This paper proposes a semi-empirical model to predict a ship’s speed loss at arbitrary wave heading. In the model, the formulas that estimate a ship’s added resistance due to waves attacking from ...different heading angles have been further developed. A correction factor is proposed to consider the nonlinear effect due to large waves in power estimation. The formulas are developed and verified by model tests of 5 ships in regular waves with various heading angles. The full-scale measurements from three different types of ships, i.e., a PCTC, a container ship, and a chemical tanker, are used to validate the proposed model for speed loss prediction in irregular waves. The effect of the improved model for speed loss prediction on a ship’s voyage optimization is also investigated. The results indicate that a ship’s voyage optimization solutions can be significantly affected by the prediction accuracy of speed loss caused by waves.
As increasing numbers of merchant ships navigate in the Arctic waters, more energy efficient navigation in the Arctic is needed for both economic and environmental purposes. This paper aims to ...provide a comprehensive analysis of energy efficiency of ice-going ships. Firstly, a data-driven model based on neural network theory is developed to predict the energy efficiency of ships in the Arctic. Then, a route with optimum energy efficiency is presented, intended to cut costs and be as environmentally friendly as possible. Finally, a case study is carried out to analyze the performance of a case study ship sailing at various environmental conditions. The results indicate that when planning the route for such an Arctic ship, it would be shortsighted only to focus on distance rather than energy efficiency. Moreover, the model shows good agreement between the simulation and real-life navigation. It is expected that the construction of this multi-angle, energy efficiency optimization model could help to improve Arctic navigation.
•A data-driven model for predicting energy efficiency of ships in ice-covered waters is investigated.•The ship speed for optimum energy efficiency in various ice conditions is recommended.•A routing model is developed for ships searching optimum energy efficiency routes in ice-covered water.•A case study of Chinese merchant vessel Yong Sheng is carried out.
Accurate prediction of ship speed for given engine power and encountering sea environments is one of the key factors for ship route planning to ensure expected time of arrivals (ETA). Traditional ...methods need first to compute a ship's total resistance based on theoretical calculations, which are often associated with large uncertainties. In this paper, two statistical approaches are investigated to establish models for a ship's speed prediction. The measurement data of a containership during one year's sailing are used for the demonstration and validation of the presented statistical methods. The pros and cons of the methods are compared in terms of capability, robustness, and accuracy of the prediction. By means of the measured engine Revolutions Per Minute (RPM) and extracted sea environments along the ship's sailing routes, the statistical methods are shown to be able to give reliable speed predictions. Further investigation is needed to test the capability of the statistical methods for the speed prediction using engine power instead of RPM.
•Autoregressive process and Mixed Effect statistical models are introduced to derive a ship’s speed/RPM characteristics.•The speed/RPM characteristics are described in terms of encountered sea environments.•One year’s performance data of a 2800TEU containership is used to demonstrate the applications of above statistical models.•Sea environments are extrapolated from climate reanalysis data, with wind/waves from ECMWF and current from NOAA.•The prediction errors are less than 1% for all analysed voyages.
In this study, different operation factors affecting a ship’s wave statistics are studied, such as the slow steaming and voyage optimizations. Especially, the impact of various voyage optimization ...methods on the long-term wave statistics and corresponding fatigue damage during ship operations is investigated by comparing the encountered waves with the design wave scatter diagram. Three years of full-scale measurements from a container ship sailing in the North Atlantic are employed to study the impact, in addition to noon reports from two fleets of container ships and VLCCs. Furthermore, the benefits of using voyage optimizations for minimum fatigue damage accumulation during operation are discussed. The large difference of wave statistics is found when the ship follows routes generated by various optimization methods and the design diagram. For some westbound voyages, the voyage optimization methods can significantly decrease the ship’s fatigue damage accumulations, leading to longer fatigue life.
The safe and efficient navigation of ships traversing the Northern Sea Route demands accurate information regarding sea ice concentration. However, the sea ice concentration forecasts employed to ...support such navigation are often flawed. To address this challenge, this study advances a statistical interpolation method aimed at reducing errors arising from traditional interpolation approaches. Additionally, this study introduces an autoregressive integrated moving average model, derived from ERA5 reanalysis data, for short-term sea ice concentration forecasts along the Northern Sea Route. The validity of the model has been confirmed through comparison with ensemble experiments from the Coupling Model Intercomparison Project Phase 5, yielding reliable outcomes. The route availability is assessed on the basis of the sea ice concentration forecasts, indicating that the route will be available in the upcoming years. The proposed statistical models are also shown the capacity to facilitate effective management of Arctic shipping along the Northern Sea Route.
Ships can be operated more efficiently by utilizing intelligent decision support integrated with onboard data collection systems. In this study, a Bayesian optimization-based decision support system, ...which utilizes ship performance models built by machine learning methods, is proposed to help determine the operational set-points of two engines for double-ended ferries. By optimizing the ferries’ power allocation between the stern and bow engines, the Decision Support System (DSS) will simultaneously attempt to keep the ETA of the ferry fixed under a set of operational constraints using the Bayesian optimization. Its objective is to minimize fuel consumption along individual trips. Based on simulation environment, the DSS can reduce at maximum 40 % fuel consumption with no significant change of the ETA. Final full-scale experiments of a double-ended ferry demonstrated an average of 15 %, where at least half of this saving was achieved by the optimized power allocation between bow and stern engines.
A voyage optimization algorithm is an essential component in a ship's routing concerning safety, energy efficiency, arrival punctuality, etc. In this study, predictive optimization is integrated with ...an Isochrone-based voyage optimization algorithm for energy-efficient sailing. Different waypoints generation and grid partition strategies in search spaces are proposed to achieve smooth convergence toward the destination, and costs ahead of the current sailing time stages are estimated in the cost function to avoid the local suboptimization. Based on these measures, this paper introduces the Isochrone-based predictive optimization (IPO) method that can achieve enhanced and robust performance in real-time multi-objective voyage optimization. The unrealistic routes with abrupt turns that occur in the traditional Isochrone and graph search methods are avoided. The IPO method can suggest energy-efficient routes in diverse sailing environments, while complying with punctuality requirements in voyage planning. Meanwhile, it requires a few computational resources that enable online and real-time adjustment during voyage execution, adapting to dynamic sailing environments. Its efficiency and effectiveness are demonstrated by six case study voyages from a chemical tanker with full-scale measurements, and further compared with other widely used voyage optimization methods. The results show that the proposed method can provide smooth routes with subtle turns with 5% fuel reduction on average for all case voyages, with around 40 seconds runtime.
This paper proposes a semi-empirical model to estimate a ship’s speed loss at head sea. In the model, the formulas to estimate a ship’s added resistance due to waves have been further developed to ...better consider the ship hull forms, in addition to other main particulars. Based on the model experimental tests of 11 ships in regular head waves, the new formulas have more flexible forms and can better fit the test results than other similar models. In addition, this model proposes a significant wave height based correction factor multiplied to the conventional integration to compute wave resistance in irregular waves. This factor is supposed to consider the impact of coupled ship motions in high waves on a ship’s added resistance due to waves. The model is validated by the full-scale measurement from two vessels, a PCTC and a chemical tanker. The encountered weather conditions along the sailing routes are extracted from the reanalysis metocean data. The results indicate that the proposed model can provide quite accurate predictions of ship speed loss in head sea operations.
•A semi-empirical model is proposed to estimate a ship’s speed loss at head sea.•Formulas to estimate added resistance due to waves are further developed.•A wave height related correction factor is proposed in irregular waves.•The improved model is validated by experimental data in regular waves from 11 ships.•The proposed speed loss prediction model is demonstrated by full-scale measurements.
Ocean-crossing ship structures continuously suffer from wave-induced loads when sailing at sea. The encountered wave loads cause significant variations in ship structural stresses, leading to ...accumulated fatigue damage. Where large inherent uncertainties still exist, it is now common to use spectral methods for direct fatigue calculation when evaluating ship fatigue. This paper investigates the use of a machine learning technique to establish a model for 2800TEU container vessel fatigue assessment. Measurement data from 3 years of cross-Atlantic sailing demonstrated and validated the machine learning model. In this investigation, the ship’s motions were used as inputs to build a machine learning model. The fatigue damage amounts predicted using a machine learning model were compared with those obtained from full-scale measurements and direct fatigue calculation. The pros and cons of the methods are compared in terms of their capability, robustness, and prediction accuracy.
It is common practice today to carry out fatigue assessments of ship structures using direct calculation procedures to compute fatigue loads. Many numerical codes are available for use in such ...fatigue load analyses. In addition to the various degrees of computation complexity associated with fatigue estimation methods, such methods also have large inherent uncertainties. In this investigation, a comparative study was carried out for two container ships using various typical direct fatigue calculation methods. The fatigue damage amounts calculated using these methods were compared with those obtained from full-scale measurements. Most of the direct calculation approaches investigated yielded similar fatigue damage estimates. The approach that employs nonlinear time-domain hydrodynamic analysis and the finite element method yields reasonable and conservative fatigue damage results and is therefore recommended. In addition, the results of this study confirm that various measures of wave environments and of the variation in wave models are important sources of uncertainty in fatigue life prediction.
•We compared five typical methods for fatigue assessment of ship structures.•Two container vessels operating in the North Atlantic were used for case studies.•The numerical results were compared with the full-scale measurements.•We studied various measures of wave environment and the variance in wave models.•The uncertainties and the degrees of computation complexity were discussed.
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