Aerospace Aluminum Alloy Research Articles

Sustainable recycling of aluminum scraps to recycled aerospace-grade 7075 aluminum alloy sheets

The production of aerospace-grade aluminum alloy sheet is characterized by stringent demands, resulting in a low yield rate. The processing of this material generates considerable amounts of highly alloyed scrap, complicating its recycling due to the challenge of maintaining melt cleanliness. This study employed an aerospace-grade melt refining system to purify the recycled 7075 alloy melt obtained from comprehensive scrap remelting. The melt's cleanliness was assessed using Porous Disc Filtration Analysis (PoDFA) and Liquid Metal Cleanliness Analyzer (LiMCA) and Alscan. The microstructure of the ingots and sheets was examined through Scanning Electron Microscopy (SEM) and Electron Backscatter Diffraction (EBSD), whereas the mechanical properties of recycled sheets were evaluated and benchmarked against those of primary sheet at an aerospace-certified testing facility. The findings indicate that the recycled 7075 sheet meets aviation standards, with no significant differences in microstructure or performance when compared to primary sheet. Furthermore, the study highlights the economic benefits of recycling scrap, revealing a potential cost saving of $4210.8 per ton of recycled sheet. The findings presented herein offer a theoretical framework and empirical evidence supporting the development of a recycling system for aerospace scraps and the certification of airworthiness for recycled aerospace aluminum alloy.

Failure evaluation on tailor made aerospace aluminum alloys via underwater friction stir welding employing predictive machine learning technologies

Employing tailor-made alloys with uneven thickness achieves light weighting, a critical issue for reducing emissions, leading to lower aircraft pollutants and fuel costs. The research utilizes advanced machine learning techniques such as Gaussian process regression (GPR), artificial neural networks (ANN) linear regression (LR), and support vector machines (SVM) to predict the ultimate tensile strength of underwater friction stir welding of AA6082-T6 and A2219-T83 tailor-made joints. The models have been evaluated with an assortment of kernel functions, including the polynomial kernel (PK), the radial basis function (RBF), and the Pearson VII universal kernel (PUK). To acquire experimental data, we used a Central Composite Design (CCD) technique, incorporating various factors in the process encompassing tool tilt angle (TA), rotating speed (RS), and welding speed (WS). The SVM radial basis function model (SRBP) had a maximum correlation coefficient of 0.9995 and a minimum root mean square error value (RMSE) of 0.5433 in the training set and 0.6271 in the test set. The ANN model predicted the UTS with an error margin of 0.21%, while the SRBP model showed a 0.52% error, and the LR model exhibited a significantly higher error of 7.73%. A peak tensile strength of 252.98 MPa was recorded in the S20 specimen, accounting for 85.61% of the base metal’s (AA6082 T6) strength. A reduced acute tearing ridge indicates petite, shallow dimples due to the inherent cooling. Through the analysis of metrics and residuals, high accuracy rates were observed when employing the ANN and SRBP models to predict mechanical traits.

Prediction of corrosion fatigue crack growth rate in aluminum alloys based on incremental learning strategy

The 2xxx series aerospace aluminum alloys, vital for aircraft structures due to their excellent mechanical strength and corrosion resistance, face challenges with corrosion fatigue failure, impacting material integrity and aircraft safety. Accurately predicting the corrosion fatigue crack growth rate is crucial for these materials’ reliability in aerospace applications, ensuring safety and operational efficiency. Various unique incremental learning strategies like structural optimization, regularization, and replay were used to enhance the predictive model’s adaptability to continually updated data without the need to retrain the entire model, thus overcoming “catastrophic forgetting.” Based on these strategies, a series of XGBoost models for the prediction of corrosion fatigue crack growth rate in aerospace aluminum alloys have been developed. The results demonstrate that the replay strategy excels in maintaining the accuracy of historical data, while structural optimization and regularization strategies stand out in adapting to new data and effectively preventing overfitting. Combining these three strategies, the models maintain good accuracy and a low forgetting rate across all steps, with an accuracy rate exceeding 0.95 and a forgetting rate below 0.05 in all incremental steps, showcasing excellent knowledge retention capabilities. The models achieve a balanced performance in learning new tasks and retaining old knowledge.

Effect of Salt Spray Corrosion Performance on Variable Polarity Plasma Arc Welding of Aerospace Aluminum Alloy

Effect of Salt Spray Corrosion Performance on Variable Polarity Plasma Arc Welding of Aerospace Aluminum Alloy

Quantitative Detection for Fatigue Natural Crack in Aero-Aluminum Alloy Based on Pulsed Eddy Current Technique

Aero-space aluminum alloys, as vital materials in aerospace engineering, find extensive application in various aerospace components. However, prolonged usage often leads to the emergence of fatigue natural cracks, posing significant safety risks. Therefore, research on accurate quantitative detection techniques for the cracks in aerospace-aluminum alloys is of vital importance. Firstly, based on the three-points bending experimental model, this paper prepared the fatigue natural crack specimen, and the depth of the natural crack is calibrated. Then, given the complexity of geometric characteristics inherent in natural cracks, the pulsed eddy current signal under the different natural crack depth is acquired and analyzed using an experimental study. Finally, to better exhibit the non-linearity between PEC signal and crack depth, a GA-based BPNN algorithm is proposed. The Latin Hypercube method is considered to optimize the population distribution in the genetic algorithm. The results indicate that the characterization accuracy reaches 2.19% for the natural crack.

Role of stacking sequence, metal sheets, and nano particle on strength and toughness of FMLs

The effect of nano particle inclusion and the stacking sequence/metal volume fraction on the tensile strength and energy absorption properties of Fiber Metal Laminates (FML) is investigated. The FML structure is composed of lightweight thin sheets of aerospace grade aluminum alloy 7075 and unidirectional glass fiber composite sheets with Araldite LY5052 thermoset epoxy system as the matrix. The volume fraction of aluminum sheets in the FML structure was varied by increasing the number of aluminum sheets from 2 to maximum 4. In the second batch, the epoxy matrix is reinforced with of multi-walled carbon nano tubes and nano diamond particles together, each with 0.15 wt%. The purpose is to enhance the properties of the epoxy matrix to facilitate higher inter-laminate adhesion (FRP and aluminum). The results of the tensile testing show that with the increase of the metal volume fraction, the tensile strength as well energy absorbing capability (toughness) both are increased. The inclusion of the nano-reinforcements has increased the tensile strength and the toughness of the FML structure as compared to that of the FMLs without nano particles. The strength-to-weight ratio of FML structures is also increased after the inclusion of nano reinforced as desired for aerospace applications.

Surface engineering of aerospace aluminium alloys: Understanding alloying effects on chemical pre-treatment and sol-gel coating adhesion

The sol–gel process is a chemical surface preparation method based on hydrolysis and polycondensation reactions for enhanced adhesion for metallic substrates in adhesive bonding and coating applications. This paper describes an investigation into the effect of the microstructural complexity of two commonly used aerospace aluminium alloys (AAs) 2024-T3 and 7075-T6, on the response to different surface pre-treatments before deposition of the sol-gel coating and subsequent adhesive bonding.Different surface pre-treatments, including two abrasive treatments and three chemical surface pre-treatments were used, and their effect on surface chemistry, wettability and roughness was assessed. Surfaces were characterized by scanning electron microscopy, X-ray photoelectron spectroscopy, profilometry and static contact angles. A hybrid silane sol-gel film was deposited on the differently pre-treated aluminium alloys, an epoxy adhesive was applied and the adhesion properties were evaluated using pull-off testing. The role of the altered physicochemical properties of the pre-treated surfaces was related to the adhesion strength of the sol–gel reinforced epoxy/aluminium interfaces.The microstructural complexity of the aerospace alloys caused non-uniform responses to the pre-treatments, proving the importance of compatibility between material and treatment conditions. Statistical analysis revealed that, despite that overall higher adhesion values were obtained on rougher surfaces, only a strong correlation exists between the surface hydroxyl fraction and adhesion strength. The relation of roughness and water contact angle to interfacial adhesion was found to be non-significant.The findings of this study underscore the critical role of surface pre-treatments and their impact on adhesion strength in aerospace aluminium alloys, providing valuable insights for the effective utilization of sol-gel coatings in adhesive bonding and coating processes.

MFC-PINN: A method to improve the accuracy and robustness of acoustic emission source planar localization

Aluminum alloys used in aerospace can be monitored for cracks using acoustic emission (AE) technology, ensuring structural safety. However, data-driven deep learning models for AE source planar localization of defects in aerospace aluminum alloy plates suffer from poor prediction ability for unknown data and require a large amount of data. Additionally, physical models are heavily influenced by noise. To address these challenges, this paper proposes a multimodal fusion convolutional physical information neural network (MFC-PINN) model that considers numerical-type and image features, improving the model’s comprehensive performance and generalization ability. The model also uses physical equations as constraints, reducing the dependence on large amounts of data and improving the prediction ability for unknown data. MFC-PINN performs well on datasets in complete, incomplete, and noisy conditions, especially in predicting unknown data in high-noise conditions. The study ensures the reproducibility of experiments and the validity of modules through sub-sampling cross-validation and ablation study.

Analytical modeling of cutting force in vibration-assisted helical milling of Al 7075 alloy

Vibration-assisted helical milling is considered a promising hole-making process in the aerospace industry. The prediction of cutting force magnitude and behavior is very important to determine the cutting power, produce tight tolerance, eliminate tool wear, and improve the hole quality. Therefore, the main goal of this work is to establish a cutting force model and evaluate the cutting force coefficients, based on a mechanistic approach, during vibration-assisted helical milling of aerospace aluminum alloy (Al 7075). The process kinematics, the chip geometry including the chip width and chip thickness variations, and the tool-workpiece engagement are theoretically analyzed throughout the whole machining time. A set of experimental tests is implemented at different conditions of tangential feed and helical pitch. Additionally, model validation is performed to discuss the quality and accuracy of the presented model. Consequently, the behavior of the cutting force components against the application of ultrasonic vibration at different cutting conditions is demonstrated. The results show that the analytical and the experimental results are well agreed with a relatively small error percentage. The cutting force components generally increase as tangential feed and helical pitch increase. Moreover, the superimposed ultrasonic vibration causes a rapid tool-workpiece separation increasing the analytical and the experimental oscillation of the cutting force components, thus decreasing the average calculated cutting force.

Impact of graphene nanosheets on adhesion and corrosion performance of reinforced polyurethane coating for aerospace aluminium alloy 2024-T3

This investigation aims to create an integrated multilayer coating system for the surface of aerospace aluminium alloy 2024-T3. A solution-sonication mixing approach was applied to fabricate low-cost and high-efficiency layers. The coating system consisted of three main layers: pretreatment, green epoxy primer (GEP), and polyurethane (PU) top coating layer. To create the pretreatment layer, 50% graphene oxide (GOLMdis) was functionalized using a 50% 3-aminopropyltriethoxy silane coupling agent (SCA). The PU top coating layer was grafted with 1–3% wt. of GOLMdis to improve its resistance to environmental influences. Various analytical techniques such as Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), and Thermogravimetric analysis (TGA) were used to evaluate the properties of the PU-GO layer. The results confirmed the graft of GOLMdis onto the surface of PU, proving the existence of an interaction between the nanosheets and the polymer. The corrosion resistance performance of the multilayer coating systems was evaluated using electrochemical and adhesion tests. The 50%GO-SCA/Epoxy/2%GO-PU coating system outperforms other coating systems. It exhibited a significant improvement in the real impendence (Zre) by up to 9068 % compared to other coating systems. Moreover, only 5% of the coating was removed during the adhesion analysis. The results confirm the successful incorporation of anti-corrosion graphene oxide fillers into the multilayer coating system for corrosion protection of aerospace alloy 2024-T3.

Machining Surface Improvement through Electric- and Flow-Field Adjustments in Flying Electrochemical Milling of AA 2219.

Electrochemical milling is an ideal technique for machining large-scale 3D structures that consist of aerospace aluminum alloys. The distribution of the electric and flow fields are vital to the quality of the machined surface, and the structures of the inner flow channel and bottom outlet have different effects on the electric and flow fields on the machining surface. In this study, two specialized structures of a tool cathode were optimized by simulating the electric and flow fields, and a reasonable design basis for the tool cathode was obtained. Based on this, an ECM experiment was performed with the same machining parameters using different tools, and a 20 mm × 20 mm plane was machined. The experimental results showed that using an appropriate tool cathode can create ideal flow and electric fields, resulting in better processing. After optimizing, the machining plane arithmetic mean deviation decreased by 43% (from 14.050 μm to 6.045 μm), and the region elevation difference decreased by 52% (from 105.93 μm to 55.17 μm).

Damage Monitoring and Localization Imaging of Aluminum Alloy Thin-Walled Structure Based on Remote Bonding Fiber Bragg Gratings Sensing.

In this paper, the damage monitoring investigation based on the remote bonding fiber Bragg grating sensing is performed on the aerospace aluminum alloy thin-walled structure with prefabricated damage. Firstly, an ultrasonic excitation-fiber Bragg gratings (UE-FBGs) sensing experimental platform is established for the simulation of defects monitoring, in which the sensors are placed at a certain distance from the bonding area. Secondly, different arrangements of exciters and receivers are utilized for the original signals and the damage signals. Subsequently, the raw signals are processed by filter and feature extraction in order to denoise the signals and acquire the parameters sensitive to the damage. Finally, an improved Reconstruction for Image Defects (RAPID) algorithm is used to locate and reconstruct the pre-existing damage. The results show that the proposed system improves the sensitivity of the FBG receiver signal and the accuracy of the damage imaging.

Review of the state of art of Li-based inhibitors and coating technology for the corrosion protection of aluminium alloys

The quest for novel alternatives to hexavalent-chromium-based corrosion inhibitors is of utmost significance and urgency. Strict international health and safety regulations, due to growing concerns regarding the impact of hexavalent chromium on human health and the environment, have pushed the commercial introduction of many alternative inhibitor types, but the implementation of alternative active protective primers for structural parts in the aerospace industry is still pending. This endeavour has proven to be remarkably challenging, as the potential replacement coating types must meet numerous functional requirements encompassing cost-effectiveness and exceptional corrosion protection for intrinsically corrosion susceptible aerospace aluminium alloys. In recent years, considerable attention has been drawn to lithium salts as environmentally friendly corrosion inhibitors forming the basis for a novel active protective coating technology. The involvement of lithium ions has been shown to play a pivotal role in the conversion process of aluminium alloy surfaces by stabilizing the reaction products, thereby facilitating the gradual development of a protective layer with a multi-layered configuration, which exhibits considerable variability in morphology, depending on local chemical and electrochemical conditions. The versatility of the lithium-based corrosion protection extends to their application as corrosion inhibiting pigments in organic coatings or as a pre-treatment, directly forming conversion layers, thereby enhancing their practical implementation. However, previous chromate replacement reviews only introduced the promising outcomes provided by the lithium technology, omitting key details of its development and formation mechanism. This paper critically reviews and summarizes the studies conducted to date on lithium-based inhibitor technologies for the corrosion protection of aluminium alloys as well as topics to be investigated in the future.

Machining aerospace aluminium alloy with cryo-treated and untreated HSS cutting tools

ABSTRACT In this study, effects of drilling parameters and cryogenic treatment, which were applied to the cutting tool (M35 HSS drill bit), on the burr width, surface roughness (Ra), chip formation and tool wear were investigated in drilling of AA2024-T3 aluminium alloy under dry drilling conditions. In this context, the drilling parameters determined based on the Taguchi experimental design were employed, and also, the analysis of variance (ANOVA) and regression analysis were performed. The spindle speed (1500, 3000 and 4500 rev/min), feed rate (100, 150 and 200 mm/min) and cutting tool (cryo-treated and untreated M35 HSS tools) were selected as machining parameters. In terms of average burr width, the performance of the cryo-treated (DC&T) HSS drill bit was 28.91% (for the highest value) and 46.96% (for the lowest value) better than that of the untreated (UT) HSS drill bit. According to Ra values, the performance of DC&T HSS drill bit was 13.29% (for highest value) and 12.01% (for lowest value) better than that of UT HSS drill bit. The flank wear (VB) of UT HSS drill bit was found to be approximately four times greater than the flank wear of DC&T HSS drill bit.

Synthesis and characterization of (Al,Si)3(Zr,Ti)-D022/D023 intermetallics: Understanding the stability of silicon substitution

(Al,Si)3(Zr,Ti)-D022/D023 are phases that may form in aerospace and automotive aluminium alloys. The substitution of Zr/Ti in these solid solutions is widely reported in the literature; however, it remains relatively unexplored for Si. In this work, in situ precipitation of (Al,Si)3(Zr,Ti)-D022/D023 intermetallics was performed using Al-Si-Zr-Ti alloys. The precipitation, sedimentation and concentration of numerous intermetallic particles were accomplished by filtrating the residual molten aluminium using a temperature/pressure-controlled vessel adapted with a PoDFA filter. A combination of SEM, TEM, XRD and EMP analysis allowed the identification of (Al,Si)3(Zr,Ti)-D022/D023 intermetallics concentrated within α-FCC matrices of non-Si-doped (sample S2) and Si-doped (samples S4 and S6) alloys. EDS analysis confirmed that Zr and Ti substitute each other in the D022 and D023 phases, whereas Si substitutes in Al sites. Acceptance of Si inside the D023 phase was not expected according to FTlite (FactSage) and TCAL7 (Thermo-Calc) databases. Additionally, Si was found to enhance the formation of (Al,Si)3(Zr,Ti)-D022 intermetallics with high Zr-content, contrary to FactSage 7.3 predictions. TEM results showed intermetallic/FCC crystal coherency for samples S2 and S6, implying that these intermetallics acted as nucleation sites for the Al-phase due to their small lattice mismatch. Furthermore, Si site occupancy was calculated for both (Al,Si)3Ti-D022 and (Al,Si)3Zr-D023 phases via DFT, showing that sites 2b and 4e are the most favorable for Si occupation, respectively. Finally, a thermodynamic model is derived to describe Si substitution upon solidification. Experimental and numerical examinations indicate that Si substitution preferentially occurs in the D022 intermetallics compared to the D023 phase.

Experimental investigation on tool pin profile for defect-free multi-layered laminates using friction stir additive manufacturing

Friction stir additive manufacturing (FSAM) is a sub-set of solid-state additive manufacturing technique that falls under sheet lamination additive manufacturing. This technique employs friction stir welding (FSW) to produce large, multi-layered parts via the plate addition method. Sufficient heat generation and material mixing are the basic requirements of FSAM, which are primarily dependent on the tool pin profile and the optimal selection of process parameters. Therefore, three tools with distinct pin profiles were selected (plain cylindrical, cylindrical threaded, and taper threaded) at variable tool transverse speeds (20, 40, 60 mm/min). The current study investigates the influence of pin profile and welding speed on material mixing and heat generation, specifically in terms of defects produced between the bonded layers of aerospace aluminum alloy Al-7075. A tool rotational speed of 500 rpm and 1200 rpm with a tool tilt angle of 2.5° were employed for all three tools to develop a 4-layered laminate. It was observed that among all, taper threaded tool pins produced defect-free laminates at 500 and 1200 rpm for all three welding speeds. This was attributed to the higher microhardness with grain size ranging from 0.96 μm to 1.47 μm. Overall, a 95.61 % reduction in grain size was achieved using the taper threaded tool pin profile compared to the as-received base material. Microhardness was enhanced with the increase in transverse speed and building height, furtherer highlighted with statistical analysis.

Sustainable recycling of aerospace-grade ultra-clean 7050 aluminum alloy melts through argon refining without secondary aluminum dross generation

The refining of aluminum scraps commonly employs nitrogen-fluxes to eliminate impurities. However, the aluminum nitride (AlN) generated by the reaction between nitrogen and the aluminum melt, along with residual fluxes, contribute to low cleanliness of the recycled aluminum melt and pose difficulties for the disposal of secondary aluminum dross (SAD). Our innovative research has resulted in the recycling of aerospace-grade clean aluminum alloy melts. The results indicate that the argon bubble floating process adsorbs inclusions and hydrogen, achieving an aerospace-grade ultra-clean melt. The solid-liquid interface between the tube wall and the melt provides a diffusion channel for hydrogen atoms, and the bubbles rising up along the wall lead to a higher hydrogen content in the melt. The argon refining dross is primarily composed of Al and Al2O3, which can be recycled as a raw material for aluminum electrolysis. Argon refining can decrease the hydrogen content and the number of inclusions with particle size ≥40 μm in the recycled aluminum melt to the level of aerospace aluminum alloy melt. Nonetheless, the particle size ≥20 μm remains 1.5–2.5 times that of primary aluminum.

On the low temperature fatigue crack growth behavior of AA7075-T651 in ultra-high vacuum environments

It is well-established that the fatigue crack growth behavior of aerospace aluminum alloys in high altitude applications is sensitive to both temperature and water vapor pressure. To isolate the role of temperature, fatigue crack growth experiments were performed on AA7075-T651 under ultra-high vacuum conditions (<6x10−6 Pa) at temperatures ranging from 23 °C to −65 °C. All da/dN–ΔK relationships exhibit the following: (1) a temperature-independent Paris regime at high ΔK, (2) a transition from the Paris regime to a sharply reduced da/dN, which occurs at higher ΔK as the temperature decreases, and (3) a coalescence in da/dN for all temperatures in the threshold region. Interestingly, the point of deviation from the Paris regime is found to correlate with a transition from a flat, transgranular fracture morphology to slip band cracking (SBC) across all conditions. The likely mechanisms governing the observed behaviors are discussed, focusing on the role of slip.

Local scanning electrochemical microscopy analysis of a lithium-based conversion layer on AA2024-T3 at progressive stages of formation

Scanning electrochemical microscopy (SECM) is employed to characterize the evolution of local electrochemical surface activity during lithium-based conversion layer formation on legacy aerospace aluminium alloy AA2024-T3. Initially, three types of studied intermetallic particles - S-, θ- and constituent phases - act as active cathodic areas. Subsequently, θ- and constituent phases show passivation preceding that of S-phase particles during the later conversion layer formation stages. The entire surface, including the matrix region, shows a higher reactivity at the beginning and then gradually shows decreasing reactivity. Hydrogen evolution-generated bubbles attach to the alloy surface and locally hinder the conversion layer formation, weakening the corrosion protection the conversion layer provides at those locations.

Performances of cryo-treated and untreated cutting tools in machining of AA7075 aerospace aluminium alloy

The quality of drilled holes in aluminium alloys used in the aerospace industry is vital to ensure high-precision structural integrity. For this reason, optimum selection of cost-effective cutting tools and cutting parameters is of great importance. Nowadays, due to their high cost and supply difficulties, there is a great interest in improving the performance of traditional HSS cutting tools as an alternative to ceramic, carbide and coated cutting tools. HSS cutting tools are widely used in different industries due to their cost-effectiveness and suitability to improve tool performance. In this research, the performances of cryo-treated (DC&amp;T) and untreated (UT) HSS cutting tools used in dry machining of AA7075 aluminium alloys were investigated. Thanks to DC&amp;T processes applied to HSS cutting tool, improvements have occurred in its microstructure. The hardness value of HSS cutting tool increased by 6.89% with the effect of DC&amp;T processes applied. When the highest and lowest Ra values obtained using DC&amp;T and UT HSS cutting tools were compared, it was seen that DC&amp;T HSS cutting tool performed better by 11.05% and 25.91%, respectively. It has been determined that the hole surface quality of the aluminium workpiece machined with DC&amp;T and UT HSS drills is negatively affected by the increase in spindle speed and feed rate. The highest S/N ratios calculated according to Ra values of holes drilled on aluminium workpieces using DC&amp;T and UT HSS cutting tools were found to be -7.12 dB (2.27 μm) and -9.62 dB (3.03 μm), respectively. In the ANOVA analysis, it was determined that the most effective parameters on Ra values were spindle speed (70.62%), tools (18.19%) and feed rate (9.98%), respectively. In the regression analysis, R2 value for Ra values was calculated as 98.30%. High R2 value result shows that the model developed is quite successful in estimating Ra values.