The importance of the engine-propeller model accuracy on the performance prediction of a marine propulsion system in the presence of waves
Introduction
Ship transportation is the backbone of the global economy and the international market. Around 80 per cent of the global trade volume and over 70 per cent of the world trade value are carried by sea and are handled by ports worldwide (Hoffmann et al., 2018). On the other hand, the shipping sector is responsible for the annual emission of around 2.5 per cent of global greenhouse gases (GHGs) and about 940 million tonnes of CO2 (Smith et al., 2015).
Countermeasures against the environmental pollution from ships resulted in new mandatory regulations such as the Initial IMO (International Maritime Organization) Strategy on Reduction of GHG Emissions from Ships and the Energy Efficiency Design Index (EEDI). The former was brought into effect in April 2018 by the International Maritime Organization’s Marine Environment Protection Committee (MEPC) to reduce ship emissions and to improve the environmental performance of new and existing vessels. According to the strategy, the total annual global greenhouse gas emissions have to be reduced by at least 50 per cent by 2050 compared to 2008. The latter was introduced in July 2011 by the IMO for the prevention of air pollution from new vessels. The lower the EEDI, the more energy-efficient is the ship, and the higher its environmental performance. The EEDI formulation encourages the power reduction of the main engine and slow steaming.
These mandatory regulations drew attention to both the estimation of ship performances in waves and the implementation of alternative marine fuels. Liquefied natural gas could be a valid option for the latter. The combustion products for lean burn gas engines contain 25 per cent lower CO2 and 85 per cent lower NOx emission values than a marine diesel oil or marine gas oil (Chorowski et al., 2015). It is estimated that the proportion of liquefied natural gas in the global marine fleet will rise from the current 0.3 per cent to over 23 per cent by 2050 (Asariotis et al., 2019). The estimation of ship performances in waves is crucial for two reasons. First, the evaluation of the added resistance caused by waves plays a significant role in the reduction of the main engine size. Second, the presence of waves changes the engine operating point and, as a consequence, modifies the ship emissions. Nevertheless, ships are generally not optimally efficient in realistic sea states. Marine propulsion plants are typically optimized in ideal conditions where the presence of waves is taken care of by adding a margin to the estimation of the speed-power relationship for a newly built ship in trial conditions. Therefore, it is expected that more energy-efficient ships can be designed if the effect of waves on the propulsion plant is taken into account during the optimization phase.
The effect of waves on the ship propulsion system is a complex physical process resulting from the interaction between the sea environment, vessel performance, and propeller-shaft-engine response. In particular, in case of severe weather conditions, the propeller might come out of the water, causing a drop in the engine torque and, eventually, a drastic increase of propeller rate of revolutions accompanied by intense vibrations. For marine diesel engines, the increased resistance induced by waves might generate what is known as the torque-rich effect. This phenomenon causes the reduction of ship speed, overloading for the main engine, higher fuel consumption, and can lead to the failure of the ship propulsion system (Van Uy, 2016). Therefore, studying the hull-propeller-shaft-engine interaction in realistic conditions is crucial to get a better insight into the overall propulsion system response and to estimate the required engine size accurately.
Full-scale testing is the most accurate method to understand how ship performances are affected by propeller-shaft-engine dynamics. An example of such investigation was carried out by Ogawara et al. (1972), where the dynamic performances of the propulsion system of a container ship were studied. However, full-scale experiments are expensive, time-consuming, and difficult to setup. Numerical computations are a valid alternative, at least in the early phases of the ship propulsion design process. Kyrtatos et al. (1999) predicted the transient response of a large two-stroke marine diesel engine subjected to fluctuating loads obtained from either model tests or the standard propeller law. The main engine was coupled with appended models for the shaft, propeller, ship hull, and the engine speed governor. They demonstrated the overall model reliability to predict the dynamic response of a complete marine power plant system. Campora and Figari (2003) modeled a propulsion plant of a twin shaft arrangement with a controllable-pitch propeller in a MATLAB-SIMULINK environment. The ship propulsion model consisted of separate blocks for the medium-speed diesel engine, governor, hull, controllable-pitch propeller, telegraph, and shaft line. The propeller model was based on either the propeller open water curves or measurements. Taskar et al. (2016) investigated the effect of waves on the propulsion system of the KVLCC2 tanker along with a method to estimate the propeller wake field in waves. A large two-stroke marine diesel engine model was coupled with the open water data of the KVLCC2 propeller using an inertial shaft model in a MATLAB-SIMULINK environment. The thrust and torque losses due to the propeller emergence were also investigated. This research demonstrated the importance of studying ship performances in waves by utilizing an engine-propeller coupled model. Yum et al. (2017) developed a simulation model of a mechanical propulsion system in waves for the KVLCC2 tanker. The propulsion system included the vessel hull, mechanical shaft, large two-stroke diesel engine, and speed regulator. The shaft was modeled as a single rigid-body with friction, and open water data were used for the propeller model. Simulation results provided a better understanding of the effect of waves on ship performances.
The main goal of this study is to determine the importance of the time-varying wake field, ship motions, propeller emergence and engine response to predict the performance in waves of a marine propulsion system. This is achieved by modelling the propulsion system at three different levels of complexity. The three implementations of the same propulsion system model (steady, unsteady with fixed engine speed, and unsteady with variable engine speed) are compared in terms of estimated engine torque, propeller efficiency, and computation performance. The considered propulsion system is powered by a medium-speed four-stroke natural gas engine with a controllable-pitch propeller. The DTU-developed unsteady low-order boundary-element method ESPPRO (Regener, 2016) is implemented in inhomogeneous inflow for the propeller model. The GT-POWER Engine Simulation Software (Gamma Technologies, 2019a) is used for the engine modelling. The overall propulsion plant model is developed in the MATLAB-SIMULINK co-simulation environment.
Section snippets
Case vessel
A full-scale LNG powered vessel is utilized in the present study. The main specifications of the ship, propeller characteristics and engine specifications are shown respectively in Table 1, 2, and 3.
Propulsion system model
The MATLAB-SIMULINK co-simulation environment with a fixed-step solver is utilized to design the overall propulsion system model. The data exchange between subsystem blocks is limited to time-discrete communication points. The subsystems are solved separately and independently from each other. The exchanged data between blocks are extrapolated based on the information from the previous time-discrete communication points.
Fig. 1 shows the block diagram of the coupled system. Five main subsystem
Method
The propulsion system performance in waves is usually estimated by avoiding the complexity of creating a unique propulsion system model. Generally, the presence of the engine is neglected, and the propeller performances are computed by ignoring ship motions, propeller emergence, and time-varying propeller speed and wake field. Taskar et al. (2016) showed that these assumptions are not sufficient to study the effect of waves on the propulsion system of the KVLCC2 tanker powered by a large
Comparison 1: Model 1 vs Model 2
This comparison is necessary to understand the effect of the time-varying wake field, ship motions, and propeller emergence on the prediction of the propulsion system performance in waves.
The time-varying wake field creates fluctuating engine loads, which may differ considerably from the time-invariant engine torque estimated in steady conditions. Ship motions cause the propeller depth to change in time, which may lead to a drop in engine torque if the propeller is in proximity or above the
Conclusions
The performance of a propulsion system powered by a medium-speed four-stroke LNG engine with a controllable-pitch propeller was computed. This was performed by modelling the marine propulsion system at three different levels of complexity. The three implementations of the same propulsion system model (steady, unsteady with fixed engine speed, and unsteady with PID control system) were compared in terms of estimated engine torque and speed and propeller efficiency. This was necessary to
CRediT authorship contribution statement
Simone Saettone: Conceptualization, Methodology, Software, Formal analysis, Writing - original draft, Writing - review & editing, Visualization. Sadi Tavakoli: Conceptualization, Methodology, Software, Writing - original draft. Bhushan Taskar: Conceptualization, Methodology, Writing - review & editing. Michael Vincent Jensen: Conceptualization, Writing - review & editing. Eilif Pedersen: Conceptualization, Supervision, Project administration. Jesper Schramm: Conceptualization, Supervision,
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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