For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| SFC5024 | Deep Learning Technologies Application | 3 | 6 | Major | Master/Doctor | 1-4 | Smart Factory Convergence | - | No |
| This course introduces deep learning techniques and theories with an emphasis on practical application. It includes concepts and methods used to optimize highly parameterized models, the modules that make up them, and a common neural network architecture. Applications ranging from computer vision to natural language processing and decision making (reinforcement learning) are demonstrated. Through in-depth programming assignments, students learn how to implement these basic building blocks and build them using PyTorch, a popular deep learning library. In the final project, students will apply what they learn to real-world scenarios by exploring these concepts with problems they are passionate about. | |||||||||
| SPE5001 | Introduction to Energy ICT | 3 | 6 | Major | Master/Doctor | 1-4 | Korean | Yes | |
| This class is to study the development of sensor network and signal processing techniques such as filtering, transformation, and feature extraction for online-monitoring and diagnosis of power plant facilities with a aid of an internet-of-things (IoT) technology. In addition, the concepts of prognostics and health management (PHM) and cyber-physical system (CPS) will be introduced, and the related hands-on practices will also be conducted. | |||||||||
| SPE5003 | State-of-the-art Combustion Engineering | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to study the principles and state-of-the-art engineering issues of combustion applied in power generation. The topics for the combustion principles include the combustion reaction and chemical kinetics, detailed combustion processes of gas and coal. The advanced topics cover coal gasification, biomass conversion, emission of NOx and other pollutant and issues in coal-fired boilers and gas turbines. | |||||||||
| SPE5005 | Advanced Plant CFD | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This class is to study the principles of computational fluid dynamics (CFD) and its application to power plant facilities. CFD principles cover the discretization of governing equations, boundary conditions, and submodels for turbulence, radiation and other phenomena. Then, the skills of CFD is taught through tutorial-based practice using a commercial code, ANSYS Fluent, for the flow, particle behavior, combustion, chemical reactions and heat transfer in power plant facilities. | |||||||||
| SPE5007 | Seminars on Smart Power Engineering | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to acquire knowledges on smart power engineering through seminars of experts on key issues in power generation and technologies of 4th industrial revolution. Various topics will be covered in the seminars including up-to-date energy policy, new power generation facilities, virtual plant, diagnostics and life-time prediction of plant equipment based on artificial intelligence and big data technologies. The class also include overseas excursion to advanced power plants. | |||||||||
| SPE5008 | New Environmental Technologies for Power Generation | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to acquire knowledges on pollutant emission and removal, greenhouse gas, and environmental impact in the field of power generation. Topics include the formation mechanisms and removal technologies of various pollutants such as NOx, SOx, heavy metals and particulate matter. Issues on primary and secondary particulate matter and recent development for carbon capture and storage technologies are also covered. | |||||||||
| SPE5010 | Thesis Research 1 on Smart Power Engineering | 3 | 6 | Major | Master/Doctor | 1-4 | Korean | Yes | |
| This course is to acquire research credits by individual research for master degree on smart power engineering. The individual research include technology review, planning of research methodology, data acquisition and analysis using experimental and numerical techniques, derivation of conclusion, and thesis writing. | |||||||||
| SPE5011 | Thesis Research 2 on Smart Power Engineering | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
| This course is to acquire research credits by individual research for master degree on smart power engineering. The individual research include technology review, planning of research methodology, data acquisition and analysis using experimental and numerical techniques, derivation of conclusion, and thesis writing. | |||||||||
| SPE5012 | Sensor and Measurment Technology | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to study the fundamental principles and applications of various sensors for heat transfer, velocity, pressure, temperature, vibration, and material diagnostics used in power plants. | |||||||||
| SPE5013 | Big Data for Plant Application | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to study the big data techniques applied to power plant facilities. The topics include data mining to extract meaningful information from huge data set measured from numerous sensors and devices, and various analytics techniques to optimize the efficiency and pollutant emission, to diagnose equipments and to predict their life-time by using machine learning algorithms. | |||||||||
| SPE5014 | New Power Generation Technolgies | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to study the principles and applications of energy conversion for thermal power generation and new/renewable energy production. The topics of thermal power generation cover the steam cycle power generation and gas turbines based on the principles of thermodynamics and cycles. The topics of new/renewable energy cover the theory and application of fuel cells, wind power and thermovoltaics. | |||||||||
| SPE5015 | Plant Safety Diagnostics and Prediction | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to learn the mechanical principles of solid and materials and practical topics on the creep, fatigue, corrosion, and life-time prediction of actual materials applied in the high temperature processes of power generation. | |||||||||
| SPE5016 | Cases Studies on Energy 4IR | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class is to study various cases and to conduct hands-on practices of 4th industrial revoluation technologies applied to the power generation sector. Case studies are focused on the AI/deep learning and digitial plant technologies for diagnostics, enhancement of combustion and pollution control, performance prediction, and efficiency improvement in conventional steam power plants and renewable facilities (solar and wind power). Using actual data collected from those cases, hands-on practices are also conducted. | |||||||||