Towards Improved Prediction of Ship Performance: A Comparative Analysis on In-service Ship Monitoring Data for Modeling the Speed-Power Relation

Accurate modeling of ship performance is crucial for the shipping industry to optimize fuel consumption and subsequently reduce emissions. However, predicting the speed-power relation in real-world conditions remains a challenge. In this study, we used in-service monitoring data from multiple vessels with different hull shapes to compare the accuracy of data-driven machine learning (ML) algorithms to traditional methods for assessing ship performance. Our analysis consists of two main parts: (1) a comparison of sea trial curves with calm-water curves fitted on operational data, and (2) a benchmark of multiple added wave resistance theories with an ML-based approach. Our results showed that a simple neural network outperformed established semi-empirical formulas following first principles. The neural network only required operational data as input, while the traditional methods required extensive ship particulars that are often unavailable. These findings suggest that data-driven algorithms may be more effective for predicting ship performance in practical applications.Comment: 15 page

On the importance of antifouling coatings regarding ship resistance and powering

This paper aims to introduce one of the latest investigations on development of marine antifouling coatings and also to demonstrate the importance of the type of antifouling coatings on fouling accumulation and ship resistance/powering. First, marine biofouling and fouling prevention methods are reviewed. A recent research study (EU FP7 FOUL-X-SPEL Project) concerning a novel and environmentally friendly antifouling coating is presented and discussed. Next, a case study is carried out to assess the effect of fouling on ship resistance and powering. A vessel is selected and the roughness on the hull surface induced by different level of fouling is considered. The increase in frictional resistance and effective power is evaluated for each particular case by using boundary layer similarity law analysis and experimental data. The results emphasise that the type of antifouling coatings has a great importance on the amount of fouling accumulation, hence on ship performance especially in low speed

A Validation Study of Full-Scale CFD Simulation for Sea Trial Performance Prediction of Ships

Shipping is a critical component of global trade but also accounts for a substantial portion of global greenhouse gas emissions. Recognising this issue, the International Maritime Organisation (IMO) has implemented new measures aimed at determining the energy efficiency of all ships and promoting continuous improvements, such as the Energy Efficiency Existing Ship Index (EEXI). As Computational Fluid Dynamics (CFD) can be used to calculate the EEXI value, RISE-SSPA1 and Flowtech have developed a CFD-based method for predicting full-scale ship performance with SHIPFLOW v7.0, which meets the new requirements of IMO. The method is validated through an extensive comparison study that examines the delivered power and propeller rotation rate between full-scale CFD predictions and high-quality sea trials using 14 common cargo ships of varying sizes and types. The comparison between the CFD predictions and 59 sea trials shows that both delivered power and RPM can be predicted with satisfactory accuracy, with an average comparison error of about 4% and 2%, respectively. The numerical methods used in this study differ significantly from the majority of the state-of-the-art CFD codes, highlighting their potential for future applications in ship performance prediction. Thorough validation with a large number of sea trials is essential to establish confidence in CFD-based ship performance prediction methods, which is crucial for the credibility of the EEXI framework and its potential to contribute to shipping decarbonisation

An investigation into the development of an advanced ship performance monitoring and analysis system

PhD ThesisThe complete ban on TBT in marine antifouling coatings in 2008, rocketing fuel prices over the past six years, environmental concern and upcoming energy efficiency indices for ships have resulted in a strong interest of the shipping industry to monitor, evaluate and optimise ship performance. Furthermore, the complete ban on TBT in anti-fouling coatings resulted in new types of foul-release hull-coatings, based con silicon, whose effectiveness and performance still needs to be evaluated. Because of the difficulty of measuring coating roughness in service and the large effect of marine bio-fouling on ship performance, a research project was setup at Newcastle University in collaboration with a major paint company to investigate the ways to evaluate hull coating through ship performance monitoring. This thesis describes the details of this project which aimed to investigate the feasibility of a real-time ship performance monitoring and analysis (PM&A) system by implementation and evaluation onboard a 16m research vessel and 300.000dwt VLCC. The thesis starts with a review of the state of art of PM&A systems. The main weaknesses of existing PM&A systems is that often abstract logbook data is used as input and that too little attention is paid to data quality. Furthermore, the systems often act as a black box, showing little insight in data analysis, harming the reliability and trustworthiness of output indicators. Additionally, there are large differences in the way that performance data is corrected to standard conditions, resulting in contradicting and unreliable performance indicators. The thesis focuses therefore on theoretically sound, transparent data analysis and improved data collection. In the thesis, all performance affecting environmental and operational conditions have been reviewed including sensor characteristics and data acquisition aspects. Based on the experience from the analysis of the data collected from both vessels, it reveals that automatic, real-time data collection and rational filtering for periods of acceleration, deceleration, course deviation, drift, shallow water and ship motion is the way forward for accurate performance monitoring. Performance analysis is highly sensitive to errors in shaft torque and ship speed through water. A frequently calibrated/validated shaft torque & RPM sensor and Doppler speed log are therefore the most important sensors for performance monitoring. Speed logs are T.W.F. Hasselaar PhD thesis, 2010 ii affected by many environmental conditions and cannot be used directly for performance monitoring. Other ways to determine ship speed through water, e.g. using the propeller inflow speed, are however affected by hull fouling and loading deviations unless corrected for accordingly. Corrections using full scale trials are then necessary to avoid overestimation of the effects of hull fouling on ship performance. To avoid these errors, a method is described to use the speed log by evaluating its reliability and utilise its reading for performance analysis only in periods where it can be considered reliable. A new transparent analysis method is described to analyse ship performance based on conversion of torque and rpm at constant ship speed. The method differentiates between the hull and propeller performance by empirically correcting the propeller open water diagram for roughness (periodically measured by divers). Evaluation of the proposed PM&A system on both vessels indicates that reliable performance indicatgors can be calculated but that fluctuations in performance indicators of ±12% remain unavoidable due to inaccurate wave observations and errors from the speed log. Trials on the research vessel furthermore show that the system is able to identify fouling, but sensor accuracy requires further research so that fouling can be defined with less performance data and higher reliability. This thesis demonstrates for the first time in open literature that the design and implementation of a transparent and fully automatic, real-time, shipboard PM&A system is perfectly viable and can be installed on any ship with the use of reliable sensors.International Pain

Uncertainties in simulation model for ice loads prediction in level ice with respect to structural reliability

Arctic shipping is increasingly in focus due to the diminishing ice cover due to the effects of climate change. With new shipping routes opening up, navigation in ice-covered waters receives increasing attention in industry and academia. One of the key issues in the design of ice-going vessels is the required plate thickness to withstand the ice loads. Several regulations have been developed, containing formulae for determining the place thickness for different ice classes. On the other hand, various engineering tools have been developed for simulating the ship performance in ice, with several of these tools explicitly aiming to determine the ice loads on the hull. Such tools in principle provide alternative means to determine the safety level of the hull elements based on first-principle modeling. In this report, a risk-based design approach is taken as a starting point for contextualizing the determination of the required plate thickness based on a structural reliability analysis. The focus of the work is to analyze the importance of the uncertainties in the ice loads resulting from a ship performance in ice simulation model, in relation to the structural reliability as calculated based on the simulated ice load time series. The study centered on the influence of the applied empirical parameters in the model design on the predicted ice loads with respect to the long-term safety and reliability analysis of the ship. The various assumptions in the simulation model for ship performance in ice are systematically varied to quantify the uncertainty about the safety index and failure probability of a plate under ice loading. The results showed that the predicted loads from the simulation model lead to some about of uncertainties across the investigated parameters, indicating the limited usefulness of the simulation model in a risk-based design context. The estimated uncertainties were however based on the relative variations of the simulated ice loads and the estimated safety index corresponding to each case studied. With these results, the suspicion for inherent uncertainties in the ice prediction model’s performance associated with the applied parameters was justified. Hence, to obtain better or improved performance from the ice prediction model, the sources of uncertainties should be minimized or eliminated. Also, with the ultimate aim of developing models and tools for risk-based design of ships in Arctic and other ice-covered waters, areas of further research and development in context of the ship performance in ice simulation model are highlighted to reduce the uncertainties

Towards Uncertainty Analysis of CFD Simulation of Ship Responses in Regular Head Waves

Ship hydrodynamic performance prediction in waves is a common practice in the early stages of the ship\ua0design process as the interaction between the ship and waves may adversely affect the hydrodynamic responses of\ua0the ship in comparison to calm water. Various well-established\ua0numerical and experimental methods are often utilized\ua0for prediction of ship performance in waves. Although the model tests are expensive and time consuming,\ua0a\ua0high level of accuracy is often achieved in such experiments. On the other hand, with respect to the increased computational\ua0power, prediction of ship performance in waves by the numerical methods based on Computational Fluid\ua0Dynamics (CFD) techniques are gradually acquiring more popularity. However, the validity of the incorporated\ua0discretization schemes and modelling assumptions in these state-of-the-art\ua0CFD methods are often overlooked and\ua0the method accuracy is mainly assessed through the validation of the results based on the respective model test\ua0data. Validation as an engineering exercise aims to show that the right equations are solved, while verification\ua0(mathematical exercise) is required to demonstrate that equations are solved right [1].\ua0The eventual objective of this research is to perform verification and validation exercises of a ship performance\ua0prediction in regular head waves using CFD, whereas in this paper, the working progress is presented\ua0which may be subjected to significant revisions. To this end, extensive attempts have been made to investigate\ua0numerical wave propagation without the presence of the hull. Ship responses in waves are significantly influenced\ua0by the wave excitation forces. Therefore, not only high level of accuracy is required for the simulation of the numerical\ua0waves, but also quantification of the numerical uncertainties are of a great importance. This becomes even\ua0more challenging when the ship hydrodynamic responses, such as motions and added resistance in waves, exhibit\ua0dependencies on wave steepness. In this paper, the main focus of such uncertainty analyses is on the systematic\ua0grid convergence study

Development of a ship performance model for power estimation of inland waterway vessels

A ship performance model is an important factor in energy-efficient navigation. It formulates a speed–power relationship that can be used to adjust the engine loads for dynamic energy optimisation. However, currently available models have been developed for sea-going vessels, where the environmental conditions are significantly different from those experienced on inland waterways. Inland waterway shipping has great potential to become a mode of transport that can both improve safety and reduce emissions. Therefore, this paper presents the development of an energy performance model specifically for inland waterway vessels (IWVs). The holistic ship energy system model is based on empirical methods, from resistance to engine performance prediction, established in a modular code architecture. The resistance and propulsion prediction in confined waterways are captured by a newly developed method, considering a superposing of shallow water and bank effect. Verification against model tests and high-fidelity simulations indicate that the selected empirical methods achieved good accuracy for predicting ship performance. The resistance prediction error was 5.2% for single vessels and 8% for pusher-barge convoys based on empirical methods. The results of a case study investigating the performance of a self-propelled vessel under dynamic waterway data, indicate that the developed model could be used for onboard power monitoring and energy optimisation during operation

Data-driven Ship Performance Models - - Emphasis on Energy Efficiency and Fatigue Safety

Due to digitalization in the maritime industry, a huge amount of ship operation-related data has been collected. The main objective of this thesis is to exploit machine learning/big data analytics to build data-driven ship performance models, focusing on speed-power relationship modeling, and fatigue accumulation assessment during a ship’s operation at sea.The speed-power performance models are established in three different ways: 1) semi-empirical white-box models, 2) machine learning black-box methods, and 3) physics-informed grey-box models. The white-box models include improved semi-empirical formulas for ship added resistance due to head waves, and further developed formulas in arbitrary wave headings. Validation studies using three case study ships show good agreement between the speed predictions by the white-box models and the long-term averages of full-scale measurements. Different supervised machine learning methods’ capabilities have been compared for black-box modeling. The XGBoost algorithm is found to have the most reliable predictive ability, with the highest efficiency suitable for onboard devices. The novel grey-box models are proposed by considering the physical principles in model tests and big data information from real sailing. It has been demonstrated that the proposed grey-box models can improve prediction accuracy by approximately 30% for ship speed estimation and provides 50% less cumulative error of sailing time than the black-box methods.The impact of voyage optimization-aided operations on the encountered wave conditions and ship fatigue damage is investigated in this thesis. By recommending appropriate routes, voyage optimization can greatly extend the fatigue life of a ship by at least 50%. The machine learning techniques are also applied to a ship’s fatigue assessment. The results indicate that the proposed data-driven fatigue assessment model could increase accuracy by approximately 70% for the case study vessel compared to other prominent spectral methods

Scaling of wetted-transom resistance for improved full-scale ship performance predictions

Determining a ship\u27s propulsive power is a critical stage in the design phase in which the evaluation of the stern plays a crucial role. Different flow regimes can be observed depending on the position and shape of the transom. This paper investigates the wetted-transom flow characteristics and their implications on the 1978 ITTC Performance Prediction Method. In the case of flow separation, such as the wetted-transom flow, the current ITTC-78 procedure does not provide an alternative method. Therefore, two alternative methods were proposed based on the investigations of CFD computations on seven hull forms. The firstly proposed method is a combined EFD&CFD method called the two form factor method. It requires CFD computations in model and full-scale, and it can handle any case of flow separation, including the wetted-transom flow. The second proposed method is an empirical correction formula for the hulls with a wetted-transom flow. Finally, the full-scale speed-power relations between the speed trials and the full-scale predictions from the two alternative methods and the standard ITTC-78 method were presented. It is observed that the two suggested methods considerably improve the correlation between the predictions and the speed trials

PENGARUH FASILITAS DAN SARANA PENUNJANG TERHADAP EFEKTIVITAS KEGIATAN BONGKAR MUAT SERTA DAMPAKNYA TERHADAP PENINGKATAN KINERJA KAPAL DI PT. PELINDO II (PERSERO) CABANG SUNDA KELAPA

Abstract: This study aims to, partially, examine the effect of main and supportingfacilities on the effectiveness of loading and discharging activities and theincreasing of ship performance, the effect of the effectiveness of loading anddischarging activities on ship performance; and simultaneously, examine the effectof main and supporting facilities on the effectiveness of loading and dischargingactivities and ship performance at PT. Pelindo II (Persero) of Sunda KelapaBranch. The increasing of throughput will give a positive impact to the loading andunloading activities and the ship performance in the harbor. This study usedsecondary data sourced from company performance data in 2011- 2015. Datawere analyzed using linear regression. Results showed that, partially, mainfacilities had no significant effect on the effectiveness of loading and dischargingactivities and the ship performance; supporting facilities had a significant effect onthe effectiveness of loading and discharging activities, but had no significant effecton ship performance; the effectiveness of loading and discharging activities had asignificant effect on ship performance. Simultaneously, the main and supportingfacilities have significant effects on the effectiveness of loading and dischargingactivities and the increasing of ship performance.Keywords: Main Facilities, Supporting Facilities, Effectiveness of Unloading andUploading Activity, Ship Performance.Abstrak: Penelitian ini bertujuan untuk, secara parsial, menguji pengaruh fasilitasdan sarana penunjang terhadap efektifitas kegiatan bongkar muat danpeningkatan kinerja kappa, dan pengaruh efektivitas kegiatan bongkar muatterhadap kinerja kapal, serta secara simultan menguji pengaruh fasilitas dansarana penunjang terhadap efektivitas kegiatan bongkar muat dan kinerja kapal diPT. Pelindo II (Persero) Cabang Sunda Kelapa. Penambahan throughput akanberdampak positif pada kegiatan bongkar muat dan kinerja kapal di pelabuhan.Penelitian ini menggunakan data sekunder perusahaan yaitu data kinerja tahun2011- 2015. Metode analisis data yang digunakan adalah analisis linear berganda.Hasil penelitian menunjukkan bahwa secara parsial, fasilitas tidak berpengaruhsignifikan pada efektivitas kegiatan bongkar muat dan kinerja kapal; saranapenunjang berpengaruh signifikan pada efektivitas kegiatan bongkar muat namuntidak berpengaruh signifikan pada kinerja kapal; dan efektivitas kegiatan bongkarmuat berpengaruh signifikan pada kinerja kapal. Secara simultan, fasilitas dansarana penunjang berpengaruh signifikan pada efektivitas kegiatan bongkar muatdan kinerja kapal.Kata Kunci: Fasilitas, Sarana Penunjang, Efektivitas Kegiatan Bongkar Muat,Kinerja Kapa