The autonomy of transport systems presents a transformative opportunity to enhance logistics efficiency, improve safety, and support decarbonization. In the maritime sector, the International Maritime Organization (IMO) has been working since 2016 to develop a mandatory regulatory framework for Maritime Autonomous Surface Ships (MASSs), aiming to finalize a comprehensive code. Simultaneously, pilot projects are underway in national waters under the oversight of national administrations. Naval applications of autonomous ships demonstrate their potential, as emerging doctrines highlight their strategic and operational advantages. Although the military sector is not governed at the international level, safely managing interactions between military and commercial MASSs is crucial for ensuring safe navigation. Classification societies play a vital role in achieving high safety standards and ensuring regulatory compliance. This study aims to propose a framework for certifying maritime autonomous vessels. Through a thorough analysis of the existing literature and by identifying gaps, this study outlines a structured pathway to facilitate the certification and operation of MASSs, addressing key technical, operational, and safety considerations. This research contributes to designing a risk-informed approach for the development of autonomous surface vehicles.

Existing studies and methodologies do not offer designers clear guidelines for selecting optimal catamaran geometric parameters. Most focus on separate geometric characteristics or hull elements to minimize total resistance, providing only general trends that are not applicable when designing hull forms that differ from those in the mentioned studies. In this paper, a methodology is presented to evaluate the total resistance of a catamaran by determining its optimal geometric parameters. The approach involves selecting geometric parameters, defining variation limits to suit the design task, choosing appropriate evaluation methods and analyzing the results to identify the optimal catamaran geometric parameters. The application of the proposed methodology is achieved through the evaluation of different geometric parameters of an existing catamaran, such as its length, demihull separation, and hull symmetry. The CFD software Flow3D 2022 R1 is used to assess the influence of the selected geometric parameters on the total resistance of the catamaran, which is supported by experimental setup verification and validation using model tests. The results are analyzed using the system proposed in the developed methodology, enabling the selection of optimal geometric parameters for the considered catamaran design task. The research highlights the significance of optimizing catamaran hull forms by adjusting demihull spacing, symmetry, and length to achieve improved hydrodynamic performance and resistance reduction for applications during the vessel design stage.

This paper presents results of numerical simulation of the aftpart hull form of a research vessel. The wake rolls onto the transom platform, therefore creating additional resistance to the movement of the vessel. To solve the problem and to propose the optimal transom form, the study was carried out using the method of successive approximations and computational fluid dynamics (CFD) algorithms. The flow lines around the hull of the vessel and the wave pattern behind the hull were analysed, and the optimal transom form was chosen. Water resistance analysis was carried out to prove the efficiency of the chosen solution.

This paper presents the results of a numerical study on the parameters that affect the efficiency of the cogeneration cycle of a ship’s power plant. The efficiency was assessed based on the excess power (N_gen.) of a free turbine, operated with the inflow of gaseous nitrogen, which was used to generate electricity. A mathematical model and simulation of the regenerative cycle were created and adjusted to operate with a dual-fuel (diesel-liquid natural gas (LNG)) six-cylinder four-stroke engine, where the energy of the exhaust gas was converted into mechanical work of the regenerative cycle turbine. The most significant factors for N_gen. were identified by parametrical analysis of the cogeneration cycle: in the presence of an ‘external’ unlimited cold potential of the LNG, N_gen. determines an exhaust gas temperature Te_g of power plant; the pressure of the turbo unit and nitrogen flow are directly proportional to N_gen. When selecting the technological units for cycle realization, it is rational to use high flow and average ${\pi }_T$ pressure (~3.0–3.5 units) turbo unit with a high adiabatic efficiency turbine. The effect of the selected heat exchangers with an efficiency of 0.9–1.0 on N_gen. did not exceed 10%. With LNG for ‘internal’ use in a ship as a fuel, the lowest possible temperature of N₂ is necessary, because each 10 K increment in N₂ entering the compressor decreases N_gen. by 5–8 kW, i.e., 5–6%.

The introduction of Maritime Autonomous Surface Ships (MASSs) requires reliable engineering methods to demonstrate safety levels comparable to those of conventional manned vessels. This paper presents a mission-based stochastic reliability framework for the comparative assessment of manned and unmanned ship configurations, with a focus on engineering design and verification. The methodology is based on Reliability Block Diagrams (RBDs), where ship missions are decomposed into critical functional subsystems and evaluated over mission-limited operational profiles. To address the uncertainty inherent in component failure data for autonomous systems, Mean Time to Failure (MTTF) values are treated as stochastic variables rather than fixed parameters. A Monte Carlo simulation approach is used to propagate uncertainty from component level to overall mission reliability, producing probability distributions of mission success. The proposed framework is applied to a Search and Rescue Patrol Vessel, comparing manned and unmanned configurations under identical mission scenarios and durations. Results indicate that, for moderate uncertainty levels, the unmanned configuration achieves equal or higher mission reliability, while increasing uncertainty reduces the statistical separation between the two solutions. The approach provides a practical and replicable tool to support reliability-driven design decisions for autonomous marine systems.