The objective of Module I (9 credits): Transport Phenomena in Fluids is to provide in-depth knowledge of the dynamics of transport-diffusion-dispersion phenomena in surface water bodies, with particular reference to estuarine and coastal environments. The course aims to provide the skills necessary to develop mathematical models suitable for the treatment of the main phenomena of interest, as well as their application to the simulation and study of realistic cases. At the end of the course, students will be able to: understand and model the dynamics of transport-diffusion-dispersion phenomena, apply mathematical models of appropriate complexity to realistic cases, obtain numerical data and interpret their meaning.
The objective of Module I (6 credits): Ocean Dynamics is to provide in-depth knowledge of the dynamics of phenomena characterizing the dynamics of seas and oceans, with particular reference to estuarine and coastal environments. The course aims to provide the skills necessary to develop mathematical models suitable for the treatment of the main phenomena of interest, as well as their application to the simulation and study of realistic cases. Upon completion of the course, students will be able to: understand and model the dynamics of turbulent transport-diffusion-dispersion phenomena; apply mathematical models of appropriate complexity to realistic cases; obtain numerical data and interpret their meaning.
The objective of Module I (6 credits): Ocean Dynamics is to provide in-depth knowledge of the dynamics of phenomena characterizing the dynamics of seas and oceans, with particular reference to estuarine and coastal environments. The course aims to provide the skills necessary to develop mathematical models suitable for the treatment of the main phenomena of interest, as well as their application to the simulation and study of realistic cases. Upon completion of the course, students will be able to: understand and model the dynamics of turbulent transport-diffusion-dispersion phenomena; apply mathematical models of appropriate complexity to realistic cases; obtain numerical data and interpret their meaning.
