This subject introduces important mathematical methods required in engineering such as manipulating vector differential operators, computing multiple integrals and using integral theorems. A range of ordinary and partial differential equations are solved by a variety of methods and their solution behaviour is interpreted. The subject also introduces sequences and series including the concepts of convergence and divergence.

Topics include: Vector calculus, including Gauss’ and Stokes’ Theorems; sequences and series; Fourier series, Laplace transforms; systems of homogeneous ordinary differential equations, including phase plane and linearization for nonlinear systems; second order partial differential equations and separation of variables.

The aim of this subject is to provide an introduction to modelling the stresses and deformations that occur when axial, torsional and flexural loads are applied to a body in static equilibrium, as well as the translational and rotational motions that eventuate in a body subject to different load applications. This material will be complemented with laboratory and project based approaches to learning.

The subject provides the basis for all the mechanical engineering subjects that follow. The calculations introduced in this subject are the most common type of calculations performed by professional mechanical engineers in all sectors of the industry.

INDICATIVE CONTENT

Topics to be covered include free-body diagrams; equilibrium; force systems; stresses and strains; coordinate systems; statically indeterminate systems; flexure; bending under combine loads; torsion; power transmission; kinematics; relative motion; particle kinetics; impulse and momentum; vibration; rigid body motion; angular impulse and momentum; work and energy.

AIMS

The aim of this subject is to develop an understanding of fundamental modelling techniques for the analysis of systems that involve electrical phenomena. This includes networks models of “flow-drop” one-port elements in steady state (DC and AC), electrical power systems, simple RC and RL transient analysis, and basic functional models for digital systems consisting of combinational logic. This subject is a core pre-requisite for the four subjects that define the Electrical Systems Major in the Bachelor of Science. The subject is also a core requirement for the Master of Engineering (Electrical, Mechanical and Mechatronics).

INDICATIVE CONTENT

Topics include:

Electrical phenomena – charge, current, electrical potential, conservation of energy and charge, the generation, storage, transport and dissipation of electrical power.

Network models – networks of “flow-drop” one-port elements, Kirchoff’s laws, standard current-voltage models for one-ports (independent sources, resistors, capacitors, inductors, transducers, diodes), analysis of static networks, properties of linear time-invariant (LTI) one-ports and impedance functions, diodes, transformers, steady-state (DC and AC) analysis of LTI networks via mesh and node techniques, equivalent circuits, and transient analysis of simple circuits;

Electrical power systems – overview of power generation and transmission, analysis of single-phase and balanced three-phase AC power systems.

Digital systems – electrical encoding of information and the digital abstraction, analog-to-digital and digital-to-analog conversion, quantization and resolution, switching algebra, combinational logic networks, and transient timing issues.

This material will be complemented by exposure to software tools for the simulation of electrical and electronic systems and the opportunity to develop basic electrical engineering laboratory skills using a prototyping breadboard, digital multimeter, function generator, DC power supply, and oscilloscope.

AIMS

Many engineering disciplines make use of numerical solutions to computational problems. In this subject students will be introduced to the key elements of programming in a high level language, and will then use that skill to explore methods for solving numerical problems in a range of discipline areas.

INDICATIVE CONTENT

• Algorithmic problem solving
• Fundamental data types: numbers and characters
• Approximation and errors in numerical computation
• Fundamental program structures: sequencing, selection, repetition, functions
• Simple data storage structures, variables, arrays, and structures
• Roots of equations and of linear algebraic equations
• Curve fitting and splines
• Interpolation and extrapolation
• Numerical differentiation and integration.

This subject will cover the modelling of a range of physical systems across multiple domains as ordinary differential equations, and then introduce the mathematical techniques to analyse their open loop behaviour.

Topics include:

• Development of low order models of a range of electrical, thermal, mechanical, pneumatic and hydraulic dynamic systems
• Different representations of these systems (time and, frequency domains) and transformations between them (Laplace, Fourier and Z-transforms)
• Representations of systems – transfer functions, Bode plots, state space, block diagrams, etc
• Identification of linear time invariant systems (least squares identification)
• Relation to time domain properties of open loop responses – stability, oscillations, etc.

MATLAB will be used throughout the course to complement the presented concepts.

The aim of this subject is to equip students with computational tools for solving common physical engineering problems. The focus of the lectures is on archetypical physical engineering problems and their solutions via the effective implementation of classical algorithms.

Indicative content: asymptotic notation, abstract data structures, sorting and searching, numerical integration of ordinary differential equations and two-point boundary value problems, numerical stability and convergence.

AIMS

The aims for this subject is for students to develop an understanding of approaches to solving moderately complex problems with computers, and to be able to demonstrate proficiency in designing and writing programs. The programming language used is Java.

INDICATIVE CONTENT

Topics covered will include:

• Java basics
• Console input/output
• Control flow
• Defining classes
• Using object references
• Programming with arrays
• Inheritance
• Polymorphism and abstract classes
• Exception handling
• UML basics
• Interfaces
• Generics

The aim of this subject is to give participants both practical experience in, and theoretical insights into, elements of engineering innovation.

The subject is intense, challenging, experiential and requires significant self-direction. Participants will work on an innovation project sponsored by a local organisation.

A key theme is that the individual cannot be separated from the technical processes of engineering innovation. The impact of both individual and team contributions to the engineering and innovation processes will be examined in the context of real world challenges.

All project sponsors will require that students maintain the confidentiality of their proprietary information. Some project sponsors will require students to assign any Intellectual Property created (other than Copyright in their Assessment Materials) to the University. The projects may vary in the hours needed for a successful outcome.

Critical Communication for Engineers (CCE) addresses the skills vital for professional success. Problem analysis skills and being able to present solutions effectively to your engineering peers, leaders and the broader community are a powerful combination. These are the focus of CCE.

They are challenging skills to learn—and you will likely work to improve them throughout your career. Effective communication is not merely about how to write a report or to give a formal presentation. Developing a strong argument—having something insightful to communicate—is essential for capturing the attention of an audience. This requires developing good interpersonal skills for gathering information and testing ideas.

The subject is divided into four ‘topics’ presented in sequence through the semester. Each topic is self-contained and dedicated to a different engineering issue. There is an assessment for each topic, meaning that you will be able to apply what you have learned from one topic to the following topics. This way, you will have a lot of opportunities to practise and develop your analytical and communication skills.

AIMS

This subject provides an introduction to automatic control systems, with an emphasis on classical techniques for the analysis and design of feedback interconnections. The main challenge in automatic control is to achieve desired performance in the presence of uncertainty about the system dynamics and the operating environment. Feedback control is one way to deal with modelling uncertainty in the design of engineering systems. This subject is a core requirement in the Master of Engineering (Electrical, Electrical with Business, Mechanical, Mechanical with Business and Mechatronics).

INDICATIVE CONTENT

Topics include:

* Modelling for control, linearization, relationships between time and frequency domain models of linear time-invariant dynamical systems, and the structure, stability, performance, and robustness of feedback interconnections;

* Frequency-domain analysis and design, Nyquist and Bode plots, gain and phase margins, loop-shaping with proportional, integral, lead, and lag compensators, loop delays, and fundamental limitations in design; and

* Actuator constraints and anti-windup compensation.

This material is complemented by the use of software tools (e.g. MATLAB/Simulink) for computation and simulation, and exposure to control system hardware in the laboratory.

This subject continues from Engineering Mechanics to deepen the understanding of (momentum-based) Newtonian Mechanics. It focuses on the study of the motion of rigid bodies in 3D space in kinematics, kinetics and finally the Newton Euler approach of obtaining the equation of motion as well as collision of rigid bodies. Extension to multi-body systems is introduced in each concept. System analysis is introduced by focusing on a case study of gyroscopic motion.

Kinematics of rigid bodies:

• Non inertial coordinate systems
• Rotation representation
• Angular velocity and acceleration in non-inertial frame
• Constraints.

Rigid Body Kinetics

• Kinetics of rigid bodies:
• Inertia tensor, principle axis
• Parallel axis theorem.

Newton-Euler Approach to obtaining equation of motion.

Collision of Rigid Bodies:

• Impulse-momentum principle
• Collision of point masses (particles)
• Collision of unconstrained rigid bodies
• Collision of constrained rigid bodies.

Gyroscopic motion.

AIMS

This subject provides a practical introduction to the design of microprocessor-based electronic systems. The lectures and project work will expose students to the various stages in an engineering project (design, implementation, testing and documentation) and a range of embedded system concepts.

INDICATIVE CONTENT

Topics covered may include: digital computer architecture, example microprocessor architectures, pipelining and caching, system-level programming in assembly language and C for a specific microprocessor; bus standards and protocols, bus interfacing, interrupt servicing; operating systems concepts, multi-tasking, resource management and real-time issues; interfacing to the analog world via analog-to-digital and digital-to-analog converters; standard software tools, including compilers and debuggers, schematic and PCB layout with an emphasis on design for high speed switching circuits.

This material will be complemented by exposure to standard software tools, including compilers and debuggers, schematic and board layout software. The subject will include a level of industry engagement, to provide broader examples of engineering projects, through guest lectures.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

This subject continues from Dynamics to deepen the students’ understanding of Engineering Mechanics, specifically focusing on Analytical Mechanics:

• Kinematics and Generalised Coordinates.
• Virtual Work and Virtual Displacement, Generalised Force.
• Energies: Kinetic, Potential.
• Lagrange approach: dealing with constraints.
• Lagrange’s Approach to obtaining equation of motion.
• Comparison to Newton-Euler Approach.
• Hamiltonian Mechanics.
• Linearisation of system dynamics about equilibrium points (system stability about equilibrium points.

AIMS

This subject provides an introduction to modern control theory with a particular focus on state-space methods and optimal control. The role of feedback in control will be reinforced within this context, alongside the role of optimisation techniques in control system synthesis. This subject is a core requirement in the Master of Engineering (Mechatronics).

INDICATIVE CONTENT

Topics include:
State-space models - first-order vector differential/difference equations; Lyapunov stability; linearisation; discretisation; Kalman decomposition (observable, detectable, reachable and stabilisable subspaces); state-feedback and pole placement; output-feedback and observer design in both continuous-time and discrete-time.
Optimal control - dynamic programming; linear quadratic regulation in both continuous-time and discrete-time. Model predictive control in discrete-time; moving-horizon with constraints.

AIMS

This subject develops a fundamental understanding of the concepts behind and tools used for the analysis and design of analog and digital electronic systems. This is one of four subjects that define the Mechatronics Systems major in the Bachelor of Science and it is a core requirement of the Master of Engineering (Mechatronics).

INDICATIVE CONTENT

Topics include:

Analog systems - time-domain differential equation models of RLC networks, initial conditions, transient response, transfer functions, frequency response, passive filters, impedance functions, two-port networks and dependent sources and matrix circuit representations, op-amp models.

Digital systems – encoding information and digital data processing, CMOS realisation of basic logic gates, timing contracts, acyclic networks, switching algebra, combinational logic synthesis, cyclic networks and memory, finite-state machines, metastability, synchronous timing and synchronisation, data-processing paths, control logic and stored-program machines.

Aspects of these topics will be explored through laboratory work involving simulation tools and hardware experiments.

Mechatronics Design aims to provide students with knowledge, skills, and exposure to the integrated design process of mechatronics systems.

It provides the appreciation of the components of mechatronics systems, such as sensors and actuators, the fundamental principal of operation for these components, their strengths and weaknesses, and its operational characteristics. This leads into the design process of integrated iterative design, division of a system into sub-systems, component selection and sizing, and the inclusion of various considerations into a quantifiably justified design.

The subject also provides wider background knowledge of mechatronics, exposing students to current state-of-the-arts and challenges. Design exercises with increasing degrees of complexity will form the continuous assessment in this subject to put the material covered in the lecture into practice.

Topics covered include:

• Mechatronics design concepts:
• • integrative design concepts
  • analogies between electrical and mechanical systems
  • appreciation of components of mechatronics systems
  • formulation of design requirements
  • design exercise and justifications
  • optimal division into sub systems
  • component selection and sizing
  • prototype development
  • appraisal of benefit and cost
• Evolution of mechatronics design and challenges
• Case studies.

AIMS

Machine Learning is the study of making accurate, computationally efficient, interpretable and robust inferences from data, often drawing on principles from statistics. This subject aims to introduce students to the intellectual foundations of machine learning, including the mathematical principles of learning from data, algorithms and data structures for machine learning, and practical skills of data analysis.

INDICATIVE CONTENT

Indicative content includes: cleaning and normalising data, supervised learning (classification, regression, linear & non-linear models), and unsupervised learning (clustering), and mathematical foundations for a career in machine learning.

AIMS

The subject will introduce the basics of computer networks to students through a study of layered models of computer networks and applications. The first half of the subject deals with data communication protocols in the lower layers of OSI and TCP/IP reference models. The students will be exposed to the working of various fundamental networking technologies such as wireless, LAN, RFID and sensor networks. The second half of the subject deals with the upper layers of the TCP/IP reference model through a study of several Internet applications.

INDICATIVE CONTENT

Topics covered include: Introduction to Internet, OSI reference model layers, protocols and services, data transmission basics, interface standards, network topologies, data link protocols, message routing, LANs, WANs, TCP/IP suite, detailed study of common network applications (e.g., email, news, FTP, Web), network management, and current and future developments in network hardware and protocols.

AIMS

This subject deals with principles of sensing, sensor networking and multiple sensor data fusion. It provides an appreciation of challenges in designing and implementing wired and wireless sensor based solutions in a range of applications.

INDICATIVE CONTENT

Topics covered include:

• Sensors (construction and characteristics)
• Filtering of sensor outputs (up to Kalman filtering options)
• Sensor networks (communication between sensors, how to arrange/coordinate large #s of sensors)
• Multisensor data fusion (SLAM, KF or equivalent)
• Case studies.

AIMS

This subject is intended to give students an overview of the present state-of-the-art in industrial motion control and the likely future trends in control design. Students will be exposed to and have practical experience in the design and implementation of advanced controllers for various motion control problems.

Advanced modelling and control topics will include system identification, modelling and compensation of friction and other disturbances, industrial servo loops, model-based and model-free controller design, and adaptive control. Applications will be drawn from industrial, medical and transport automation (eg robots, machine tools, production machines, laboratory automation, automotive and aerospace by-wire systems).

INDICATIVE CONTENT

Advanced modelling and control topics will include system identification, modelling and compensation of friction and other disturbances, industrial servo loops, model-based and model-free controller design, and adaptive control. Applications will be drawn from industrial, medical and transport automation (eg robots, machine tools, production machines, laboratory automation, automotive and aerospace by-wire systems).

AIMS

The subject aims to introduce the students to the automation technologies, specifically: robotics and process automation. The use of robots and automated systems in carrying out various tasks will be discussed and the fundamental computational techniques associated with the operation of a robotic manipulator and a general automated system will be introduced. The subject will familiarise the students with the roles, strengths, and capabilities of robotics and automation technologies, as well as how to achieve the said capabilities.

INDICATIVE CONTENT

Robotics: manipulator kinematics, including inverse and direct kinematics, manipulator velocity and static forces, trajectory planning, manipulator dynamics, linear control of manipulators and robot designs and robotic programming.

The subject involves undertaking a substantial project conducted in a small group (typically 2-3 students) requiring an independent investigation on an approved topic in advanced engineering design or research. Students will present their findings in a conference podium presentation format, held at the end of semester two.

The emphasis of the project can be associated with either:

• A well-defined project description, often based on a task required by an external, industrial client. Students will be tutored in the synthesis of practical solutions to complex technical problems within a structured working environment, as if they were professional engineering practitioners; or
• A project description that will require an explorative approach, where students will pursue outcomes associated with new knowledge or understanding, within the mechanical science disciplines, often as an adjunct to existing academic research initiatives.

It is expected that the Mechatronics Capstone Project will incorporate findings associated with both well-defined professional practice and research principles.

AIMS

The subject will introduce the basics of computer networks to students through a study of layered models of computer networks and applications. The first half of the subject deals with data communication protocols in the lower layers of OSI and TCP/IP reference models. The students will be exposed to the working of various fundamental networking technologies such as wireless, LAN, RFID and sensor networks. The second half of the subject deals with the upper layers of the TCP/IP reference model through a study of several Internet applications.

INDICATIVE CONTENT

Topics covered include: Introduction to Internet, OSI reference model layers, protocols and services, data transmission basics, interface standards, network topologies, data link protocols, message routing, LANs, WANs, TCP/IP suite, detailed study of common network applications (e.g., email, news, FTP, Web), network management, and current and future developments in network hardware and protocols.

AIMS

Machine Learning is the study of making accurate, computationally efficient, interpretable and robust inferences from data, often drawing on principles from statistics. This subject aims to introduce students to the intellectual foundations of machine learning, including the mathematical principles of learning from data, algorithms and data structures for machine learning, and practical skills of data analysis.

INDICATIVE CONTENT

Indicative content includes: cleaning and normalising data, supervised learning (classification, regression, linear & non-linear models), and unsupervised learning (clustering), and mathematical foundations for a career in machine learning.

AIMS

This subject involves students undertaking professional work experience at a Host Organisation’s premises. Students will work under the supervision of both a member of academic staff and an external supervisor at the Host Organisation.

During the period of work experience, students will be introduced to workplace culture and be offered the opportunity to strengthen their employability. Students will undertake seminars covering topics that will include professional standards of behaviour and ethical conduct, working in teams, time management and workplace networking.

AIMS

This subject is intended to give students an overview of the present state-of-the-art in industrial motion control and the likely future trends in control design. Students will be exposed to and have practical experience in the design and implementation of advanced controllers for various motion control problems.

Advanced modelling and control topics will include system identification, modelling and compensation of friction and other disturbances, industrial servo loops, model-based and model-free controller design, and adaptive control. Applications will be drawn from industrial, medical and transport automation (eg robots, machine tools, production machines, laboratory automation, automotive and aerospace by-wire systems).

INDICATIVE CONTENT

Advanced modelling and control topics will include system identification, modelling and compensation of friction and other disturbances, industrial servo loops, model-based and model-free controller design, and adaptive control. Applications will be drawn from industrial, medical and transport automation (eg robots, machine tools, production machines, laboratory automation, automotive and aerospace by-wire systems).

AIMS

The subject aims to introduce the students to the automation technologies, specifically: robotics and process automation. The use of robots and automated systems in carrying out various tasks will be discussed and the fundamental computational techniques associated with the operation of a robotic manipulator and a general automated system will be introduced. The subject will familiarise the students with the roles, strengths, and capabilities of robotics and automation technologies, as well as how to achieve the said capabilities.

INDICATIVE CONTENT

Robotics: manipulator kinematics, including inverse and direct kinematics, manipulator velocity and static forces, trajectory planning, manipulator dynamics, linear control of manipulators and robot designs and robotic programming.

Upon completion, students are expected to gain an overview of a major branch of artificial intelligence known as computational intelligence or soft computing, and their applicability to mechatronic systems. Students are expected to practice some of the methods they learn on real and synthetic data and appreciate the strengths and limits of the approaches they learn.

A variety of topics in computational intelligence are expected to be covered, with selections to be made from 1) neural networks including generative networks, deep neural networks and convolution neural networks, 2) learning methods including unsupervised learning, reinforcement learning and semi-supervised learning, 3) appreciation of other Computational Intelligence methods: fuzzy systems and evolutionary algorithms and 4) an introduction to stochastic dynamic programming and its relationship to AI. Mechatronic applications in broader terms and case studies from other relevant areas of engineering will be discussed.

AIMS

The subject will introduce the basics of computer networks to students through a study of layered models of computer networks and applications. The first half of the subject deals with data communication protocols in the lower layers of OSI and TCP/IP reference models. The students will be exposed to the working of various fundamental networking technologies such as wireless, LAN, RFID and sensor networks. The second half of the subject deals with the upper layers of the TCP/IP reference model through a study of several Internet applications.

INDICATIVE CONTENT

Topics covered include: Introduction to Internet, OSI reference model layers, protocols and services, data transmission basics, interface standards, network topologies, data link protocols, message routing, LANs, WANs, TCP/IP suite, detailed study of common network applications (e.g., email, news, FTP, Web), network management, and current and future developments in network hardware and protocols.

AIMS

The subject aims to provide an understanding of the principles on which the Web, Email, DNS and other interesting distributed systems are based. Questions concerning distributed architecture, concepts and design; and how these meet the demands of contemporary distributed applications will be addressed.

INDICATIVE CONTENT

Topics covered include: characterization of distributed systems, system models, interprocess communication, remote invocation, indirect communication, operating system support, distributed objects and components, web services, security, distributed file systems, and name services.

AIMS

Mobile devices are ubiquitous nowadays. Mobile computing encompasses technologies, devices and software that enable (wireless) access to services anyplace, anytime, and anywhere. This subject will cover fundamental mobile computing techniques and technologies, and explain challenges that are unique to mobile computing. In particular, the development of software for mobile devices requires hands-on experience that cannot be captured using simulation environments or emulators. Mobile device have limited computing power and restrictions on the communication bandwidth, latency and network availability. Equally important, mobile device are also confined by their input mechanisms and their output capabilities such as screen size and resolution. This subject will enable students to develop mobile phone applications and provide them with hands-on experience.

INDICATIVE CONTENT

• A survey of mobile operating systems and development environments; including a discussion of Android and iOS
• Development of interfaces for mobile devices and dealing with different input modalities
• Wireless messaging fundamentals such as push and pull, as well as messaging services such as SMS and MMS and their implementation
• Wireless personal area network standards such as Bluetooth, UWB (ultra-wide band) and ZigBee
• Fundamentals of wireless wide area networks (WWAN) and 4G standards such as LTE and WiMAX enabling wireless broadband access, and the underlying code-, frequency- and time-based multiplexing techniques
• Architectures for thin clients
• Routing in mobile ad-hoc networks and vehicular ad-hoc networks
• RFID (radio frequency identification), in particular how to interrogate RFID tags and anti-collision, and how to maintain security and privacy
• In- and outdoor positioning techniques (GPS) for mobile devices, as location-based services are seen to be one of the key emerging application areas in mobile computing
• Location privacy in mobile computing applications
• Mobile agents, i.e., software programs that can migrate between different hosts.

AIMS

The Internet, World Wide Web, bank networks, mobile phone networks and many others are examples for Distributed Systems. Distributed Systems rely on a key set of algorithms and data structures to run efficiently and effectively. In this subject, we learn these key algorithms that professionals work with while dealing with various systems. Clock synchronization, leader election, mutual exclusion, and replication are just a few areas were multiple well known algorithms were developed during the evolution of the Distributed Computing paradigm.

INDICATIVE CONTENT

Topics covered include:

• Synchronous and asynchronous network algorithms that address resource allocation, communication
• Consensus among distributed processes
• Distributed data structures
• Data consistency
• Deadlock detection
• Lader election, and
• Global snapshots issues.

AIMS

The growing popularity of the Internet along with the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we do parallel and distributed computing (PDC). Cluster and Cloud Computing are two approaches for PDC. Clusters employ cost-effective commodity components for building powerful computers within local-area networks. Recently, “cloud computing” has emerged as the new paradigm for delivery of computing as services in a pay-as-you-go-model via the Internet. These approaches are used to tackle may research problems with particular focus on "big data" challenges that arise across a variety of domains.

Some examples of scientific and industrial applications that use these computing platforms are: system simulations, weather forecasting, climate prediction, automobile modelling and design, high-energy physics, movie rendering, business intelligence, big data computing, and delivering various business and consumer applications on a pay-as-you-go basis.

This subject will enable students to understand these technologies, their goals, characteristics, and limitations, and develop both middleware supporting them and scalable applications supported by these platforms.

This subject is an elective subject in the Master of Information Technology. It can also be taken as an Advanced Elective subject in the Master of Engineering (Software).

INDICATIVE CONTENT

• Cluster computing: elements of parallel and distributed computing, cluster systems architecture, resource management and scheduling, single system image, parallel programming paradigms, cluster programming with MPI
• Utility computing: foundations and grid computing technologies
• Cloud computing: cloud platforms, Virtualization, Cloud Application Programming Models (Task, Thread, and MapReduce), Cloud applications, and future directions in utility and cloud computing
• "Big data" processing and analytics in distributed environments.

AIMS

Machine Learning is the study of making accurate, computationally efficient, interpretable and robust inferences from data, often drawing on principles from statistics. This subject aims to introduce students to the intellectual foundations of machine learning, including the mathematical principles of learning from data, algorithms and data structures for machine learning, and practical skills of data analysis.

INDICATIVE CONTENT

Indicative content includes: cleaning and normalising data, supervised learning (classification, regression, linear & non-linear models), and unsupervised learning (clustering), and mathematical foundations for a career in machine learning.

AIMS

The key focus of this subject is the foundations of autonomous agents that reason about action, applying techniques such as automated planning, reinforcement learning, game theory, and their real-world applications. Autonomous agents are active entities that perceive their environment, reason, plan and execute appropriate actions to achieve their goals, in service of their users (the real world, human beings, or other agents). The subject focuses on the foundations that enable agents to reason autonomously about goals & rewards, perception, actions, strategy, and the knowledge of other agents during collaborative task execution, and the ethical impacts of agents with this ability.

The programming language used in this subject is Python. No lectures or workshops on Python will be delivered

INDICATIVE CONTENT

Topics are drawn from the field of advanced artificial intelligence including:

• Search algorithms and heuristic functions
• Classical (AI) planning
• Markov Decision Processes
• Reinforcement learning
• Game theory
• Ethics in AI planning

AIM

This subject develops the theoretical and practical tools required to understand, construct, validate and apply models of standard electrical and electronic devices. In particular, students will study the theoretical and practical development of models for devices such as resistors, capacitors, inductors, transformers, motors, batteries, diodes, transistors, and transmission lines. In doing so, students will gain exposure to a variety of fundamental fields in physics, including electromagnetism, semiconductor materials and quantum electronics. This material will be complemented by exposure to experiment design and measurement techniques in the laboratory, the application of models from device manufacturers, and the use of electronic circuit simulation software.

INDICATIVE CONTENT

Topics include:

Vector calculus for device modelling, Maxwell’s equations, physics of conductors and insulators, passive device models (including for resistors, capacitors and inductors), lumped and distributed circuit models for wired interconnections (including treatment of signal integrity and termination strategies), semiconductors and quantum electronics, static and dynamic models for p-n junctions diodes and bipolar junction transistors.

AIMS

The aim of this subject is to develop a thorough understanding of the main concepts, techniques and performance criteria used in the analysis and design of digital communication systems. Such systems lie at the heart of the information and communication technologies (ICT) that underpin modern society. Digital communications have become the preferred option for many communication devices, replacing analogue systems, due to their robustness to noise, ease of standardisation and increased scale of integration.

INDICATIVE CONTENT

This subject provides an in-depth treatment of the main concepts and techniques used in the analysis and design of digital communication systems.

Topics include:

• Source coding; data compression; entropy;
• Digital modulation and demodulation, with and without bandwidth constraints; signal constellations in signal vector space; M-ary signalling and probability of error calculations for AWGN channels; Nyquist’s criterion, pulse shaping and equalisation; sequence detection; Viterbi’s algorithm;
• Mutual information and channel capacity; BSC and erasure channels; Shannon bounds; channel coding; erasure coding; block codes; convolutional / trellis codes; error-correction; and decoding methods.

This material is complemented by examples such as JPEG, the compact disc, satellite communication systems, and mobile communication systems.

AIMS

This subject provides an in-depth introduction to statistical signal processing.

INDICATIVE CONTENT

Students will study a selection of the following topics:

• Applications of statistical signal processing;
• A review of stochastic signals and systems fundamentals – random processes, white noise, stationarity, auto- and cross-correlation functions, spectral- and cross-spectral densities, properties of linear time-invariant systems excited by white noise;
• Parameter estimation - least squares and its properties, recursive least squares and least mean squares, optimisation-based methods, maximum likelihood methods;
• Kalman, Wiener and Markov filtering;
• Power spectrum estimation.

This material will be complemented with the use of software tools (e.g. MATLAB) for computation and a DSP (Digital Signal Processor) based development platform for the implementation of signal processing algorithms in the laboratory.

AIMS

This subject provides an introduction to probability theory, random variables, random vectors, decision tests, and stochastic processes. Uncertainty is inevitable in real engineering systems, and the laws of probability offer a powerful way to evaluate uncertainty, to predict and to make decisions according to well-defined, quantitative principles. The material covered is important in fields such as communications, data networks, signal processing and electronics. This subject is a core requirement in the Master of Engineering (Electrical, Mechanical and Mechatronics).

INDICATIVE CONTENT

Topics include:

• Foundations – combinatorial analysis, axioms of probability, independence, conditional probability, Bayes’ rule;
• Random variables (rv’s)– definition; cumulative distribution, probability mass and probability density functions; expectation and variance; functions of an rv; important distributions and their properties and uses;
• Multiple random variables – joint cumulative distribution, probability mass and probability density functions; independent rv’s; correlation and covariance; conditional distributions and expectation; functions of several rv’s; jointly Gaussian rv’s; random vectors;
• Sums, inequalities and limit theorems – sums of rv’s, moment generating function; Markov and Chebychev inequalities; weak and strong laws of large numbers; the Central Limit Theorem;
• Decision testing - maximum likelihood, maximum a posterior, minimum cost and Neyman-Pearson rules; basic minimum mean-square error estimation;
• Stochastic processes – mean and autocorrelation functions, strict and wide-sense stationarity; ergodicity; important processes and their properties and uses;
• Introduction to Markov chains.

This material is complemented by exposure to examples from electrical engineering and software tools (e.g. MATLAB) for computation and simulations.

AIMS

This subject provides an in-depth coverage of transistor (MOSFET and BJT) devices and their use in common circuits. In particular, students will study topics including: transistor operating modes and switching; principles of CMOS circuits; transistor biasing; current-source/emitter-amplifiers; low-frequency response; followers; class B amplifiers; current limiting; current sources and mirrors; differential pairs; feedback in amplifiers and stability; operational amplifiers; operational amplifier circuits; and voltage regulation. This material will be complemented by exposure to circuit simulation software tools and the opportunity to further develop circuit construction/test skills in the laboratory.

INDICATIVE CONTENT

Design-focused field-effect and bipolar elementary transistor models, and design of elementary amplifier stages and biasing circuits. Static and dynamic behaviour of amplifier circuits including frequency response, feedback and stability, slew-rate and clipping. Operational amplifiers and opamp based circuits; voltage regulators, references and voltage converters. Verification of electronic circuits using simulation.

AIMS

This subject provides an introduction to the analysis and design of telecommunication signals and systems, in the presence of uncertainty. The emphasis is on understanding the basic concepts that underpin the physical layer of modern communication systems.

INDICATIVE CONTENT

Topics to be covered include:

• Introduction to communication systems including historical developments and comparisons between analogue and digital communications.
• Review of assumed knowledge from linear algebra, signals and systems and probability and random processes.
• The sampling theorem, analog-to-digital conversion, complex baseband representation of passband signals, filtering of random processes, power spectral density, bandwidth of random signals, additive white Gaussian noise (AWGN), signal-to-noise ratio.
• Communication over baseband AWGN channels including modulation techniques (pulse amplitude modulation, orthogonal modulation), signal space representation, optimal detectors, matched filters, error probability calculations and bandwidth / power trade-off.
• Communication over passband AWGN channels including modulation techniques (phase shift keying, quadrature amplitude modulation and frequency shift keying), optimal coherent detectors, noncoherent detectors and error probability calculations.
• Communication over linear time-invariant channels including concepts of distortion, inter-symbol interference, pulse shaping, Nyquist’s criterion, equalization, sequence detection and the Viterbi algorithm.
• Synchronization including carrier, symbol and frame synchronization.

AIMS

This subject provides an introduction to the fundamental theory of time domain and frequency domain representation of discrete time signals and linear time invariant dynamical systems, and how this theory is used to analyse and design digital signal processing systems and algorithms. Topics include:

• Applications of signal processing techniques;
• Sampling of analog signals, anti-aliasing filters;
• Frequency-domain analysis of signals and systems, Discrete Time Fourier Transform, Discrete Fourier Transform, Fast Fourier Transform;
• Digital filters, low-pass, high-pass, band-pass, stop-band and all pass filters. Phase and group delay, FIR and IIR filters;
• Design of digital FIR and IIR filters;
• Multi-rate signal processing, with a focus on up-sampling, down-sampling, and sampling rate conversion;
• Simple non-parametric methods for spectral estimation.

This fundamental material will be complemented by exposure to MATLAB tools for signal analysis and a DSP (Digital Signal Processor) based development platform for the implementation of signal processing algorithms in the laboratory.

INDICATIVE CONTENT

Sampling of continuous time signals, Design of anti-aliasing filters, Time and frequency representation of discrete time signals and discrete time linear time invariant systems, Discrete Time Fourier Transform and z-transform and their properties, Low order lowpass, highpass, bandpass, bandstop filters, All-pass filter, Design of IIR filters using the bilinear transformation, Design of FIR filters with linear phase using windowing techniques and the Parks McClelland method, Discrete Time Fourier transform and its properties, Fast Fourier Transform, The use of the DFT in implementation of linear filtering algorithms, Up-sampling and down-sampling, multistage and computationally efficient implementations of up-samplers and down-samplers, Energy and power spectra for deterministic signals.

AIMS

The aim of the subject is to provide theoretical and practical treatment of high-speed electronics. Through the subject, students will grasp the fundamental properties and models of high-speed signals and interconnects, acquire high-speed digital design skills with a focus on the modelling, analysis, design and application of high speed transistors, logic gates and modern logic families, and master the high-speed analogue design capability including the design of oscillators and filters for RF applications. The students will be exposed to the state-of-the-art technologies that are shaping the fast evolving semiconductor industry.

INDICATIVE CONTENT

The topics include:

• Fundamental properties of analogue systems;
• Smith charts: principles and applications;
• High-speed analogue circuits: voltage control oscillators, matching networks, and low noise amplifiers;
• Bipolar junction transistors: device, switching, and logic;
• CMOS: device, switching and logic;
• High-speed signalling consideration: power dissipation, heat, signal propagation, and termination.

The use of mathematical optimisation is widespread in business, where it is a key analytical tool for managing and planning business operations. It is also required in many industrial processes and is useful to government and community organizations. This subject will expose students to operations research techniques as used in industry. A heavy emphasis will be placed on the modelling process that turns an industrial problem into a mathematical formulation. The focus will then be on how to solve the resulting mathematical problem with mixed-integer programming techniques.

AIMS

This subject consists of three distinct and fundamentally related topics -

• An introduction to the fundamentals of materials science will be given on atomic structure and bonding, crystal structures and defects, elastic and plastic deformation, dislocations and strengthening and failured (fast fracture, fatigue and creep)
• The mechanics of materials section will extend the concepts of material mechanical behaviour by detailing elastic/inelastic behaviour and introducing the concepts of stress and strain analysis. Topics covered may include the definition of principal stresses, plane stress, plane strain, two-dimensional stress and strain analysis, torsion, pure bending, transverse loading, Mohr’s circle, failure criteria, inelastic behaviour, residual stress
• This subject will also provide an introduction to finite element analysis (FEA) and its application for stress-strain analysis. Particular emphasis will be placed on the fundamental mechanisms by which materials fail under loading.

INDICATIVE CONTENT

• Mechanics: the definition of principal stresses, plane stress, plane strain, two-dimensional stress and strain analysis, torsion, pure bending, transverse loading, Mohr’s circle, failure criteria, inelastic behaviour, residual stress.
• Materials: atomic structure and bonding, crystal structures and defects, elastic and plastic deformation, dislocations and strengthening and failure (fast fracture, fatigue and creep).
• Finite element analysis (FEA): FEA procedure, application of FEA to discrete systems and continuous bodies.

AIMS

This course is an introduction to basic principles of fluid mechanics and thermodynamics. These two subjects are introduced together in a single course, reflecting the large degree of cross-over in applications and basic first principles between the two subjects.

Fluid mechanics is a very important core subject, influencing a diverse range of engineering systems (aircraft, ships, road vehicle design, air conditioning, energy conversion, wind turbines, hydroelectric schemes to name but a few) and also impacts on many biological (blood flow, bird flight etc) and even meteorological studies. As engineers, we are typically concerned with predicting the force required to move a body through a fluid, or the power required to pump fluid through a system. However, before we can achieve this goal, we must start from fundamental principles governing fluid flow.

Thermodynamics could be defined as the science of energy. This subject can be broadly interpreted to include all aspects of energy and energy transformations. Like fluid mechanics, this is a hugely important subject in engineering, underpinning many key engineering systems including power generation, engines, gas turbines, refrigeration, heating etc. This unit again starts from first principles to introduce the basic concepts of thermodynamics, paving the way for later more advanced units

This course aims to develop a fundamental understanding of thermodynamics and fluid mechanics, based on first principles and physical arguments. Real world engineering examples will be used to illustrate and develop an intuitive understanding of these subjects.

INDICATIVE CONTENT

Topics include:

Fluid Mechanics - fluid statics, static forces on submerged structures, stability of floating bodies; solid body motion; fluid dynamics; streamlines; pathlines and streaklines; conservation of mass, momentum and energy; Euler's equation and Bernoulli's equation; control volume analysis; dimensional analysis; incompressible flow in pipes and ducts; boundary layers; flow around immersed bodies; and drag and lift.

Thermodynamics - heat and work, ideal non-flow and flow processes; laws of thermodynamics; Carnot's principle; Clausius inequality; direct and reversed heat engines; thermal efficiencies; properties of pure substances; change of phase; representation of properties; steam and air tables; and vapour equation of state, ideal gases.

AIMS

This subject builds upon previous fluids subjects, providing students with the basic skills necessary to calculate fluid flows around bodies. Broadly speaking the subject is divided into two units; Unit 1: potential flow and Unit 2: compressible flow. These could equally be described as subsonic and supersonic aerodynamics respectively. Fluid flows have broad reaching applications in many engineering systems and examples as broad as building ventilation, mixing, as well as meteorological applications are considered in unit 1. The supersonic course is more firmly concentrated on aeronautical / astronautical applications.

Both units will start from the basic equations of motion governing fluid flow, and build a useable set of tools that enable the students to calculate flow fields in potential and supersonic flows. This approach will give students a clear sense of the origins of the tools that they use, and also a clear sense of the limitations. Such knowledge is necessary since these theories provided much of the backbone to early computational fluid dynamics packages used in industry.

The two units are strongly linked by the same goal. Throughout the potential flow unit, we build slowly from first principles, proving the utility of potential flow solutions, adding building block flows until eventually the course culminates with a demonstration of how these techniques can be used to calculate the flow (and lift coefficient) of subsonic airfoils. The supersonic unit follows a similar approach, building from first principles, until we eventually develop a set of tools that enables the calculation of the flow (and lift coefficient) of supersonic airfoils. In doing so, students will be introduced to many aspects of supersonic aircraft design.

INDICATIVE CONTENT

This subject introduces students to analysis techniques used in subsonic and supersonic flows. Topics covered include (Unit 1) basic introduction to inviscid flow with and without vorticity; concepts and analysis using stream function and velocity potential; incompressible viscous flow past bodies with vortex shedding; magnus effect; complex velocity potential; (Unit 2) speed of sound; aerodynamic heating; normal and oblique shock waves; expansion fans; theories of thin airfoils; shock expansion theory; boundary layer and shock wave interactions; the `sound barrier’; experimental techniques.

AIMS

This subject aims to equip students with the skills to undertake abstract and concrete design tasks at an intermediate level, taking into account the wider engineering environment and the ability to select suitable manufacturing processes to realise their designs. As a result, students will also be able to modify products and processes to improve their performance.

This subject will consider the design of machine elements and introduce the manufacturing processes to produce these elements. It will present concurrent design of systems and products; computer-based techniques for geometric modelling and materials selection. The impact of variability in manufacturing will be accounted for in approaches to uncertainty in design, including tolerance technology. It will provide project-based experience in the use of conceptual design techniques and in the management of larger open-ended, team-based design tasks.

INDICATIVE CONTENT

• Fundamentals of materials selection, shape efficient structures and Cambridge Materials Selector.
• Design of springs, columns, pressure vessels, contact loading, bolted joints and pinned and welded joints.
• Nature of quality in design, Quality Function Deployment (QFD), Failure Modes and Effects Analysis (FMEA), tolerance technology, and design for manufacturing, assembly and disassembly.

AIMS

As a result of satisfactorily participating in this subject, students should be able to undertake design tasks at an intermediate level, considering performance under uncertain system integrity due to fatigue and wear, and have the ability to design or select suitable ameliorating solutions.

INDICATIVE CONTENT

Topics covered in this subject may include: general concepts of function, integrity, value, quality, efficient use of resources in the synthesis of solutions to design problems; specific mechanical elements such as gears and other common means of power transmission, and their design; development of understanding, in the engineering paradigm, of general concepts such as: function, integrity, value, quality, the efficient use of resources in the synthesis of solutions to design problems.

Students will also be exposed to -

• Design for fatigue: characteristics of fatigue fracture, two-dimensional (2-D) and three-dimensional (3-D) stress conditions
• Management of the design process: initial appreciation, information flows and networks, characteristics of manufacturing processes affecting product design
• Cumulative damage hypothesis
• The Weibull distribution
• Design for wear: surface phenomena and tribology; its application to bearings and seals
• Quantitative measures of reliability.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

EPH is a mandatory requirement for completing the Master of Engineering.

AIMS

This subject introduces the concept of microstructure and explores its relationship with processing and properties in the context of basic types of engineering materials and their applications. Topics covered include: diffusion, phase equilibrium and diagrams, phase transformation, metallic alloys, ceramics, polymers, composites, surface and other selected non-mechanical properties.

INDICATIVE CONTENT

Diffusion, phase equilibrium and diagrams, phase transformation, metallic alloys, ceramics, polymers, composites, surface and other selected non-mechanical properties.

AIMS

There are 2 related, major topics of study in this subject. Each of these topics will analyse aspects of important thermodynamic devices and will then be integrated to analyse their combined effects in selected devices:

• Cycle analysis: gas turbines, refrigeration and steam cycles
• Heat transfer: conduction, convection, radiation and heat exchangers

INDICATIVE CONTENT

• Heat transfer: 1-D conduction, external convection, internal convection, heat exchangers and thermal radiation
• Cycle analysis: Brayton cycles, turboject cycles, Rankine cycles, refrigeration cycles

AIMS

The study of fluid dynamics is one of the fundamental disciplines in Mechanical Engineering. In the first part of the course, students will learn about boundary-layer theory, which is a key element of aerodynamic design. A guest-lecture series on wind engineering will build on this knowledge to give students a perspective on one of the most important forms of renewable energy in our society today.

In the second part of the course, students will learn about data acquisition and analysis. These skills are required of engineers working with the technology of today and into the future. The course will help students understand the costs, difficulties and possibilities afforded by sensor systems and instrumentation, with applications for, but not limited to, fluid dynamics.

INDICATIVE CONTENT

This subject will cover selected advanced topics in fluid mechanics. Building on previous fluids courses, the subject is broadly split into two units, although content of these will overlap.

Unit 1: Turbulence and boundary layers. Topics covered include Navier-Stokes equations applied to wall-bounded flows, similarity solutions of the boundary-layer equations, Blasius solution, Falkner-Skan solution, separated flows, turbulent boundary layers, Reynolds-averaged Navier-Stokes equations, dimension analysis, pipe friction, Von Karman momentum integral equation, roughness.

Unit 2: Experimental techniques. Through a series of lectures, labs and assignments, students will be introduced to key concepts of experimental (and numerical) techniques related to fluid mechanics. Topics will include: data analysis (to include correlations, discrete Fourier transform, energy spectra); Particle Image Velocimetry (PIV); hot-wire anemometry; advanced potential flow numerical techniques.

AIMS

This subject is an introduction to combustion theory and applications. In the first part we discuss combustion fundamentals, including thermodynamics, chemical kinetics, conservation equations, and application of these principles to solve simple flames and reacting flows. In the second part we discuss combustion engines and the combustion phenomena in spark-ignition and compression-ignition engines.

INDICATIVE CONTENT

• Chemical thermodynamics and kinetics - flame temperatures, Gibbs free energy and equilibrium, chemical kinetics, combustion mechanisms of common fuels.
• Governing equations - mass, momentum, species and energy conservation for idealized reactors and simplified reacting flows.
• Flames - theoretical analyses of laminar flames, premixed flame (flame speed, quenching, flame stabilization), diffusion jet flame (flame geometry, conserved scalar, soot formation).
• Reciprocating engines - engine cycle analysis, turbulent combustion in spark ignition and diesel engines, cylinder-pressure analysis, pollutant formation and emission control, alternative power-trains and fuels.

AIMS

This subject focuses on advanced materials and their engineering applications. Selected metallic, ceramic and polymer materials and their composites are analysed in the context of applications. When relevant, the topics will be reinforced by introducing the latest development in research.

The selected advanced materials may include light alloys, ferrous alloys, superalloys, intermetallic alloys, ultrafine and nano structured alloys, amorphous alloys, metal matrix composites, structural and functional ceramics, and/or structural and functional polymers.

Students may be required to study engineering cases or research papers and/or conducting experiments in a laboratory.

INDICATIVE CONTENT

The selected advanced materials may include light alloys, ferrous alloys, superalloys, intermetallic alloys, ultrafine and nano structured alloys, amorphous alloys, metal matrix composites, structural and functional ceramics, and/or structural and functional polymers.

AIMS

This course will build on the fundamental theories defined previously in Mechanics & Materials. Two principal theories in the determination of stress within a structure are energy methods and three-dimensional analysis.

INDICATIVE CONTENT

Topics covered in this course will include engineering plasticity, design of pressure vessels and pipes, thick-walled cylinders, shrink fitting, duplex pressure vessels, inelastic deformation, residual stresses, membrane theory of shells of revolution, yielding, rotating shells, local bending stresses, stress analysis of rotating discs with and without holes, shrink fitting, initial and ultimate yielding, fracture mechanics and fatigue, and introduction to the finite element method.

AIMS

This course will expand on the basic principles established previously in Solid Mechanics.

Methods of three-dimensional stress and strain analysis will be extended to allow the student to obtain solutions using analytical and/or numerical methods. These will include the analyses of principal stresses and strains, three dimensional Mohr’s circles, strain gauge experimentation and failure criteria. In addition, this unit will focus on plastic deformation of solids, including the analysis of residual stresses and the collapse load of structures. The responses of materials to fatigue and fracture, as well as their creep and viscoelastic behaviour, will also be explored. Finally, this unit will provide a number of examples of experimental applications of solid mechanics analysis based on modern research techniques.

The goal of Advanced Solid Mechanics is to consolidate the solid mechanics principles presented in the student’s Engineering degree, and the equip students with skills required to solve a range of engineering problems they have not seen before. In addition, this subject seeks to teach a number of modern research methods, techniques and skills by drawing on biomechanical research in the field of solid mechanics, and the major challenges in the field.

INDICATIVE CONTENT

The following topics, delivered through lectures, guest seminars, group problem solving activities, and tutorials, will be assessed:

• Three dimensional stress-strain analysis (weeks 1-2)
• Strength theories and yield criteria (weeks 3-4)
• Plastic behaviour of materials (weeks 5-6)
• Fracture Mechanics(weeks 7-8)
• Contact (weeks 9-10)
• Creep and Viscoelasticity (week 11)
• Biomechanics (week 12)

Electromagnetic components, such as motors, generators, actuators and sensors are critical to many growth industries. These industries include: Robotics, Automotive, Biomedical, Renewables, Aerospace and Agriculture. Electromagnetic Technologies aims to provide students with the knowledge and skills to design electromagnetic devices from first principles and to utilise such components in the appropriate manner for industrial solutions.

This subject will introduce students to the fundamentals of electromagnetic theory before exposing them to a range of industry focussed design projects. For these projects, the students will be expected to:

• Understand the context of the component design requirements
• Formulate the design in a way that allows theoretical analysis
• Conduct the analysis
• Utilise the analysis to design or select (and where possible build) the component
• Take measurements to compare the experimental performance against the theory

The subject also provides wider background knowledge of design engineering, exposing students to industry standard methods of information gathering, analysis and selection.

Topics covered include:

• Electromagnetic theory
• Finite-element methods
• Magnetic actuators
• Electric motor design
• Thermal analysis
• Acoustic analysis
• Electromagnetic sensors

AIMS

One of the main challenges in developing enterprise-wide distributed systems is in choosing the right software architectures. In this subject students will study software architectures in depth and the principles, techniques and tools for creating, developing and evaluating software architectures

INDICATIVE CONTENT

Topics covered in this subject will be drawn from: design styles and architectural patterns; design strategies; domain specific architectures; evaluation of designs; architectural design for non-functional requirements; and modelling architectures.