ESE5008 Environmental Fluid Mechanics: Fundamentals and Simulation Methods

This is an introductory level course dealing with the properties and behavior of fluids in usual civil, ocean and environmental engineering applications. The fundamental principles of continuity, energy and momentum are introduced and applied to applications that include fluid statics, fluid dynamics, pipe flows, similarity laws, fluid loading, unsteady flows, as well as influence of boundary layers on outer potential flow.

The course provides essential knowledge for studying natural flow phenomena in rivers, oceans, and the atmosphere, as well as the engineering design of hydraulic structures. In addition, this course introduces key state-of-the-art numerical techniques, followed by direct applications using popular open source CFD codes.

Upon successful completion, students will have the knowledge and skills to:

1. Interpret and explain environmental water flows at small, large and global scale. Understand key mathematical foundations covering the main fluid mechanics equations as well as the most popular numerical techniques to solve them.

2. Explain the physical principles of convection, fluid momentum, viscous forces, drag and diffusion.

3. Evaluate the environmental impact on water flows of engineered water management systems (including dams, ships, pipes and channels).

ESE5010 Data Analysis for Environmental Engineering and Science

As one of the fastest-moving fields, data science has profoundly impacted environmental research. It supports our deeper understanding of the complex natural environment and facilitates the development of new engineering strategies to mitigate crises such as climate change.

This is an introductory level course to provide fundamental concepts and encourage open-ended exploration of the increasingly topical intersection between data science and the environmental sciences. In particular, the course offers a general description and hands-on practice of various state-of-the-art data analysis technologies to address common data problems faced in environmental science and engineering, particularly data complexity, spatial and temporal reasoning, and uncertainty quantification.

Upon successful completion, students will have the knowledge and skills to choose and apply state-of-the-art data analysis techniques to various environmental science and engineering problems.