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UAV accident investigation is essential for safeguarding the fast-growing low-altitude airspace. While near-daily incidents are reported, they were rarely analyzed in depth as current inquiries remain expert-dependent and time-consuming. Because most jurisdictions mandate formal reporting only for serious injury or substantial property damage, a large proportion of minor occurrences receive no systematic investigation, resulting in persistent data gaps and hindering proactive risk management. This study explores the potential of using large language models (LLMs) to expedite UAV accident investigations by extracting human-factor insights from unstructured narrative incident reports. Despite their promise, the off-the-shelf LLMs still struggle with domain-specific reasoning in the UAV context. To address this, we developed a human factors analysis and classification system (HFACS)-guided analytical framework, which blends structured prompting with lightweight post-processing. This framework systematically guides the model through a two-stage procedure to infer operators’ unsafe acts, their latent preconditions, and the associated organizational influences and regulatory risk factors. A HFACS-labelled UAV accident corpus comprising 200 abnormal event reports with 3600 coded instances has been compiled to support evaluation. Across seven LLMs and 18 HFACS categories, macro-F1 ranged 0.58–0.76; our best configuration achieved macro-F1 0.76 (precision 0.71, recall 0.82), with representative category accuracies > 93%. Comparative assessments indicate that the prompted LLM can match, and in certain tasks surpass, human experts. The findings highlight the promise of automated human factor analysis for conducting rapid and systematic UAV accident investigations.

Purpose Bulk material-handling equipment development can be accelerated and is less expensive when testing of virtual prototypes can be adopted. However, often the complexity of the interaction between particulate material and handling equipment cannot be handled by a single computational solver. This paper aims to establish a framework for the development, verification and application of a co-simulation of discrete element method (DEM) and multibody dynamics (MBD). Design/methodology/approach The two methods have been coupled in two directions, which consists of coupling the load data on the geometry from DEM to MBD and the position data from MBD to DEM. The coupling has been validated thoroughly in several scenarios, and the stability and robustness have been investigated. Findings All tests clearly demonstrated that the co-simulation is successful in predicting particle–equipment interaction. Examples are provided describing the effects of a coupling that is too tight, as well as a coupling that is too loose. A guideline has been developed for achieving stable and efficient co-simulations. Originality/value This framework shows how to achieve realistic co-simulations of particulate material and equipment interaction of a dynamic nature.

Purpose Sliding wear is a common phenomenon in the iron ore handling industry. Large-scale handling of iron ore bulk-solids causes a high amount of volume loss from the surfaces of bulk-solids-handling equipment. Predicting the sliding wear volume from equipment surfaces is beneficial for efficient maintenance of worn equipment. Recently, the discrete element method (DEM) simulations have been utilised to predict the wear by bulk-solids. However, the sensitivity of wear prediction subjected to DEM parameters has not been systemically investigated at single particle level. To ensure the wear predictions by DEM are accurate and stable, this study aims to conduct the sensitivity analysis at the single particle level. Design/methodology/approach In this research, pin-on-disc wear tests are modelled to predict the sliding wear by individual iron ore particles. The Hertz–Mindlin (no slip) contact model is implemented to simulate interactions between particle (pin) and geometry (disc). To quantify the wear from geometry surface, a sliding wear equation derived from Archard’s wear model is adopted in the DEM simulations. The accuracy of the pin-on-disc wear test simulation is assessed by comparing the predicted wear volume with that of the theoretical calculation. The stability is evaluated by repetitive tests of a reference case. At the steady-state wear, the sensitivity analysis is done by predicting sliding wear volumes using the parameter values determined by iron ore-handling conditions. This research is carried out using the software EDEM® 2.7.1. Findings Numerical errors occur when a particle passes a joint side of geometry meshes. However, this influence is negligible compared to total wear volume of a wear revolution. A reference case study demonstrates that accurate and stable results of sliding wear volume can be achieved. For the sliding wear at steady state, increasing particle density or radius causes more wear, whereas, by contrast, particle Poisson’s ratio, particle shear modulus, geometry mesh size, rotating speed, coefficient of restitution and time step have no impact on wear volume. As expected, increasing indentation force results in a proportional increase. For maintaining wear characteristic and reducing simulation time, the geometry mesh size is recommended. To further reduce simulation time, it is inappropriate using lower particle shear modulus. However, the maximum time step can be increased to 187% TR without compromising simulation accuracy. Research limitations/implications The applied coefficient of sliding wear is determined based on theoretical and experimental studies of a spherical head of iron ore particle. To predict realistic volume loss in the iron ore-handling industry, this coefficient should be experimentally determined by taking into account the non-spherical shapes of iron ore particles. Practical implications The effects of DEM parameters on sliding wear are revealed, enabling the selections of adequate values to predict sliding wear in the iron ore-handling industry. Originality/value The accuracy and stability to predict sliding wear by using EDEM® 2.7.1 are verified. Besides, this research accelerates the calibration of sliding wear prediction by DEM.

On the basis of the influence of dry season on ship traffic flow, the gathering and dissipating process of ship traffic flow was researched with Greenshields linear flow—density relationship model, the intrinsic relationship between the ship traffic congestion state and traffic wave in the unclosed restricted channel segment was emphatically explored when the ship traffic flow in a tributary channel inflows, and the influence law of multiple traffic waves on the ship traffic flow characteristics in unclosed restricted segment is revealed. On this basis, the expressions of traffic wave speed and direction, dissipation time of queued ships and the number of ships affected were provided, and combined with Monte Carlo method, the ship traffic flow simulation model in the restricted channel segment was built. The simulation results show that in closed restricted channel segment the dissipation time of ships queued is mainly related to the ship traffic flow rate of segments A and C, and the total number of ships affected to the ship traffic flow rate of segment A. And in unclosed restricted channel segment, the dissipation time and the total number of ships affected are also determined by the meeting time of the traffic waves in addition to the ship traffic flow rate of segments. The research results can provide the theoretical support for further studying the ship traffic flow in unclosed restricted channel segment with multiple tributaries Article Highlights The inflow of tributaries' ship traffic flows has an obvious impact on the traffic conditions in the unenclosed restricted channel segment. The interaction and influence between multiple ship traffic waves and the mechanism of generating new traffic waves are explained. The expression of both dissipation time of queued ships and the total number of ships affected in the closed and unclosed restricted channel segment are given.

Deep sea mining tailings disposal is a new environmental challenge related to water pollution, mineral crust waste handling, and ocean biology. The objective of this paper is to propose a new tailings disposal procedure for the deep sea mining industry. Through comparisons of the tailings disposal methods which exist in on-land mining and the coastal mining fields, a new tailings disposal procedure, i.e., the submarine–backfill–dam–reuse (SBDR) tailings disposal procedure, is proposed. It combines deep sea submarine tailings disposal, backfill disposal, tailings dam disposal, and tailings reuse disposal for the deep sea mining industry. Then, the analytic network process (ANP) method is utilized to evaluate the performances of different tailings disposal methods. The evaluation results of the ANP show that the new proposed tailings disposal procedure is the most suitable for the deep sea mining industry.

Nowadays, the major ports around the world usually consist of multiple terminals and service centers which are often run by different operators. Meanwhile, inland terminals have been also developed to reduce port congestion and improve transport efficiency. The integrated planning of inter-terminal transport (ITT) between the seaport and inland terminals helps in providing frequent and profitable services, but also could lead to higher overall planning complexity. Moreover, the ITT system usually involves multiple stakeholders with different or even conflicting interests. Although an increasing number of studies have been conducted in recent years, few studies have summarized the research findings and indicated the directions for future research regarding ITT. This paper provides a systemic review of ITT planning: we examine 77 scientific journal papers to identify what kind of objectives should be achieved in ITT system planning, which actors should be involved, and what methodologies can be used to support the decision-making process. Based on the analysis of the existing research, several research gaps can be found. For example, the multi-modality ITT systems are rarely studied; cooperation frameworks are needed in the coordination of different actors and quantitative methodologies should be developed to reflect the different actors’ financial interests.

An active wrist can deliver both bending and twisting motions that are essential for soft grippers to perform dexterous manipulations capable of producing a wide range movements. Currently, the versions of gripper wrists are relatively heavy due to the bending and twisting motions performed by the motors. Pneumatic soft actuators can generate multiple motions with lightweight drives. This research evaluates a pneumatic soft wrist based on four parallel soft helical actuators. The kinematics models for predicting bending and twisting motions of this soft wrist are developed. Finite element method simulations are conducted to verify the functions of bending and twisting of this wrist. In addition, the active motions of the soft pneumatic wrist are experimentally demonstrated. Based on sensitivity studies of geometric parameters, a set of parameter values are identified for obtaining maximum bending and twisting angles for a bionic human wrist. Through simulation and experimental tests of the soft wrist for a soft gripper, the desired bending and twisting motions as those of a real human hand wrist are established.

In North-West Europe, the options for intermodal inland transportation of containers are increasing. Inland corridors become increasingly interconnected in hinterland networks. To minimise operating costs, new methods are required that allow integral network operations management. The network operations consist of allocating containers to available inland transportation services, that is, planning. For adequate planning it is important to adapt to occurring disturbances. In this article, a new mathematical model is proposed: the Linear Container Allocation model with Time-restrictions. This model is used for determining the influence of three main types of transit disturbances on network performance: early service departure, late service departure and cancellation of inland services. The influence of a disturbance is measured in two ways. The impact measures the additional cost incurred by an updated planning in case of a disturbance. The relevance measures the cost difference between a fully updated and a locally updated plan. With the results of the analysis, key service properties of disturbed services that result in a high impact or high relevance can be determined. Based on this, the network operator can select focus areas to prevent disturbances with high impact and to improve the planning updates in case of disturbances with high relevance. The proposed method is used in a case study to assess the impact and relevance of transit disturbances on inland services of the European Gateway Services network.

The current weaknesses of the conventional intermodal freight transportation system have led to the development of the synchromodal freight transportation concept introduced and piloted in the Netherlands. The innovative concept has the advantage of adding flexibility, cost reduction, and sustainability among other things, into the freight transportation system. The synchromodal system has not been started in any developing country yet due to its newness. In this study, we used multiple methodologies to conduct a feasibility study for the possibilities of introducing the concept in a developing country, Ghana. An intensive literature review was performed using the Grounded Theory and the Critical Success Factors (CSFs) method to identify the key factors for the introduction of the synchromodal concept. Questionnaires were administered to the primary stakeholders in the maritime-hinterland transportation sector to solicit their views about the factors necessary for the implementation. We next carried out SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to catalogue the strengths and weakness of the country in introducing the concept. The multiple regression analysis method was used to analyse the experience of stakeholders in the freight transportation business and their knowledge about the synchromodal freight transportation system. The results of the study show that it is possible to introduce the concept in the country. However, there is the need to improve the current transportation and ports infrastructure of the country considerably for successful synchromodal system adaptation. There is also the need for stakeholders education on the concept.

This paper proposed a scheme design for Sydney’s frontport check-in system, which completes check-in and baggage drop-off at Sydney’s Circular Quay, and transports the baggage to Sydney Kingsford Smith Airport by waterway, and provided a strengths, weaknesses, opportunities and threats (SWOT) analysis of Sydney’s frontport check-in system. Using the process method of quality management, the frontport check-in process was divided into three sub-processes: baggage consignment, baggage packing and transportation, and airport baggage handling. The eight key elements of each sub-process such as input, output, resources, and methods, etc. were discussed, the key factors influencing the cost of baggage transportation were analyzed, and the cost control measures such as adopting economic speed, reducing fuel consumption of the main engine, improving the ship loading rate, and raising loading and unloading efficiency were proposed. At the same time, two different types of baggage transportation ships and other parameters that affect the cost such as the number of berths, ships, lifting machineries, and the yard area were analyzed and calculated through calculation cases. This scheme is a beneficial addition to the existing in-town check-in system.