Electrodeposited carbon nanostructured nickel composite coatings: A review

The utilization of high-strength materials that can retain their strength after successive use under high mineral moisture (maximum weight of 1098 kg) for aerospace, automotive, and electromagnetic devices is challenging. Generally, coatings of nickel (Ni) and its alloys are utilized in the aforementioned applications, but the continuous use of the system degrades its mechanical stability and structural integrity. For the automotive and aerospace uses, the material should have high mechanical strength, wear tolerance, corrosion resistance, and magnetism. The bare Ni coatings can be altered with enhanced mechanical, tribological and electrochemical performances by using various reinforcements in the coatings. The abundantly used reinforcing agents are mainly carbonaceous nanoallotropes (such as graphene, carbon nanotubes, and diamond) for the fabrication of composite coatings. The current review unfolds the introduction of nickel and the major cause of damage to bare nickel coatings. Moreover, the review sheds light on how to mitigate the damage of nickel coatings with an emphasis on giving a flavor of distinct carbonaceous nanoallotropes. The conjugated studies on mechanical, wear, corrosion, and magnetic behavior of electrodeposited Ni-carbonaceous composite coatings are embraced in the review. Therefore, the present review can be endorsed by the readers for the protection of aircraft, automotive, and electromagnetic appliances.

Cervical Spine Motion Requirements From Night Vision Goggles May Play a Greater Role in Chronic Neck Pain than Helmet Mass Properties

BACKGROUND

Chronic Neck Pain (CNP) among rotary-wing aircrew is thought to stem from night vision goggles (NVG) and counterweight (CW) systems which displace the centre of mass of the head. This investigation aimed to quantify the loads acting on the neck as a function of movement magnitude (MM), helmet conditions, and movement axes in rapid movements.

METHODS

Cervical spine kinematics during rapid head repositioning tasks for flexion-extension (FE) and axial rotation (AR) movements were measured from 15 males and 15 females. Participants moved in either a 35° (Near MM) or 70° arc (Far MM), while donning a helmet, helmet with NVG, helmet with NVG and a typical CW, and a CW Liner (CWL). Measured EMG from three muscles bilaterally and used to drive a biomechanical model to quantify the compression and shear acting at the C5-C6 joint.

RESULTS

In AR, the NVGs were associated with the largest compression magnitudes, 252 (24) N. CW conditions decreased the maximum compression to 249 (53) N. For FE, the compression was 340 N for the Far MM trials and 246 N for Near MMs. Changing the helmet configuration only modestly influenced these magnitudes in FE.

CONCLUSION

Every 30° of MM increased compression by 57 to 105 N. The reduction of the moment of inertia by 16% in the CWL did not reduce reaction forces. Joint loads scaled proportionately with head-supported weight by a factor of 2.05. The magnitudes of loads suggest a cumulative loading pathway for CNP development.

Fatigue among Air crews on (Ultra)-Long-Range flights - A comparison of subjective fatigue with objective concentration ability

Introduction

Long duty times are common in the aviation industry, especially with the introduction of ultra long range flights (ULR). This article aims to compare the subjective fatigue assessment and concentration ability of flight crews with objective concentration and alertness tests during (U)LR-flights.

Method

The study examined different (U)LR-flights. Before, during and after the flights subjective fatigue and concentration ability of the flight crew was examined with visual analog scale and objective attention and concentration ability with the FAIR-2 test respectively the 3-min Psychomotor Vigilance Test. For statistical analysis we used a repeated ANOVA with a post-hoc-analysis and a Wilcoxon signed-rank test for connected samples.

Results

In total 28 crew members were examined. Subjective concentration ability declined and fatigue increased significantly over the course of flights. However, no significant changes were observed in the objective concentration tests performed before and after the flights.

Conclusions

The study found that fatigue significantly increased with flight time, particularly during night hours at the window of circadian low of the crews. However, objective concentration performance showed no significant deterioration over time. The study's results were consistent with previous research, except for the finding that objective concentration was still stable. The study also compared the findings to another profession and found similar results regarding the performance of complex tasks after long working hours while experiencing fatigue.

Pratical applications

This study helps to understand the effects of ultra long-range flight on fatigue and concentration of the air crew and can help to improve safety issues on such flights.

Additive manufacturing of titanium-based alloys- A review of methods, properties, challenges, and prospects

The development of materials for biomedical, aerospace, and automobile industries has been a significant area of research in recent years. Various metallic materials, including steels, cast iron, nickel-based alloys, and other metals with exceptional mechanical properties, have been reportedly utilized for fabrication in these industries. However, titanium and its alloys have proven to be outstanding due to their enhanced properties. The β-titanium alloys with reduced modulus compared with the human bone have found more usage in the biomedical industry. In contrast, the α and α+β titanium alloys are more utilized to fabricate parts in the automobile and aerospace industries due to their relatively lightweight. Amongst the numerous additive manufacturing (AM) techniques, selective laser and electron beam melting techniques are frequently used for the fabrication of metallic components due to the full densification and high dimensional accuracy they offer. This paper reviews and discusses the different types of AM techniques, attention is also drawn to the properties and challenges associated with additively manufactured titanium -based alloys. The outcome from this study shows that 3D printed titanium and titanium-alloys exhibit huge prospects for various applications in the medical and aerospace industries. Also, laser-assisted 3D technologies were found to be the most effective AM method for achieving enhanced or near-full densification.

Application of Digital Twins in multiple fields

With the development of science and technology, the high-tech industry is developing rapidly, and various new-age technologies continue to appear, and Digital Twins (DT) is one of them. As a brand-new interactive technology, DT technology can handle the interaction between the real world and the virtual world well. It has become a hot spot in the academic circles of all countries in the world. DT have developed rapidly in recent years result from centrality, integrity and dynamics. It is integrated with other technologies and has been applied in many fields, such as smart factory in industrial production, digital model of life in medical field, construction of smart city, security guarantee in aerospace field, immersive shopping in commercial field and so on. The introduction of DT is mostly a summary of concepts, and few practical applications of Digital Twins are introduced. The purpose of this paper is to enable people to understand the application status of DT technology. At the same time, the introduction of core technologies related to DT is interspersed in the application introduction. Finally, combined with the current development status of DT, predict the future development trend of DT and make a summary.

An integrated machine learning model for aircraft components rare failure prognostics with log-based dataset

Predictive maintenance is increasingly advancing into the aerospace industry, and it comes with diverse prognostic health management solutions. This type of maintenance can unlock several benefits for aerospace organizations. Such as preventing unexpected equipment downtime and improving service quality. In developing data-driven predictive modelling, one of the challenges that cause model performance degradation is the data-imbalanced distribution. The extreme data imbalanced problem arises when the distribution of the classes present in the datasets is not uniform. Such that the total number of instances in a class far outnumber those of the other classes. Extremely skew data distribution can lead to irregular patterns and trends, which affects the learning of temporal features. This paper proposes a hybrid machine learning approach that blends natural language processing techniques and ensemble learning for predicting extremely rare aircraft component failure. The proposed approach is tested using a real aircraft central maintenance system log-based dataset. The dataset is characterized by extremely rare occurrences of known unscheduled component replacements. The results suggest that the proposed approach outperformed the existing imbalanced and ensemble learning methods in terms of precision, recall, and f1-score. The proposed approach is approximately 10% better than the synthetic minority oversampling technique. It was also found that by searching for patterns in the minority class exclusively, the class imbalance problem could be overcome. Hence, the model classification performance is improved.

Data on the first endurance activity of a Brushless DC motor for aerospace applications

This article describes the data acquired during the first test activity carried out in the Reliable Electromechanical actuator for PRImary SurfacE with health monitoring (REPRISE) H2020 project. The data consist of a set of measures from an Electro-Mechanical Actuator (EMA) employed in small aircrafts, such as phase currents, positions, temperature and loads. A test bench was developed to perform endurance sessions in various loads and working conditions. Specifically, two datasets are provided: (i) measurements used to monitor the EMA degradation through time; (ii) measurements that characterize the EMA closed-loop dynamic behaviour in healthy condition. The data are helpful to develop and test system identification methods and condition monitoring approaches.

Modeling Human Volunteers in Multidirectional, Uni-axial Sled Tests Using a Finite Element Human Body Model

A goal of the Human Research Program at National Aeronautics and Space Administration (NASA) is to analyze and mitigate the risk of occupant injury due to dynamic loads. Experimental tests of human subjects and biofidelic anthropomorphic test devices provide valuable kinematic and kinetic data related to injury risk exposure. However, these experiments are expensive and time consuming compared to computational simulations of similar impact events. This study aimed to simulate human volunteer biodynamic response to unidirectional accelerative loading. Data from seven experimental studies involving 212 volunteer tests performed at the Air Force Research Laboratory were used to reconstruct 13 unique loading conditions across four different loading directions using finite element human body model (HBM) simulations. Acceleration pulses and boundary conditions from the experimental tests were applied to the Global Human Body Models Consortium (GHBMC) simplified 50th percentile male occupant (M50-OS) using the LS-Dyna finite element solver. Head acceleration, chest acceleration, and seat belt force traces were compared between the experimental and matched simulation signals using correlation and analysis (CORA) software and averaged into a comprehensive response score ranging from 0 to 1 with 1 representing a perfect match. The mean comprehensive response scores were 0.689 ± 0.018 (mean ± 1 standard deviation) in two frontal simulations, 0.683 ± 0.060 in four rear simulations, 0.676 ± 0.043 in five lateral simulations, and 0.774 ± 0.013 in two vertical simulations. The CORA scores for head and chest accelerations in these simulations exceeded mean scores reported in the original development and validation of the GHBMC M50-OS model. Collectively, the CORA scores indicated that the HBM in these boundary conditions closely replicated the kinematics of the human volunteers across all loading directions.

Aerospace Dermatology

Evolutionarily, man is a terrestrial mammal, adapted to land. Aviation and now space/microgravity environment, hence, pose new challenges to our physiology. Exposure to these changes affects the human body in acute and chronic settings. Since skin reflects our mental and physical well-being, any change/side effects of this environment shall be detected on the skin. Aerospace industry offers a unique environment with a blend of all possible occupational disorders, encompassing all systems of the body, particularly the skin. Aerospace dermatologists in the near future shall be called upon for their expertise as we continue to push human physiological boundaries with faster and more powerful military aircraft and look to colonize space stations and other planets. Microgravity living shall push dermatology into its next big leap-space, the final frontier. This article discusses the physiological effects of this environment on skin, effect of common dermatoses in aerospace environment, effect of microgravity on skin, and occupational hazards of this industry.