Ship Propulsion Plant Performance Assessment Using An Artificial Neural Network

Nowadays, more than in the past, the attention towards the environmental impact of shipping has gained great interest. In particular, several international rules were issued to set new standards in terms of ship energy efficiency and emissions. Most of the actual worldwide fleets are not compliant with the new standards, and it is unthinkable that ship-owners will replace the existing ships with new buildings in a short time. According to this, the retrofit of either the propulsion plant or auxiliary system is the good compromise choice. The first task that the designer has to face is the evaluation of the actual propulsion plant performance to detect where to act. On the view of this, the authors present two different approaches to identify the performance of an existing ship propulsion plant equipped with a four-stroke diesel engine and a controllable pitch propeller. The first approach is the standard approach, relying on the static performance assessment of the required power and fuel consumption, starting from the design data of the hull and machinery, not always available several years past ship fabrication. The second approach is based on the application of an artificial neural network, trained using the results of sea trials. Ship speed, shaft revolution speed, pitch angle, engine torque and fuel consumption have been recorded, then part of the data have been used as a training set for the artificial neural network, and the remaining as a validation set to compare the two approaches. The main idea is to evaluate the best strategy, in term of developing time and accuracy, to obtain the global, even if static, evaluation of the propulsion plant performance, with the final aim to have a handy tool to be used to assess potential energy saving solutions. Eventually, a comparison between the two methodologies and sea trials is shown and critically discussed

ENERGY EFFICIENT SHIP VOYAGE PLANNING BY 3D DYNAMIC PROGRAMMING

Energy efficiency is a crucial issue in ship management and operation. A proper fuel saving oriented routing strategy can be helpful in reducing running costs and pollutant emissions, as well as increasing the voyage safety and comfort. This paper presents a methodology for ship voyage planning based on 3D dynamic programming. It aims to select the optimum courses and related speed profile for a ship voyage in accordance to a minimum fuel consumption strategy, on the basis of the ship response to wave and wind conditions inferred from weather forecast maps. The ship voyage is parametrized as a multi-stage decision process where the fuel optimization is carried out in a discretized space-time domain and the optimal solution, in relation to the arrival time requirements and motion related constraints, is found by a dynamic programming algorithm which has been developed and implemented by the authors. Simulation trials for a merchant ship sailing different typical routes in the Mediterranean Sea, in a wide range of weather conditions and using high quality weather forecast maps, are presented and discussed. With respect to previous authors\u2019 publications, the presented methodology shows the high potential benefit of detailed weather forecast maps as well as the innovative use of a minimum distance algorithm

Marine gas turbine monitoring and diagnostics by simulation and pattern recognition

Several techniques have been developed in the last years for energy conversion and aeronautic propulsion plants monitoring and diagnostics, to ensure non-stop availability and safety, mainly based on machine learning and pattern recognition methods, which need large databases of measures. This paper aims to describe a simulation based monitoring and diagnostic method to overcome the lack of data. An application on a gas turbine powered frigate is shown. A MATLAB-SIMULINK\uae model of the frigate propulsion system has been used to generate a database of different faulty conditions of the plant. A monitoring and diagnostic system, based on Mahalanobis distance and artificial neural networks have been developed. Experimental data measured during the sea trials have been used for model calibration and validation. Test runs of the procedure have been carried out in a number of simulated degradation cases: in all the considered cases, malfunctions have been successfully detected by the developed model

Simulation Techniques for Design and Control of a Waste Heat Recovery System in Marine Natural Gas Propulsion Applications

Waste Heat Recovery (WHR) marine systems represent a valid solution for the ship energy eciency improvement, especially in Liquefied Natural Gas (LNG) propulsion applications. Compared to traditional diesel fuel oil, a better thermal power can be recovered from the exhaust gas produced by a LNG-fueled engine. Therefore, steam surplus production may be used to feed a turbogenerator in order to increase the ship electric energy availability without additional fuel consumption. However, a correct design procedure of the WHR steam plant is fundamental for proper feasibility analysis, and from this point of view, numerical simulation techniques can be a very powerful tool. In this work, the WHR steam plant modeling is presented paying attention to the simulation approach developed for the steam turbine and its governor dynamics. Starting from a nonlinear system representing the whole dynamic behavior, the turbogenerator model is linearized to carry out a proper synthesis analysis of the controller, in order to comply with specific performance requirements of the power grid. For the considered case study, simulation results confirm the validity of the developed approach, aimed to test the correct design of the whole system in proper working dynamic conditions

Optimal Management of a Diesel-Electric Propulsion Plant with Either Constant or Variable Diesel Generators Speed

In recent years, diesel-electric propulsion has become a standard for many ship types. The traditional way to manage the electric flow onboard is by using AC distribution, and to run diesel generators at constant rotational speed to get the correct distribution frequency and to limit the weight and the size of the electric machinery. More recently, the current progress in DC field allowed exploiting the advantages of this technology, for instance, greater flexibility in the mode of operation of diesel generators in terms of rotational speed, with benefits in terms of efficiency. In this article, a pleasure craft, originally powered with a traditional propulsion plant, is repowered with two alternative diesel-electric propulsion plant layouts: a standard one, with AC distribution and torque controlled diesel generators at a constant speed, and a DC-link one with variable speed controlled generators. Variable speed diesel generators require a custom control system to manage the additional degree of freedom involved. For such a reason, the optimal working points of the diesel engines are assessed in design and off-design conditions by using a genetic algorithm, with the final aim of minimising the overall fuel consumption rate. The performance of the two analysed propulsion plants are evaluated and compared at different power levels. Eventually, the results are presented and discussed

COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles

A random sampling based algorithm for ship path planning with obstacles

The paper presents a path planning algorithm for ship guidance in presence of obstacles, based on an ad hoc modified version of the Rapidly-exploring Random Tree (RRT*) algorithm. The proposed approach is designed to be part of a decision support system for the bridge operators, in order to enhance traditional navigation. Focusing on the maritime field, a review of the scientific literature dealing with motion planning is presented, showing potential benefits and weaknesses of the different approaches. Among the several methods, details on RRT and RRT* algorithms are given. The ship path planning problem is introduced and discussed, formulating suitable cost functions and taking into account both topological and kinematic constraints. Eventually, an existing time domain ship simulator is used to test the effectiveness of the proposed algorithm over a number of realistic operation scenarios. The obtained results are presented and critically discussed

Development of a navigation support system by means of a synthetic scenario

The main idea of this paper is to connect a synthetic scenario and a time domain ship dynamic simulator, in order to enhance the situational awareness of the bridge crew. The VR is used to represent the surrounding environment, and the Human-In-The-Loop (HITL) techniques permits the user to interact with the simulation. The combined use of a simulator and a synthetic scenario allows multiple choices, such as performing emergency or non-standard manoeuvres, receiving feedbacks and, in case, making the proper actions on the ship. In this paper, this approach is applied to develop a VR-based decision support system for collision avoidance, firstly implementing simple collision avoidance strategies and then elaborating the tool to visualise the information in a synthetic 3D scenario. At the end of the paper, results related to the described application are presented, and the benefits and the weakness of the proposed methodology are discussed

A simulation based tool to assess the propulsion performance of modern conventional submarines

The propulsion system of modern conventional submarines features multiple energy conversion and storage devices and users, which operate closely interconnected. The basic design and sizing of the components commonly rely on steady-state calculations, neglecting the interactions between the propulsion system components. An adequately tailored simulation-based approach is beneficial to ensure the design fulfills the operating requirements in the advanced design phases. Time-domain simulation provides information otherwise unavailable with standard design tools. Moreover, the decision-making process involved in modeling the system and developing the simulation tool shares several similarities with the actual design of the physical system. This paper proposes a simulation model of the propulsion system of a conventional submarine. The theoretical aspects, hypotheses, and simplifications are first discussed. The proposed approach is then applied to a case study to show the potential benefits arising from dynamic simulation when evaluating the performance of a conventional submarine unit

Optimisation of a Diesel-Electric Ship Propulsion and Power Generation System Using a Genetic Algorithm

In recent decades, the design of ship propulsion systems has been focusing on energy efficiency and low pollutant emissions. In this framework, diesel\u2013electric propulsion has become a standard for many ship types and has proven its worth for flexible propulsion design and management. This paper presents an approach to the optimal design of diesel\u2013electric propulsion systems, minimising the fuel consumption while meeting the power and speed requirements. A genetic algorithm performs the optimisation, used to determine the number and type of engines installed on-board and the engines\u2019 design speed and power, selecting within a dataset of four-stroke diesel engines. The same algorithm is then adapted and applied to determine the optimal load sharing strategy in off-design conditions, taking advantage of the high flexibility of the diesel\u2013electric propulsion plants. In order to apply the algorithm, the propulsion layout design is formulated as an optimisation problem, translating the system requirements into a cost function and a set of linear and non-linear constraints. Eventually, the method is applied to a case study vessel: first, the optimal diesel\u2013electric propulsion plants are determined, then the optimal off-design load sharing and working conditions are computed. AC and DC network solutions are compared and critically discussed in both design and off-design conditions