Ship Power Research Articles

A Distance-Field-Based Pipe-Routing Method.

Pipes are commonly used to transport fuels, air, water, gas, hydraulic power, and other fluid-like materials in engine rooms, houses, factories, airplanes, and ships. Thus, pipe routing is essential in many industrial applications, including ship construction, machinery manufacturing, house building, laying out engine rooms, etc. To be functional, a pipe system should be economical while satisfying spatial constraints and safety regulations. Numerous routing algorithms have been published to optimize the pipe length and the number of elbows. However, relatively few methods have been designed to lay out pipes which strictly meet the spatial constraints and safety regulations. This article proposes a distance-field-based piping algorithm to remedy this problem. The proposed method converts the workspace into a 3D image and computes a distance field upon the workspace first. It then creates a feasible space out of the workspace by peeling the distance field and segmenting the 3D image. The resultant feasible space is collision-free and satisfies the spatial constraints and safety regulations. In the following step, a path-finding process, subjected to a cost function, is triggered to arrange the pipe inside the feasible space. Consequently, the cost of the pipe is optimized, and the pipe path rigidly meets the spatial constraints and safety regulations. The proposed method works effectively even if the workspace is narrow and complicated. In three experiments, the proposed method is employed to lay out pipes inside an underwater vehicle, a machinery room, and a two-story house, respectively. Not only do the resultant pipes possess minimal costs, but they also meet the spatial constraints and safety regulations, as predicted. In addition to developing the routing procedure, we also design a visualization subsystem to reveal the progression of the piping process and the variation of the workspace in the run time. Based on the displayed images, users can therefore evaluate the quality of the pipes on the fly and tune the piping parameters if necessary.

An efficient and accurate approach for zero-frequency added mass for maneuvering simulations in deep and shallow water

An overall increase in ship sizes in conjunction with a general decrease in ship powering has increased the relevance of reliably predicting a ship’s maneuvering performance. These predictions rely often on mathematical models based on modified Taylor series expansion, where nonlinear multivariate algebraic polynomials that require hydrodynamic coefficients are determined from physical or numerical planar motion mechanism (PMM) tests. The added mass coefficients are needed for a fast and accurate simulation. For maneuvering simulations, these added mass coefficients should be obtained for zero frequency. Despite the advance of high-performance computing, numerical PMM tests based on solving the unsteady Reynolds-averaged Navier–Stokes equations is time-consuming and often not suitable for practical design-related investigations. Furthermore, hydrodynamic coefficients obtained from PMM tests are frequency-dependent. An alternative to numerical PMM tests consists of steady numerical tests. This kind of analysis requires much less computing time and effort for the users. However, the acceleration-dependent hydrodynamic forces and moments cannot be derived from these steady computations. Here we introduced a fast and accurate procedure to obtain water depth-dependent zero-frequency added mass and added moment of inertia. Using Euler Equations, we impulsively accelerated the ship hull over only one time step. We validated our method against an analytical solution for an ellipsoid. We performed systematic computations of added mass and added moment of inertia for two benchmark containerships, a benchmark tanker, and a cruise ship, thereby demonstrating the effects of water depth on added mass for different hull shapes.

A new method for optimal ship design in real sea states using the ship power profile

Typically, ships are designed for calm water and a constant design speed. However, a ship experiences different speeds and sea conditions over her lifetime. Following the significant correlations between environment and ship behavior at sea, efforts are needed to design energy-efficient and safe ships with good performances in realistic sea conditions. This article proposes a method for optimization of the design of a ship with respect to different levels of propulsive power and different operational conditions using a probabilistic approach. The objective of the optimization is the average ship speed, averaged over all propulsion power and environmental condition combinations based on a long-term analysis. The proposed approach is tested on a Post-Panamax container ship operating in the route from Busan to Hamburg port. The decision variables are the ship and propeller main dimensions. Comparisons with traditional methods used in ship design are also presented. Comparing the proposed method with the traditional methods indicates that 7.89% increase in average ship speed is obtained, demonstrating that the proposed method is effective in designing better ships for actual sea states. Better performance in rough sea for the ship designed with the proposed method is also reported.

Fault diagnosis of ship power equipment based on adaptive neural network

Abstract In recent decades, international shipping trade has been developing continuously. The ship is the main transportation carrier of international shipping, and the power equipment on the ship is in an absolutely critical position, and its working condition is also directly related to the safe running of the ship. Therefore, the research on the ship’s power plant and fault diagnosis system is particularly important. Due to the actual operation of the ship power plant, the characteristics of the components are inevitably changed. Therefore, the corresponding equipment fault diagnosis technology also has a certain importance for the health management system of power equipment. As for the problem that the current ship equipment fault identification method is not widely applicable and the accuracy is not high enough, this paper aims to make the ship fault diagnosis faster and more accurately. It effectively solves the problem of timeliness and accuracy of fault diagnosis. This paper takes ship power equipment as the research object, firstly, introduces and proposes a diagnosis method of adaptive neural network structure, and applies it to fault detection and estimation. Next, this paper uses the adaptive neural network model for ship fault diagnosis. The accuracy of the adaptive neural network designed in this paper is better than that of the conventional neural network, and when the number of training samples is small. It can still obtain an ideal network through training to ensure that the fault detection of power equipment health parameters has high accuracy. The simulation results show that, compared with the common methods, the network model can effectively reduce the fault diagnosis error. The correct rate of fault diagnosis is over 93%, which improves the speed, accuracy, and applicability of fault diagnosis.

OPERATIONAL IDENTIFICATION OF THE SHIP’S POWER PLANT TECHNICAL CONDITION FOR SOLVING PROBLEMS OF PREVENTIVE MANAGEMENT

Possible approaches to solving the problem of operational identification of the technical condition of ship power plants are considered. It is shown that the means of technical diagnostics used on modern ships are intended only for effective maintenance and repair of power equipment and they are not adapted for timely provision of information on the technical condition of the ship’s power plant necessary to ensure preventive management in abnormal operating modes. The definition of operational identification of the technical condition as a process of technical diagnostics of a ship’s power plant for the purposes of preventive and emergency management of its technical condition is given. The provision is substantiated that the means of technical diagnostics should not only identify the inoperable state of the elements of the ship’s power plant, but also predict its functioning mode after the shutdown of the inoperable generator unit and provide information to the warning control equipment about the necessary adjustment of external conditions to ensure its trouble-free transition to a partially operational state. It is shown that, unlike existing diagnostic tools, the goal-setting of operational identification of the technical condition of a ship’s power plant dictates the need to take into account such an important factor as the rate of the controlled parameter change, to determine the probable time for this factor to reach its maximum permissible value. The necessity of mandatory identification of inoperable elements of a ship’s power plant and the implementation of control actions aimed at eliminating an emergency situation until the overload of operable units and disabling them by means of protection is substantiated. It is established that the information obtained as a result of identification will allow the decision-making preparation system to formulate recommendations to the maintenance personnel and the preventive protection system about the necessary impacts on the ship’s power plant in order to exclude emergency situations. The main reasons for the overload of the ship’s power supply system are analyzed, algorithms for the practical solution of the problem of operational identification of the technical condition of the ship’s power plant for cases related to the overload of serviceable machines due to the shutdown of inoperable units are developed.

Data-Driven Efficiency Modeling and Analysis of All-Electric Ship Powertrain: A Comparison of Power System Architectures

In this article, a data-driven dynamic efficiency model is developed for efficiency evaluation and comparison of ship electric powertrain with various system configurations. Based on the proposed method, the entire powertrain efficiency is assessed from the fuel consumption to the propulsion unit and the rest of the onboard load. The efficiency model is repeated for the conventional diesel electric and the hybrid power system with batteries. In the latter case, the efficiency of the battery system is also included in the model. Then, the analysis is extended for different power system architectures such as AC and DC onboard power systems. As a case study, system efficiency in a cruise ship is investigated using a real operational profile. A comprehensive analysis is performed to demonstrate the loss distribution in each subsystem of a hybrid AC and DC power system. For a fair comparison between AC and DC, the battery charge level is equalized based on fuel compensation. The case study shows that hybridizing the ship power system increases system efficiency and enhances operational flexibility for the studied use case vessel. Furthermore, the DC hybrid power system can improve the efficiency of the whole ship powertrain due to the variable-speed operation of engines.

Electric Power Integration Schemes of the Hybrid Fuel Cells and Batteries-Fed Marine Vessels—An Overview

Transportation electrification is undergoing a significant transition toward the utilization of efficient and reliable energy sources and smart integration schemes, where this transitioning is continuously facing ever-tightening challenges in order to comply with the increased environmental regulations. Among the different means of transportation, global maritime transport is responsible for 2%–3% of global greenhouse gas (GHG) emissions, and it is predicted to increase to 17% by 2050 if no changes are adapted. Hence, the international maritime organization (IMO) has targeted to reach a 50% reduction in GHG emissions by 2050 compared to 2008. Hence, alternative energy sources shall be utilized in order to meet these strict GHG emissions reduction targets, where battery- and hydrogen-fed fuel cells can play a vital role in such aspects. Since the output of these two energy sources is unregulated dc voltage, their connection to the whole ship power system can be accomplished in several ways, where each way has its features, in addition to utilizing different power conditioning stages (PCSs), and these features are not well clarified and compared in the literature. Hence, this article presents an overview of the possible integration schemes that can be utilized in fuel cell- and battery-fed vessels, which is supported with a comparative assessment. This is also presented along with highlighting the state-of-the-art PCSs that are available in the market and can be utilized in these integration schemes within marine vessels. Such overview and comparative assessment are seen to be of significant importance and added value for researchers and developers in both the academic and industrial sides in order to accelerate the adoption of fuel cells in marine systems for zero-emission shipping.

Разработка модели переходных процессов в трансформаторе при емкостном характере нагрузки

Voltage transformers with capacitive loading during transients can cause significant distortion of the secondary voltage of the ship's network. For the analysis, a well-known nonlinear model of a single-phase two-winding transformer is used, in which the magnetic flux is divided into “working” and leakage fluxes coupled to individual windings that close outside the core. For practical purposes, when using such transformers, it is important to know both the conditions for the occurrence of autoparametric oscillations and the dynamics of the transient process. It is convenient to carry out a comparative evaluation of capacitive power take-off schemes on a computer, which makes it possible to reproduce non-linear characteristics and vary parameters over a wide range, which is difficult in physical modeling. The results of the study of a short circuit downstream of the reactor in the capacitor selection circuit proved that the short circuit at the terminals of the intermediate transformer does not affect the elements of the upper arm of the voltage divider, but significantly affects the lower arm of the divider and the compensating reactor, as a result, subharmonics appear. It is shown that the developed model is convenient for studying the influence of transient processes (short circuits) on the elements of a voltage divider. The applied model is universal for ship power networks and can be used for both capacitive and inductive dividers. A divider circuit with specific parameters has been modeled and relevant studies have been carried out. Mathematical results are verified on a physical model, which confirmed the correctness of the mathematical model. It has been inferred that a decrease in the phase voltage leads to a decrease in the overvoltage on the divider elements during a short circuit behind the compensating reactor of the power take-off circuit.

Adaptive bus‐voltage control of ship power system with online fluctuation prediction

To ensure the power quality of a ship power system under disturbances due to changing sea states, an adaptive bus-voltage controller with online load power fluctuation prediction is proposed to stabilize the ship bus voltage. The controller uses an online sequence extreme learning machine to update the output weight matrix and achieve an accurate online prediction of the ship load power fluctuations under the disturbance of random uncertainties. A stable additional control signal is provided to the bus-voltage controller for adaptive operation. The prediction results are used to optimize the coordinated control of multiple generation systems and improve the bus-voltage control performance by updating the droop control coefficients online. The adaptability provided by the online prediction algorithm and the performance of the bus-voltage control are verified using recorded voyage data of an offshore marine engineering transport vessel.

Prediction of the Ultra-Large Container Ships' Propulsion Power at the Initial Design Stage

Container ships represent the fastest growing segment of maritime transport. The need to reduce unit transportation costs and environmental impact has led to development of the most capacious ultra-large container ships operating on the world's major shipping routes. A representative database of ultra-large container ships was created and further subdivided according to the main technical parameters. Using a simple cubic regression model, based on the least squares method, an equation, compliant to the general propeller law, was developed to predict the propulsion power of ultra-large container ships as a function of their sailing speed. The results obtained using the developed equation should be sufficiently close to the results of the exact verification calculations at the technical design stage. Then this prediction would find application in the design of both main propulsion, as well as waste heat and cold recovery systems.

Испытания, проверки и диагностическое обеспечение судовых силовых трансформаторов среднего напряжения

Object and purpose of research. The study deals with the diagnostic Issues of ship MV transformers from factory acceptance tests to harbor trials. The purpose is to analyse the requirements and advanced diagnostic tools for status monitoring of ship power transformers, as well as to overview the Issues of electrodynamic withstand checks on transformers. Materials and methods. Stages (operations) are considered that ship power transformers undergo from the stage of factory acceptance tests to harbor trials. Requirements of ship transformers are analyzed. Foreign and Russian tools to check and measure power transformer parameters in industry as well as requirements for electrodynamic withstand testing are compared. Main results. It is shown that in view of high operational risks associated with accidents and failures of onboard transformers it is not enough to check transformer characteristics after transportation or storage (prior to onboard installation) for ensuring their high reliability. Functional analysis of foreign and Russian diagnostic instruments is presented, and vectors for improvement of the Russian tools are defined for the interest of shipbuilding industry. It is shown that the electric withstand tests are particularly important when new designs and technologies are used where reliable verification is impossible neither through calculations nor through modeling, while large safety margins are economically not viable. Conclusion. If some power units in the electric propulsion system (EPS) fail, extra costs would be spent on docking the vessel, dismounting of good equipment and hull structures to remove out-of-order equipment. Regulatory documenttation does not specify the scope of EPS components’ checkup after transportation or storage. Technical measures to ensure reliability of EPS elements include diagnostics of EPS elements prior to their installation on board the ship and during commissioning trials. Diagnostic tools of foreign make have more functional capabilities as compared to Russian instruments. Choice of specific devices and decisions to go for extra costs to further develop the Russian instruments should be based on feasibility studies. New regulations are required for testing rectifier transformers for electrodynamic withstand at short-circuit fault, as well as development and modernization of regional inter-industry shock test facilities.

Combined machine learning and physics-based models for estimating fuel consumption of cargo ships

The International Maritime Organization (IMO) has enforced stricter limits on the Greenhouse Gas (GHG) emission due to environment and climate concerns. Many measures have emerged to reduce GHG emission from shipping. However, the effectiveness and applicability of any measure depend on ship type, ship size, operational mode and the operating ocean environment. Estimation of ship fuel consumption and emission in actual shipping scenarios are fundamental input to evaluate the impacts of shipping on the environment and climate, and to evaluate the effect of new measures to reduce GHG emission. A model for estimating ship fuel consumption and emission, based on ship hydrodynamical models and machine learning techniques, utilizing information from Automatic Identification System (AIS), the ship information database and metocean data is presented in this paper. The model is able to estimate the ship fuel consumption at high computational speed by utilizing machine learning (ML) technology, to evaluate the effect of new measures to reduce GHG emission. The power consumption calculated by the combined model is compared with measurement data from two container ships and two bulk carriers for validation. This validation shows that the model can predict ship power consumption well.

Two-level model predictive control energy management strategy for hybrid power ships with hybrid energy storage system

Compared with the load power characteristics of ground power systems, the intermittent and random fluctuation of ship load power demand brings challenges to the energy management system of ship power systems. To achieve fuel economy and solve the problem of power fluctuation, the hybrid energy storage system (HESS) composed of the battery pack and ultra-capacitor is applied to the diesel-electric hybrid ship. A two-level model predictive control (MPC) strategy consisting of two optimization stages is proposed. The first stage aims to determine the power distribution solution of the diesel generator and battery at a large time-scale. In the second stage, the operation strategy of the ultracapacitor is determined at a small time-scale based on the power distribution solution of the first stage. The conventional MPC-based strategy and global optimization strategy based on dynamic programming (DP) are compared with the proposed strategy. The simulation results show that the proposed strategy has better fuel saving ability, and realizes the clear power frequency division between the supercapacitor and battery. In addition, the proposed strategy can also approach the performance of global optimization.

Application and Development of Selective Catalytic Reduction Technology for Marine Low-Speed Diesel Engine: Trade-Off among High Sulfur Fuel, High Thermal Efficiency, and Low Pollution Emission

In recent years, the International Maritime Organization (IMO), Europe, and the United States and other countries have set up different emission control areas (ECA) for ship exhaust pollutants to enforce more stringent pollutant emission regulations. In order to meet the current IMO Tier III emission regulations, an after-treatment device must be installed in the exhaust system of the ship power plant to reduce the ship NOx emissions. At present, selective catalytic reduction technology (SCR) is one of the main technical routes to resolve excess NOx emissions of marine diesel engines, and is the only NOx emission reduction technology recognized by the IMO that can be used for various ship engines. Compared with the conventional low-pressure SCR system, the high-pressure SCR system can be applied to low-speed marine diesel engines that burn inferior fuels, but its working conditions are relatively harsh, and it can be susceptible to operational problems such as sulfuric acid corrosion, salt blockage, and switching delay during the actual ship tests and ship applications. Therefore, it is necessary to improve the design method and matching strategy of the high-pressure SCR system to achieve a more efficient and reliable operation. This article summarizes the technical characteristics and application problems of marine diesel engine SCR systems in detail, tracks the development trend of the catalytic reaction mechanism, engine tuning, and control strategy under high sulfur exhaust gas conditions. Results showed that low temperature is an important reason for the formation of ammonium nitrate, ammonium sulfate, and other deposits. Additionally, the formed deposits will directly affect the working performance of the SCR systems. The development of SCR technology for marine low-speed engines should be the compromise solution under the requirements of high sulfur fuel, high thermal efficiency, and low pollution emissions. Under the dual restrictions of high sulfur fuel and low exhaust temperature, the low-speed diesel engine SCR systems will inevitably sacrifice part of the engine economy to obtain higher denitrification efficiency and operational reliability.

Food Aid Cargo Preference: Impacts on the Efficiency and Effectiveness of Emergency Food Aid Programs

This paper examines the impact of cargo preference requirements, which create market power for US-flagged ships, on the effectiveness of the Food for Peace emergency food aid program of the US Agency for International Development (USAID). We find that cargo preference requirements increase real ocean transportation costs per metric ton by 68 percent for packaged-goods shipments and 101 percent for bulk-commodity shipments. These differences in cost impacts appear to be associated with differences in the impacts of the mandate on market concentration in the packaged-goods and bulk-commodity shipment markets. These higher costs reduce USAID’s capacity to serve millions of families each year.

Parametric investigation and optimal selection of the hybrid turbocharger system for a large marine four-stroke dual-fuel engine

• Thermodynamic modelling of large marine dual fuel engine with hybrid turbocharger. • Parametric investigation to identify influence on the engine performance and emissions. • Hybrid turbocharger rated power optimal selection for the considered annual profile. • Installation of a hybrid turbocharger leads to 2–4% surplus energy production. Hybrid turbochargers can become an attractive solution for new built and retrofitted ship power plants, as their use can result in increasing the plant efficiency and reducing emissions. This study aims at computationally investigating the hybrid turbocharger effects on a large marine dual-fuel four-stroke engine performance and emissions characteristics as well as determining its electrical generator optimal size for the case of a ship power plant considering an actual operating profile. An existing model of a large marine four-stroke dual-fuel engine of the zero/one-dimensional type, which was developed in the commercial software GT-Power, is extended to include the hybrid turbocharger sub-model. This model is subsequently employed to carry out a parametric investigation considering a wide range for the hybrid turbocharger electric motor power. The derived results are analysed to identify the variations of the investigated dual fuel engine performance and emissions parameters in the whole engine operating envelope at both the diesel and gas modes, whilst taking into account the engine and its components operational limits. For the considered annual load profile, the results demonstrate that the optimal nominal size of the hybrid turbocharger electric motor power is 300 kW and leads to an annual energy surplus between 2% and 3% of the annually delivered engine mechanical energy. This study benefits the quantification of the hybrid turbocharger impact on large marine dual fuel four-stroke engines as well as the ship energy efficiency, thus providing useful decision support to facilitate the shipboard implementation of this technology.

Holistic Energy Efficiency and Environmental Friendliness Model for Short-Sea Vessels with Alternative Power Systems Considering Realistic Fuel Pathways and Workloads

Energy requirements push the shipping industry towards more energy-efficient ships, while environmental regulations influence the development of environmentally friendly ships by replacing fossil fuels with alternatives. Current mathematical models for ship energy efficiency, which set the analysis boundaries at the level of the ship power system, are not able to consider alternative fuels as a powering option. In this paper, the energy efficiency and emissions index are formulated for ships with alternative power systems, considering three different impacts on the environment (global warming, acidification, and eutrophication) and realistic fuel pathways and workloads. Besides diesel, applications of alternative powering options such as electricity, methanol, liquefied natural gas, hydrogen, and ammonia are considered. By extending the analysis boundaries from the ship power system to the complete fuel cycle, it is possible to compare different ships within the considered fleet, or a whole shipping sector, from the viewpoint of energy efficiency and environmental friendliness. The applicability of the model is illustrated on the Croatian ro-ro passenger fleet. A technical measure of implementation of alternative fuels in combination with an operational measure of speed reduction results in an even greater emissions reduction and an increase in energy efficiency. Analysis of the impact of voluntary speed reduction for ships with different power systems resulted in the identification of the optimal combination of alternative fuel and speed reduction by a specific percentage from the ship design speed.

Analysis of double-layer vibration isolation characteristics of ship power equipment

The vibration isolation device of ship power equipment is the key equipment to protect it from damage, and its performance determines whether the ship can sail safely. To address the problem that it is difficult to achieve the optimal vibration isolation performance of ship’s double-layer vibration isolation, this paper establishes a vibration transmission theory model of ship’s power equipment double-layer vibration isolation system, derives the vibration displacement transmission rate formula based on the model, and studies the influence law of the stiffness ratio of the lower and upper layers of vibration isolation devices, the mass ratio of the intermediate raft frame to the power equipment and the damping of the upper and lower layers of vibration isolation devices on the vibration transmission. The results show that reducing the stiffness ratio of upper and lower layer vibration isolators and increasing the mass ratio of intermediate raft frame and power equipment can reduce the two resonant frequencies and narrow the interval between the two resonant frequencies, and increasing the damping of upper and lower layer vibration isolators can reduce the vibration peak at the two resonant frequencies, but the vibration isolation effect in the high frequency band becomes worse. It provides a theoretical basis for the design optimization of the double-layer vibration isolation system for ship's power equipment.

Fault diagnosis of ship power station based on LSTM neural network algorithm

Ship power station is an important part of the ship, and the fault types of ship power station are complex. In this paper, Simulink software platform is used to simulate and model various short-circuit faults of ship power station. The current and voltage parameters of each phase are selected as the source of the data set, and the data are processed and the prediction image is plotted in MATLAB. LSTM neural network algorithm solves the problem of long-term dependence compared with other algorithms, and has a high degree of interpretation of the predicted data. The results show that the fault diagnosis model based on LSTM neural network algorithm can well diagnose the fault mode of ship power station.

Regression Modelling Estimation of Marine Diesel Generator Fuel Consumption and Emissions

This study aims to estimate the fuel consumption of marine diesel generators onboard. Objective technical specifications and operational data on the ship's power generating plants and port calls were collected from an oceangoing oil/chemical tanker and used to develop the mathematical model of the plant in the Python and MATLAB environment. The model consists of alternators, prime movers and load distributions of the ship’s power generating plant and provides information on fuel consumption in metric tons calculated based on hours of operation and specific fuel consumption data. Regression models have helped predict future fuel consumption for the plant and the optimal model for the dataset was identified by comparing four different algorithms. As the results have shown the Ordinary Least Squares Regression to be optimum, it was used to make one, five, and ten-year predictions. The predictions for one-year, five-year, and ten-year periods are 4,322,436, 10,684,860, and 18,615,472 t respectively. The selected model predicts fuel consumption with R2 of 0.999, MAE of 3.932, and RMSE of 2.935. Fuel consumption predictions facilitated plant emission calculation.