid sandwich structures

AbstractThe carbon fiber composite grid sandwich structure represents an innovative category of lightweight composite sandwich structures, showcasing remarkable attributes including reduced weight, high‐specific strength, exceptional specific stiffness, and robust design flexibility. Using ABAQUS, the high‐velocity impact performance of carbon fiber composite grid sandwich structure is numerically simulated. This study delved into examining the impact patterns arising from various factors, including the equivalent density, height, and geometric configuration of the core layer. Additionally, the effects of the impact punch's initial velocity, size, and impact position on the high‐speed impact resistance performance of the carbon fiber composite grid sandwich structure were explored. The fracture absorption work of the structure and the kinetic energy attenuation rate of the impact punch are positively correlated with the equivalent density, height of the structural core layer, as well as the initial velocity and dimensions of the impact punch. Notably, the square carbon fiber composite grid sandwich structure was most significantly influenced by the equivalent density of the core layer, while the mixed carbon fiber composite grid sandwich structure was most sensitive to variations in core layer height and punch size. When impacted at the intersection of the ribs, compared with the central position between the two ribs, the structure shows enhanced fracture absorption energy and greater impact kinetic energy attenuation rate.Highlights The structure was modeled based on the interlocking assembly process. The high‐velocity impact resistance of the structure was studied. Different structural parameters were designed for the core layer to study. The initial velocity, size and impact position of the punch were involved.

Three-Dimensional Defect Characterization of Ultrasonic Detection Based on GCNet Improved Contrast Learning Optimization

In order to automate defect detection with few samples using unsupervised learning, this paper, considering materials commonly used in aircraft, proposes a phased array ultrasonic detection defect identification method using non-defect samples for training, and three-dimensional characterization is completed on this basis. A phased array ultrasonic device was used to detect two typical structures: a carbon fiber composite cylinder structure and a metal L-shaped structure. No damage label image was required, and the non-damaged sample was used as the the network training input. Based on contrast learning and the cross-registration loss of common features, a feature-matching network was constructed to extract the common features of undamaged detection data, and the performance was optimized by combining STN and GCNet modules. When the detection data of the sample were input to the aforementioned network, the defect distribution representing the location and rough shape of the defect was obtained through Mahalanobis distance calculation. The length was estimated using the S-scan image sequence sampling method. Additionally, the depth of the hole was estimated by combining the B-scan data with line recognition. According to the original model of the sample, the 3D characterization of defects was completed by pyautocad. In the experimental stage, three ablation experiments were carried out to verify the necessity of each module, and performance comparisons were mainly evaluated by F1 score and visualization using four existing well-known anomaly detection methods.

Damage mapping via electrical impedance tomography in complex AM shapes using mixed smoothness and Bayesian regularization

Additive manufacturing (AM) holds immense potential for rapidly producing complexly-shaped composite components and structures. However, AM is also well known for producing composites of lesser quality than more traditional manufacturing methods. Hence, nondestructive evaluation (NDE) and/or embedded sensing (i.e. integrated NDE) is important for mitigating failures in these materials. Unfortunately, many prevailing NDE modalities are ill-suited for complex AM-produced shapes or are not amenable to embedded sensing. To overcome this limitation, we herein study electrical impedance tomography (EIT) as a means of detecting and localizing damage in a complexly-shaped carbon fiber composite truss structure produced by Impossible Objects. Unlike the current state of the art which is overly fixated on applying EIT to flat composite plates not representative of real components and structures, this work shows that EIT can indeed adeptly find damages in complex shapes. We also present a novel mixed smoothness + conditionally Gaussian regularization formulation for the EIT inverse problem that shows marked improvement over the traditionally used smoothness-only prior. Combined, these two contributions are an important step in translating EIT into practice for AM composites.

Electrothermal properties of short carbon fiber/PLA composite structure and its fast response behavior

AbstractIn this study, a new short carbon fiber (SCF) composite structure with electric triggering shape memory properties is developed. The SCF is cast on poly (lactic acid) substrate, then encapsulated by polyvinyl alcohol after drying and molding. In the experiment, the conductivity of the short carbon fiber/PLA sample with 5 mm conductive soft segment and 0.1 mm thickness diamond grid reached the 87.3 S/m, and the temperature of the substrate is higher than its glass transition temperature under 3 V voltage, indicating that the electric heating manner is feasible and stable. The shape recovery rate of the composite structure reaches 91.36%, and the shape memory deformation time is 18 s. This study provides a low‐cost and efficient preparation method for SCF reinforced composite structure, which is promoting the development and application of electric triggering shape memory polymers.

Crashworthiness of recycled carbon fiber composite sinusoidal structures at dynamic rates

Fiber reinforced polymer composites are finding applications in the automotive space for structurally critical applications including crash management. The use of recycled carbon fiber reinforcement can greatly reduce carbon emissions. In this study, recycled carbon fiber composites were manufactured into a self-supporting geometry using three matrices: polyphenylene sulfide (PPS), acrylonitrile butadiene styrene (ABS), and a structural epoxy, and subsequently crushed between flat platens at dynamic rates ranging from 4.6 to 9.1 m s−1 at temperatures in a range of −40 °C to 80 °C. Load-displacement data was used to evaluate their specific energy absorption, crush efficiency, and steady-state crush stress. The energy absorption of the ABS composites was strongly sensitive to temperature, while the PPS composites exhibited strong crush efficiency dependence with both rate and temperature. The epoxy composites exhibited stable crush behavior at dynamic crush rates but exhibited a dramatic reduction in crush efficiency relative to quasi-static tests. The results of this study indicate that recycled fiber composites can achieve very high energy absorption levels (50–80 kJ kg−1 at room temperature) that make them an excellent alternative to more expensive and less environmentally friendly continuous virgin fiber laminates.

A Mixed Samples-Driven Methodology Based on Denoising Diffusion Probabilistic Model for Identifying Damage in Carbon Fiber Composite Structures

X-ray imaging is a common non-destructive detection method for Carbon Fiber Composite Structures (CFCS) that is useful in identifying damage in CFCS-cored wires. In recent years, deep learning models that incorporate classification and objection detection have become frequently utilized by the non-destructive testing industry. These models typically rely on the assumption that there are sufficient annotated failure samples from history that have been measured and can be used for training. Unfortunately, in real-world measurements, it is often challenging to obtain these types of samples. To address the issue of small sample size in such scenarios of real-world field testing, this paper propose a mixed samples-driven methodology based on the Denoising Diffusion Probabilistic Model (DDPM) for identifying damage in CFCS. First, new samples are synthesized through DDPM module to improve the robustness of a small sample size. Then, the synthesized sample, along with a small number of authentic samples measured from real-world testing, are then integrated and fed into a DenseNet-based module. Lastly, the mixed samples-driven architecture is then constructed and employed to diagnose the damage of CFCS. The effectiveness of this approach is demonstrated through experiments in real-world field testing.

Dynamic crush response of compression molded planar isotropic carbon fiber reinforced composites

AbstractVehicle mass reduction can be achieved through the utilization of carbon fiber reinforced composites within the vehicle body structure. In this study, planar isotropic compression molded carbon fiber reinforced composites are studied for their potential utilization as automotive primary energy absorbing structures. The energy absorption behavior of a discontinuous randomly oriented 2‐D planar isotropic carbon fiber reinforced nylon 6 thermoplastic composite and a continuous 2 × 2 twill quasi‐isotropic carbon fiber reinforced epoxy thermoset composite are studied by dynamic flat plaque crush testing. Post‐mortem failure modes of both materials are related back to their load‐displacement and energy‐displacement curves under different test conditions. It is shown that crush fixture support length dictates the failure mode and specific energy absorption (SEA) of all fiber reinforced composites tested. In addition, elevated temperature testing of the nylon 6 carbon fiber reinforced composites reduces the SEA in all test configurations. Finally, an automotive carbon fiber composite front end energy absorbing structure is considered as the replacement over a legacy metallic energy absorbing structure. Mass reduction benefits beyond the improved SEA of the composite as compared to the metallic structure it replaces are discussed by considering the increased crush length efficiency of the composite structure which can reduce the vehicle front end length, and therefore the mass of the vehicle. These results are expected to direct the future development of fiber reinforced composites structures in energy absorbing automotive structures.

Linear annular path damage probability distribution based ultrasonic guided wave method for position imaging and tracking of multi-damage on plate-like carbon fiber composite structure

Plate-like carbon fiber composite is an important component of the main bearing structure of spacecraft and high-speed trains, which has significant advantages in reducing the dead weight and energy consumption, and improving the carrying capacity. However, due to long-term exposure to complex service environments, material properties will be changed, these changes accumulated to a certain extent will lead to structural damage, threatening equipment operation and personal safety. To facilitate the attainment of mastering structural health states, this paper proposes a damage position imaging and tracking technology based on linear annular path damage probability distribution and ultrasonic guided wave for composite plate-like structures. Firstly, according to the dispersion curve, the propagation velocity characteristics of guided wave on composite structure are analyzed. Then, combined with the limited number of measured propagation velocities, the group velocity of the A0 mode in each direction is fitted. Based on the fitted velocity, the time-of-flight (TOF) map for all search points on each path can be pre-constructed. Subsequently, the damage TOFs and absolute TOF difference threshold are combined to obtain the annular damage probability distribution map of each sensing path. Ultimately, the total damage probability of the whole monitoring region is obtained by summing up the path damage probability, which can directly reflect the current damage position. Experimental results show that the proposed method has obvious advantages in imaging and tracking of single or multiple damage positions. It is hoped that the findings in this paper can provide new ideas for long-term damage state monitoring of the composite structures.

Modelling and evaluation of carbon fibre composite structures using high-frequency eddy current imaging

The mechanical performance of carbon fibre reinforced polymer (CFRP) composites is determined by the stacking sequence of specifically orientated ply lamina layers. In these multi-layer structures, global ply misalignment and local fibre waviness can occur during the manufacturing process, leading to reduced performance and structural failure during operation. High-frequency eddy-current testing (ECT) has previously demonstrated its capability for detecting orientation-related features, including fibre orientation and waviness. However, accurate sensor optimisation and inversion of orientation & material structure cannot be achieved without proper, validated modelling techniques to simulate CFRP features. The lack of suitable models is in part due to CFRP exhibiting highly-complex electromagnetic interactions between fibres, lamina and the ECT sensors, which are challenging to integrate. This work proposes a novel finite element modelling approach to simulate the ECT response to planar multi-layered CFRP components. The fibre tow structure of each unidirectional ply is modelled using orientation dependant 2D conductivity tensor waveforms, and virtual 2D ECT scans are simulated by shifting the waveforms within the model mesh. The results demonstrate that idealised electromagnetic characteristics of the CFRP structure can be successfully modelled compared with experimental data and that 2D ECT data of complex CFRP layers structures can be simulated with improved computational speeds, up to 5x faster compared to standard approaches. Automated data-analysis tools, including Radon transform (RT) and 2D FFT, are employed to validate the simulated 2D scan data through the characterisation of fibre orientations and simulated 2D scans used to evaluate the orientation inversion techniques. The results demonstrate that RT analysis detects fibre orientations with better accuracy, precision and consistency than equivalent 2D FFT analysis techniques. The simulation also demonstrates the reduced resistivity losses compared with isotropic materials caused by the different heterogeneous and multi-layer structures. It predicts high current densities at interfaces of plies with orthogonal orientations, resulting in an effective interface skin-depth.

Mechanical behaviors of the carbon fiber reinforced X-core sandwich structure under the dynamic compression

A split Hopkinson pressure bar technique was applied to investigate the dynamic response of carbon fiber composite sandwich structures with the X-cores. The compressive mechanical behaviors of the composite X-core unit cells and its foam reinforced unit cells at the strain rates ranging from 3•10−4 s−1 to 600 s−1 were obtained. During the dynamic tests, the dynamic stress equilibrium state in the unit cells was achieved by adopting the pulse sharpers and discussed comprehensively. The measured structural strength increased by 81.9 % on average at the high strain rates than that under the quasi-static compression. Under the dynamic compression, the failure modes captured by a high-speed camera were found similar with that of the quasi-static tests. Finite element analysis was utilized to study the variation history of stress and strain rate fields of the core. Because of the material failure strain enhancement effect, the experimental and simulated compressive strength of the composite unit cells both increased significantly at the high strain rates. At the same high-speed compressive strain rate, the dynamic reinforcement effect of the composite sandwich unit cell was smaller than that of the parent material.

Carbon Fiber Composite Honeycomb Structures and the Application for Satellite Antenna Reflector with High Precision

Carbon Fiber Composite Honeycomb Structures and the Application for Satellite Antenna Reflector with High Precision

Study of Critical Material Parameters for Curing Deformation of Aerospace Wing Composites before Numerical Simulation

Because of the advantages of lightweight and high-strength integrated molding of composite materials at low cost, thus, large-scale carbon fiber composite structures are widely used in aerospace applications. However, the curing deformation of large-scale composite structures will produce a certain shape deviation, which cannot meet the needs of the installation. If forced assembly will form large installation stress, which will seriously jeopardize the mechanical properties and lifetime of the composite parts. Therefore, it is being studied to control the curing deformation of largescale composite structures, which is important to ensure the quality of the structure, reduce the cost and improve the service life of the structure. The traditional composite parts development model requires large-scale sample testing, uncontrollable manufacturing quality, low efficiency, and other problems. In particular, the curing and molding process involves the intersection of several disciplines such as thermal, chemical and mechanics, so it is increasingly important to study the curing deformation of large-scale composite structures to improve R&D efficiency, control quality, and reduce cost.

Microwave cavity resonator sensor with an octagonal cross section for thickness measurement of coatings on carbon fibre composites

Manual painting is commonly conducted on an aircraft's exterior, and the coating thickness should be within the allowable range. For quality control, the thickness requires accurate assessment. However, the current non-destructive testing techniques for metallic substrates cannot be well suited to the widely used carbon fibre-reinforced polymer composites, which are less conductive. Here we present a new microwave cavity resonator sensor, in which an octagonal cross section (an intermediate shape between a cylinder and a sphere) is adopted to easily eliminate mode degeneracy. A design strategy incorporating electromagnetic simulation is presented, and an accurate model is developed for the extraction of the resonance frequency and quality factor from the asymmetrical responses. In the tests, the open cavity is placed on a composite sample, and coating thickness change causes cavity wall impedance perturbation, leading to resonance frequency shift. From the experiments, a linear relationship is seen between the coating thickness difference and resonance frequency shift, thereby facilitating the estimation process. As the resonant electromagnetic fields are similar to those of the cylindrical TE011 mode, insensitivity to the conductivity and anisotropy of the composite is also demonstrated, enabling convenient implementation. Reasonable accuracy is obtained for thicknesses up to 2 mm. In the prediction of two- and multi-layered coating cases, errors within ±5% are obtained. The sensor developed offers efficient on-site measurement of paint coatings on carbon fibre composite structures.