Elements of mathematics and scripting useful for the study of materials.
| On completion of the unit, the student will be capable of: | Classification level | Priority |
|---|---|---|
| handle mathematical tools (matrices, vectors, tensors, diff. operators) | 3. Apply | Essential |
| solve PDEs and ODEs | 2. Understand | Important |
| formulate and solve a problem in 3D or 2D geometry | 3. Apply | Essential |
| describe and analyze non-reproducibility of experimental tests | 4. Analyse | Essential |
| serenely handle informatic tools | 3. Apply | Essential |
| script in python and matlab | 3. Apply | Important |
| interact with experts in numerical modelling | 2. Understand | Essential |
| Percentage ratio of individual assessment | Percentage ratio of group assessment | ||||
|---|---|---|---|---|---|
| Written exam: | 60 | % | Project submission: | % | |
| Individual oral exam: | % | Group presentation: | % | ||
| Individual presentation: | % | Group practical exercise: | % | ||
| Individual practical exercise: | 40 | % | Group report: | % | |
| Individual report: | % | ||||
| Other(s): % | |||||
| Type of teaching activity | Content, sequencing and organisation |
|---|---|
| Lecture + Training | Vectors, matrices and tensors 2D and 3D geometry |
| Coding | Application on image segmentation on python : extraction of polygonal features, simplification thereof and post-processing on GMSH |
| Lecture + Training | Ordinary Differential Equations, Euler method Statistics and probabilities Non-linear problems and solvers (Newton and fixed-point) |
| Coding | Droplet trajectory simulation through (non-)linear ODE solving and probabilistic assessment of the impact point on matlab |
| Lecture + Training | Differential operators and Partial Differential Equations Signal processing and Fast Fourier Transform |
| Coding | Resolution of diffusive equations by FFT on matlab, simulation of a sample distortion (through external library on matlab) and visualization (GMSH) |