High Angle Research Articles

Fatigue mechanisms at 450°C of a highly twined (>70%) and HIP-densified IN718 superalloy additively manufactured by laser beam powder bed fusion

Fatigue resistance at elevated temperatures is crucial for certifying aerospace structures additively manufactured by the laser beam powder bed fusion (PBF-LB) method with IN718 superalloy. This study employed a multi-step, supersolvus heat treatment process with hot isostatic pressing (HIP), called RHSA, to minimize pores and brittle phases. Stress intensity factor (△K) calculations using data from X-ray computed tomography and shape factors referencing finite element analysis (FEA) studies confirmed the suppression of △K below the threshold of conventional IN718 (∼5 MPa√m), shifting fatigue behavior to grain-structure-dominated. Despite a very high twin boundary (TB) fraction (>70%), fatigue tests at 450°C and R = 0.1 demonstrated low scatter. Slip trace analysis and high-resolution electron backscatter diffraction (EBSD) revealed that TB-induced strain concentration became prominent only at high △K, causing cracking at 45⁰ to the loading direction. The randomly oriented TBs with higher angles (60⁰) compared to high-angle grain boundaries (HAGBs) (30–40⁰) likely enhanced slip resistance and provided a net strengthening effect, which can explain the lower-than-average TB% along fracture paths. These insights suggest that a high TB fraction is not detrimental if fatigue stress is not excessive, alleviating concerns about annealing twins during defect minimization in AM IN718, allowing novel processes to improve fatigue resistance in PBF-LB IN718.

Are Modern Market-Available Multi-Rotor Drones Ready to Automatically Inspect Industrial Facilities?

Industrial inspection is a well-known application area for unmanned aerial vehicles (UAVs), but are modern market-available drones fully suitable for inspections of larger-scale industrial facilities? This review summarizes the pros and cons of aerial large-scale facility inspection, distinguishing it from other inspection scenarios implemented with drones. Moreover, based on paper analysis and additionally performed experimental studies, it reveals specific issues related to modern commercial drone software and demonstrates that market-available UAVs (including DJI and Autel Robotics) more or less suffer from the same problems. The discovered issues include a Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) shift, an identification of multiple images captured from the same point, limitations of custom mission generation with external tools and mission length, an incorrect flight time prediction, an unpredictable time of reaching a waypoint with a small radius, deviation from the pre-planned route line between two waypoints, a high pitch angle during acceleration/deceleration, an automatic landing cancellation in a strong wind, and flight monitoring issues related to ground station software. Finally, on the basis of the paper review, we propose solutions to these issues, which helped us overcome them during the first autonomous inspection of a 2400 megawatts thermal power plant.

Effect of austenitizing temperature on variant selection of martensite transformation in a 2 GPa grade steel

The correlation of prior austenite grain (PAG) size, mechanical properties, and the variant selection in martensite transformation of a 2 GPa grade automobile steel has been systematically investigated by using a combination of scaning electron microscopy (SEM), electron backscatter diffraction (EBSD), and uniaxial tesile tests. As the austenitizing temperature decreases from 970 °C to 870 °C, the as-quenched microstructure of the studied steel is fully lath martensite. Meanwhile, the average size of PAG is refined from 7.2 ± 3.9 μm to 2.1 ± 1.2 μm, and the volume fraction of high angle grain boundaries (HAGB) is increased from 59.8% to 72.3%, accompanied with an increased number fraction of grains belonging to closely spaced planes (CP) group. With the refinement of the PAGs, the martensitic variant selectivity becomes strong, and the Bain group variant selection discretely transites to the CP group, resulting in a dominate CP group. Consequently, a tensile strength of 2014 ± 33 MPa, a tensile elongtation of 12.9 ± 0.5% and a maximum strength × ductility production of 26.0 ± 1.4 GPa·%, are obtained when the austenitization temperature is at 920 °C.

Re-evaluating winter carbon sink in Southern Ocean by recovering MODIS-Aqua chlorophyll-a product at high solar zenith angles

Satellite ocean color observations are extensively utilized in global carbon sink evaluation. However, the valid coverage of chlorophyll-a concentration (Chla, mg m−3) measurements from these observations is severely limited during autumn and winter in high latitude oceans. The high solar zenith angle (SZA) stands as one of the primary contributors to the reduced quality of Chla products in the high-latitude Southern Ocean during these seasons. This study addresses this challenge by employing a random forest-based regression ensemble (RFRE) method to enhance the quality of Moderate Resolution Imaging Spectroradiometer (MODIS) Chla products affected by high SZA conditions. The RFRE model incorporates the color index (CI), band-ratio index (R), SZA, sensor zenith angle (senz), and Rayleigh-corrected reflectance at 869 nm (Rrc(869)) as predictors. The results indicate that the RFRE model significantly increased the MODIS observed Chla coverage (1.03 to 3.24 times) in high-latitude Southern Ocean regions to the quality of standard Chla products. By applying the recovered Chla to re-evaluate the carbon sink in South Ocean, results showed that the Southern Ocean’s ability to absorb carbon dioxide (CO2) in winter has been underestimated (5.9–18.6 Tg C year−1) in previous assessments. This study underscores the significance of improving the Chla products for a more accurate estimation of winter carbon sink in the Southern Ocean.

Numerical study of proton exchange membrane water electrolyzer performance based on catalyst layer agglomerate model

In this work, a two-dimensional two-phase model of proton exchange membrane water electrolyzer (PEMWE) is developed, in which the catalyst layer (CL) is represented using agglomerate model. The effects of CL composition, porous transport layer (PTL) material properties and operating conditions on PEMWE performance are investigated. The results indicate that small size of catalyst agglomerate around 0.25 μm would benefit PEMWE performance. Appropriate increase of catalyst loading, porosity and ionomer volume fraction in the CL improves PEMWE performance, but their further increment leads to high mass transfer resistance, limiting the improvement of electrolyzer performance. The porosity and ionomer volume fraction of the catalyst layer are suggested to be lower than 0.5 and 0.6, respectively. The catalyst loading should be lower than 1.5 mg cm−2 when the CL porosity is higher than 0.3. The PTLs with high permeability, porosity and low contact angle is beneficial for the gas–liquid two-phase flow and avoiding the overheat and water shortage in the electrolyzer. Increasing the inlet velocity accelerates the bubble removal process, but might results in significant temperature drop, degrading the PEMWE performance. The most suitable temperature of inlet liquid is around 353.15 K. The results provide important guidance for the optimization design of high-performance PEMWE.

Analysis of the effects of inclination and configuration of the electroosmotic field on the cooling performance of a microchannel

The study investigates the effect of using electroosmotic pumps on the cooling of electrical devices in micro scales. The mutual effects of the microchannel inclination (ranging from 0° to 75°) and configuration of the electric field on the heat transfer have not been investigated. To this end, a numerical code based on the finite volume method (FVM) and Semi-Implicit Method for Pressure Linked Equations (SIMPLE) was developed in Fortran to model the two-dimensional flow dynamics and heat transfer. Two different arrangements were considered for the discrete heat sources and electroosmotic fields to examine their effects on fluid dynamics and heat transfer rate at Re=10. In addition, the effects of electrical parameters, which directly affect the flow dynamics, were also considered. Results indicate that decreasing the heat transfer rate at higher angles is because of the velocity mitigation, whereas an increase in the Grashof number causes a reverse effect. Altering the layout of heaters and electric field from the condition in which heat sources are facing each other (Arrangement 1) to the condition in which heat sources are not facing each other (Arrangement 2), leads to the formation of swirling flow, increased flow rate, and decreased average Nusselt number. The optimum configuration for maximum cooling performance is found in Arrangement 1 with the Grashof number of 0 and inclination angle of 0°, in which the highest average Nusselt number of 5.815 is achieved. Despite the reduction in cooling efficiency at higher angles, Arrangement 1 outperforms Arrangement 2.

The nonlinear behavior of generic tail fins for small wind turbines

This paper describes analysis and measurements of the yaw response of tail fins for small wind turbines. It is based on an extension of unsteady slender body theory (USBT) to cover non-slender fins and high angles of incidence, both of which make the theory nonlinear. We provide three main additions to the substantial literature on linearized USBT for tail fins. First, USBT is extended to high angles by modeling the nonlinear vortex dynamics. Second, the restriction to slender bodies is removed by modeling the chordwise load variation. Third, we consider the effect of time-varying wind speed. The extended theory is compared to wind tunnel measurements of the yaw behavior of delta, elliptical, and rectangular tail fins without a rotor and nacelle. The fins were released from initial yaw angles of −40° and −80°; the latter is of sufficient magnitude to show the importance of the nonlinear yaw dynamics. Generally good agreement was found between the theory and measurements, and the theory was shown to be more accurate than a “polar” or quasi-steady model which uses only the lift and drag of a delta planform. Of the three planforms, the rectangular one showed the lowest accuracy in terms of frequency but the damping was accurately predicted. Overall, the results demonstrate the importance of nonlinearity in the response of a yawing tail fin, particularly for the higher aspect ratio fins at large yaw angles.

CO2 detection using In and Ti doped SnO2 nanostructures: Comparative analysis of gas sensing properties

This research explores the gas-sensing characteristics of undoped SnO2, as well as indium (In:SnO2) and titanium (Ti:SnO2) doped SnO2 nanostructures, which were synthesized using a homogeneous precipitation technique. Structural analyses indicate the presence of a tetragonal rutile phase with a preferred orientation along the (110) plane, with both doped samples showing shifts towards higher angles. Raman spectroscopy confirms the vibrational modes associated with SnO2 in both the pure and In: SnO2 samples, while the Ti: SnO2 sample reveals vibrational modes corresponding to both SnO2 and TiO2. Fourier-transform infrared (FTIR) spectroscopy indicates shifts in the O-Sn-O and Sn-O bonds in the doped samples, suggesting the effects of doping. X-ray photoelectron spectroscopy (XPS) results imply a combination of SnO and SnO2 phases in the undoped SnO2, while In: SnO2 samples display In-O bonding and the presence of metallic indium, and Ti: SnO2 shows Ti-O bonding. Scanning electron microscopy (SEM) images show agglomerated particles in the pure and In-doped samples, whereas the Ti-doped samples exhibit a flake-like structure. Transmission electron microscopy (TEM) analysis verifies the integration of dopants into the SnO2 crystal lattice, with average crystallite sizes measured at 44.46 nm for undoped, 34.06 nm for In: SnO2, and 42.63 nm for Ti: SnO2. Gas-sensing experiments for CO2 detection reveal that In: SnO2 demonstrates the most significant sensing response. These results underscore the impact of doping on the structural, morphological, and gas-sensing attributes of SnO2 nanostructures, offering important insights for the advancement of efficient carbon dioxide sensors.

Enhancing durability and oil-water separation efficiency with plasma-treated graphene oxide coated mesh

In recent years, there has been a surge in interest surrounding the fabrication and utilization of superhydrophobic and superhydrophilic surfaces, driven by their exceptional functionalities and properties. Graphene Oxide (GO) has inherent hydrophilicity and underwater superoleophobicity, which has made this material a particularly capable candidate for oil-water separation. Addressing the persistent challenge of efficient oil-water separation in industrial contexts, this study presents the fabrication of a GO-coated stainless steel mesh via a facile dip coating method augmented by an intermediate two-step O2 plasma treatment. The coated meshes were tested with various oil and water mixtures, including neutral, acidic, saline, and hot water, to find separation efficiency and recyclability. Notably, the meshes can achieve excellent separation efficiency of approximately 98.9 % and a superior flux of 11,464 L m−2 h−1 driven by gravity. This is a significant improvement over GO-coated meshes without O2 plasma treatment. Moreover, the plasma-treated meshes exhibit robust long-term durability and chemical stability, maintaining high underwater oil contact angles ≥119° even after extended immersion in diverse pH mediums and salt solutions for 150 days. This work showcases the practical viability of plasma-treated GO-coated meshes for oil-water separation applications and establishes a framework for systematically evaluating their long-term performance in harsh immersion conditions.

An High Efficiency Angle and Range Estimation Method for Three-Dimensional Near-Field Sources Based on Higher-Order Cumulants

An High Efficiency Angle and Range Estimation Method for Three-Dimensional Near-Field Sources Based on Higher-Order Cumulants

Synthesis, characterization, and application of films made from highly substituted N-perfluoroacylated chitosan

Highly substituted perfluoroacylated chitosan can alter the physicochemical properties of chitosan; however, the currently synthesized perfluoroacylated chitosan has a low degree of substitution. In this study, we present a simple method for the homogeneous preparation of highly substituted N-perfluoroacylated chitosan, conducted at room temperature without requiring strict anhydrous or oxygen-free conditions. Various perfluorocarbon chains were successfully attached to chitosan through a reaction between perfluorinated acid esters and amines, catalyzed by DBU. The synthesized N-perfluoroacylated chitosan, with high degree of substitution, demonstrated excellent solubility in common organic solvents. Comprehensive characterization was performed using elemental analysis, nuclear magnetic resonance (including two-dimensional NMR), gel permeation chromatography, infrared spectroscopy, X-ray diffraction, and thermal analysis. The resulting films exhibited high water contact angles. Notably, as the fluorocarbon chain length increased, tensile strength gradually decreased, while elongation at break improved. Additionally, water uptake, water vapor transmission rate, and oxygen transmission rate all exhibited a declining trend. The films exhibited good biocompatibility, and in the grape preservation experiment, HFBC treatment effectively delayed grape aging and deterioration while enhancing quality preservation. These results suggest that HFBC film holds promising potential for food packaging applications.

Sm-MOF decorated cotton for efficient on-demand oil-water separation and organic pollutants removal

Complex wastewater containing oil–water and contaminant mixtures is a constant threat to ecosystems and public health. However, efficient water–oil separation and water treatment are required, with a preference for simple but universal matrices for possible large-scale applications. Herein, effective oil–water separation and organic pollutant removal are simultaneously realized on cotton balls decorated with polydimethylsiloxane combined with a samarium metal–organic framework. Cotton balls containing polydimethylsiloxane (10 %) and Sm-MOF (Synthesis temperature was 110 ℃, 15 mg/L) were successfully prepared by a simple precipitation method, with a high water contact angle of 150.75 ± 1.1°. After pre-wetting with a low surface energy solution, the modified cotton was endowed with repeatable super-wetting transitions between superhydrophobic/superoleophilic and superhydrophilic/underwater superoleophobic properties. In addition to on-demand separations of immiscible oil–water mixtures at a rate of 95 %, water-in-oil emulsions could be separated by the addition of different surfactants. The mechanism of demulsification of the treated cotton ball was studied based on the type of emulsifier and the results of emulsified oil separation. Cotton balls modified with 10 % PDMS and Sm-MOF (Synthesis temperature was 140 °C; 15 mg/L) showed higher adsorption capacity compared to pure cotton balls, adsorbing about 98.7 % of Eriochrome Black T within 2 h. Cotton balls modified by PDMS and Sm-MOF are an effective, safe and green material with promising applications in the simultaneous separation of oil–water mixtures and removal of organic pollutants from water systems.

Convolutional-Neural-Network-Based Autonomous Navigation of Hera Mission Around Didymos

The European Space Agency (ESA)’s Hera mission requires autonomous visual-based navigation in order to safely orbit around the target binary asteroid system Didymos and its moon Dimorphos in 2027. Nevertheless, the performance of optical-based navigation systems depends on the intrinsic properties of the image, such as high Sun phase angles, the presence of other bodies, and, especially, the irregular shape of the target. Therefore, to improve the navigation performance, thermal and/or range measurements from additional onboard instruments are usually needed to complement optical measurements. However, this work addresses these challenges by developing a fully visual-based autonomous navigation system using a convolutional-neural-network (CNN)-based image processing (IP) algorithm and applying it to the detailed characterization phase of the proximity operation of the mission. The images taken by the onboard camera are processed by the CNN-based IP algorithm that estimates the position of the geometrical centers of Didymos and Dimorphos, the range from Didymos, and the associated covariances. The results show that the developed algorithm can be used for a fully visual-based navigation for the position of the Hera spacecraft around the target with good robustness and accuracy.

Modelling П-Shaped Concentrating Optics for Lcpv Solar Cells Using Fresnel Lens

Abstract Most concentrating optics do not show good performance at higher incidence angles and have low acceptance angles and, therefore, they require a high-accuracy solar tracking system, which is costly. In this study, by detailed investigation of optics of the proposed П-shaped concentrating optics, it was found that system remained high in terms of optical efficiency and its concentration ratio at certain higher incidence angles. During the work, ray path through the concentrating optics, width of the light spot at different incidence angles were calculated. Optical efficiency, geometrical concentration ratio, concentration ratio at different incidence angles were found by the results of COMSOL Multiphysics calculations. It was found that the system had a high optical efficiency of approximately 95% and its concentration ratio of 3x-5x was at the range of ±0-20 degrees of incidence angle, and it could reduce the work of a solar tracking system. As well, an increase in the optical efficiency could be seen from 0 to 5 degrees of the incidence angle and an increase in the concentration ratio could be seen from 0 to 12 degrees of the incidence angle in terms of the reflective mirrors which helped redirect the rays to the solar cells. Optical systems with such a high incidence angle could reduce the performance of the solar tracker system, and it reduced the overall cost and energy consumption of the LCPV.

Simple fabrication of breathable poly (vinylidene fluoride) fibrous membranes decorated by silica nanoparticles with enhanced waterproof property

In recent years, scientists have undertaken various preparation approaches to improve the waterproof and moisture permeability of fiber membranes, among which electrospinning has emerged as the simplest and most effective one. In this paper, poly (vinylidene fluoride) /silica (PVDF/SiO2) fibrous membranes were prepared by one-step electrospinning combined with heat treatment. The morphology, surface wettability, water resistance and moisture permeability of the fibrous membranes were also characterized. When the concentration of PVDF was 12 wt.%, the nanofiber membranes exhibited the most uniform and optimal morphology. In addition, the fiber membranes not only exhibited a high water contact angle (WCA) (135.56 °) and a small maximum pore size (dmax) (1.77 μm), but also demonstrated a large hydrostatic pressure (116.86 kPa) and a moderate water vapor transmission rate (WVTR) (3.53 kg m-2 d-1). The PVDF/SiO2 fibrous membranes with good waterproof and moisture permeability obtained in this work are expected to improve the comfort of protective textiles and expand the application range.

Characterization of L12-Al3Ce phase and its purification mechanism in the Al-Ce-TiCN alloy

Rare earth element Ce has a positive purifying effect on Fe and Si impurities in pure aluminum. In this study, we unveiled the mechanism of Ce purification of Fe and Si impurities in commercial pure aluminum at the atomic scale via utilizing the properties of TiCN nanoparticles, which exhibit distribution along grain boundaries and impede solute atom diffusion at specific cooling rates. The transition phase L12-Al3Ce was characterized in aluminum, which is considered to be an important transition phase to purified products. Furthermore, High Angle Dark Field Scanning Transmission Electron Microscopy (HADDF-STEM) and 3D Atom Probe Tomography (3D-APT) results showed that Ce could respectively enrich the Fe and Si impurities, resulting in the formation of Al-Ce-Fe and Al-Ce-Si clusters. Density functional theory (DFT) results indicated that Fe and Si atoms can incorporate into L12-Al3Ce crystal, forming more stable structures and therefore giving rise to the formation of Al-Ce-Si and Al-Ce-Fe nanoclusters. This study provides atomic-scale insights into the mechanism of Ce purifying Fe and Si impurities in aluminum.

Influence of Maximum Airfoil Camber Position on Hydrofoil Cavitation Performance

Abstract This study’s primary goal is to investigate how various airfoils’ maximum camber positions affect hydrofoil cavitation performance. Through numerical simulation, the cavitation low properties of hydrofoils with various maximum camber positions are compared. The accuracy of the modi ied turbulence viscosity and SST k-ω turbulence model on the temporal and spatial evolution characteristics of cavitation near the hydrofoil is evaluated by combining it with the model test. Analysis is done on the cavitation low ield of four airfoils at two distinct design angles of attack (+4° and +6°) with varying maximum camber locations (fmax = 35%C, 40%C, 50%C, and 60%C). The indings indicate that at 35%C, the hydrofoil’s maximum camber position has improved cavitation performance. The hydrofoil’s cloud cavitation evolution time is shorter than that of the original hydrofoil, and during the same time period, more cavitation is generated. The lift-to-drag ratio and lift coef icient of the cavitation low ield are signi icantly improved at both angles of attack. At the same time, the vorticity distribution and entropy generation distribution can be effectively reduced under the design angle of attack and high angle of attack cavitation, and the hydraulic loss in the cavitation low ield can be reduced. This research can serve as a guide for optimizing the hydrofoil’s cavitation performance and designing the impeller of the axial low pump that follows.

Research on assisted recovery algorithm of stall state based on signal guidance

Abstract Given the lack of quantitative guidance in the current stall recovery process, which leads to the pilot’s misoperation or untimely recovery, referring to the energy control theory of complex state recovery, a stall state-assisted recovery algorithm based on pitch angle, engine thrust, and roll angle signal guidance was determined. The structure pilot model and the kinematics simulation model of aircraft at a high angle of attack were established. The effectiveness of the algorithm has been verified by simulation analysis. The man-machine closed-loop simulation analysis results show that the algorithm can guide the pilot in effectively recovering from stall conditions under different stall scenarios and engine failure conditions.

NUMERICAL STUDY OF GRADUAL CHANGE IN SHAFT DIAMETER AND RELIEF GROOVE RADIUS ON STRESS CONCENTRATION FACTOR

The purpose of this work is to investigate the effect of relief groove radius and the taper in gradual diameter change of shaft on stress concentration factors. Finite element analysis was used to conduct theoretical research in order to reduce the maximum value of stress in stepped shafts. In comparison based on a straight shaft without relief groove, the results show the decrease of taper angle has a significant effect in decrease the values of stress concentration factors. On the other hand, the increase of location of relief grooves from shaft shoulder tends to increase the stress concentration factors values, especially at high taper angle.

Design and Implementation of a Dual-Axis Solar Tracking System with IoT-Enhanced Monitoring Using Arduino

The position of the sun varies over the day and with the seasons, making it difficult for conventional fixed solar panel systems to achieve optimum energy production. By reorienting the panels to face the sun, solar tracking systems solve this problem. This study suggests a dual-axis solar tracker system that continuously adjusts the panels to stay perpendicular to sunlight in order to maximize energy capture. The system uses sensors to monitor the sun's elevation and azimuth angles. Light sensors, motor controllers, microcontrollers, control algorithms, and an Internet of Things (IoT) monitoring system are some of the system's essential parts. The microprocessor determines the ideal angles for panel alignment based on the location of the sun as detected by the light sensors. The motor driver then adjusts the panels appropriately. The sun's position is accurately and smoothly tracked using dual-axis tracking systems, which employ sensors to detect solar position and actuators controlled by sophisticated algorithms to adjust the panels accordingly. Real-time parameter monitoring of the solar panel is done using an IoT-enabled webpage. The study's findings show that the dual-axis solar tracker system performs noticeably better in terms of energy capture efficiency than fixed installations, especially in areas with high solar incidence angles and fluctuating sunshine.