The article addresses the problem of forecasting vessel movement trajectories, which is integral to safe divergence systems for predicting and assessing navigation situations. For accurate navigation situation assessment, safe divergence systems must generate precise forecasts of target vessel trajectories. It is established that addressed and broadcast messages of the Automatic Identification System (AIS) with IDs 1, 2, 3, and 5 (dynamic and static information), as well as messages with IDs 6 and 8 (route information), can be utilized for this purpose. The format of route information messages, as per IMO Circular SN.1/Circ.289, is presented. The use of route information in forecasting target vessel trajectories enhances prediction accuracy and improves navigation situation assessment. However, certain challenges in using route information are identified, along with examples of incorrect operation in trajectory prediction systems. It is demonstrated that the route information currently transmitted in AIS messages is insufficient for accurate trajectory prediction. This limitation arises because the existing route information transmission system was not originally designed for trajectory prediction tasks. Consequently, the limited applicability of current AIS messages is highlighted, and the necessity of developing a dedicated route information transmission system via AIS channels to address trajectory prediction tasks is substantiated. Proposals for the content of AIS messages in such a system are formulated.

The article analyzes the current operating conditions for "M-PR" class mixed navigation vessels within the anchorage areas of Port Kavkaz. The analysis considers the geographic regions and navigation seasons for "M-PR" vessels in the Kerch Strait and adjacent Black Sea areas, as regulated by the Rules of the Russian Classification Society. To extend the operating season for self-propelled cargo ships of the "M-PR" class in this region, an approach is proposed based on maintaining equivalent safety levels compared to a reference route. Characteristic navigation conditions for these vessels are determined for the period from March to November, inclusive, within the 10-mile coastal zone extending from the Kerch Strait to the port of Novorossiysk. This determination incorporates an analysis of available shelter locations and the current navigational situation in this water area. A calculation of safety criterion fulfillment is suggested for three routes to account for the specific operational characteristics of mixed navigation vessels within the anchorage areas of Port Kavkaz, where cargo is transshipped to storage vessels. Emergency situations involving mixed navigation vessels in the Kerch Strait area are analyzed. Based on the study results, adjustments to the Russian Classification Society's regulatory framework are proposed regarding the operating season for "M-PR" class vessels in the 10-mile coastal zone from the port of Novorossiysk to the Kerch Strait. For the months with the most severe hydrometeorological conditions (from March to November), the introduction of a wave height restriction of h3% ≤ 2.0 m is justified. Other measures aimed at improving navigation safety under current conditions are also considered.

The handling and safety of perishable goods are key tasks in seaport operations. Perishable goods are primarily transported using specialized vehicles or insulated containers designed to maintain a specific temperature regime. These goods include seafood delivered to ports by ships equipped with refrigeration systems. Schedules are developed for processing refrigerated vessels, specifying timeframes for loading and unloading operations based on available lifting and transport equipment as well as vehicles for transporting seafood to storage facilities or consumers. The fleet of lifting and transport equipment significantly influences port operation schemes, cargo turnover, technological process costs, port throughput capacity, and warehouse storage capacity. Automation in lifting and transport equipment partially eliminates human factors from technological processes, thereby improving efficiency but potentially reducing vehicle handling speed. Modeling serves as an effective method for identifying problem areas. Prolonged loading and unloading times beyond scheduled limits or extended exposure of seafood on docks—particularly during summer—adversely impact quality characteristics; thus, minimizing outdoor exposure time is crucial. During modeling of loading and unloading technologies, specific technological operations affecting perishable goods' quality characteristics were identified. Petri nets were employed to simulate these technological processes. The analysis of simulation results revealed not only problem areas but also conflict situations that can be addressed through situational management and adjustments in loading/unloading technologies. Vehicle processing efficiency—apart from that influenced by lifting and transport equipment—is managed via an information system that ensures timely data processing, directly impacting decision-making speed in conflict scenarios.

The article analyzes the peculiarities of remote control of a marine autonomous surface ship in port waters using data obtained from conventional navigational technical means. It highlights that for the effective operation of an automated navigation system controlling a marine autonomous surface ship, a monitoring system must be developed. This system's task is to collect data from the technical means of the controlled object in real-time, analyze them, and subsequently determine and forecast the ship's condition (safe or unsafe) with necessary reliability. Based on these results, possible scenario variants are formed to ensure vessel safety, aiding the automated navigation system or external captain in making optimal decisions. Differences between controlling a classical vessel with a crew on the navigation bridge and remotely controlling an autonomous surface vessel by an external captain under port conditions are presented. The accuracy of classical navigation tasks is calculated based on international and national requirements for measuring capabilities of conventional navigational equipment in relation to remote control without detailing individual equipment models' characteristics. A comparison of the obtained calculation results with international and national safety requirements is made, identifying weaknesses in current technologies and providing recommendations for improving navigation data quality to successfully perform ship-to-ship operations in remote control mode within port waters. The importance of developing new technologies for autonomous ship control to overcome existing navigation aids' shortcomings and enhance safety in port conditions is emphasized.

The study examines the feasibility of organizing the delivery and processing of bulk cargo at marine container terminals experiencing reduced cargo turnover due to the sanctions imposed by Western countries. It is emphasized that such a task arises from the need to maximize the transport potential of delivery modes bringing goods to the port and the capacity of transshipment complexes not initially designed for handling bulk cargo. Modeling a transport system capable of optimizing this process necessitates a comprehensive evaluation of the operational performance of transport means throughout the entire route—from the manufacturing plant to the marine container terminal. The paper explores the possibility of developing a model for creating a transport system based on forming a container train unit consisting of "railway platform – bulk containers" and provides a brief description of this concept. During the analysis of related processes, it is highlighted that the accumulation of bulk containers depends on several factors: the circulation period of the circular container train delivering goods to the terminal, delivery schedules, vessel carrying capacity at the terminal, and meteorological conditions that may delay vessel operations. The study presents examples calculating the required number of bulk containers under various projected transport system parameters, including cargo delivery times to the terminal, waiting times for marine tonnage availability, and delays due to atmospheric conditions. The conclusion suggests that employing innovative technologies for handling bulk cargo could lead to significant increases in cargo turnover and expansion of the hinterland boundaries served by the marine terminal.

A literature review addressing the issue of the human factor has been conducted. A representative sample was compiled, with its completeness determined by the criterion of the absence of new interpretations of the term "human factor." A list of definitions for the term "human factor" was compiled, highlighting that different sources assign varying meanings to this concept. Each definition contains a fundamental judgment. A classification of these judgments was carried out, identifying five groups: human errors, characteristics of professional activity, characteristics of a person, structural aspects, and the importance and complexity of the research subject. It is concluded that the studied topic—human activity in performing professional tasks—can be described using terms such as "human element," "human factor," "successful professional activity," "human factors," "individual psychological traits," "physical and social environment," and "human condition." Definitions were formulated for each term. A structural-logical scheme illustrating the interconnections between these concepts was proposed. As the most general concept, it is suggested to use "human element" as an essential part (element) of a complex system, specifically a complex technical device—a vessel—representing human manifestations in professional activity. The spectrum of such manifestations is extensive, forming a continuum. At one pole are human "errors" (the human factor), while the other pole lacks a universally recognized term; therefore, it is proposed to use "successful professional activity." The driving forces behind human manifestations in professional activity are human factors, encompassing individual psychological traits, physical and social environments, and the condition of the specialist executing them. The proposed structural-logical scheme enables more precise formulation of scientific objectives whose solutions will enhance navigation safety by accounting for the human element.

The problem of correlation-extreme navigation is addressed based on the reconstructed spline template of informativeness, incorporating a priori information about the safe movement of vessels in conflict navigation spaces. The paper focuses on the practical implementation of intelligent ship motion control guided by the principle of analyzing the geophysical field geometry when enabling autonomous ship movement along an electronic spline trajectory. The study substantiates terrain-based navigation principles by comparing measured navigation parameters with a pre-created virtual informative template via an extreme correlation functional for continuous vessel location updates. An analysis of alternative positioning reveals the advantages and disadvantages of various autonomous map-aided navigation methods, emphasizing their potential accuracy. The hypothesis of spatial and surface field navigation as the sole alternative to satellite systems is examined. Alternative navigation is proposed as an assistive technology to complement traditional satellite positioning, ensuring maximum noise resistance and cybersecurity in operational situational awareness. Integrity monitoring is studied as a modern criterion for validating navigation information. The application of integrity is hypothesized to improve real-time iterative coordinate calculations in alternative positioning. A new procedure is developed to optimize grid approximation point distribution by determining the effective positions of sliding nodes. Computational implementation of a wide range of correlation-extreme navigation tasks is achieved through enhanced Pascal programs. The proposed algorithm, tested with spline function methods, provides harmonized assistance to navigators, extending situational awareness horizons for watch assistants navigating challenging scenarios.

This work proposes a possible method to reduce nuclear fuel overconsumption during maneuvering by utilizing sliding steam pressure technology. It is noted that since the beginning of atomic icebreaker operations in the Arctic, there has been significant overconsumption of nuclear fuel during maneuvering of nuclear power plants, and finding solutions to reduce this is a pressing goal. A proposal is made for a temporary transition to sliding steam pressure in the main steam pipeline at the initiative of the navigator, who maneuvers the icebreaker and can control the power of the electric propulsion system. Currently, the navigator cannot independently increase the reactor power even if required for safe navigation. It is noted that all atomic icebreaker projects have limitations on the power of the electric propulsion system set by the central control post operator of the nuclear steam generating system, and the navigator cannot independently increase reactor power for emergency maneuvers. Attention is drawn to the fact that if the navigator still sets the power of the electric propulsion system above the specified power limit, the load from the main turbogenerators is automatically removed and the previous power limit is restored. A modification is proposed where the navigator, without requesting a new increase in reactor power from the central control post, can independently increase reactor power during emergency maneuvers. This allows significantly reducing the limitation on the power of the electric propulsion system and the corresponding reactor power when performing work in the Arctic on a specific route section without compromising navigation safety. It is noted that this solution provides nuclear fuel savings and extends the active zone campaign. Evaluations performed in the research show significant nuclear fuel savings when using sliding steam pressure technology to overcome short-term unlikely obstacles arising in complex ice conditions in the Arctic.

This article addresses the issue of determining the ability of marine diesel oil to penetrate into the structure of a composite material made with reinforcing glass fabrics and a polyester binder. The penetration capability is assessed by measuring the weight change of samples cut from a standard plate of polymer composite material before and after immersion in a container with marine diesel oil for a specified duration. A low penetration rate of diesel oil into this material has been established, depending on its structure—specifically, on the arrangement of reinforcing materials and whether or not the edges were treated with polyester resin after cutting from the standard plate. The mechanical properties (tensile, compressive, and flexural strength) of the composite material after removal from diesel oil are reported. This study also examines how processing the ends of cut samples with polyester resin affects marine diesel oil penetration into polymer composite structures. The influence of sample layering (glass wool and roving fiberglass) in a liquid medium (diesel oil) on mechanical characteristics during bending, stretching, and compression is analyzed. The article presents research findings that demonstrate a direct correlation between ultimate strength, breaking force, and the number of roving layers in polymer composite materials treated with polyester resin. Experimental results reveal how diesel oil penetrates composite materials, altering their mechanical properties upon immersion in a liquid medium. Findings from an experimental study on various reinforcement schemes confirm the feasibility of using these materials in ship hull structures. Specifically, these materials are recommended for manufacturing marine tanks designed for storing diesel oil.

The purpose of this work is to develop information digital technologies in terms of modeling methods and formalized descriptions of technological process control that are associated with increasing the reliability of water transport systems by reducing the likelihood of transport risks occurring. As part of this goal, the problem of developing mathematical methods for accounting for the partial delay of the protective effect in risk management models is being addressed. This is done in the context of growing requirements for the safe digitalization of water transport, given a wide range of risk factors of both engineering-material and informational nature. A theoretical probabilistic approach to optimizing costs for reducing risks, considering both these costs and possible losses from risk realization, has recently been developed in industry research on water transport. However, the models considered have not accounted for the possible and sometimes inevitable delay in the effect, as costs for anti-risk measures are not fully realized immediately. This situation is analogous to distributed-lag analysis of incomplete construction, which was developed under planned economy conditions. The results of this work include new optimization mathematical models that account for the possible delay in the effect of additional costs, thereby reducing overall risk damage.

The purpose of the study is to enhance methods for computer monitoring and parametric identification of models describing vessels' fuel consumption characteristics. These improvements aim at analyzing and forecasting energy efficiency indicators of water transport facilities and optimizing the operational modes of diesel generator units. The paper proposes an algorithm for parametric identification of input-output characteristics across various technological processes and systems (technical, biological, economic, social, environmental, etc.) based on measurement data using approximate motor (regression) neural networks. The algorithm enables quantitative error assessment of parametric optimization using the Euclidean norm. Unlike traditional methods relying on statistical series for model fitting, the proposed approach trains a multilayer neural network with backpropagation to minimize deviations in output signal values from reference values by adjusting synaptic weight coefficients. The study demonstrates that radial neural networks with fixed structures—comprising one hidden layer with nonlinear activation functions and one output layer with linear activation functions—are suitable for solving problems in this domain. These networks ensure accurate image mapping based on the Euclidean metric while simplifying training modes and maintaining acceptable approximation and identification accuracy. The algorithm has been implemented to estimate parameters of a vessel's fuel consumption model based on statistical series with a predefined initial approximation. It can also be applied to identify energy consumption characteristics in the inland water transport sector when calculating target indicators and developmental metrics.