Search Results (77)

The integration of axial flux motors into canned motor pumps offers a promising approach to overcome the efficiency and size limitations of traditional designs, particularly in critical sectors like aerospace. However, the hydrodynamics in magnetic gap between the stator and rotor are poorly understood. This study investigates the effect of magnetic gap on performance and internal flow. Six magnetic gap schemes are developed, ranging from 0.2 to 1.2 mm. Numerical simulations are conducted, and simulation results showed good agreement with experimental data. The magnetic gap exhibits a non-linear effect on performance. The peak head coefficient occurs at a 0.4 mm gap and maximum efficiency at 1.0 mm. At a 0.2 mm gap, strong viscous shear forces increase disk friction loss and create high-vorticity flow. As the gap widens, flow transitions from viscosity-dominated to inertia-dominated, leading to a more ordered flow structure. The blade passing frequency is the dominant frequency. For a gap of 0.8 mm, the pressure fluctuation intensity is lowest. By analyzing performance, head coefficient, velocity, vorticity, entropy production, and pressure fluctuations, a gap of 0.8 mm is identified as the optimal design. This study provides critical guidance for optimizing the design of axial flux canned motor pumps. Full article

Picosecond laser trepanning is a key technology for fabricating film cooling holes in aero-engine turbine blades, overcoming the limitations of conventional machining such as severe tool wear and thermal damage. However, optimizing this advanced process to achieve consistent, high-quality results remains a challenge. This study therefore systematically investigates the influence of key laser parameters (power, scanning speed, defocusing distance, and number of scans) on the geometric quality (diameter, taper, and roundness) of holes trepanned in GH4169 superalloy. The experimental results revealed that laser power and defocusing distance are the dominant factors controlling hole diameter and taper. Furthermore, a critical trade-off was identified concerning the number of scans: while more scans improved exit roundness, they also detrimentally increased entrance diameter and taper due to heat accumulation. Based on these findings, we propose a defect control strategy prioritizing a lower number of scans in the initial phase to effectively suppress molten material formation and preserve surface integrity. This work provides a valuable technological reference and theoretical foundation for the low-damage, high-reliability laser manufacturing of high-performance aerospace components. Full article

Surrogate modeling has been rapidly evolving in the field of aerospace engineering, further reducing the cost of computational analyses. These models often require large amounts of information to learn the underlying process, which is at odds with obtaining and using the highest-fidelity data. This study assesses the efficacy of multi-fidelity modeling (MFM) to improve simulation accuracy while reducing computational cost. A database of hovering rotor simulations with perturbations of the rotor design and operating conditions was first generated using two different fidelity levels of the OVERFLOW 2.4D Computational Fluid Dynamics software. MFM was then used to quantify the effectiveness of this approach for the development of accurate surrogate models. Multi-fidelity models based on Gaussian Process Regression (GPR) were derived for hovering rotor performance prediction given the geometric rotor blade inputs that currently include twist, planform, airfoil, and the collective pitch angle. The MFM approach was consistently more accurate at predicting the hold-out test data than the surrogate model with high-fidelity data alone. An MFM using just 20% of the available high-fidelity training data was as accurate as a solely high-fidelity model trained on 80% of the available data, representing an approximate fourfold reduction in computational cost. Full article

The safe removal of residual flammable contaminants from vertical mixer blades is a crucial challenge in aerospace propellant production. While robotic cleaning has become the preferred solution due to its precision and operational safety, the complex helical geometry of mixer blades presents significant challenges for robotic systems, primarily in three aspects: (1) dynamic sub-region division, requiring simultaneous consideration of functional zones and residue distribution, (2) ensuring path continuity across surfaces with varying curvature, and (3) balancing time–energy efficiency in discontinuous cleaning sequences. To address these challenges, this paper proposes a novel robotic cleaning path planning method for complex curved surfaces. Firstly, we introduce a blade surface segmentation approach based on the k-means++ clustering algorithm, along with a sub-surface patch boundary determination method using parameterized curves, to achieve precise surface partitioning. Subsequently, robot cleaning paths are planned for each sub-surface according to cleaning requirements and tool constraints. Finally, with total cleaning time as the optimization objective, a genetic algorithm is employed to optimize the path combination across sub-facets. Extensive experimental results validate the effectiveness of the proposed method in robotic cleaning path planning. Full article

Blades are widely used in the engines of aerospace vehicles, fans of near-space aerostat, and other equipment, and they are the key to completing energy conversion and pressure adjustment of the capsule. Blade tip timing (BTT) is the most cost-efficient approach for the monitoring of blades. The reliability and validity of BTT is mainly investigated through numerical simulation and experimental verification. However, not all researchers are able to carry out the expensive and time-consuming task of rotating the blade test bench and its monitoring systems. Therefore, a good and easily understood simulator is necessary. In this paper, an effective BTT simulation model that is capable of considering various uncertainties such as installation errors, probe accuracy, sampling clock frequency, speed fluctuations, and mistuning is presented. A blade multi-harmonic vibration model is also presented, which is not only easy to implement but also simplifies the solution of dynamic equations. Also, the simulation results show that the proposed model is accurate and consistent with the experimental results. This will help researchers to achieve an improved understanding of BTT and form the basis for conducting research in related areas in a short period of time. Full article

Aerospace engines ingest small particles when operating in a particulate-rich environment, such as sandstorms, atmospheric pollution, and volcanic ash clouds. These micron particles enter their cooling channels, leading to film-cooling hole blockage and thus thermal damage to turbine blades made of nickel-based single-crystal superalloy materials. This work studied the collision and deposition mechanisms between the micron particles and structure surface. A combined theoretical and numerical study was conducted to investigate the effect of deposits on particle collision and deposition. Finite element models of deposits with flat and rough surfaces were generated and analyzed for comparison. The results show that the normal restitution coefficient is much lower when a micron particle impacts a deposit compared to that of particle collisions with DD3 nickel-based single-crystal wall surfaces. The critical deposition velocity of a micron particle is much higher for particle–deposit collisions than for particle–wall collision. The critical deposition velocity decreases with the increase in particle size. When micron particles deposit on the wall surface of the structure, early-stage particle–wall collision becomes particle–deposit collision when the height of the deposits is greater than twice the particle diameter. For contact between particles and rough surface deposits, surfaces with a shorter correlation length, representing a higher density of asperities and a steeper surface, have a much longer contact time but a lower contact area. The coefficient of restitution of the particle reduces as the surface roughness of the deposits increase. The characteristic length of the roughness has little effect on the rebounding rotation velocity of the particle. Full article

High-temperature fretting wear typically occurs on mechanical contact surfaces in high-temperature environments, with displacement amplitudes generally in the micrometer range (≤300 μm), such as the turbine disks and blades in aerospace engines, and the piston rings in automotive engines. The study performed tangential fretting wear tests between superalloy specimens and Si₃N₄ balls under 700 °C to investigate the influence of ground and milled surface morphologies on the high-temperature fretting wear behavior. The experimental results show distinct wear mechanisms for the two surface types: ground specimens exhibit adhesive and oxidative wear, while milled specimens experience fatigue and abrasive wear. Both wear modes intensify with increasing load and fretting frequency. A comprehensive surface morphology characterization method, combining fractal dimension (FD) and surface roughness, is proposed. The study reveals that the roughness parameters Sa and Ra are strongly correlated with the Coefficient of Friction, while FD is strongly correlated with the wear volume. This study provides a novel approach to characterizing the evolution of surface morphology during high-temperature fretting wear. Full article

Stiffened panels are extensively used in aerospace applications, particularly in wing and fuselage sections, due to their favorable strength-to-weight ratio under in-plane loading conditions. This research employs the commercial finite element software Ansys-19 to analysis the critical buckling and ultimate collapse load of an aluminum stiffened panel having a dimension of 1244 mm (Length) × 957 mm (width) × 3.5 mm (thickness), with three stiffener blades located 280 mm away from each other. Both the critical buckling load and post-buckling ultimate failure load of the panel are validated against the experimental data found in the available literature, where the edges towards the length are clamped and simply supported, and the other two edges are free. For nonlinear buckling analysis, a plasticity power law is adopted with a small geometric imperfection of 0.4% at the middle of the panel. After the numerical validation, the investigation is further carried out considering four different lateral pressures, specifically 0.013 MPa, 0.065 MPa, 0.085 MPa, and 0.13 MPa, along with the compressive loading boundary conditions. It was found that even though the pressure application of 0.013 MPa did not significantly impact the critical buckling load of the panel, the ultimate collapse load was reduced by 18.5%. In general, the ultimate collapse load of the panel was severely affected by the presence of lateral pressure while edge compressing. Three opening shapes—namely, square, circular, and rectangular/hemispherical—were also investigated to understand the behavior of the panel with openings. It was found that the openings significantly affected the critical buckling load and ultimate collapse load of the stiffened panel, with the lateral pressure also contributing to this effect. Finally, in critical areas with higher lateral pressure load, a titanium panel can be a good alternative to the aluminum panel since it can provide almost twice to thrice better buckling stability and ultimate collapse load to the panels with a weight nearly 1.6 times higher than aluminum. These findings highlight the significance of precision manufacturing, particularly in improving and optimizing the structural efficiency of stiffened panels in aerospace industries. Full article

Turbines are rotating machines that generate power by the expansion of a fluid; due to their characteristics, these turbomachines are widely applied in aerospace propulsion systems. Due to the clearance between the rotor blade tip and casing, there is a leakage flow from the blade pressure to the suction sides, which generates energy loss. There are different strategies that can be applied to avoid part of this loss; one of them is the application of so-called desensitization techniques. The application of these techniques on gas turbines has been widely evaluated; however, there is a lack of analyses of hydraulic turbines. This study is a continuation of earlier analyses conducted during the first stage of the hydraulic axial turbine used in the low-pressure oxidizer turbopump (LPOTP) of the space shuttle main engine (SSME). The previous work analyzed the application of squealer geometries at the rotor tip. In the present paper, winglet geometry techniques are investigated based on three-dimensional flowfield calculations. The commercial CFX v.19.2 and ICEM v.19.2 software were used, respectively, on the numerical simulations and computational mesh generation. Experimental results published by the National Aeronautics and Space Administration (NASA) and data from previous works were used on the computational model validation. The parametric analysis was conducted by varying the thickness and width of the winglet. The results obtained show that by increasing the winglet thickness, the stage efficiency is also increased. However, the geometric dimension of its width has minimal impact on this result. An average efficiency increase of 2.0% was observed across the entire turbine operational range. In the case of the squealer, for the design point, the maximum efficiency improvement was 1.62%, compared to the current improvement of 2.23% using the winglet desensitization technique. It was found that the proposed geometries application also changes the cavitation occurrence along the stage, which is a relevant result, since it can impact the turbine life cycle. Full article

As a candidate material for turbine blades in aerospace engines, Nb-Si-based alloys have attracted significant research attention due to their high melting point and low density. However, their poor high-temperature oxidation resistance limits practical applications. Different alloying elements, including Ti, Mo, and Hf, were added to Nb-Si-based alloys to study the microstructural evolution of alloys. Additionally, the oxidation behavior and the oxidation kinetics of different alloys, as well as the morphology and microstructure of oxide scale and interior alloys at 1523 K from 1 h to 20 h were analyzed systematically. The current findings indicated that the Mo element is more conducive to promoting the formation of high-temperature precipitates of β-Nb₅Si₃ than the Ti and Hf elements. Inversely, the Ti element tends to cause the transition from high-temperature-phase β-Nb₅Si₃ to low-temperature-phase α-Nb₅Si₃, while the Hf element improves the appearance of the γ-Nb₅Si₃ phase but inhibits the other phases and refines the primary Nbss effectively. Noteworthily, compared with the oxidation weight gain of different alloys, Nb-16Si-20Ti-5Mo-3Hf-2Al-2Cr alloy has excellent high-temperature oxidation resistance, in which the oxidation products are TiNb₂O₇, Nb₂O₅, SiO₂, TiO₂, and HfO₂. It can be determined that in the oxidation process, the Ti element will preferentially form an oxide film of TiO₂, thereby wrapping around the matrix phases, protecting the matrix, and improving the antioxidant capacity, while the Hf element can form an infinite solid solution with the matrix and consume the small number of oxygen atoms entering the matrix, so as to achieve the effect of improving the oxidation resistance. Full article

Restoring components in the hot gas path of turbine engines after service-induced degradation is crucial for economic efficiency. This study investigates the printability of Rene 65 powder on a degraded first-stage turbine blade using two additive manufacturing techniques: Laser Powder Bed Fusion (L-PBF) and Laser Powder Directed Energy Deposition (L-DED). Deposited material was evaluated using optical microscopy (OM), scanning electron microscopy (SEM), and Electron Backscatter Diffraction (EBSD) to characterize its crystallographic texture, while microhardness testing provided insight into its mechanical properties. Our results show that L-PBF excels at replicating intricate features, such as small cooling holes, and produces a highly texturized microstructure oriented parallel to <001> under optimal parameters (80 W, 400 mm/s, unidirectional scanning), although at a slower pace. In contrast, L-DED offers a versatile, rapid, and cost-effective method for repairing medium to large parts, yielding an equiaxed microstructure and higher as-printed hardness—approaching GTD 111 values due to an aging effect from high heat input. Both processes effectively restored the dimensional integrity of degraded blade tips, paving the way for more sustainable and economical maintenance strategies in the aerospace industry. Full article

In X-ray industrial computed tomography (ICT) imaging, beam hardening artifacts significantly degrade the quality of reconstructed images, leading to cupping effects, ring artifacts, and reduced contrast resolution. These issues are particularly severe in high-density and irregularly shaped aerospace components, where accurate defect detection is critical. To mitigate beam hardening artifacts, this paper proposes a correction method based on the VGG16 feature extraction network. Continuous convolutional layers automatically extract relevant features of beam hardening artifacts, establish a nonlinear mapping between artifact-affected and artifact-free images, and progressively enhance the model’s ability to understand and represent complex image features through stacked layers. Then, a dataset of ICT images with beam hardening artifacts is constructed, and VGG16 is employed to extract deep features from both artifact-affected and reference images. By incorporating perceptual loss into a convolutional neural network and optimizing through iterative training, the proposed method effectively suppresses cupping artifacts and reduces edge blurring. Experimental results demonstrated that the method significantly enhanced image contrast, reduced image noise, and restored structural details, thereby improving the reliability of ICT imaging for aerospace applications. Full article

Integrating machine learning into additive manufacturing offers transformative opportunities to optimize material properties and design high-performance, fatigue-resistant structures for critical applications in aerospace, biomedical, and structural engineering. This study explores mechanistic machine learning techniques to tailor microstructural features, leveraging data from ultrasonic fatigue tests where very high cycle fatigue properties were assessed up to $1\times {10}^{10}$ cycles. Machine learning models predicted critical fatigue thresholds, optimized process parameters, and reduced design iteration cycles by over 50%, leading to faster production of safer, more durable components. By refining grain orientation and phase uniformity, fatigue crack propagation resistance improved by 20–30%, significantly enhancing fatigue life and reliability for mission-critical aerospace components, such as turbine blades and structural airframe parts, in an industry where failure is not an option. Additionally, the machine learning-driven design of metamaterials enabled structures with a 15% weight reduction and improved yield strength, demonstrating the feasibility of bioinspired geometries for lightweight applications in space exploration, medical implants, and high-performance automotive components. In the area of titanium and aluminum alloys, machine learning identified key process parameters such as temperature gradients and cooling rates, which govern microstructural evolution and enable fatigue-resistant designs tailored for high-stress environments in aircraft, biomedical prosthetics, and high-speed transportation. Combining theoretical insights and experimental validations, this research highlights the potential of machine learning to refine microstructural properties and establish intelligent, adaptive manufacturing systems, ensuring enhanced reliability, performance, and efficiency in cutting-edge engineering applications. Full article

Aircraft gas turbine blades operate in aggressive, generally oxidizing, atmospheres. A solution to mitigate the degradation and improve the performance of such components is the deposition of thermal barrier coatings systems (TBCs). High-velocity air fuel (HVAF) is a very efficient process for coating deposition in TBC systems, particularly for bond coats in aerospace applications. However, its low-temperature variant has received little attention in the literature and could be a promising alternative to limit oxidation during spraying when compared to conventional methods. This study has the main objective of analyzing how the geometry of the low-temperature HVAF gun influences the microstructure and the in-flight oxidation of MCrAlX coatings. To that end, a low-temperature HVAF torch is used to deposit MCrAlX coatings on a steel substrate with different nozzle lengths. In-flight particle diagnosis is used to measure the MCrAlX particle velocity, and to correlate to the nozzle geometry and to analyze its influence on the final coating. The microstructure of the coatings is assessed by scanning electron microscopy (SEM) and the material oxidation is analyzed and measured on a field emission scanning transmission electron microscope (FE-STEM) equipped with focused ion beam (FIB) and by Energy Dispersive Spectroscopy (EDS). Full article

With the growing demand for aero-engine turbine blades, the resource consumption and environmental impact of superalloy powder in the manufacturing process have become increasingly significant. This study focuses on IN718 nickel-based superalloy powder and establishes a recycling method based on powder mixing. By mixing sieved recycled powder with new powder at a 1:1 mass ratio, comprehensive characterization tests, including powder morphology analysis, particle size distribution, blade printability evaluation, mechanical property tests (tensile strength at both 25 °C and 650 °C), and microhardness measurements, demonstrated that the blended powder maintained performance characteristics comparable to new powder, with no statistically significant differences observed. Furthermore, this study introduces the life cycle assessment (LCA) methodology into the field of superalloy powder recycling, providing a novel technical approach for sustainable development in aerospace manufacturing. A quantitative analysis of environmental impacts throughout the blended powder recycling process indicates that this method can reduce carbon emissions by 45% and energy consumption by 48%. Full article