Weather Routing Research Articles

A ferry route in the Skagerrak optimised via VISIR-2

Abstract Urgent measures are needed for the shipping industry to contribute proportionately to climate change mitigation. To date, the potential of weather routing has not been reproducibly assessed, especially for short sea shipping. We employ the open-source VISIR-2 model on a ferry passage in the Skagerrak (the strait among Norway, Sweden, and Denmark), considering both sea currents and waves. By computing 5,840 least-CO2 optimal routes for 2023, we find promising results, particularly for voyages from Denmark. The savings follow a bi-exponential distribution, with over 10% CO2 emissions savings achievable on about ten days per year. Specifically, the Norwegian coastal current can be harnessed to enhance speed over ground and reduce overall emissions. The vessel performance curve needs to be tailored to specific ships in service, and the optimisation algorithm should be developed to enable just-in-time arrivals.

Investigating the influence of e-navigation and S-100 over the computation of the weather route

The weather route presents significant potential in identifying the most efficient route for vessels, enabling the optimisation of distance, time, or fuel consumption. Although there have been notable advancements in most technologies in recent years, weather routing has failed to keep pace with these developments. The purpose of this document is to determine whether a specific IMO’s concept called e-navigation may have an impact on vessel’s route optimisation. Today, mariners are required to integrate heterogeneous data types (hydrographic, weather, oceanographic, etc.) that are transmitted on board via various devices and in diverse formats in order to execute weather routing. When e-navigation becomes operational, relevant marine-related data will be accessible in a standardised format on a unified device. The objective of this work is to examine the potential of S-100 in the context of weather routing and route optimisation for the benefit of navigation. There are two methodologies discussed: manual and automated. A range of S-100-based products will be evaluated in relation to a variety of optimisation algorithms in order to predict whether e-navigation could be advantageous in addressing the weather routing problem. Constraints regarding the implementation of electronic navigation and the mariners’ duties are outlined in the final part of the paper.

VISIR-2: ship weather routing in Python

Abstract. Ship weather routing, which involves suggesting low-emission routes, holds potential for contributing to the decarbonisation of maritime transport. However, including because of a lack of readily deployable open-source and open-language computational models, its quantitative impact has been explored only to a limited extent. As a response, the graph-search VISIR (discoVerIng Safe and effIcient Routes) model has been refactored in Python, incorporating novel features. For motor vessels, the angle of attack of waves has been considered, while for sailboats the combined effects of wind and sea currents are now accounted for. The velocity composition with currents has been refined, now encompassing leeway as well. Provided that the performance curve is available, no restrictions are imposed on the vessel type. A cartographic projection has been introduced. The graph edges are quickly screened for coast intersection via a K-dimensional tree. A least-CO2 algorithm in the presence of dynamic graph edge weights has been implemented and validated, proving a quasi-linear computational performance. The software suite's modularity has been significantly improved, alongside a thorough validation against various benchmarks. For the visualisation of the dynamic environmental fields along the route, isochrone-bounded sectors have been introduced. The resulting VISIR-2 model has been employed in numerical experiments within the Mediterranean Sea for the entirety of 2022, utilising meteo-oceanographic analysis fields. For a 125 m long ferry, the percentage saving of overall CO2 expenditure follows a bi-exponential distribution. Routes with a carbon dioxide saving of at least 2 % with respect to the least-distance route were found for prevailing beam or head seas. Two-digit savings, up to 49 %, were possible for about 10 d in a year. In the case of an 11 m sailboat, time savings increased with the extent of path elongation, particularly during upwind sailing. The sailboat's routes were made approximately 2.4 % faster due to optimisation, with the potential for an additional 0.8 % in savings by factoring in currents. VISIR-2 serves as an integrative model, uniting expertise from meteorology, oceanography, ocean engineering, and computer science, to evaluate the influence of ship routing on decarbonisation efforts within the shipping industry.

Reducing carbon footprint of ships in voyage planning: A case study of Atlantic passage

Determining the most efficient ship routes is crucial for ensuring both safety and fuel savings during voyage planning. Great circle Navigation (GC) and weather routing (WR) are the two most common methods used by navigators for ocean crossings. GC Navigation is renowned for its potential to save time and fuel by following shorter routes over long distances; however, it may expose vessels to adverse weather conditions and sea states due to navigating at higher latitudes. On the other hand, weather routing integrates pilot charts and meteorological data to identify safer routes, albeit potentially longer, minimizing risks associated with rough weather. This study focuses on route planning for a handy-sized tanker contracting a westbound Atlantic ocean voyage within a specific timeframe. The main objective of the study is to evaluate the efficacy of these two methods. The GC route components were computed using spherical trigonometry equations, while weather routing planning relied on pilot charts and meteorological data. Environmental conditions were simulated and tested in the Transas Full Mission Simulator (NTPRO 4000). The results reveal that the WR method provides 21.3% higher energy efficiency than GC. The insights derived from this research contribute significantly to enhancing the operational efficiency and safety standards of commercial vessels.

Multi-objective ship weather routing method based on the improved NSGA-III algorithm

This study investigates a multi-objective weather routing problem for ships, aiming to minimize operational costs, sailing time, and CO2 emissions simultaneously. Departing from conventional graph search algorithms based on nodes, we incorporate the ship's operational context, utilizing heading angle and speed as direct variables. Employing the Non-Dominated Sorting Genetic Algorithm III (NSGA-III) to solve the above problem, we observed convergence difficulties due to the traditional random initial population strategy. To address this, an improved NSGA-III is proposed, generating the initial population based on a route from a combination of sampling and the A* algorithm. The proposed method is applied to routes in the North Atlantic and the North Pacific, revealing that, compared to the commonly used A* and 3D Dijkstra methods, it can achieve over a 1.5 % reduction in ship operating costs, surpassing 6 % in certain scenarios. Additionally, we conducted an analysis of set coverage and inverted generational distance. The findings indicate that the improved NSGA-III algorithm exhibits superior convergence and diversity compared to the traditional NSGA-III algorithm.

Research on safety evaluation and weather routing optimization of ship based on roll dynamics and improved A* algorithm

With the steady growth of international trade, sea transport has become indispensable, leading to an increase in maritime accidents. The sinking of the Russian Black Sea Fleet flagship, the guided missile cruiser “Moskva,” underscores the critical need for enhanced maritime safety. However, the dynamics of ship stability, particularly under transverse wind and wave conditions, remain unclear. We aimed to explore ship navigation safety by using the Moskva incident as a case study. Specifically, our objective was to investigate the influence of wind and waves on ship stability, calculate the capsizing probability of the vessel, and devise a fast and safe return path to port. We conducted a comprehensive review of existing literature on ship stability and path-planning algorithms. Leveraging this knowledge, we established the dynamics equation under transverse wind and wave conditions and integrated risk and vulnerability indicators to obtain a quantitative sea-area risk zoning map. Additionally, we employed the A* algorithm to plan a path under International Maritime Organization rules restrictions. Our findings reveal insights into ship stability dynamics and the importance of considering environmental factors in navigation safety. We calculated the capsizing probability of Moskva and devised a fast and safe return path to port, highlighting the practical application of our methodology. This study contributes to the understanding of ship navigation safety by addressing the knowledge gap in ship stability dynamics. Our findings underscore the significance of considering environmental factors in navigation safety planning. However, limitations exist in terms of data availability and model accuracy. Future research should explore additional factors impacting ship stability and refine path-planning algorithms for enhanced safety.

Weather Routing Benefit for Different Wind Propulsion Systems

_ Impact of weather routing on a post-panamax bulk carrier equipped with different wind propulsion systems was studied. The studied wind propulsion systems were rotor sails, wing sails, and suction wings and the studied route was a typical bulk carrier route between China and Brazil. A 4 degrees of freedom (4-DoF) performance prediction program was used to generate a performance model of the ship with different wind propulsion devices and the performance models were used in the voyage optimization. The voyage optimization simulations were carried out using historical weather data during the years 2015 to 2019 with one departure per week on both ways. It was found that there is a significant reduction in fuel consumption when weather routing is used on wind propulsion ships, but the magnitudes of the weather routing benefit vary from system to system depending on its versatility. Higher benefits from weather routing were found first for rotor sails, then for suction wings, and finally for wing sails.

Voyage of Learning: Cruise Ships Weather Routing and Maritime Education

The cruise ship companies place the highest emphasis on the safe operations of the vessels and safety of both crew and passengers. The ship’s captains are subsequently encouraged to use weather routing services for optimum route throughout the intended voyages. By providing guidance on the safest and most efficient routes, these systems help prevent accidents caused by unpredictable weather conditions. In this regard, the implementation of weather routing systems in maritime education and training has become crucial in ensuring the safety of cruise ships and their passengers. Moreover, weather routing systems have helped improve fuel efficiency, which is essential in the current environmental climate. Maritime education and training programs have adapted to include courses on these systems, ensuring that future captains have the knowledge and skills necessary to navigate through the ocean safely and efficiently.

Evaluation of carbon dioxide emission based on energy efficiency existing ship index during oceanographic navigation

ABSTRACT This paper evaluates the energy-saving potential of ships by analyzing their carbon dioxide emissions on 20 oceanic voyages using weather routing. The Energy Efficiency Existing Ship Index (EEXI) is used to measure a ship's energy efficiency. The voyages include routes connecting major international seaports and hubs in Asia and North America. Practical measurements were taken on board the ships using weather routing reports and ship record data. The study reveals that the E05 and W05 routes are the most energy-efficient, while the E01 and W08 routes have the highest emissions and fuel consumption. The E05 route has the optimum EEXI and the lowest CO2 emissions. Conversely, the E10 route has the highest EEXI, while W08 has the highest fuel consumption and the worst EEXI. The study emphasises the importance of reducing greenhouse gas emissions and improving energy efficiency in the shipping industry. The results demonstrate the potential benefits of using weather routing and EEXI for assessing and improving the energy efficiency of ships.

Arctic weather routing: a review of ship performance models and ice routing algorithms

With the accelerated melting of the Arctic sea ice, the opening of the Northeast Passage of the Arctic is becoming increasingly accessible. Nevertheless, the constantly changing natural environment of the Arctic and its multiple impacts on vessel navigation performance have resulted in a lack of confidence in the outcomes of polar automated route planning. This paper aims to evaluate the effectiveness of two distinct models by examining the advancements in two essential components of e-navigation, namely ship performance methods and ice routing algorithms. We also seek to provide an outlook on the future directions of model development. Furthermore, through comparative experiments, we have examined the existing research on ice path planning and pointed out promising research directions in future Arctic Weather Routing research.

Vessel weather routing subject to sulfur emission regulation

The International Maritime Organization (IMO) rolled out a set of new regulations that limit the sulfur content in the fuel oil used by ships, which came into effect from 2020. This study aims to explore the operational decisions of vessels inside and outside emission control areas (ECAs) under uncertain weather conditions and scrutinizes the economics of two types of ships: fuel-switching and scrubber installation. Such operational decisions include speed, trim, and path decision. We construct a navigation grid system, in which each grid contains weather parameters and sea condition. This navigation grid system can be applied to other type of ships due to the well-established cost structure. To improve fuel consumption estimation, we train fuel consumption estimation functions with respect to weather parameters, sea conditions, and operational decisions. This study then develops a stochastic dynamic programming model to optimize the path decisions, vessel speed, and trim. To evaluate the efficiency of the developed stochastic dynamic programming model, we further conduct a case study on a Post-Panamax container vessel that operates westbound from Hamburg to Houston. We identify the path decision, speed and trim under ECAs and the uncertain weather conditions. Surprisingly, this case study demonstrates that the ship utilizing fuel-switching takes a detour trip; in contrast, the ship with a scrubber chooses the shortest path by maximizing the speed. Additionally, we observe a knock-on effect — scrubber installation lifts carbon dioxide emissions due to increased vessel speed outside the ECA region. Rich managerial insights and potential policy implications are discussed.

Generating a path-search graph based on ship-trajectory data: Route search via dynamic programming for autonomous ships

Voyage optimization is critical for voyage planning and an important approach for realizing the autonomous and green operation modes for ships. In recent years, voyage optimization (also referred to as weather routing) has been extensively investigated and commercial solutions have also been launched. It is used to find the shortest path (optimum path) for voyage planning, which can help reduce the operating costs of the ship. However, accurately estimating fuel costs and validating routes within an acceptable computational time remain challenging. In this study, we devised methods to generate a path-search graph based on ship-trajectory data and determined an optimal route based on dynamic programming. The trajectory data of the vessels were extracted from their automatic identification systems, and the errors contained in the data were discarded via preprocessing. The trajectory data were subsequently simplified using the Douglas–Peucker method, following which a path-search graph was created using Delaunay triangulation and the number of vertices were reduced using the quadtree method. The search graph was validated using a high-resolution bathymetric chart, and dynamic programming was adopted to determine the optimal route for minimizing fuel costs. Changes in the operational performance caused by meteorological conditions were calculated, and the fuel costs were estimated using the wind resistance coefficient and SHOPERA-NTUA-NTU-MARIC method. The effect on power was determined by the effect of current on the vessel speed; this methodology was simulated and tested on oil tankers, container ships, and car and gas carriers. The fuel saved for each vessel compared to that used for the shortest path was estimated when sailing the transpacific and transatlantic routes; a maximum fuel reduction of approximately 7.8% was estimated. The proposed methods can be applied to various ship types and maritime zones to reduce the computation time of path-search graph generation while considering the high-resolution map and accurately estimating the fuel-oil consumption.

Mitigating stochastic uncertainty from weather routing for ships with wind propulsion

Reducing the shipping sector's contribution to climate change requires urgent emission reductions this decade. Both weather routing and wind propulsion offer immediate solutions, where combining sails with efficient routing amplifies the performance of each technology. However, while large emission savings are theoretically available, the impact of stochastic uncertainty from wind forecasts is unknown. Here, we present a novel approach that exploits fuel consumption calculations from over a thousand departures across three routes to characterise stochastic uncertainty. We show that routes with ideal wind conditions and long voyage times are most sensitive to uncertain forecast inputs, reducing savings from Flettner rotors and weather routing by up to 44% when a priori weather routing strategies are used. This paper further shows how an adaptive weather routing strategy can be used as an accurate prediction tool to reduce uncertainty on all routes investigated, reliably amplifying carbon savings from Flettner rotors by between 1.16 and 2.48 times typical great circle route savings. Overall, this paper provides greater assurance around the previously estimated carbon savings that serves to strengthen confidence in a wind-assisted decarbonisation strategy and its potential to provide essential emission reductions this decade.

Ship weather routing featuring w-MOEA/D and uncertainty handling

The paper presents a new version of evolutionary multi-objective weather routing (WR) for ships taking into account uncertainties of weather forecasts in route optimization. The method applies authors’ w-MOEA/D algorithm: MOEA/D framework incorporating Decision Maker’s (DM) preferences by means of w-dominance relation. Owing to this, DM preferences are taken into account throughout optimization, allowing the process to focus on the part of vast objective’s space. Only the part of Pareto front being of interest to DM is generated, thus the process converges faster, without sacrificing quality of the final set. All of the above is essential for the WR method, which pursues three objectives while trying to meet multiple constraints and handling uncertainty of weather data. The final method has been implemented as a part of client–server system architecture, whose client part has been installed on board of a m/v Monte da Guia (MdG) vessel navigating between the Portuguese coast and the Azores. The method has then been verified in the course of computer simulations and its results have been compared with real MdG GPS routes. The comparison shows that the presented method is able to find routes that bring progress in terms of the objectives’ while satisfying the constraints.

A comprehensive review of emission reduction technologies for marine transportation

The marine environment is experiencing significant impacts due to increased shipping traffic. The maritime industry must develop a low-carbon shipping strategy to comply with the increasingly strict emission regulations. This paper comprehensively reviews various decarbonization technologies, including navigation systems, hull design configuration, propulsion and power systems, and alternative fuels. By comparing a wide range of technologies in terms of their emission reduction potential and economic feasibility, this paper is intended to provide a full picture of alternative methods for future green shipping. Alternative fuels and hybrid power systems are found to have high potential for reducing carbon emissions and enhancing sustainability. The type of ship, its design configurations, and operation parameters affect the performance of optimal weather routing systems. With the current maritime policy and technological development, the transition from traditional marine fuel to liquefied natural gas can act as a temporary solution and provide significant decarbonization for maritime transportation. The emission reduction potential can be further enhanced with alternative fuels combined with hybrid power systems with high control flexibility.

Optimized Route Planning under the Effect of Hull and Propeller Fouling and Considering Ocean Currents

Route planning procedures for ocean-going vessels depend significantly on prevailing weather conditions, the ship’s design characteristics and the current operational state of the vessel. The operational status considers hull and propeller fouling, which significantly affects fuel oil consumption coupled with route selection. The current paper examines the effect of the fouling level on the selection of the optimized route compared with the clean hull/propeller as well as the orthodrome/loxodrome route. A developed weather routing tool is utilized, which is based on a physics-based model for the calculation of the main engine’s fuel oil consumption enriched to account for different fouling levels of the hull and the propeller. A genetic algorithm is employed to solve the optimization problem. A case regarding a containership in trans-Atlantic transit using forecasted weather data is presented. The effect of ocean currents is also examined as it was derived that they greatly affect route selection, revealing a strong dependence on the level of fouling. Ignoring the fouling impact can result in miscalculations regarding the estimated fuel oil consumption for a transit. Similarly, when ocean currents are ignored in the route planning process, the resulting optimal paths do not ensure energy saving.

Collision risk-informed weather routing for sailboats

Selected COLREG rules, good seamanship and sheer common sense indicate that it is in a sailboat's interest to follow collision-free routes without relying on large power-driven ships to give way. Until now, however, no method has integrated a sailboat's weather routing with collision risk monitoring and collision avoidance. Therefore, a new deterministic approach to combine the above features within one method is introduced here. The proposed method is based on Dijkstra's algorithm, where edges may be temporarily removed due to the presence of other ships. This paper presents a design of the main weather routing algorithm and the collision risk monitoring part, which applies an elliptic domain generated automatically around the target and dependent on the target's length. The method has been implemented and tested in a series of computer simulations. The results are provided and discussed here. They confirm the method's effectiveness in terms of determining collision-risk-free routes, as well as its acceptable computational time. They also show how the latter can be shortened at the cost of obtaining suboptimal routes. Finally, they emphasize the importance of considering successive weather forecasts, risk monitoring and route updates.

Ship routing optimization using bacterial foraging optimization algorithm for safety and efficient navigation

Efficient operation plays a vital role to develop a sustainable shipping fleet with cost competitive. The requirements for economic efficiency, energy efficiency, reducing emissions, and increasing safety and security lead to an innovative model in the optimal weather routing system. The vessel routing is influenced by the quality of meteorological and oceanographic data such as wind, waves, and currents. In this study, the model optimization of weather routing considers the meteorological and oceanographic information, ship's characteristics combined with an adaptive bacterial foraging optimization algorithm (BFOA) will be introduced and applied to the ship’ navigation at sea. The simulation results will be evaluated the effectiveness and reliability of the model. This model will support ships’ navigation to be safer and more comfortable, operate more efficiently and reduce emissions.

Efficient ship weather routing using probabilistic roadmaps

This paper introduces the probabilistic roadmap (PRM) concept in maritime transportation for solving the ship weather routing (SWR) problem. SWR is a path finding problem that seeks for the optimum route (path) for a ship moving from an initial port to a final desired port considering the weather conditions (winds, waves, sea currents). PRM is an old effective algorithm for robot motion planning based on a systematic use of a graph-based map which represents the robot's workspace. Using this map PRM explores feasible paths around the obstacles until finding a collision-free path between the starting and goal configurations of the robot. Considering the digital map of the ship's navigation area as well as forecasting data (updated every 3 h) concerning the weather conditions, a modified PRM algorithm is presented for tackling SWR. The proposed algorithm starts by taking random samples across the ship's navigation area which follow a particular distribution. Then, it uses a local planner to construct a large undirected graph (a roadmap) with nodes all the generated sample points connected with feasible (collision-free) edges (paths). Each path is related with a weight estimated by considering the weather conditions in the corresponding sea's region. Finally, given the departure and desired arrival ports, a modified Dijkstra's algorithm is applied to the resulting graph to search for the optimal path in terms of both fuel consumption and travel time that connects the two ports in the roadmap. The proposed algorithm operates in real-time determining the best solution within less than 1 min. Simulation simulations over the Aegean archipelagos as well as the Mediterranean Sea demonstrate the efficiency of the developed algorithm.

ТРЕНДИ ЦИФРОВИХ ТЕХНОЛОГІЙ В МОРЕГОСПОДАРЮВАННІ

The article describes the essence and global vectors of the development of modern digital technologies, which are decisive for the maritime complex. Innovative trends in the Digital sphere in the direction of maritime transportation are analyzed. The potential and prospects of application of blockchain technology on the path of digitalization of enterprises of the maritime complex are considered. The main directions of blockchain integration into the marine industry are identified to help increase the efficiency of current processes and create new ones. It is determined that the automation of workflow and transactions, the solution of trust between counterparties, the creation of a single open and safe database with smart contracts, to register information about sea vessels, including global risks and their impact on transportation, for interactive contracts and marine insurance policies are one of the most promising blockchain realizations in marine logistics. The study emphasizes that the Internet of things is quite powerfully used in the field of maritime to improve the connection between the vessel and the shore, as well as for intellectual and digital traffic management. It has been proven that a more dense interface between vessels and ports includes an analysis of large databases to reduce the time for transportation and time spent on the entrance of vessels to ports and other areas with intense traffic, thereby helping to reduce port overload. The article stipulates that the intellectualization of maritime transport makes it possible to optimize the use of fuel and energy resources, promotes weather forecasting and effective weather routing, which are the main directions of development of digital technologies in sea economy. One of the most serious directions of digitalization in the maritime industry is cybersecurity. The concept of another digital traine is analyzed and revealed-the use of automated vessels and drones. It is stated that on time among the achievements of digitization in the maritime industry there is work on autonomous marine surfaces, since similar to autonomous technologies in other industries, automated vessels can ensure increased safety and saving of funds by removing the human factor from certain operations.