This study addresses the operation of unsupported hydroelectric facilities, including the Cheboksary hydroelectric complex, which can cause significant changes in the hydrological and channel regimes of the downstream sections, leading to progressive channel erosion and reductions in water levels. A comprehensive assessment is presented of the impact of non-metallic building material extraction on the channel morphology and navigable conditions of the Volga River between km 1187.0 and 1255.0 downstream of the Cheboksary hydroelectric complex. The methodology is based on two-dimensional mathematical modeling of sediment transport and flow characteristics using the Saint- Venant equation system in the FLOOD software package. Modeling was performed for two states of the channel: the actual (existing) and the design state (considering full quarry development). Results indicate that quarry development has a limited effect on the level regime. The Sidelnikovskoye field exerts the greatest influence on flow hydraulics, where current velocities along the navigable channel are reduced by half, and local bottom deformations are observed in some areas. Development of other fields causes reduced current velocities without inducing washouts, as the velocities in these areas remain below the calculated non-washout threshold. The analysis suggests that under current conditions, channel quarrying for the extraction of non-metallic building materials will not produce adverse effects, will not further reduce water levels, will not exacerbate channel erosion, and will not deteriorate navigable conditions in this section of the Volga River.

The paper presents the results of research conducted by the scientific team at the Siberian State University of Water Transport over several years, aimed at addressing one of the critical components of the search and rescue process in maritime transport incidents — enhancing the speed of detection of rescue vehicles (SS) from emergency vessels, which may carry crew members and passengers. The study investigates a small belt hydrodynamic anchor consisting of a metal frame covered with a metal mesh, to which narrow belt strips are sewn closely along the upper edge of the frame to establish its optimal design characteristics. The paper describes the construction of the anchor and illustrates its appearance. The primary goal of the tests was to obtain quantitative characteristics of the anchor during experimental trials on a bench setup capable of simulating the orbital circular motion of the anchor on waves of varying heights. Experiments were conducted in the university’s experimental pool using a crank stand that mimicked the orbital movement of a rescue vehicle on a wave. During testing, the orbital cycle period varied from 4 to 8 seconds, the angle of attack of the hydrodynamic anchor from 15° to 30°, and the deflection angle of the anchor flap from 35° to 50°, while recording the tension of the suspension cable. The results indicate that the optimal performance of the belt hydrodynamic anchor is achieved at an angle of attack of 25°, a flap deflection angle of 50°, and an orbital cycle period exceeding 7 seconds. These parameters are recommended for the design of fixed installation values for belt hydrodynamic anchors on rescue vehicles to minimize wind-wave drift. The study provides essential design guidelines for improving the operational efficiency and safety of rescue operations at sea.

This study presents a performance comparison of two algorithms for predicting vessel latitude based on seabed depth data. The first algorithm is classical, relying on the search for a string in a depth reference matrix that is closest to current measurements according to the mean absolute error. The second algorithm is based on a neural network, which predicts vessel latitude using a sequence of measured depth values as input. The neural network model is constructed using algorithms for dataset creation, training, and testing. The network consists of ten hidden layers, each containing 200 neurons with hyperbolic tangent activation functions. A validation set is employed during training to calculate the maximum absolute error, which serves as a criterion for optimal network state. Training, validation, and test datasets are generated via pseudo-random variations of the reference depth matrix to account for sea level fluctuations and systematic measurement errors. Depth data are prepared for five different spatial steps in latitude and longitude based on a layer of spot soundings from an electronic navigational chart. For each dataset variant, the neural network is trained and its computational performance is compared to that of the classical search algorithm. Results demonstrate a significant computational advantage of the neural network for maximal reference data volume. However, as the dataset volume decreases due to increased spatial steps, this advantage diminishes, and the neural network no longer outperforms the classical method.

This study develops a gradient-based formalization of the closest point of approach (CPA) distance of ships, intended as a foundation for analyzing navigational situations and planning collision avoidance maneuvers. The relevance of the study stems from the necessity for a rigorous, clear, and visually interpretable description of the CPA distance. The research investigates the process of ship collision avoidance and examines the properties of the scalar field of the CPA distance within the space of controlled ship speed components along both the meridian and the parallel. The objective of the work is to obtain a gradient-based representation of the CPA distance and to interpret the resulting data from the perspective of practical navigation. The methods employed comprise established mathematical approaches in navigation, which describe navigational parameters through the magnitude and direction of their gradients, as well as the geometric interpretation of both the scalar field of the CPA distance and the vector field of its gradient. Both the magnitude and direction of the CPA gradient are explicitly determined, and their relationship with the time to CPA and the geometry of CPA isolines is systematically analyzed. The study demonstrates that the orthogonality of the gradient relative to the corresponding isolines provides a natural and effective basis for selecting the most appropriate collision avoidance maneuver. Moreover, the research substantiates the use of gradient-based formalization in collision risk assessment and the design of algorithms for ship collision avoidance. The main conclusions confirm that the CPA gradient possesses independent navigational significance and should be regarded as a fundamental characteristic of the ship collision avoidance process, providing both analytical insight and practical guidance for the safe and efficient maneuvering of controlled vessels within their navigational domain.

The study addresses cognitive hazards, also referred to as “demons” in the work of M. Endsley, which contribute to reductions in a navigator’s situational awareness during watchkeeping duties on the ship’s bridge. Despite the widespread adoption of advanced information and communication technologies in maritime operations, accidents on transport vessels remain frequent, with human error identified as the primary cause. Such errors often result from lapses in situational awareness triggered by cognitive hazards encountered while monitoring the navigational environment. When these hazards are unrecognized, they compromise the quality of observation, reducing the navigator’s ability to perceive, comprehend, and anticipate the development of the surrounding situation over time. Cognitive hazards are difficult to identify, creating challenges for collecting sufficient data to model human mental and physical states and behavior in various, especially critical, scenarios. To address these challenges, mathematical tools that integrate statistical and expert assessments can be applied. The study proposes Bayesian belief networks to evaluate the impact of cognitive hazards on navigational incidents. This method allows direct assessment of the probability of an incident arising from emerging hazards, facilitating risk analysis, and inverse evaluation of the probabilities of causes for incidents that have already occurred. A Bayesian belief network is presented to model conditional probabilistic relationships between events linking potential cognitive hazards to the navigator’s situational awareness and the immediate causes of incidents, using a grounding scenario as an illustrative example. The network enables comprehensive analysis of how cognitive hazards propagate through decision-making on the bridge and quantifies their contribution to maritime risk, providing practical guidance for improving navigation safety and supporting further research integrating human factors into probabilistic risk assessments in ship operations.

This study addresses the assessment of optimal decision-making for the organization of delivery and transshipment of bulk cargoes through a sea container terminal using a systematic approach. The topic is relevant due to declining container traffic at domestic seaports and the need to explore the potential use of freed port capacities for handling cargoes that are not typical for such facilities, particularly packaged and bulk fertilizers from manufacturing plants located deep in the hinterland or beyond its borders. Applying a systematic approach as an effective problem-solving tool allows the complex process of forming a transport system for product promotion to be divided into several subsystems, each addressing specific tasks. In particular, subsystems for transporting bulk cargo to the terminal and conducting loading and unloading operations at the seaport are considered to identify a single optimal technology for the overall process. It is emphasized that decisions regarding organization and management of the technology cannot rely solely on assessments of the production capabilities of individual links in the cargo promotion chain; instead, a comprehensive analysis of all system components is required. In this study, decisions regarding delivery and transshipment of bulk cargoes through the container terminal are proposed to be based on preliminary assessments of the capacities of cargo handling complexes included in the transport system. The conclusion highlights that achieving the planned volumes of bulk cargo delivery and shipment with minimal time and cost is possible only when all factors affecting the system’s operation as a whole are considered.

This paper presents research on the development of a new type of ship speed measuring device based on microelectromechanical systems (MEMS). A design deficiency in the configuration proposed in the authors’ earlier publications has been identified. Computer-based calculations demonstrated a significant error in determining vessel speed, caused by inaccurate measurement of static water pressure resulting from fluid flow around a cylindrical body. Further studies were carried out using modern software packages to evaluate errors in vessel speed measurement and to determine the optimal geometry of the log tube and the best locations for installing pressure sensors. Based on the results of numerical simulations, an improved design is proposed that reduces measurement error. Experimental testing of a prototype under real marine conditions confirmed the feasibility of measuring a vessel’s relative speed using MEMS components. The model presented in this study eliminates many of the drawbacks characteristic of previous generations of hydrodynamic logs. The device has been significantly miniaturized, creating prospects for installation on both conventional vessels and small autonomous maritime craft. Key directions for further research are highlighted.

This paper examines the issue of determining a reliable estimated navigable level (ENL) for inland waterways of regional significance. The accurate determination of the actual ENL on the inland waterways of the Russian Federation is directly linked to ensuring navigation safety. The ENL establishes a regulatory parameter essential for navigators, enabling the safe transit of vessels through movable or fixed navigable bridge spans, and the vertical clearance of such spans is established on the basis of the ENL. An incorrect determination of the lower boundary of the ENL may result in either a reduction or an increase in the actual vertical clearance: in the former case, certain vessels may be denied passage through movable or fixed navigable bridge spans; in the latter case, if the actual vertical clearance is lower than the prescribed value, a navigational accident may occur during vessel transit within the bridge span. The precise determination of the ENL is particularly important for waterways of regional significance, some of which are located within large urban areas with developed river and canal systems supporting regular navigation. Within the city limits of St. Petersburg, for example, there are 66 bridges with navigable spans permitting vessel transit, and vessels passing through these spans frequently operate with minimal vertical clearance margins; therefore, it is essential to determine the ENL accurately for each individual bridge. Only such an approach ensures the required level of navigation safety while maintaining an adequate level of waterway operational efficiency through the operation of vessels with maximum permissible dimensions on regional waterways where bridges with navigable spans are located.

This study investigates the applicability of diesel cranking with an external power source for evaluating piston ring friction. Experiments were conducted on an air-cooled 2Ch10.5/12 diesel engine with a nominal power of 22  kW. The temperatures of the motor oil in the crankcase and of the ambient air were maintained constant at 85 ±  1 °C and 30 ± 1 °C, respectively. Mechanical losses were evaluated by two methods: 1) diesel cranking with an external power source and 2) comparison of indicated and effective powers at 30 % of nominal engine load. Mineral oils I-20A, MS-20, as well as their mixtures, were used as motor oils during testing. Mechanical losses determined by diesel cranking with an electric motor were approximately 16 % lower than those determined by comparison of indicated and effective powers. Assuming that the major fraction of the reduction in mechanical losses is caused by a lower force pressing the piston rings against the cylinder wall, the friction coefficients of the piston rings were calculated. The obtained friction coefficient values exceeded those reported in scientific literature by more than five times. This indicates that the change in piston ring friction is not the main cause of the reduction in mechanical losses during the transition from motor operation to diesel cranking. Therefore, piston ring friction cannot be determined by comparing mechanical losses obtained in cranking and motor regimes. An analysis of the causes of the reduction in mechanical losses during the transition from motor operation to diesel cranking was carried out.

The This study analyzes organizational and technological approaches to improving the manufacturability, or technological efficiency, of constructing floating power units (FPUs), which represent a promising solution for energy supply to Arctic territories and the infrastructure of the Northern Sea Route. The relevance of the work is determined by state plans for Arctic development and the necessity of mastering serial production of FPUs, which requires reducing labor intensity, construction time, and costs while ensuring high quality of hull structures and the safety of nuclear power installations. The purpose of the research is to systematize organizational and technical measures aimed at improving efficiency at all stages of the FPU life cycle. The study examines the experience of constructing the “Akademik Lomonosov” and distributed shipyard projects, identifying ten key technological positions in production, including lofting, hull processing, outfitting, and testing. The authors propose developing general technical requirements (GTR) for the fabrication of hull structures, protective shells, and pipelines, as well as introducing albums of standard hull structures and welded joints to standardize production. Particular attention is given to design and technological solutions, such as optimizing the placement of cutouts in sections, minimizing assembly welded joints, and applying probabilistic methods, including PERT/COST, for estimating durations. The study further considers improvements in non-destructive testing of welded joints, the transition to national standards, the potential use of polymer pipelines for auxiliary systems, and optimization of the testing program for protective shells and reactor compartment barriers. A comprehensive system of organizational and technical measures has been developed, covering technological support for construction, quality management, and documentation unification. The obtained results can serve as a methodological basis for the development of manufacturability management programs in serial production of FPUs and may be adapted for other Arctic vessel projects, providing both practical guidance and a framework for improving construction efficiency while maintaining safety and reliability.

Low Low-speed two-stroke cross-head engines remain dominant among the power units that provide propulsion for large-capacity merchant vessels. This article examines the main directions and prospects for improving marine two-stroke low-speed engines. Based on the consideration of general design principles, the primary areas of focus are fuel efficiency, environmental safety, and operational reliability. Despite the high thermodynamic efficiency of the engine cycle, there remain reserves for further reducing specific fuel consumption by minimizing internal losses and maximizing the utilization of exhaust gas energy. The study addresses environmental aspects of marine diesel power plants based on low-speed engines and outlines the prospects for various technologies to comply with current regulations on limiting harmful emissions from exhaust gases. Key areas of development for reducing nitrogen oxide emissions include direct control of in-cylinder combustion processes, exhaust gas recirculation, and selective catalytic reduction. The potential of specific methods for decreasing sulfur and particulate matter emissions is also discussed. Particular attention is given to reducing greenhouse gas emissions, with the use of alternative fuels such as natural gas, methanol, and ammonia highlighted as promising solutions in the foreseeable future. The article further emphasizes the importance of operational reliability, identifying the monitoring of the technical condition of the power plant as the most effective approach. Overall, the paper provides an integrated perspective on improving the performance, safety, and sustainability of marine two-stroke low-speed engines, highlighting technological trends and practical solutions for decarbonization, emission control, and enhanced reliability of large- scale marine propulsion systems.

The research focuses on developing a comprehensive method for assessing the technical condition of marine diesel engines using multidimensional analysis. In the context of tightening environmental standards and increasing reliability requirements for diesel engines, the development of comprehensive approaches that provide an integral assessment of their technical condition during the transition to predictive maintenance systems is relevant. The main problem addressed in this work is the absence of a comprehensive approach that enables the integration of disparate data from heterogeneous diagnostic systems into a single objective assessment of the technical condition of marine diesel engines. The object of the research is the processes of diagnosing marine diesel engines, and the subject is the existing methods for comprehensive assessment of their technical condition. The aim of the study is to develop a method that ensures an integral assessment and operational visualization of the technical condition of a marine diesel engine, provides a quantitative evaluation of its degree of degradation, enables objective comparison of different marine diesel engines, and formalizes decisions regarding the need for repair. To achieve this aim, the task of coordinating heterogeneous diagnostic features (parametric, vibroacoustic, oil analysis data, etc.) characterized by different units of measurement and time scales is addressed. The proposed approach is based on multidimensional analysis. The assessment procedure includes classification of diagnostic parameters, their linear normalization to a unified dimensionless scale, and transformation of the multidimensional diagnostic space into a two-dimensional visual model — a radar chart. For quantitative evaluation, the area of the chart is calculated and modified by introducing weighting coefficients that reflect the significance of each parameter; additionally, coefficients characterizing wear asymmetry and uniformity of unit degradation are introduced. The integral coefficient of technical condition is defined as the ratio of the chart area of the engine under study to the area of a reference chart constructed using reference parameter values. The developed mathematical apparatus and applied method allow calculation of the integral indicator (for example, 39.47 %, corresponding to an unsatisfactory condition) and visual identification of the most degraded units based on geometric parameters of the chart. The proposed method enables the integration of heterogeneous diagnostic parameters into a single integral indicator and supports the transition from scheduled preventive maintenance to condition-based maintenance, thereby improving safety, reliability, and economic efficiency of marine power plants and other sources of mechanical energy.

This study presents an integrated signal processing and machine learning framework for automatic status prediction of shipboard equipment. The research investigates the utilization of advanced mode decomposition techniques, with a particular focus on the integration of the Hilbert- Huang Transform (HHT) with state-of-the-art machine learning algorithms. The proposed approach is based on adaptive time-frequency decomposition, employing HHT methods in conjunction with Variational Mode Decomposition (VMD) algorithms. These techniques enable precise analysis of the functional characteristics of operating modes while mitigating the adverse effects of noise contamination. The decomposed components are used as input for neural network training, with careful selection of network architecture to identify characteristic malfunctions of shipboard equipment. Special emphasis is placed on the VMD-KAN-LSTM hybrid architecture, which combines preprocessing based on VMD using the Kolmogorov- Arnold Network (KAN) with the Long Short- Term Memory (LSTM) model. This hybrid architecture effectively captures non-linear interactions between system components and temporal dependencies inherent in the data. The efficacy of the proposed methodology was evaluated through experimental validation using data from a marine reciprocating compressor. Comparative experiments, employing LSTM combined with VMD-KAN and alternative methods, demonstrated that the integration of VMD significantly improves classification accuracy in the presence of interfering noise. Notably, the VMD-KAN-LSTM architecture exhibited the highest diagnostic accuracy among the models tested. The findings emphasize the benefits of decomposition methods for monitoring and predictive maintenance of shipboard equipment and demonstrate that combining time-frequency analysis with machine learning provides a robust approach for ensuring operational reliability and longevity of critical marine systems.

This study develops an approach to intelligent support for monitoring transport and logistics services in integrated supply chains based on risk management. The relevance of the work is determined by the growing uncertainty and risk burden in transport and logistics processes, geopolitical instability, transformation of logistics routes, and increased competition between transport modes. Special attention is given to water transport, which is highly dependent on natural, infrastructural, organizational, and technological factors, increasing the likelihood of cascading effects within supply chains. The aim of the research is to form a concept for integrated risk monitoring of transport and logistics services and to develop an intelligent decision support system to ensure sustainable and safe functioning of integrated supply chains. The object of the research is transport and logistics services as part of integrated supply chains, while the subject is the methods and tools for monitoring and assessing risks arising during their implementation. The methodological basis includes risk management, system analysis, expert assessments, and methods for forming and analyzing management decision alternatives. The study describes procedures for obtaining relevant risk information, presents the structure of the intelligent support system, details the content of its semantic core, and explains the algorithm for selecting optimal management solutions. The results substantiate the expediency of using intelligent systems for monitoring risks in transport and logistics services, highlight the role of critical points in water transport for ensuring supply chain resilience, and emphasize the importance of data visualization in improving decision efficiency and validity. The proposed approach is applicable to various classes of transport and logistics services, including water transport, whose facilities may be considered critical points of integrated supply chains with increased risk exposure.