In order to meet current and future efforts to reduce fuel consumption and gas emissions, an increasing number of ships are being retrofitted with one of the wind-assisted propulsion solutions. In this paper, the effects of retrofitted wind-assisted propulsion on the efficiency of the propeller are investigated. The installed ship propeller is usually designed to operate under specific conditions; once the thrust force from the sails is added, the operating point of the propeller changes. Taking into consideration the reduced efficiency of the propeller, which is no longer operating in its optimal regime, the actual wind-assisted propulsion contribution can be calculated. The wind-assisted contribution is calculated with a velocity prediction program as a reduction in conventional propulsion power output by maintaining the vessel’s designed speed. From the calculated variations in sail thrust force, dependent on the wind speed, the propeller efficiency is analyzed for different operating states. The propulsion efficiency of the propeller was analyzed with a performance characteristics calculation tool that has been developed and presented in this paper. From the meteorological data obtained from Copernicus Marine Services and available ship documentation, a case study was conducted for a selected route.

Air pollution from the shipping industry is an ongoing problem that requires exploring innovative technologies for effective resolution. The integration of wind-assisted ship propulsion (WASP) technology offers a promising route towards decarbonisation of the shipping industry. The paper investigates possible fuel savings and CO2 reduction by implementing wind assisted propulsion on a case-study vessel operating on a known route in the Adriatic Sea. The long-term contribution of added wind propulsion is analysed by implementing a Velocity Prediction Program (VPP) and available meteorological data for the area of interest. VPP is modified to predict the contribution of wind propulsion to the overall propulsion necessary to achieve the vessel design speed. The case study quantifies long-term fuel savings for ship operating a liner route and harnessing favourable (predictable) north-west winds, complementing the conventional propulsion systems.

This study sets and evaluates a practical framework for predicting ship resistance under real operational conditions along a global shipping route. Despite extensive research, the literature lacks straightforward studies that separately assess wind, wave, and current resistance using real-world performance data for ships in varying conditions. To address this gap, a methodology is established using recommended semi-empirical approaches combined with full-scale onboard operational measurements and Copernicus Marine Service environmental data in a unified assessment procedure. Calm water resistance is scaled from reference values under near-calm conditions, wind resistance is calculated using established regression models, wave-induced resistance is estimated using state-of-the-art semi-empirical formulations and spectral calculations, and current effects are modelled through a dynamic correction based on speed-over-ground measurements. The aim is to assess the reliability and applicability of added resistance calculation methods recommended by recent regulatory standards. Validation is performed by comparing the predicted resistance components, converted to equivalent shaft power, against full-scale onboard shaft-power measurements. In addition, a comparison between onboard measurements of wind and current and Copernicus data is presented. Predicted resistance components are validated against full-scale power measurements, showing agreement with an average error of approximately 9%. The resulting framework provides a practical tool for assessing energy losses due to environmental factors along specific routes using readily available ship data.

Prediction and management of ship resistance in realistic sea conditions can play a significant role in reducing fuel consumption and carbon emissions. It usually relies on physical model testing and empirical formulas, both facing limitations in early-stage design and in adapting to operational variabilities like weather. Building on our ongoing study where a physics-based framework for added resistance calculation was developed, this paper presents a multi-branch Artificial Neural Network (MbANN) designed to decompose added resistance into distinct contributions from wind, waves, and currents, using only total measured resistance as supervision. The model was trained on operational data during a case-study voyage and evaluated across 14 input arrangements. Results show that the ANN achieved high accuracy in predicting added resistance and its components, as well as particularly robust performance for current resistance. Predictions of wind and wave resistance were less consistent but showed promising results. MbANN showed solid capability of decomposing total added resistance to its physical subcomponents, thus offering flexibility in handling complex environmental interactions. These findings highlight the potential of MbANN-based decomposition to complement hydrodynamic models for operational energy efficiency assessment and compliance with EEXI and CII requirements.

This study presents a full-voyage operational validation of a load optimization strategy applied to a Dual-Fuel Diesel-Electric (DFDE) liquefied natural gas (LNG) propulsion system. The proposed approach was evaluated onboard an LNG carrier equipped with five four-stroke dual-fuel engines. The operational validation was conducted exclusively with the generator engines operating in LNG (gas) mode, while operation on conventional liquid fuels was outside the scope of this study. A complete 26-day voyage cycle, including cargo loading, loaded passage, cargo discharge, and ballast passage, was defined. Representative steady-state operating intervals for each operational mode were analyzed under both conventional Power Management System (PMS) load distribution and optimized load allocation. Real-time manual redistribution of engine loads was performed to validate the proposed load optimization strategy under real operating conditions. The results show consistent fuel savings across all operating modes, with the highest reduction observed during ballast passage (1.51%), followed by loaded passage (0.74%). A voyage-scale analysis reveals cumulative fuel savings exceeding 22 metric tons per operational cycle, equivalent to annual reductions of more than 300 metric tons under typical service conditions. These savings consistently reduce both carbon dioxide (CO₂) and nitrogen oxides (NO_x) emissions across all operating modes. Ultimately, the proposed load optimization strategy demonstrated stable performance under the investigated steady-state operating conditions and provides a practical approach to improving ship energy efficiency. The results support the potential application of the proposed strategy in existing ship energy management systems, while further validation under long-term and transient operating conditions is recommended.