DD2365/FDD3371 VT27 Advanced Computation in Fluid Mechanics (11776)

The goal of the course is to develop theoretical and practical skills in the field of computational fluid mechanics, with a focus on adaptive finite element methods, and to apply these skills to real world fluid mechanics problems. Research challenges in the field are highlighted, e.g., with respect to simulation of turbulent flow. The first part of the course presents a theoretical background and gives an introduction to computational tools, which are used in the second part of the course focused on project work. Projects are carried out either in pairs of two students, or as individual projects.

DD2365 is a mandatory course for the  Computational Science subtrack (Parallel Computation) of the Master's programme in Computer ScienceMaster's programme in Computer Science.

FDD3371 is a course on doctoral level (third cycle). 

Course schedule (Time Edit): TBA

Preparatory work: Introduction

Week plan

• w1 - Viscous flow + Unsteady flow
• w2 - Adaptive mesh refinement + Fluid-structure interaction
• w3 - Turbulence and Shock waves + Lab oral examination and project introduction (mandatory)
• w4 - Individual work
• w5 - Project seminar (minimum 4 mandatory)
• w6 - Project seminar (minimum 4 mandatory)
• w7 - Project seminar (minimum 4 mandatory)
• w8 - Project seminar (minimum 4 mandatory)
• w9 - Project seminar (minimum 4 mandatory)
• w10 - Project seminar (minimum 4 mandatory)
• w11 - Final project presentations (mandatory)

Lab oral examination: TBA

Schedule 4 mandatory project seminars: TBA

Final project presentations are scheduled for: TBA

Examination 
3.5hp (Grade: A, B, C, D, E, FX, F)

• Project presentations (4 progress + 1 final): max 20p = 50% of grade
• Project report (originality + analysis + structure): max 20p = 50% of grade 
• Grading: A (32p), B (26p), C (20p), D (16p), E (12p) 
  [Note: The automatic grading in Canvas is wrong – ignore it!]

Project
4.0hp (P/F)

• 4 lab reports (Jupyter notebooks) 
• 1 lab oral examination
• 1 project specification (max 1 page)
• 4 project progress presentations 
• 1 final project presentation
• 1 project report 

Teacher

• Johan Hoffman

Recommended prerequisite is any of the following courses: 

DD2363 Methods in Scientific Computing

SF2561 The Finite Element Method

Or similar.

Contact the course coordinator if unsure. 

Literature

Literature list

Course software repository

DD2365 FEniCSx GitHub repo ( legacy: DD2365 FEniCS repo)

Extra material

• Gallery of Fluid Motion
• UN Sustainable Development Goals

FDD3371 registration

The course will be joint run with the FDD3371 course on doctoral level (third level). To take the FDD3371 course please send an email to the course coordinator where you give the necessary information, use "FDD3371" in the email subject line. 

FDD3371 examination

• Pass the course assignments for DD2365 with at least grade B. 
• Submit a 1-page project proposal for future research work based on your project as an appendix to your project report, and present this as part of your final project presentation (P/F). 

Course specific information about generative AI

• Generative AI tools allowed according to given guidelines