Search Results (35)

Material Extrusion (MEX) process is increasingly used to fabricate components for structural applications, driven by the availability of advanced materials and greater industrial adoption. In these contexts, understanding the mechanical performance of printed parts is crucial. However, conventional methods for assessing anisotropic elastic behavior often rely on expensive equipment and time-consuming procedures. The aim of this study is to evaluate the applicability of the impulse excitation of vibration (IEV) in characterizing the dynamic mechanical properties of a 3D-printed composite material. Tensile tests were also performed to compare quasi-static properties with the dynamic ones obtained through IEV. The tested material, Nylon 12CF, contains 35% short carbon fibers by weight and is commercially available from Stratasys. It is used in the fused deposition modeling (FDM) process, a Material Extrusion technology, and exhibits anisotropic mechanical properties. This is further reinforced by the filament deposition process, which affects the mechanical response of printed parts. Young’s modulus obtained in the direction perpendicular to the deposition plane (E₃₃), obtained via IEV, was 14.77% higher than the value in the technical datasheet. Comparing methods, the Young’s modulus obtained in the deposition plane, in an inclined direction of 45 degrees in relation to the deposition direction (E₄₅), showed a 22.95% difference between IEV and tensile tests, while Poisson’s ratio in the deposition plane (v₁₂) differed by 6.78%. This data is critical for designing parts subject to demanding service conditions, and the results obtained (orthotropic elastic properties) can be used in finite element simulation software. Ultimately, this work reinforces the potential of the IEV method as an accessible and consistent alternative for characterizing the anisotropic properties of components produced through additive manufacturing (AM). Full article

Additive manufacturing (AM) is gaining widespread adoption in the manufacturing industry due to its capability to fabricate intricate and high-performance components. In parallel, the increasing emphasis on functional materials in AM has highlighted the critical need for accurate prediction of the mechanical behavior of composite systems. This study experimentally investigates the tensile strength and surface quality of carbon fiber-reinforced nylon composites (PA12-CF) fabricated via fused deposition modeling (FDM) and models their behavior using artificial neural networks (ANNs). A Taguchi L27 orthogonal array was employed to design experiments involving five critical printing parameters: layer thickness (100, 200, and 300 µm), infill pattern (gyroid, honeycomb, and triangles), nozzle temperature (250, 270, and 290 °C), printing speed (50, 100, and 150 mm/s), and infill density (30, 60, and 90%). An analysis of variance (ANOVA) revealed that the infill density had the most significant influence on the resulting tensile strength, contributing 53.47% of the variation, with the strength increasing substantially at higher densities. In contrast, the layer thickness was the dominant factor in determining surface roughness, accounting for 53.84% of the variation, with thinner layers yielding smoother surfaces. Mechanistically, a higher infill density enhances the internal structural integrity of the parts, leading to an improved load-bearing capacity, while thinner layers improve the interlayer adhesion and surface finish. The highest tensile strength achieved was 69.65 MPa, and the lowest surface roughness recorded was 9.18 µm. An ANN model was developed to predict both the tensile strength and surface roughness based on the input parameters. Its performance was compared with that of three other machine learning (ML) algorithms: support vector regression (SVR), random forest regression (RFR), and XGBoost. The ANN model exhibited superior predictive accuracy, with a coefficient of determination (R² > 0.9912) and a mean validation error below 0.41% for both outputs. These findings demonstrate the effectiveness of ANNs in modeling the complex relationships between FDM parameters and composite properties and highlight the significant potential of integrating ML and statistical analysis to optimize the design and manufacturing of high-performance AM fiber-reinforced composites. Full article

The rapid advancement of 3D printing technologies has greatly assisted drone manufacturing, particularly through the use of composite filaments. This paper explores the impact of fiber-reinforced materials, such as carbon-fiber-infused PLA, PETG, and nylon, on the mechanical performance, weight optimization, and functionality of unmanned aerial vehicles (UAVs). The study highlights how additive manufacturing enables the fabrication of lightweight yet structurally robust components, enhancing flight endurance, stability, and payload capacity. Key advancements in high-speed fused filament fabrication (FFF) printing, soluble support materials, and embedded electronics integration are examined, demonstrating their role in producing highly functional UAV parts. Furthermore, the challenges associated with material processing, cost, and scalability are discussed, along with solutions such as advanced extruder designs and hybrid manufacturing approaches that combine 3D printing with CNC machining. By utilizing composite filaments and innovative fabrication techniques, 3D printing continues to redefine drone production, enabling rapid prototyping and on-demand customization. The use of carbon-fiber-infused PLA, PETG, and nylon has demonstrated outstanding improvements in strength-to-weight performance, structural durability, and dimensional stability—key factors for enhancing flight endurance, maneuverability, and payload capacity in UAV applications. These composite materials also support the integration of embedded electronics and functional features, reinforcing their suitability for high-performance drone parts. Looking forward, future research should explore the potential of nanocomposite filaments not as a replacement but as a complementary advancement to existing composites. These materials offer opportunities for further enhancing multifunctionality, such as thermal/electrical conductivity and in situ sensing, which could expand UAV capabilities significantly. Full article

Fuel cells, propulsion systems, and reaction control systems (RCSs) are just a few of the space applications that depend on pressure vessels (PVs) to safely hold high-pressure fluids while enduring extreme environmental conditions both during launch and in orbit. Under these challenging circumstances, PVs must be lightweight while retaining structural integrity in order to increase the efficiency and lower the launch costs. PVs have significant challenges in space conditions, such as extreme vibrations during launch, the complete vacuum of space, and sudden temperature changes based on their location within the satellite and orbit types. Determining the operational temperature limits and endurance of PVs in space applications requires assessing the combined effects of these factors. As the main propellant for satellites and rockets, hydrogen has great promise for use in future space missions. This study aimed to assess the structural integrity and determine the thermal operating limits of different types of hydrogen pressure vessels using finite element analysis (FEA) with Ansys 2019 R3 Workbench. The impact of extreme space conditions on the performances of various kinds of hydrogen pressure vessels was analyzed numerically in this work. This study determined the safe operating temperature ranges for Type 4, Type 3, and Type 1 PVs at an operating hydrogen storage pressure of 35 MPa in an absolute vacuum. Additionally, the dynamic performance was assessed through modal and random vibration analyses. Various aspects of Ansys Workbench were explored, including the influence of the mesh element size, composite modeling methods, and their combined impact on the result accuracy. In terms of the survival temperature limits, the Type 4 PVs, which consisted of a Nylon 6 liner and a carbon fiber-reinforced epoxy (CFRE) prepreg composite shell, offered the optimal balance between the weight (56.2 kg) and a relatively narrow operating temperature range of 10–100 °C. The Type 3 PVs, which featured an Aluminum 6061-T6 liner, provided a broader operational temperature range of 0–145 °C but at a higher weight of 63.7 kg. Meanwhile, the Type 1 PVs demonstrated a superior cryogenic performance, with an operating range of −55–54 °C, though they were nearly twice as heavy as the Type 4 PVs, with a weight of 106 kg. The absolute vacuum environment had a negligible effect on the mechanical performance of all the PVs. Additionally, all the analyzed PV types maintained structural integrity and safety under launch-induced vibration loads. This study provided critical insights for selecting the most suitable pressure vessel type for space applications by considering operational temperature constraints and weight limitations, thereby ensuring an optimal mechanical–thermal performance and structural efficiency. Full article

SCF/PA6 composites have gained extensive industrial applications due to their superior processability and moldability, with long-fiber pellet injection molding being the predominant manufacturing technique. However, systematic investigations into injection molding parameter optimization and its mechanistic impacts on tensile strength remain scarce. This study employed the Taguchi method to investigate the effects of four critical process parameters—injection pressure, melt temperature, mold temperature, and injection time—on the tensile strength of short-carbon-fiber-reinforced nylon 6 (SCF/PA6), while elucidating their underlying mechanisms. The optimal parameter combination within the experimental range was determined to be an injection pressure of 100 bar, a melt temperature of 280 °C, a mold temperature of 100 °C, and an injection time of 2 s. Under these optimized conditions, the tensile strength reached 184.33 MPa, representing an 8.05% enhancement over baseline values. Mechanistic analysis revealed that melt temperature and injection time (essentially reflecting injection velocity) primarily govern fiber orientation distribution. Notably, melt temperature additionally regulates molecular chain orientation in the amorphous matrix regions. Injection pressure predominantly influences process-induced defect formation and material densification. Mold temperature exhibits a negligible impact on tensile strength. Full article

Battery pack casings with a total energy of 12.432 kWh were designed using two types of materials: aluminum alloy and carbon fiber reinforced composite filament based on polyphthalamide or high-performance/high-temperature nylon (PPA-CF). The effectiveness of mechanical metamaterials (lattice and auxetic structures) in mitigating the levels of random vibrations in the battery pack casings was studied using a numerical method. Both structures demonstrate outstanding capabilities with a 97% to 99% reduction in vibration levels in the aluminum casing. However, the capabilities of these structures in mitigating vibration levels in the PPA-CF casing are very limited, in that they can only mitigate approximately 63.8% and 92.8% of the longitudinal vibrations at the top cover of the casing and center of its front and back walls, respectively. Compared to PPA-CF, aluminum alloy shows better vibration mitigation performance with or without structural modification. Full article

Three-dimensionally-printed carbonfiber-reinforced composites are increasingly replacing thermosetting polymers and metals due to their lightweight structure and enhanced mechanical performance. This investigation examines the mechanical, thermal and tribological characteristics of 3D-printed nylon (PA6) composites reinforced with 0.5 wt.% multi-walled carbon nanotubes (MWCNTs), 15 wt.% short carbon fibers (CF), and a hybrid combination of both, consisting of 0.5 wt.% MWCNTs and 15 wt.% CF. This study focuses on evaluating the individual and synergistic effects of these reinforcements on the performance of nylon-based composites. A series of characterizations, including mechanical, thermal, tribological, morphological and FTIR analyses, are conducted. The tensile and flexural strengths of the hybrid composite are improved by 35% and 42%, respectively, compared to pure nylon. The findings emphasize the substantial influence of hybrid reinforcement on enhancing mechanical, thermal, and tribological properties, providing useful information on the possible utilization of these composites in engineering applications requiring high-performance materials. Full article

3D-printed short-carbon-fiber-reinforced thermoplastic composites have attracted significant attention from both the academic and industrial communities due to their remarkable advantages such as lightweight, high strength, and recyclability. However, in most of the current 3D-printing-related nylon composites, the content of short carbon fibers is generally low, and the influence laws of short carbon fibers on the mechanical properties of the composites have not been fully explored. This paper focuses on short-carbon-fiber-reinforced nylon (SCF/PA) composites with short-carbon-fiber contents of 15 wt%, 25 wt%, and 35 wt%, respectively. It studies in depth their mechanical properties and related characteristics. The research results show that with the increase in the short-carbon-fiber content, the melt flow rate of the SCF/PA composites shows a downward trend. In terms of mechanical properties, when the short-carbon-fiber content is 25 wt%, the tensile strength and flexural strength of the composite reach their maximum values, which are 101.43 MPa and 173.16 MPa, respectively. Compared with pure nylon, the improvement ranges are 17.01% and 21.4%, respectively. When the short-carbon-fiber content is 35 wt%, the impact resistance of the material reaches its optimal value, which is 6.02 KJ/m², an increase of 38.1% compared with pure nylon. At the same time, when the short-carbon-fiber content is 35 wt%, the thermal deformation temperature of the material also shows a certain degree of slight increase. In summary, the research results of this paper will provide more abundant and detailed experimental data support for 3D-printed short-carbon-fiber-reinforced nylon composites in various different application scenarios, facilitating further exploration and application in related fields. Full article

In short-carbon-fiber-reinforced polyamide 66 articles shaped by 3D printing (3D-SCFRPA66), the interfaces between printed layers are often susceptible to damage, and the composite is excessively brittle. Therefore, a novel treatment for 3D-printed short-carbon-fiber-reinforced polyamide (3D-SCFRPA66) using homogeneous low-potential electron beam irradiation (HLEBI) to enhance tensile properties was investigated. In 3D-SCFRPA66 samples, ductility was measured based on the following parameters: strain at tensile strength (corresponding to homogeneous deformation) (ε_ts) and resistance energy to homogeneous deformation, a measure of toughness (E_hd), which were both substantially increased. An HLEBI dose of 43.2 kGy at an acceleration potential of 210 kV for the finished 3D-SCFRPA66 samples increased the ε_ts and E_hd values from 0.031 and 1.20 MPa·m for the untreated samples to 0.270 and 6.05 MPa·m for the treated samples, increases of 771% and 504%, respectively. Higher HLEBI doses of 86, 129, or 215 kGy also increased the ε_ts and E_hd values to lesser degrees. Electron spin resonance (ESR) data in the literature show that HLEBI creates dangling bonds in Nylon 6. Since PA66 and Nylon 6 are constructed of C, N, and O and have similar molecular structures, HLEBI apparently severs the (-C-N-) bonds in the backbone of PA66, which have the lowest bond-dissociation energy (BDE) of ~326 to 335 kJ mol⁻¹. This shortens the PA66 chains for higher ductility. In addition, for Nylon 6, X-ray photoelectron spectroscopy (XPS) data in the literature show that HLEBI reduces the N peak while increasing the C peak, indicating the occurrence of shortening chains via dangling bond formation accompanied by increases in crosslinking with carbon bonds. However, caution is advised, since HLEBI was found to decrease the tensile strength (σ_ts) and initial elasticity ([dσ/dε]_i) of 3D-SCFRPA66. This tradeoff can possibly allow the HLEBI dose to be adjusted for the desired ductility and strength while minimizing energy consumption. Full article

Additive manufacturing (AM) methods are increasingly being adopted as an alternative for mass production. In particular, Fused Deposition Modeling (FDM) technology is leading the way in this field. However, the adhesion of the layers in products produced using FDM technology is an important issue. These products are particularly vulnerable to forces acting parallel to the layers and especially to impact strength. Most products used in the industry have complex geometries and thin walls. Therefore, solid infill is often required in production, and this production must take place in the ZX orientation. This study aims to optimize the impact strength against loads acting parallel to the layers (ZX orientation) of PA6, one of the most widely used materials in the industry. This orientation is critical in terms of mechanical properties, and the mechanical characteristics are significantly lower compared to other orientations. In this study, filaments containing pure PA6 with 15% short carbon fiber and 30% glass fiber were utilized. Additionally, the printing temperature, layer thickness and heat treatment duration were used as independent variables. An L9 orthogonal array was employed for experimental design and then each experiment was repeated three times to conduct impact strength tests. Characterization, Taguchi optimization, and factor analyses were performed, followed by fracture surface characterization by SEM. As a result, the highest impact strength was achieved with pure PA6 at 8.9 kJ/m², followed by PA6 GF30 at 8.1 kJ/m², and the lowest impact strength was obtained with PA6 CF15 at 6.258 kJ/m². Compared to the literature and manufacturer datasheets, it was concluded that the impact strength values had significantly increased and the chosen experimental factors and their levels, particularly nozzle temperature, were effective. Full article

As a key and weak point of continuous fiber-reinforced composites (CFRCs), the interface between the fiber and the matrix is vulnerable to failure under external loads, with its performance directly affecting the overall properties of CFRCs. Hence, a micro–macro coupling method that considered the microscopic properties of the interface was utilized to analyze and predict the mechanical properties of CFRCs more accurately. The microscopic mechanical parameters of the fiber–matrix interface, which were obtained using molecular dynamics, were transferred to the representative volume element (RVE). The stiffness matrix of the CFRC, required for the macroscopic finite element model, was then calculated using a unified periodic homogenization method based on the RVE and assigned to the finite element model for a macroscopic simulation. Nylon/continuous carbon fiber specimens were fabricated through additive manufacturing, with the tensile and bending strengths of the specimens obtained through tensile and three-point bending tests. The tensile strength of the experimental specimen was 200.1 MPa, while the result of the simulation containing the interface was 205.5 MPa, indicating a difference of less than 5% between the two. In contrast, the result of the simulation without an interface was 317.7 MPa, representing a high error of 58.7% compared with the experimental results. Moreover, the bending strength, Young’s modulus, and flexural modulus results with and without an interface showed the same trend as that for the tensile strength. This illustrates the effectiveness of the proposed micro–macro coupling method for analyzing and predicting the mechanical properties of CFRCs. Full article

This paper analyses mechanical property prediction through Machine Learning for continuous fiber-reinforced polymer matrix composites printed using the novel Material Extrusion Additive Manufacturing technique. The composite is formed by a nylon-based matrix and continuous fiber (carbon, Kevlar, or fiberglass). From the literature, the elastic modulus and tensile strength were taken along with printing parameters like fiber content, fiber fill type, matrix lattice, matrix fill density, matrix deposition angle, and fiber deposition angle. Such data were fed to several supervised learning algorithms: Ridge Regression, Bayesian Ridge Regression, Lasso Regression, K-Nearest Neighbor Regression, CatBoost Regression, Decision Tree Regression, Random Forest Regression, and Support Vector Regression. The Machine Learning analysis confirmed that fiber content is the most influential parameter in elasticity (E) and strength ($\sigma$). The results show that the K-Nearest Neighbors and CatBoost provided the closest predictions for E and $\sigma$ compared to the other models, and the tree-based model presented the narrowest error distribution. The computational metrics point to a size versus prediction time tradeoff between these two best predictors, and adopting the prediction time as the most relevant criterion leads to the conclusion that the CatBoost model can be considered, when compared to the others tested, the most appropriate solution to work as a predictor in the task at hand. Full article

This article investigates the impact of changes in the internal structure of composite materials on their dynamic properties. The present research focuses on 3D-printed specimens with different reinforcement fiber arrangements. The specimens are printed on a Markforged Mark Two 3D printer. The base material is nylon filled with chopped carbon fibers (Onyx) and the reinforcement is in the form of long carbon, glass and Kevlar fibers. The experiment is carried out by the impact method. The principle of this method is to expose the specimen to a short impulse of force while monitoring its frequency response. The obtained results determine the natural frequencies and internal damping of the individual structures. We found that the highest damping is achieved by specimens with glass and Kevlar fibers in 45°, 90° and ±45° configurations. On the other hand, the lowest damping is achieved by specimens with carbon fibers and 0° and 0°,90° configurations. Also, the specimens with circumferential reinforcement show lower damping coefficient values. The knowledge and results of this work can be used in the development of new components; for example, in the transport industry, where the low weight and sufficient strength of components are important factors. These components have to absorb vibrations from various sources, such as motors and external influences. Full article

This paper shows how temperature influences impact energy for continuous fiber additively manufactured (AM) polymer matrix composites. AM composites were fabricated with a nylon-based matrix and four continuous reinforcements: fiberglass, high-temperature fiberglass (HSHT), Kevlar, and carbon. The tested temperatures ranged from −40 to 90 °C. The chosen printed configuration for the lattice structure and fiber volume was the configuration that was found to perform the best in the literature, with a volumetric fiber content of 24.2%. Impact tests showed that the best response was fiberglass, HSHT, Kevlar, and carbon, in that order. The impact resistance was lowered at temperatures below ambient temperatures and above 50 °C. Additionally, each material’s impact energy was adjusted to third-degree polynomials to model results, with correlation factors above 92%. Finally, the failure analysis showed the damage mechanisms of matrix cracking, delamination in the printing direction, fiber tearing, and fiber pulling as failure mechanisms. Full article

In the context of energy efficiency and resource scarcity, lightweight construction has gained significant importance. Composite materials, particularly sandwich structures, have emerged as a key area within this field, finding numerous applications in various industries. The exceptional strength-to-weight ratio and the stiffness-to-weight ratio of sandwich structures allow the reduction in mass in components and structures without compromising strength. Among the widely used core designs, the honeycomb pattern, inspired by bee nests, has been extensively employed in the aviation and aerospace industry due to its lightweight and high resistance. The hexagonal cells of the honeycomb structure provide a dense arrangement, enhancing stiffness while reducing weight. However, nature offers a multitude of other structures that have evolved over time and hold great potential for lightweight construction. This paper focuses on the development, modeling, simulation, and testing of lightweight sandwich composites inspired by biological models, following the principles of biomimetics. Initially, natural and resilient design templates are researched and abstracted to create finished core structures. Numerical analysis is then employed to evaluate the structural and mechanical performance of these structures. The most promising designs are subsequently fabricated using 3D printing technology and subjected to three-point bending tests. Carbon-fiber-reinforced nylon filament was used for printing the face sheets, while polylactic acid (PLA+) was used as the core material. A honeycomb-core composite is also simulated and tested for comparative purposes, as it represents an established design in the market. Key properties such as stiffness, load-bearing capacity, and flexibility are assessed to determine the potential of the new core geometries. Several designs demonstrated improved characteristics compared to the honeycomb design, with the developed structures exhibiting a 38% increase in stiffness and an 18% enhancement in maximum load-bearing capacity. Full article