Postgraduate Courses

Back

Expand All Print All

SEEN

Sustainable Energy and Environment

SEEN 5010
Experiment Design and Analysis
[3-0-0:3]
Background
Undergraduate study in natural science or engineering with knowledge of statistics and mathematics.
Description
This course aims to introduce principles in the design of experimental research and practical skills in the statistical analysis of results. Topics will include construction of research hypotheses, principles of statistical inference, confidence interval estimation, and differences in statistical approaches in the trials setting. It will also introduce students to skills and tools for optimal experimental design, experimental data extraction, validation, comparison and uncertainty analysis.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand the significance of experiment design for research in the sustainable energy and environment area
- 2.
  Be familiar with statistics
- 3.
  Be familiar with various parameter estimation methods
- 4.
  Know how to design physical experiments
- 5.
  Know how to design computer experiments
- 6.
  Be familiar with machine learning and surrogate modeling techniques
SEEN 5020
Design and Optimization of Energy Systems
[3-0-0:3]
Background
The course is intended for students with some, but not necessarily a deep background in linear control systems.
Description
This course aims to introduce techniques for the architecture design, optimization modelling and the economic evaluation of industrial processes and energy systems and to develop the skills required to identify the opportunity and implement optimization-based decision support tools in energy processes and systems. It covers the problem statement, modeling of processes and systems, solving methods for the simulation and the single and multi-objective optimization strategies. Topics cover process systems engineering, process and system modelling and simulation, economic evaluation, optimization strategies, and data reconciliation.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Recognize structures and dynamic behavior of energy systems
- 2.
  Master mathematical modeling and response analysis methods of energy systems
- 3.
  Learn and apply linear process control theories, including controller structure design, parameter tuning, and stability analyses
- 4.
  Execute real-time optimization and model predictive control methods for multi-objective energy system design
- 5.
  Recognize the energy systems of distributed drive electric vehicles and design optimized control algorithms
- 6.
  Apply the learned control and optimization techniques in dealing with a new scientific problem
SEEN 5030
Battery Sustainability
[3-0-0:3]
Background
Basic knowledge of chemistry, physics, and mathematics
Description
Rechargeable batteries, as one of the most versatile energy storage technologies, play a central role in the ongoing transition from fossil fuel to renewable energy. This course will focus on the environmental footprint, sustainability, and the diagnostics of batteries. History, fundamental science, and cutting-edge research will be covered in the lectures.
SEEN 5040
Modeling and Simulation of Complex Energy Systems
[3-0-0:3]
Background
Undergraduate study in Chemistry, Chemical Engineering, Material Science, Energy and Power Engineering and Mechanical Engineering
Description
The subject of transport phenomena includes three closely related topics: fluid dynamics, heat transfer, and mass transfer. Fluid dynamics involves the transport of momentum, heat transfer deals with the transport of energy, and mass transfer is concerned with the transport of mass of various chemical species. In this course, we study these three transport phenomena together. This course will also introduce various solution methods and software tools to tackle the transport phenomena equations in the form of coupled differential equations. Transport phenomena applications in several example systems (e.g., chemical and electrochemical reactors, fuel cells and batteries) will be highlighted.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand the significance of mathematical modeling in process and energy systems engineering.
- 2.
  Be familiar with mathematical modeling and parameter estimation.
- 3.
  Be familiar with thermodynamics and kinetics of fluid systems.
- 4.
  Be familiar with mass, energy, and momentum transfer.
- 5.
  Know how to reformulate and solve coupled differential equations.
- 6.
  Know how to solve transport equations with software tools.
- 7.
  Be familiar with transport modeling for various energy devices and systems.
SEEN 5060
Greenhouse Gas, Air Pollutant Emissions and Mitigation
[3-0-0:3]
Background
Undergraduate study in engineering or natural science with knowledge of chemistry or statistics and mathematics.
Description
The aims of this course are to assist students understand emission characteristics of greenhouse gas and air pollutants and their sources, how to characterize and quantify emissions for diverse source sectors, and how to mitigate greenhouse gas and air pollutant emissions. The topics will include: the introduction of greenhouse gases and air pollutants; the characteristics of sector-based greenhouse gas and air pollutant emission sources, sampling and measurement techniques, and commonly used bottom-up estimation methods for major sectors such as energy, industry, transportation, households, and others; the uncertainty and validation of bottom-up emission inventory; the application of big data and innovative methodologies to emission inventory development; and major strategies and green technologies for mitigating greenhouse gas and air pollutant emissions.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand emission source characteristics of greenhouse gases and air pollutants and their environmental impacts.
- 2.
  Understand major methods, instruments and techniques for measuring, calculating and reducing air pollutant and greenhouse gas emissions for major source sectors.
- 3.
  Apply a range of quantitative methods to build air pollutant and greenhouse gas emission inventories.
- 4.
  Understand and apply a range of methods to conduct uncertainty analysis and validation of greenhouse gas and air pollutant emission inventory.
- 5.
  Understand and apply a range of big data-based methods to develop near-real-time greenhouse gas and air pollutant emission inventory.
- 6.
  Apply a range of qualitative and quantitative methods to analyze emission reduction potentials of different techniques or policy scenarios.
SEEN 5090
Physical Chemistry of Advanced Energy Materials
[3-0-0:3]
Background
Students with background in Material Science and Engineering, Energy Engineering, Chemistry, and Physics are recommended.
Description
The development of sustainable energy heavily relies on the advancements of corresponding key energy materials. The material’s quality and system stability are closely determined by the related physical chemistry process. This course introduces main concepts and practical application of thermodynamics and kinetics of the key energy materials. It includes basic laws of classical and irreversible thermodynamics, phase equilibria, theory of solutions, chemical reaction thermodynamics and kinetics, surface phenomena, diffusion etc. This course would provide students with insights and deep understandings of the physical chemistry aspects of materials and enable the students to conduct energy material syntheses and energy system experiments with advanced thermodynamic and kinetic foundations.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Know how to use modern thermodynamic models for the description of a chemical reaction and phase transformation in energy materials.
- 2.
  Gain insights into the energy-related materials and materials processes from both thermodynamics and kinetics point of view.
- 3.
  Understand the laws of thermodynamics and solution theory of materials.
- 4.
  Examine and evaluate microstructural evolution.
- 5.
  Describe the kinetics of the mass transport in solids including the process of surface and interfaces.
- 6.
  Apply the fundamentals of materials thermodynamics and kinetics to energy material engineering and design.
- 7.
  Demonstrate independent and critical thinking, and develop a growth mindset.
SEEN 5100
Hydrogen Energy and Fuel Cell
[3-0-0:3]
Description
This course covers hydrogen properties, use and safety, fuel cell technology and its systems, fuel cell engine design and safety, and design and maintenance of a heavy-duty fuel cell engine. The different types of fuel cells and hybrid electric vehicles are presented. The system descriptions and maintenance procedures focus on proton-exchange membrane (PEM) fuel cells with respect to heavy-duty transit applications. The PEM fuel cell engine was chosen as it is the most promising for automotive applications, and its transit application is currently the most advanced.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Develop a basic understanding of the chemical and physical foundations of hydrogen fuel production, hydrogen economy; and the electrochemical, thermodynamic and transport processes governing fuel cell operation.
- 2.
  Calculate fuel cell efficiency; estimate losses and performance; calculate fuel/oxidant consumption rates and water/heat production rates.
- 3.
  Gain a perspective on materials for fuel cells and develop an understanding of their characterization and transport properties.
- 4.
  Develop an understanding of the advantages, limitations and suitability of various fuel cell technologies in transportation, stationary and portable applications.
- 5.
  Acquire technical competency in fuel cell technology including design, performance assessment, and quantitative analysis related to proton-exchange membrane (PEM) fuel cells.
- 6.
  Develop an appreciation for practical aspects of fueling and fuel cell system integration and operation.
- 7.
  Enhance awareness with respect to sustainability and the role and impact of energy in society.
SEEN 5110
Global Energy and Environment Policy
[3-0-0:3]
Background
Backgrounds in system modelling simulation and optimization, energy analytics, energy economics are desirable but not necessary.
Description
This course systematically introduces world energy system and the energy transition, together with theoretical and practical understanding of how energy policies are designed, shaped, advocated and implemented. Trends and projections of global energy will be evaluated, including key technologies, investment trends and subsidy policies. Afterwards, case-based teaching will be given to understand the drivers and constraints associated with national energy policy decision-making. Finally, regional and global energy policies and associated stakeholders will be discussed.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand world energy system and the energy transition, together with theoretical and practical understanding of how energy policies are designed, shaped, advocated and implemented.
- 2.
  Acquire critical knowledge and skills to understand the energy trilemma and the trade-offs that governments have to make in designing energy policies objective.
- 3.
  Identify political economy constraints, key technologies, investment trends and subsidy policies for global energy transformation.
- 4.
  Cultivate capability in critical thinking, systematic thinking, dialectical analysis, and cross-disciplinary investigation for complex problem solving.
SEEN 5120
Lifecycle Energy and Economic Analytics
[3-0-0:3]
Description
This course aims to introduce the Life Cycle Assessment (LCA) of integrated ‘source-grid-load-storage’ multi-energy system frameworks. Environmental impacts will be specifically analyzed, associated with the entire life cycle of a particular product or process. Introduction to Techno-Economic Analysis (TEA) will be given for evaluating the economic performance of a specific technology. Three different LCA approaches are introduced, i.e., attributional LCA, consequential LCA, and a hybrid (benchmarking) LCA approach. Physical meaning andcalculation approach of multiple indexes will be holistically introduced, including net direct energy consumption,levelized cost of energy, net present value, discounted payback time, LCA carbon emission, and so on. Afterwards,different application scenarios (like PV, wind turbine, battery, latent heat storages, and integrated PV-battery-building-grid systems) of LCA approach will be given to help students to learn how to apply the approach forlifecycle energy and economic analytics.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Learn the basic knowledge, understand the principles and mechanism on lifecycle energy/economic analytics in various energy systems, like conversions and storages.
- 2.
  Apply a range of qualitative and quantitative research methods to assess techno-economic feasibility of sustainable energy technologies.
- 3.
  Cultivate capability in critical thinking, systematic thinking, dialectical analysis, and cross-disciplinary investigation for complex problem solving.
- 4.
  Deliver multi-criteria decision-making on various technologies through LCA analytics.
SEEN 5130
Green Building in Sustainable Development
[3-0-0:3]
Previous Course Code(s)
SEEN 6000A
Background
Students are highly recommended to have background in building environment and energy engineering, heating, ventilation and air conditioning, thermodynamics, fluid dynamics, renewable energy and energy policy.
Description
This course is to systematically and comprehensively introduce energy consumption and carbon emission in buildings. Heat transfer mechanism and thermodynamics in HVAC will be introduced. Effective solutions on how to achieve low-carbon buildings will be introduced, such as energy-saving in green building technologies (active and passive strategies), distributed renewable energy systems, energy storages (thermal/ electrical/hydrogen), building energy conversion and management. Techno-economic-environmental analysis will be introduced, together with lifecycle carbon quantification and carbon reduction.
SEEN 5140
Digitalization and Intelligence of Integrated Building Energy Systems
[3-0-0:3]
Previous Course Code(s)
SEEN 6000D
Background
Students are highly recommended to have background in building environment and energy engineering, heating, ventilation and air conditioning, thermodynamics, fluid dynamics, solar energy systems, wind turbine and energy policy.
Description
This course aims to introduce the current situation on biologically inspired intelligence in smart buildings. Students will be well trained to conduct statistical analysis and programming experiments; to learn the principles of Artificial Neural Network, fuzzy logic, optimization algorithms and their applications to engineering problems. Technologies for the building role transition from traditional consumers towards prosumers will be comprehensively introduced through ‘source-grid-demand-storage-usage’. Peer-to-peer energy trading, cost-benefit business models and internet of energy things will be introduced. Lastly, in order to guarantee the power supply reliability during extreme weather or war period, energy resilience of distributed energy supply systems will be introduced. Multi-disciplinary areas will be involved in this subject, like fundamentals of artificial intelligence, thermodynamics, heating, ventilation and air conditioning, system modelling and simulation, renewable energy, energy economics, energy policy, and so on.
SEEN 5150
Kinetic Energy Harvesting and Conversion
[3-0-0:3]
Previous Course Code(s)
SEEN 6000F
Description
The course will discuss kinetic energy harvesting devices and systems, including: Principles of energy harvesting from wind, wave, water flow, vibration, and human motion; Architectures and design; Mechanism, electromechanical modeling and analysis of electromagnetic, piezoelectric, triboelectric, electrostatic generators; Lab experiments; Wind turbines and fluid-structure interaction; Fundamentals of vibration; Control and power conditioning circuits; Performance evaluation and optimization; Potential applications and sensing.
SEEN 5210
Energy Materials and Systems
[3-0-0:3]
Previous Course Code(s)
SEEN 6000C
Background
Basic knowledge of chemistry, physics, and mathematics.
Description
Materials are critical for the developments of advanced energy systems, which play a pivotal role towards the sustainable, carbon-neutral future. This course will introduce the working principles of a few energy systems such as fossil fuel, renewable energies, batteries, and supercapacitors. Special focus will be placed on the material aspects of these energy systems through the interrelationships of composition, processing, structure, properties, and performance.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify scientific and engineering significances in energy materials.
- 2.
  Understand the materials physics and chemistry in energy systems.
- 3.
  Apply a range of qualitative and quantitative research methods for conducting the material research for energy applications.
- 4.
  Grasp fundamental research insights and innovative ideas effectively.
- 5.
  Demonstrate independent and critical thinking, and develop new ideas towards better energy materials and systems.
- 6.
  Combine cross-disciplinary tools to address the scientific and technological challenges.
SEEN 5310
Bio-inspired Energy Systems
[3-0-0:3]
Background
This course is intended for students with general but not necessarily deep backgrounds in energy and environmental engineering.
Description
This course aims to introduce energy technologies that are inspired by bio systems and those that can be potentially applied in bio systems. Bio-inspired energy technologies such as biomimetic functional surfaces, bioinspired energy conversion or fuel production, and bionic energy and mass transport and distribution will be covered. Meanwhile, the applications of advanced energy technologies in bio systems such as bio-compatible energy systems, energy supply for artificial skeleton, and self-powered bio sensing will be reviewed.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand the significances and prospects of bioenergy technologies
- 2.
  Grasp the principles of different kinds of bioenergy technologies and resources, their role in renewable energy sources, their constraints, and application preferences
- 3.
  Transfer fundamental research insights and innovative ideas effectively and experience the application oriented design, analysis and evaluation of bioenergy technologies and systems
- 4.
  Demonstrate independent and critical thinking, and develop a growth mindset, an innovative spirit, and a global vision in the field of bioenergy
- 5.
  Apply a range of qualitative and quantitative research methods for conducting cutting-edge research and exploring applications in bioenergy technologies
SEEN 5320
Machine Learning in Advanced Energy Systems
[3-0-0:3]
Background
Undergraduate study in natural science or engineering with knowledge of linear algebra and calculus.
Description
The course aims to introduce main machine learning techniques and their applications in energy systems. The topics will include: 1) the basic concept of machine learning, big data, and energy system; 2) both basic and the state-of-the-art techniques in machine learning; 3) the application of machine learning in energy systems, especially for power systems and smart grids. The goal of the course is to prepare the students for careers in energy and artificial intelligence related areas by teaching data-driven perspective.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand the basic concepts of energy systems, big data, and machine learning.
- 2.
  Be familiar with supervised learning.
- 3.
  Be familiar with unsupervised learning.
- 4.
  Know how to apply machine learning to energy systems.
- 5.
  Know how to use Python for machine learning and energy data analysis.
SEEN 5330
Electrical Power Systems
[3-0-0:3]
Background
The course is intended for students with some, but not necessarily a deep background in circuit theory and electromagnetics.
Description
This course aims to introduce electrical power systems and electrical to mechanical energy conversion, which has become increasingly important as a way of transmitting and transforming energy in industrial, military and transportation uses. It focuses on the power storage, transmission, and conversion as well as control technologies in sustainable energy systems and electric transportation systems including electrical and hybrid electric cars. It covers fundamentals energy handling electric circuits, power electronic circuits such as inverters, and electromechanical apparatus, modeling of power systems, and control and management in power systems.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Recognize basic laws and structures of electrical power systems
- 2.
  Identify underlying principles of circuits, networks and transmission lines
- 3.
  Apply the basic theories of converters and inverters to explain and predict phenomena related to electrical energy conversion
- 4.
  Describe energy systems of electric vehicles and fundamentals of wireless power transfer
- 5.
  Analyze and solve problems involving EV energy systems and electric motor drives
SEEN 5360
Inorganic Photovoltaic Materials and Devices
[3-0-0:3]
Background
Background in Physics, Material Science and Engineering, semiconductor devices, Chemistry, and Optical Engineering is recommended.
Description
Photovoltaic plays a critical role in harvesting solar energy and secures our future sustainable and carbon-neutral society. This course introduces the mainstream photovoltaic technologies specially focused on the ones based on inorganic materials. It covers the fundamental operation and design principles for inorganic photovoltaics, technological challenges, and applications. It also provides the students with the future technological trend and basic knowledge as well as visions in the research and development of inorganic materials based photovoltaic technologies.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify the characteristics of sunlight, and calculate the incident solar power on the surface regarding the orientation and location, etc.
- 2.
  Competently communicate description of silicon solar cell technology and operation
- 3.
  Identify the design aspects of silicon solar cells such as doping concentration profiles, light management, etc.
- 4.
  Identify the characterization methodologies to measure the properties of a solar cell and research frontline for next-generation photovoltaic technologies
- 5.
  Know the classification and operation principles of inorganic compound based solar cells
- 6.
  Identify the design principles and key issues of next-generation tandem solar cell technology
- 7.
  Demonstrate independent and critical thinking, an innovative spirit, and a global vision in the solar energy conversion field
SEEN 6000
Special Topics in Sustainable Energy and Environment
[1-4 credit(s)]
Description
Selected topics of current interest in emerging areas and not covered by existing courses. May be repeated for credit if different topics are covered. May be graded by letter or P/F for different offerings.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Develop interdisciplinary concepts and knowledge in the chosen topics in Sustainable Energy and Environment
- 2.
  Acquire foundational knowledge and theories of the chosen topics
- 3.
  Appreciate the latest research trend and state-of-the-art techniques in the chosen topics
- 4.
  Apply the methodologies and techniques to real problems in the chosen topics
- 5.
  Explain the theories and applications in the chosen topics
SEEN 6100
Independent Study
[1-3 credit(s)]
Description
An independent study on selected topics carried out under the supervision of a faculty member.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Demonstrate mastery of the knowledge and skills in the selected topics related to Sustainable Energy and Environment.
- 2.
  Apply an interdisciplinary approach in examining the selected topics.
- 3.
  Critically evaluate different aspects of the selected topics.
- 4.
  Communicate findings effectively in written reports.
SEEN 6990
MPhil Thesis Research
Description
Master's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify the current development and the scientific and engineering problems in the field of Sustainable Energy and Environment.
- 2.
  Design, develop and conduct cross-disciplinary research in Sustainable Energy and Environment.
- 3.
  Communicate research findings effectively in written and oral presentations.
- 4.
  Synthesize and create new knowledge, and make a contribution to the field.
SEEN 7990
Doctoral Thesis Research
Description
Original and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify comprehensively the current development and the original scientific or technical problems in the field of Sustainable Energy and Environment.
- 2.
  Design, develop and conduct cross-disciplinary research in Sustainable Energy and Environment.
- 3.
  Communicate research findings effectively in written and oral presentations.
- 4.
  Demonstrate mastery of knowledge in the chosen field of research.
- 5.
  Synthesize and create original new knowledge.
- 6.
  Demonstrate evidences for having made substantial original contributions to the field of study.

Back