Search Results (44)

Introducing and compacting lignocellulosic biomass in aluminum structures, though recommendable in terms of higher sustainability, the potential use of agro-waste and significant weight reduction, still represents a challenge. This is due to the variability of biomass performance and to its limited compatibility with the metal. Another question may concern possible moisture penetration in the structure, which may reduce environmental resistance and result in local degradation, such as wear or even corrosion. Despite these limitations, this hybridization enjoys increasing success. Two forms are possibly available for this: introduction into metal matrix composites (MMCs), normally in the form of char from biomass combustion, or laminate reinforcement as the core for fiber metal laminates (FMLs). These two cases are treated alongside each other in this review, first because they may represent two combined options for recycling the same biomass into high-profile structures, aimed primarily at the aerospace industry. Moreover, as discussed above, the effect on the aluminum alloy can be compared and the forces to which they are subjected might be of a similar type, most particularly in terms of their hardness and impact. Both cases considered, MMCs and FMLs involved over time many lignocellulosic residues, starting from the most classical bast species, i.e., flax, hemp, sisal, kenaf, etc., and extending also to less diffuse ones, especially in view of the introduction of biomass as secondary, or residual, raw materials. Full article

This study provides an investigation into the influence of surface roughness, porosity, and chemistry on the wettability and infiltration behavior of calcia-magnesia-alumino-silicates (CMASs) in thermal and environmental barrier coatings (T/EBCs) used in high-temperature gas turbine engines. High-temperature contact angle measurements were performed at 1260 °C on 7 wt.% yttria-stabilized zirconia (7YSZ) and yttrium ytterbium disilicate (YYbDS, (Y_1/2Yb_1/2)₂Si₂O₇) to evaluate the interaction of CMASs with different surface finishes and coating microstructures. The findings demonstrate that porosity plays a dominant role in determining CMAS infiltration dynamics. In YYbDS, increasing porosity from 6.3% to 22.7% facilitated the formation of an apatite layer that limited CMAS penetration to approximately 2 µm. Surface roughness exhibited a subtler influence in that reducing Sa from 0.61 µm to 0.05 µm increased the change in the contact angle by ~2°, although its impact was found to be less significant compared to porosity and reactive chemistry. These results indicate that an integrated approach that optimizes porosity, chemistry, and surface morphology can significantly enhance CMAS resistance. The study emphasizes that leveraging both microstructural and chemical properties is critical to developing coatings capable of withstanding the harsh conditions encountered in aerospace environments. Full article

Tungsten heavy alloys (WHAs) are two-phase composites known for their exceptional density, strength, hardness, and ductility, making them ideal for radiation shielding, kinetic energy penetrators, and aerospace components. Due to their high melting point, WHAs are primarily processed via powder metallurgy, with liquid-phase sintering (LPS). Spark plasma sintering (SPS) and microwave sintering are emerging as advanced consolidation techniques. Recent research has focused on improving WHA performance through microstructural manipulation, alloying with elements like Fe, Co, Mo, and Re; rare earth oxides like Y₂O₃, La₂O₃, and Ce₂O₃; and employing high-entropy alloys (HEAs) as matrix phase. Additionally, additive manufacturing (AM) techniques are increasingly being used to fabricate complex WHA components. Despite their advantages, WHAs still exhibit limitations in penetration performance, primarily due to their tendency to form mushroom-like heads upon impact rather than self-sharpening. Ongoing research seeks to enhance shear localization, refine grain structure, and optimize processing methods to improve the mechanical properties and impact resistance of WHAs. Furthermore, modeling and simulation approaches are being explored to understand the mechanical behavior of WHAs. This review comprehensively overviews the above aspects and presents recent advances in WHA processing. Full article

Ti-Al₃Ti metal–intermetallic laminate (MIL) composites with microscale layer thickness have attracted attention in aerospace applications. However, whether millimeter-thick Ti layers can enhance the anti-penetration of Ti-Al₃Ti MIL composites under 400–1000 m/s impact velocities remains unclear. In this study, a Ti-Al₃Ti MIL composite target was prepared by hot press sintering, and the 2D finite element model validated by anti-penetration testing was used to prove that increasing the thickness of the Ti layer significantly increases the stress level and anti-penetration limit of the target. Simulations show that compared with a 0.1 mm Ti layer, a 2.5 mm Ti layer reduces the projectile residual velocity by 100% (600 m/s), 72% (800 m/s), and 38.5% (1000 m/s). With a total thickness difference of 0.1 mm, the crack propagation angles increase by 4° (0.06 mm Ti) and 14° (2.5 mm Ti) compared to a 0.4 mm Ti layer. By analyzing stress wave propagation and energy absorption during penetration, this work reveals that millimeter-thick Ti layers improve anti-penetration performance by controlling heterogeneous interface failure and the crack propagation direction through increased ductile layer thickness. These findings provide data for MIL composites and offer potential cost reductions for high-performance anti-penetration materials. Full article

Fluorescent Penetrant Inspection (FPI) is a widely used inspection technique in the aerospace industry. Because of the aging aerospace sector, and because of the safety-criticality of the inspection, aerospace companies aim to automate (parts of this) inspection process to support inspectors. This paper focuses on a model that can assist inspectors by detecting (possible) defects. YOLOv8 is selected as the object detection model. For training such models, a dataset of sufficient size and variety is necessary to ensure good performance and to prevent overfitting. Because data acquisition is still in its beginning stages, an insufficient amount of data has been acquired. In this paper, we propose a data augmentation technique named Mosaic to artificially create more training data. This technique is tested by applying it to the acquired dataset numerous times and using the resulting dataset to train models with a static architecture (YOLOv8), after which the trained models are evaluated. The best trained model had a 0.834 mAP(50-95) performance, which is an increase of 0.666 mAP(50-95) over its baseline (the model trained on the dataset without data augmentation applied). The results show that, by using this Mosaic technique, promising object detection performance via Deep Convolutional Neural Networks (DCNNs) can be achieved even when the data are limited. Full article

Previous reviews by authors indicate the continuing development and improvement of thermal protective systems through the introduction of polymer nanocomposites into polymer matrix composites. These materials perform as thermal protective systems for a variety of aerospace applications, such as thermal protection systems (TPSs), solid rocket motor (SRM) nozzles, internal insulation of SRMs, leading edges of hypersonic vehicles, and missile launch structures. A summary of the most recent global technical research is presented. Polymeric resin systems continue to emphasize phenolic resins and other materials. New high-temperature organic resins based on phthalonitrile and polysiloxane are described and extend the increased temperature range of resin matrix systems. An important technical development relates to the transformation of the resin matrix, primarily phenolic resin, into an aerogel or a nanoporous material that penetrates uniformly within the reinforcing fiber configuration with a corresponding particle size of <100 nm. Furthermore, many of the current papers consider the use of low-density carbon fiber or quartz fiber in the use of low-density felts with high porosity to mimic NASA’s successful use of rigid low-density carbon/phenolic known as phenolic impregnated carbon ablator (PICA). The resulting aerogel composition with low-density non-wovens or felts possesses durability and low density and is extremely effective in providing insulation and preventing heat transfer with low thermal conductivity within the aerogel-modified thermal protective system, resulting in multiple features, such as low-density TPSs, increased thermal stability, improved mechanical properties, especially compressive strength, lower thermal conductivity, improved thermal insulation, reduced ablation recession rate and mass loss, and lower backside temperature. The utility of these TPS materials is being expanded by considering them for infrastructures and ballistics besides aerospace applications. Full article

Laser welding, widely used in industries such as automotive and aerospace, requires precise monitoring to ensure defect-free welds, especially when joining dissimilar metallic thin foils. This study investigates the application of machine learning techniques for defect detection in laser welding using photodiode signal patterns. Supervised models, including Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Random Forest (RF), were employed to classify weld defects into sound welds (SW), lack of connection (LoC), and over-penetration (OP). SVM achieved the highest accuracy (95.2%) during training, while RF demonstrated superior generalization with 83% accuracy on validation data. The study also proposed an unsupervised learning method using a wavelet scattering one-dimensional convolutional autoencoder (1D-CAE) network for anomaly detection. The proposed network demonstrated its effectiveness in achieving accuracies of 93.3% and 87.5% on training and validation datasets, respectively. Furthermore, distinct signal patterns associated with SW, OP, and LoC were identified, highlighting the ability of photodiode signals to capture welding dynamics. These findings demonstrate the effectiveness of combining supervised and unsupervised methods for laser weld defect detection, paving the way for robust, real-time quality monitoring systems in manufacturing. The results indicated that unsupervised learning could offer significant advantages in identifying anomalies and reducing manufacturing costs. Full article

Additive manufacturing (AM) defects present significant challenges in fiber-reinforced thermoplastic composites (FRTPCs), directly impacting both their structural and non-structural performance. In structures produced through material extrusion-based AM, specifically fused filament fabrication (FFF), the layer-by-layer deposition can introduce defects such as porosity (up to 10–15% in some cases), delamination, voids, fiber misalignment, and incomplete fusion between layers. These defects compromise mechanical properties, leading to reduction of up to 30% in tensile strength and, in some cases, up to 20% in fatigue life, severely diminishing the composite’s overall performance and structural integrity. Conventional non-destructive testing (NDT) techniques often struggle to detect such multi-scale defects efficiently, especially when resolution, penetration depth, or material heterogeneity pose challenges. This review critically examines manufacturing defects in FRTPCs, classifying FFF-induced defects based on morphology, location, and size. Advanced NDT techniques, such as micro-computed tomography (micro-CT), which is capable of detecting voids smaller than 10 µm, and structural health monitoring (SHM) systems integrated with self-sensing fibers, are discussed. The role of machine-learning (ML) algorithms in enhancing the sensitivity and reliability of NDT methods is also highlighted, showing that ML integration can improve defect detection by up to 25–30% compared to traditional NDT techniques. Finally, the potential of self-reporting FRTPCs, equipped with continuous fibers for real-time defect detection and in situ SHM, is investigated. By integrating ML-enhanced NDT with self-reporting FRTPCs, the accuracy and efficiency of defect detection can be significantly improved, fostering broader adoption of AM in aerospace applications by enabling the production of more reliable, defect-minimized FRTPC components. Full article

As the demand for high-performance dissimilar material joining continues to increase in fields such as aerospace, biomedical engineering, and electronics, the welding technology of dissimilar materials has become a focus of research. However, due to the differences in material properties, particularly in the welding between metals and non-metals, numerous challenges arise. The formation and quality of the weld seam are strongly influenced by laser process parameters. In this study, successful welding of high-borosilicate glass to a TC4 titanium alloy, which was treated with high-temperature oxidation, was achieved using a millisecond pulsed laser. A series of process parameter comparison experiments were designed, and the laser welding behavior of the titanium alloy and glass under different process parameters was investigated using scanning electron microscopy (SEM) and a universal testing machine as the primary analysis and testing equipment. The results revealed that changes in process parameters significantly affect the energy input and accumulation during the welding process. The maximum joint strength of 60.67 N was obtained at a laser power of 180 W, a welding speed of 3 mm/s, a defocus distance of 0 mm, and a frequency of 10 Hz. Under the action of the laser, the two materials mixed and penetrated into the molten pool, thus achieving a connection. A phase, Ti₅Si₃, was detected at the fracture site, indicating that both mechanical bonding and chemical bonding reactions occurred between the high-borosilicate glass and the TC4 titanium alloy during the laser welding process. Full article

AISI 4340 is a medium-carbon low-alloy steel that has gained distinctive attention due to its advanced properties including high strength, high toughness, and heat resistance. This has led to its commercial usage in a wide variety of industries such as construction, automotive, and aerospace. AISI 4340 is usually machined in a hardened state through a hard-turning process, which results in high heat generation, accelerated tool wear, low productivity, and poor surface quality. The application of high-speed machining helps improve the material removal rate and surface finish quality, yet the elevated temperature at the cutting zone still poses problems to the tool’s lifespan. Apart from using advanced cutting tool materials, which is costly, researchers have also explored various cooling methods to tackle the heat problem. This paper presents a review of a sustainable cooling method known as minimum quantity lubrication (MQL) for its application in the high-speed turning of AISI 4340 steel. This study is centered on high-speed turning and the application of MQL systems in machining AISI 4340 steel. It has been observed that the hard part turning of materials with a hardness exceeding 45 HRC offers advantages such as improved accuracy and tighter tolerances compared to traditional grinding methods. However, this process leads to increased temperatures, and MQL proves to be a viable alternative to dry conditions. Challenges in optimizing MQL performance include fluid penetration and lubrication effectiveness. Full article

In recent years, self-healing polymers have emerged as a topic of considerable interest owing to their capability to partially restore material properties and thereby extend the product’s lifespan. The main purpose of this study is to investigate the nanoindentation response in terms of hardness, reduced modulus, contact depth, and coefficient of friction of a self-healing resin developed for use in aeronautical and aerospace contexts. To achieve this, the bifunctional epoxy precursor underwent tailored functionalization to improve its toughness, facilitating effective compatibilization with a rubber phase dispersed within the host epoxy resin. This approach aimed to highlight the significant impact of the quantity and distribution of rubber domains within the resin on enhancing its mechanical properties. The main results are that pure resin (EP sample) exhibits a higher hardness (about 36.7% more) and reduced modulus (about 7% more), consequently leading to a lower contact depth and coefficient of friction (11.4% less) compared to other formulations that, conversely, are well-suited for preserving damage from mechanical stresses due to their capabilities in absorbing mechanical energy. Furthermore, finite element method (FEM) simulations of the nanoindentation process were conducted. The numerical results were meticulously compared with experimental data, demonstrating good agreement. The simulation study confirms that the EP sample with higher hardness and reduced modulus shows less penetration depth under the same applied load with respect to the other analyzed samples. Values of 877 nm (close to the experimental result of 876.1 nm) and 1010 nm (close to the experimental result of 1008.8 nm) were calculated for EP and the toughened self-healing sample (EP-R-160-T), respectively. The numerical results of the hardness provide a value of 0.42 GPa and 0.32 GPa for EP and EP-R-160-T, respectively, which match the experimental data of 0.41 GPa and 0.30 GPa. This validation of the FEM model underscores its efficacy in predicting the mechanical behavior of nanocomposite materials under nanoindentation. The proposed investigation aims to contribute knowledge and optimization tips about self-healing resins. Full article

Cylindrical shell structures have excellent structural properties and load-bearing capacities in fields such as aerospace, marine engineering, and nuclear power. However, under high-pressure conditions, cylindrical shells are prone to cracking due to impact, corrosion, and fatigue, leading to a reduction in structural strength or failure. This paper proposes a static modeling method for damaged liquid-filled cylindrical shells based on the extended finite element method (XFEM). It investigated the impact of different initial crack angles on the crack propagation path and failure process of liquid-filled cylindrical shells, overcoming the difficulties of accurately simulating stress concentration at crack tips and discontinuities in the propagation path encountered in traditional finite element methods. Additionally, based on fluid-structure interaction theory, a dynamic model for damaged liquid-filled cylindrical shells was established, analyzing the changes in pressure and flow state of the fluid during crack propagation. Experimental results showed that although the initial crack angle had a slight effect on the crack propagation path, the crack ultimately extended along both sides of the main axis of the cylindrical shell. When the initial crack angle was 0°, the crack propagation path was more likely to form a through-crack, with the highest penetration rate, whereas when the initial crack angle was 75°, the crack propagation speed was slower. After fluid entered the cylindrical shell, it spurted along the crack propagation path, forming a wave crest at the initial ejection position. Full article

Aluminum alloy plates are widely used to manufacture large-scale integral structure parts in the field of aerospace. During the forming and processing of aluminum alloy plates, different degrees of residual stress are inevitably produced. Fast and accurate detection of residual stress is very essential to ensuring the quality of these plates. In this work, the longitudinal critically refracted (LCR) wave detection method based on a one-transmitter and double-receiver (OTDR) transducer and the finite element simulation were employed to obtain the residual stress. Aluminum alloy plates with different deformation amounts were fabricated by rotary forging to obtain different residual stress states. Results reveal that the plate formed by rotary forging is in a stress state of central tension and edge compression. As the deformation increases from 20% to 60%, the peak residual tensile stress increases from 156 MPa to 262 MPa, and there is no significant difference in the peak compressive stress. When the deformation reaches 60%, the difference in the residual stresses at different depths is less than 13%, which indicates that the plastic deformation zone basically penetrates the entire longitudinal cross-section of the plate. The maximum deviation between measurement and FE is 61 MPa, which means the experimental data are in good agreement with the FE results. Full article

Aluminum matrix composites (AMCs) have garnered significant attention across various industrial sectors owing to their remarkable properties compared to conventional engineering materials. These include low density, high strength-to-weight ratio, excellent corrosion resistance, enhanced wear resistance, and favorable high-temperature properties. These materials find extensive applications in the military, automotive, and aerospace industries. AMCs are manufactured using diverse processing techniques, tailored to their specific classifications. Over three decades of intensive research have yielded numerous scientific revelations regarding the internal and extrinsic influences of ceramic reinforcement on the mechanical, thermomechanical, tribological, and physical characteristics of AMCs. In recent times, AMCs have witnessed a surge in usage across high-tech structural and functional domains, encompassing sports and recreation, automotive, aerospace, defense, and thermal management applications. Notably, studies on particle-reinforced cast AMCs originated in India during the 1970s, attained industrial maturity in developed nations, and are now progressively penetrating the mainstream materials arena. This study provides a comprehensive understanding of AMC material systems, encompassing processing, microstructure, characteristics, and applications, with the latest advancements in the field. Full article

With the wide application potential of wrought aluminium alloy in aerospace, automobile and electronic products, high-quality aluminium bars prepared by the radial forging (RF) process have received extensive attention. Penetration performance refers to the depth of radial plastic deformation of forgings, which is the key factor in determining the quality of forging. In this work, the penetration performance of the radial forging process for 6063 wrought aluminium bars is investigated by simulation using FORGE software. The minimum reduction amount of the hammer is calculated based on the forging penetration theory of forging. The influence of process parameters including forging ratio (FR) and billet temperature on the effective stress and hammer load in the RF process are investigated. The RF-deformed billet is then produced with the optimal process parameters obtained from the simulation results. The average grain size of aluminium alloy semi-solid spherical material is used to evaluate the forging penetration. Simulation results showed that the effective strain at the edge and the centre of the RF-deformed billet gradually increases, but the increasing speed of the effective strain at the edge becomes low. The hammer load first decreases quickly and then gradually maintains stability by increasing the FR. It is found that low billet temperature and high FR should be selected as appropriate process parameters under the allowable tonnage range of RF equipment. Under an isothermal temperature of 630 °C and a sustaining time of 10 min, the difference in the average grain dimension between the edge and the centre positions of the starting extruded blank is 186.43 μm, while the difference in the average grain dimension between the edge and the centre positions of the RF-deformed blank is 15.09 μm. The improvement ratio of penetration performance for the RF-deformed blank is obtained as 91.19%. Full article