Airborne particles, such as dust and volcanic ash, pose a serious hazard to aircraft in flight due to their potential to cause erosion damage to engine components. It is crucial to anticipate and address the impact of erosion wear on engine performance and safety. This study aims to enhance our understanding of how volcanic ash particles behave when ingested through a high bypass turbofan engine (HBTFE) and assess the development of erosion wear in the front components. The effects of four different ash samples are assessed in various scenarios of encountering volcanic ash during cruise flight conditions. First, the flow solution is obtained for all front components, including the Pitot intake, spinner, fan, inlet guide vanes (IGVs), outlet guide vanes (OGVs), and connecting ducts. Based on the flow data, the particle motion equations are solved step by step using an in-house trajectory and erosion code. This latter adopts the Lagrangian approach, which incorporates a particle-eddy interaction model and includes probabilistic descriptions for the release positions of particles, sizes, and restitution factors. The finite element method (FEM) is used to track particles through the computational cells and determine impact positions and conditions. As a result, the Pitot intake design seems to prevent many ash particles from reaching the fan blade beyond 80% of the span. The fan blade leading edge (LE) exhibits extreme erosion on both sides. The blade’s pressure side (PS) displays erosion spreading practically on the entirety of the surface, especially near the trailing edge (TE). In contrast, the suction side (SS) has scattered erosion at lower rates. Furthermore, the rotor’s hub presents almost uniform erosion patterns, whereas the shroud depicts scattered erosion. This large fan appears to function as a separator, expelling a significant amount of ash particles through the secondary duct, thereby reducing the engine core’s susceptibility to erosion. Out of the four volcanic ash samples, those from the Kelud and Etna volcanoes appear to cause the highest hourly eroded mass, about twice as much as the samples from the Chaiten and Eyjafjallajokull volcanoes.

Among maritime accidents, fishing vessel collisions are particularly prone to both high frequency and severity. This study aims to identify the correlation between effective collision speed (Delta-V) and the severity of hull damage in fishing vessel collisions. Using data from collisions in South Korea, the study examines the influence of collision-related factors including Delta-V, collision location, collision subject, collision angle and the hull material of the impacted vessel on the extent of vessel damage. Statistical analyses and binary logistic regression were employed to assess trends and relationships between these variables. The findings confirm direct associations between hull damage severity and factors such as tonnage, collision location, the striking vessel and the extent of hull damage.

Augmented reality (AR) is a technology designed to display three-dimensional virtual elements in a real environment. This technology could reduce the cognitive load of marine operators by simplifying information interpretation. However, field tests often reveal qualitative reports of inaccurately projected virtual elements. To address this issue, we present a theoretical model to quantify the error between virtual projections and their observed positions. Numerical simulations, using normal random variables, indicate agreement between the predicted model variance and the error’s standard deviation. Furthermore, a real navigation experiment is conducted where observed errors are inferior to corresponding estimates for error bounds, further indicating the model’s adequacy. The proposed model enables real-time error estimation, system performance prediction and the specification of accuracy requirements. Overall, this study aims to contribute to the systematic definition of accuracy standards for AR-based maritime navigational assistance.

The question arises when developing and testing Unmanned Surface Vessel (USV) Manoeuvring Autonomy (MA): ‘is the performance we are seeing in our current on-water tests better than that of the last autonomy software version we deployed?’ An approach to answer this question is inspired by educators’ rubrics, in which a teacher grades a student’s work to objective criteria and then sums the individual criteria to determine the student’s overall grade. Here, individual metrics are used to evaluate a USV manoeuvring within range of another vessel. A weighted average is then applied to determine the overall score. With that objective performance value now obtained, similar manoeuvring tests can be compared between autonomy software versions to determine if the autonomy under development is progressively improving. This paper does not determine the threshold score needed to establish that a USV is safe to operate; thresholding of sufficient performance is recommended for future study.

Automatic Identification System (AIS) provides estimated position time along with reception time and a time stamp at the receiving station; however, the exact position estimation time remains unidentified. Therefore, this study examines the extent of positional error when using current AIS reception time. As a result, a maximum positional error of 116.9 m was observed between AIS and RTK-GPS (Real-Time Kinematic GPS). Subsequent time correction reduced this error to less than 10 m, with the product of ship speed and correction time nearly matching the error pre-correction. Consequently, it was concluded that transmitting position estimation time is essential for maintaining the reliability of Position Accuracy transmitted by AIS or VHF Data Exchange System (VDES). Furthermore, VDES may possess the communication capacity to transmit and receive vessel attitude data. Therefore, to assess the required transmission frequency, the data transmission period of roll and pitch attitude data was analysed through the mutual correlation of acceleration and angular velocity. The results indicated that the correlation coefficient for each axis exceeded 0.65 at frequencies of 0.5 Hz or higher.

Global Navigation Satellite Systems (GNSS) positioning and integrity monitoring models and algorithms currently generically assume that measurement errors follow a Gaussian distribution. As this is not always the case, there is a trade-off affecting system safety and availability, emphasising the need for better error characterisation in mission-critical applications. Research to date has shown advantages of Generalised Extreme Value (GEV) distribution for mapping extreme events. However, it is more complex than the Gaussian distribution, especially in the error convolution process. This paper derives a distribution, referred to as the GEV-based Gaussian distribution, that benefits from the advantages of both the GEV and Gaussian distributions in mapping extreme events and simplicity, respectively. The proposed distribution is tested against Gaussian, GEV and Generalised t distribution. The results show that the proposed distribution can provide a better bound for extreme events than the tested distribution both for pseudorange and carrier phase errors.

Traditional radiometric tracking navigation increasingly fails to meet the demands of deep space exploration. In contrast, optical navigation enables interplanetary spacecraft to navigate autonomously with higher precision. The effectiveness of image processing algorithms plays a crucial role in determining the accuracy of optical navigation systems. This paper presents a robust centroid extraction method based on a hybrid genetic algorithm. First, noise interference is effectively reduced by leveraging proximity information. Second, a fitness evaluation mechanism is introduced to assess model performance throughout the iterative process. Third, an annealing mutation operator is incorporated to prevent premature convergence to local optima. Finally, extensive comparative testing demonstrates that the proposed method offers substantial improvements in both accuracy and robustness, thereby substantially improving the reliability of the navigation system under complex conditions.

The recently discovered social place cells and grid cells in hippocampal formation are believed to be the neural basis underlying relative navigation of conspecifics. In this paper, we propose a new brain-inspired relative navigation model in a large-scale 3D environment for collective UAVs that translates the neurodynamics of the social place cell–grid cell circuit to robotic relative navigation algorithm for the first time. Our approach comprises three key parts: (1) a 3D isotropic Gaussian function-based cube social place cell network (cube-SPCNet), (2) a 3D continuous attractor neural network-based cube grid cell network (cube-GCNet), and (3) a population vector-based neural decoding module. The resulting brain-inspired relative navigation model incorporates the good relative information abstraction capabilities of the cube-SPCNet with the powerful temporal filtering capabilities of the cube-GCNet, yielding robustness and accuracy performance improvement for relative navigation. Experimental results show the new method can provide more robust and precise relative navigation results than its conventional counterpart, displaying a possible brain-inspired solution for relative navigation enhancement for collective UAVs.

Among the artefacts recovered from Warwick, an English ship wrecked in Bermuda at the end of November 1619, was a small wooden navigational device. Discovered during the 2010 archaeological field season, the object was cleaned, analysed, and later conserved. It has been identified as an analogue navigational tool known as a plain scale. A novel instrument at the time, the device showed real-world applications of complex mathematical formulas for charting a course on a map. Its presence on Warwick is striking; it is believed to be the earliest known example of a plain scale in use on board an English ship sailing to the colonies. The goal of this paper is to present the artefact, provide its historical and archaeological background, and discuss the current body of research related to its purpose in resolving navigational problems.

Three-dimensional mapping-aided (3DMA) Global Navigation Satellite System (GNSS) positioning improves the positioning in urban canyons for non-precision GNSS receivers. However, the 3DMA GNSS algorithms often produce a multimodal position solution, and simply taking the average of these modes reduces accuracy. A further problem, named ‘solution shifting’, is the effect of large numbers of low-scoring candidates shifting the overall position solution away from high-scoring regions. This study uses a clustering method to separate the different modes and exclude low-scoring regions from the position solution. Factor graph optimisation (FGO) is then used to integrate clustered 3DMA GNSS position and GNSS Doppler measurements or estimated velocity over multiple epochs. Positioning performance is assessed using data collected in London. The results show that the clustering method can successfully mitigate the multimodal effect, and integrating the FGO can mitigate the occurrence of multimodality and solution shifting. Static experiments in London achieve an RMSE of approximately 10 m for FGO 3DMA GNSS with clustering and 11 m without clustering.

Aviation employees operate in a dynamic, complex safety-critical system that is filled with uncertainty, requiring quick and correct expert decision-making. The purpose of this study is to investigate the decision-making indicators among aviation employees. Fifty-five technical engineers and air traffic controllers participated in this study by completing the Cambridge Gambling Task (CGT) at one of Iran’s airports. The CGT provides one of the most reliable and widely used decision-making assessment tasks and related indicators, including decision-making quality, risk-taking, delay aversion, deliberation time, risk adjustment and overall bet ratio. Higher risk adjustment, less deliberation time, and a lower delay aversion index resulted in better decision-making quality. Higher risk-taking does not necessarily mean lower self-control. No significant differences were observed between the studied groups, including between air traffic controllers (both Ground and Tower vs. RADAR and Approach) and between air traffic controllers and technical engineers in the CGT performance. The decision-making quality increased with age and work experience, which has important implications for training and selection processes.

The complex tasks of air traffic control (ATC) and the various factors affecting its operation have shed light on the need to build a model to predict conflict detection and resolution (CDR) performance within a traffic situation. This study aimed at developing a fuzzy-hybrid framework for quantifying various aspects in ATC consisting of the software, hardware, environment, liveware and organisation (i.e. the SHELL model) to predict CDR performance. The proposed fuzzy-hybrid SHELL framework in this study was tested using metadata from 10 prior studies in ATC. The results showed a highly accurate prediction, as indicated by the RMSE and MAPE values of 0⋅09 and 5⋅36%, respectively, indicating a high consistency of 90⋅92% for predicting the CDR performance. This framework offers a promising approach for Air Navigation Service Providers (ANSPs) to maintain air traffic safety and improve ATC operations efficiency.

The Singapore Strait, as one of the busiest shipping waterways in the world, contains two chokepoints of the Straits of Malacca and Singapore. With an increasing number of large-sized ships passing through the Singapore Strait in recent years, its traffic capacity has undoubtedly been affected significantly. Therefore, this study aims to assess the traffic capacity of the Singapore Strait under various mixed vessel compositions including different vessel types, vessel sizes and traffic volumes. A ship domain-based method for the estimation of the strait capacity and its variance is derived by using the minimum distance to collision among various vessel types. Then, based on the Automatic Identification System data, the strait capacity and its variances are quantitatively estimated for the two chokepoints of this waterway. Our results confirm that the strait capacity is decreasing with an increasing proportion of large-sized ships. It is also found that this traffic capacity is directly affected by the width of the strait, the size, the composition and the speed of the ships.