MSc Marine Engineering with Specialisation in Autonomous Marine Vehicles

This module aims to provide background education and experience in machine intelligence and autonomous system design from the algorithm level. You'll learn the basics of the predominant data analysis, machine learning, and decision-making algorithms in use today as well as applying your knowledge to a set of simple automation tasks for both real and virtual robotic platforms in the laboratory and on your own computer.

This module aims to provide you with an insight into the qualitative and quantitative systems’ reliability techniques as well as maintenance methodologies with particular emphasis to the maritime industry. The module will give you the ability to formulate, solve, report and present a comprehensive maintenance strategy based on the application of reliability and criticality analysis and assessment tools. The module will also provide you with an insight of the day-to-day operations of ships as well as explore and present features related to ships dry-dockings, inspection, repair and maintenance scheduling, regulatory regime as well as practical case studies on the above.

This module covers the following aspects:

• introduction to reliability and maintenance (definition of reliability, hazard, risk, maintenance, maintainability, criticality, availability, etc)
• reliability tools (qualitative and quantitative like FMEA, FMECA, FTA, ETA, BBNs, Markov Analysis, HAZOP, HAZID, etc)
• risk and criticality matrices
• corrective, preventive, predictive, condition-based maintenance
• Total Productive Maintenance (TPM), Reliability Centered Maintenance (RCM), Risk Based Inspection (RBI) methods. Condition Monitoring (ConMon) tool, Planned Maintenance Systems PMS, Computerised Maintenance Management Systems (CMMS)
• case studies/applications regarding machinery and hull structure of ships
• regulatory regime in relation to ship operations and maintenance (IMO, IACS, OCIMF, HSE-Safety case/ALARP, etc.)
• research and applications in the maritime sector (i.e. FSA, GBS, TMSA, KPIs etc.)
• preparation for dry-dockings, inspection, maintenance and repairs of ships and offshore structures, quotation lists, etc.
• assessment of ship operational case studies
• seminars/lectures from invited experts (maintenance/condition monitoring experts, ship managers/operators to give seminars on planned maintenance/dry-docking planning, day-to-day ship operations)

At the end of this moduleyou'll be able to:

• understand and apply various reliability software tools, concepts and strategies with application to the maritime/marine industry
• be aware of the different maintenance methodologies and their application in the maritime field and carry out maintenance strategy case studies

Assessment and feedback are in the form of the submission one coursework assignment related to reliability and criticality analysis tools and a final exam associated to the above topics.

The aim of this hands-on module is to provide you with an understanding of the general concepts, advantages and limitations of computer-based system simulation. This is achieved by introducing concepts and methods used to mathematically model a wide range of marine systems and also to design and perform simulation studies on these systems using industry standard simulation software tools.

This module will teach the following:

• introduction to simulation and advanced simulation techniques
• introduction to modelling dynamic systems
• time, Frequency (Fourier) and Complex Frequency (Laplace) domain models
• introduction to Linear and non-linear concepts
• numerical solution of dynamic systems
• modelling examples and techniques: mechanical systems, electric systems, hydraulics, thermal and fluid systems
• simulation of complex systems in marine engineering
• diesel engine thermodynamic modelling
• propulsion system modelling
• ship power plant components modelling
• develop models for ship power plant components

On completion of the module you're expected to:

• become familiar with state-of-the-art techniques employed for the modelling and simulation of Marine engineering systems
• have an understanding of simulation methodology, capabilities and evaluation procedures for a range of marine systems
• acquire the necessary skills to perform simulation scenarios as well as to analyse and interpret simulation results

Assessment comes in the form of modelling and simulation of a marine engine/propulsion system, use of the results to comprehend the system behaviour/response. You'll need to submit a report and give a presentation describing your work.

Data-driven decision-making is becoming a crucial skill to deal with emerging marine engineering systems that generate vast amounts of data from the automation system. This module aims to provide you with an understanding of the general concepts, advantages and limitations of Data-Driven methods for naval and marine engineering applications.

The module covers methodologies necessary for inferring useful information and identifying underlying patterns from raw, incomplete, noisy and corrupted data that is present in real-life marine engineering applications. This is achieved by introducing concepts and methods used to numerically model a wide range of naval and marine systems based on available data.

The module will also provide you with the opportunity to explore advanced solutions of data analytics such as nonlinear models, model selection and error estimation. The course is designed for post-graduate students who are interested in data analysis and machine learning applications. An engineering background, statistical and numerical skills would be beneficial but not necessary.

This module covers:

Introduction

1. An Introduction to Data Mining and Statistical Learning
2. Variable types and terminology

Data, Uncertainty and Learning Problems

3. Basics of Statistic
4. Regression and regression problems

Data Preprocessing and Exploratory Data Analysis

5. Data preprocessing
6. Data reduction
7. Dimensionality reduction

Supervised Learning

8. Regression
9. Classification

Overfitting and Regularization

10. Data splitting
Perceptron, Neural Networks and Kernel
11. Geometry Notation
12. Perceptron
13. Neural networks
14. Kernels

Unsupervised Learning

15. K-Means Clustering

On completion of the module you're expected to be able to:

• describe a number of models for supervised, unsupervised inference from data. Critically evaluate statistical analysis. Critically assess the fit of statistical models.
• assess the strength and weakness of each of these models, interpret the mathematical equations from linear algebra, statistics, and probability theory used in the learning models
• implement efficient learning algorithms in the MATLAB language, applied to naval architecture and marine engineering problems
• design test procedures in order to evaluate the model hyperparameters (model selection) and it’s error (error estimation). Develop an appropriate experimental research design for an engineering case study taking into account practical limitations

Summative assessments in this module will evaluate your learning, knowledge and proficiency in the context of data-driven methods. Summative assessment will be used in conjunction and alignment with formative assessment as appropriate for this module.

Digitalisation has become an essential part of the maritime industry, ultimately steered at making the sector more innovative and productive, particularly for Autonomous Marine Vehicles (AMVs).

A digital twin is a dynamic digital representation of an AMV, capable of replicating significant aspects of autonomy, including dynamics, control, guidance, and navigation. The idea is to create a virtual version of the AMV to achieve a realistic, digital simulation of the system utilising the state-of-the-art physical models.

The digital version of the system can be then utilised to mirror the behaviour of the real-world twin using the sensor updates and historical data. The digital twin can be employed to perform complex scenarios simulation to mitigate loss or performance decay by recommending changes in the use of the AMV and increases the success-probability of the mission.

Mathematical modelling and simulation of AMV is a necessary part of the digital-twin contact development. This course aims to provide the student with the skills and knowledge required to model, simulate and then analyse the complex non-linear behaviour of AMV using MATLAB/Simulink.

This module covers:

Introduction

1. An introduction to Autonomous Marine Vehicles: capabilities and potential.
2. AMV Design parameters.
3. Overview of AMV Power and Propulsion.

Modelling and Dynamics of Autonomous Marine Vehicles

4. Hydrodynamic forces and moments.
5. Six degrees of freedom of equations of motions.
6. Models for wind waves and ocean currents.

Guidance, Navigation and Control

7. Reference models
8. Trajectory tracking and manoeuvring control
9. Control methods for AMV

Modelling of Power and Propulsion plant

10. Models for propellers and motors
11. Thrust and torque modelling

AVM Applications

12. Autopilot models
13. AMV Propulsion Plant Modelling and Simulation

On completion of the model you're expected to be able to:

• understand the fundamentals if digital twins idea and concepts; including the benefits of using digital twins for Autonomous vessels. Critically evaluate how the digital twin concept is utilized for replicating significant aspects of autonomy.
• assess the strength and weaknesses of the digital representation of the systems, interpret the mathematical equations utilized to replicate significant aspects of autonomy
• implement efficient numerical models to develop dynamic simulation of real AMV problems, including behaviour prediction and performance optimisation using MATLAB/Simulink
• design test procedures to evaluate the model performances. Develop an appropriate experimental research design for an engineering case study taking into account practical limitations.

Assessment and feedback are in the form of modelling and simulation of autonomous vessels, make use of numerical simulation techniques to obtain knowledge and to comprehend the system dynamics, behaviour and response. You're requested to submit two reports, the developed digital twin models, and give a presentation describing your projects.

This module is aimed to introduce you with a comprehensive understanding of underwater vehicles as opposite to surface vehicles. This module will cover various kind of underwater vehicles, ranging from mega submarines to working-class remotely operated vehicles (ROV) till the state-of-the-art autonomous underwater vehicles (AUVs), from a naval architecture’s perspective of view to tackle the challenges in resistance & propulsion, manoeuvring, sensing, and underwater navigation, etc.

This module covers:

• introduction to underwater vehicle:
  • submarine, torpedo
  • remotely operated vehicles (ROV)
  • autonomous underwater vehicles (AUVs)
  • underwater glider
  • wave glider
• underwater environment:
  • ocean wave
  • current
  • temperature
  • salinity
  • internal wave
• resistance of underwater vehicle:
  • axisymmetric body design
  • surface to volume ratio
  • super cavitation
• propulsion of underwater vehicle:
  • marine propeller
  • contra-rotating propeller
  • ducted propeller
  • rim-driven propeller
  • pump jet
  • kort nozzle
  • vectored propulsion
• manoeuvring of underwater vehicle:
  • rudders
  • fins
  • buoyancy control
  • ballast
• underwater navigation:Inertial Navigation System/Doppler Velocity Log (INS/DVL)
• underwater communication:
  • acoustic
  • radio frequency
  • optical communication

At the end of this module you should be able to:

• achieve a comprehensive understanding of design and development of underwater vehicles and the associated sub-system on-board
• gain the ability to select, design and model the specified underwater vehicles and to evaluate the performance of the designed underwater vehicle
• understand the operation of underwater vehicle, familiarise with the on-board payload, understand the buoyancy control, the pressure compensator, underwater navigation, etc

Assessment and feedback are in the form of 50% group project and 50% final essay.

This module aims to give you a good understanding of all aspects of research work. In addition, the technological study must be accompanied by survey of the relevance and applicability of the findings to the maritime industries at large. You'll learn efficient ways to gather information, to distribute workload and to delegate, to analyse your results and to appreciate the broader implications of the whole project. In-depth technological studies will be accompanied by increasingly important competence in managerial skills, quality assurance and a sound appreciation of the economic, political, social and environmental issues crucial to professional success.

The module will teach the following:

• a detailed structure for the class is outlined in the Project Brief presented to the students. This includes details of key milestones and assessment criteria
• the project brief is reviewed each session to reflect changing technical and economic opportunities in the fields of activity embraced by the Department’s MSc courses

On completion of the module you're expected to be able to:

• develop a broad but nevertheless critical review of prospects for techno-economic growth in maritime related activities in a particular context/area of the world
• propose and evaluate specific design-related activities with a view to proposing a future research and/or development project in, for example, key areas such as offshore hydrocarbon support; marine construction/repair diversification; or maritime transportation, tourism and leisure
• present a research/development proposal to a panel drawn from industry and academia and defend the recommendations

The assessment for each group member will be made through continuous project management, the submission and presentation of the interim report as well as the submission and presentation of the final report and peer assignment.

This module aims to demonstrate the fundamental concepts of ship’s controllability and a ship’s control surfaces, and to explain the factors influencing their performance. It also aims to provide the ship operability concept from a seakeeping perspective and teach the superior seakeeping characteristics of various advanced marine vehicles.

This module covers:

• the ship operability concept and the calculation methods
• the fundamentals of station keeping
• the concept and knowledge of seakeeping considerations in design
• the seakeeping features of advanced marine vehicles
• the fundamental concept of controllability
• control surfaces and applications
• design of marine rudders
• course-keeping and course-changing control

At the end of this module you'll be able to:

• acquire an advanced knowledge of ship manoeuvrability and a ship’s control surfaces
• design a rudder for a given ship and develop its course-keeping and course-changing controller
• apply the ship operability concept into a real case study and be able to understand the factors affecting the operability of a ship

There will be two coursework assignments in this module as summative assessment. The first coursework will be about ship operability and the second coursework will be about ship controllability. Summative assessment will be used in conjunction and alignment with formative assessment as appropriate for this module.

This module aims to provide you with an understanding of the financial and operational issues that companies that manage or own ships in the various sectors of merchant shipping face, both charter and liner shipping, as well as an acquaintance with maritime sector infrastructures.

This module covers:

• international seaborne trade
• economic model for perfect competition conditions
• shipping markets and commodities transported
• charter shipping and the liner market
• supply chain management and logistics
• marine transport systems infrastructures
• geography of marine transport

At the end of this module you'll be able to:

• develop an understanding of the application of basic economic concepts in the shipping sector, its role in the world economy and the role of market sectors in seaborne transportation
• be in a position to assume managerial decisions concerning the charter market sector (wet and dry bulk cargoes)
• make decisions involving liner shipping issues and maritime transport system infrastructures

Assessment and feedback are in the form of a two-hours final exam during the Semester 1 exam diet and a group coursework assignment on selected contemporary topics of shipping economics and market sector analysis.

This module aims to provide a comprehensive introduction to the marine regulatory framework, including background to its development, description of the current framework and future enhancements, an in-depth explanation of the theoretical background, nature and meaning of each method of assessment and a quantitative demonstration of the available routes and criteria used in assessing safety.

This module includes the theoretical background to the development, relevant theoretical models, content, similarities and differences, advantages and disadvantages deriving from the use of various rules and regulations:

• Maritime Regulatory System – Introduction
• Key stakeholders in Maritime Regulations and Enforcement
• Imo, FLAG States and Classification Societies
• EU regulatory Politics and Policy
• Shipping and Environment
• ISM and Human element in Shipping
• Rule Development process and Philosophy
• Offshore Regulations

At the end of this module, you'll:

• understand the structure and functioning of Marine Regulatory Framework including, IMO, Classification Societies and National Authorities
• have knowledge on International regulations under IMO framework including, SOLAS, MARPOL, ISM and Offshore Regulations
• understand the issues with maritime and environmental safety and how rules are developed to address these issues
• understand the meanings of Prescriptive, probabilistic, performance and equivalent rules and approaches
• have developed awareness about the future regulatory developments that may affect the design and operations of the ships and other floating structures

Assessment and feedback are in the form of two course work assignments and an exam. One assignment will be individual, and the other will be a group assignment (max 3-4 people per group). The final exam will be one hour long and purely focusing on the Fundamentals of Marine Regulatory Framework. You'll be provided with the material for the exam.

This module aims to demonstrate how the principles and methods of risk analysis are undertaken and reflected in safety assessment. Risk analysis offers a variety of methods, tools and techniques that can be applied in solving problems covering different phases of the life cycle of a vessel (design, construction, operation and end-of-life) and, as such, this module will also elaborate on the practicalities of its application to a range of marine scenarios.

This module covers:

• safety, risk and risk analysis; key terminology; lessons learnt from past experience; human factors.
• formal safety assessment
• hazard Identification
• frequency analysis and consequence modelling
• quantitative risk assessment methods
• risk control and decision support, cost benefit analysis
• human Factors and Safety culture in the maritime
• industry guest lectures addressing topical issues related to maritime safety and risk

At the end of this module you'll be able to:

• understand the concepts and importance of safety, risk and of all requisite fundamentals enabling quantification of risk in the maritime context
• utilise methods and tools undertaking fundamental studies, specific to any component, system or function and in general first-principles implementation to life-cycle design
• understand and have experience of the use of risk analysis in the marine field via related case studies (risk-based ship design, operation and regulation).
• be able to appreciate components of a formal safety assessment and apply it for indicative problems of maritime operations

Assessment and feedback are in the form of one final exam (during Semester-2 diet) and two coursework assignments (assignment-one focusses on accident investigation, assignment-two is a safety assessment case study).