6 EC
Semester 2, periode 4
5132MOSI6Y
The course provides a detailed introduction to simulation and modelling techniques commonly used in the earth and natural sciences. The course is primarily intended for students from the Future Planet Studies bachelor’s program but is equally useful for those wishing to apply simulation and modelling techniques in related fields. Students in this course are required to have had experience in basic programming in Matlab, and acquaintance with classical mathematical models in geo-ecosystems or related fields such as ecology and/or evolution.
Suggested reading material will be provided together with the weekly assignments. This material is not necessary for completing the worksheets, it will be provided as extra enrichment and/or extra support.
On Mondays weekly assignments (6) will be published with the hands on activities the students need to carry out that week.
Matlab
Students will need to bring their personal laptops to the lectures, to the practicals and to the exam.
Matlab needs to be installed before the first lecture!
The students will be acquainted with simulation and modelling techniques appropriate for modeling spatially explicit dynamical processes based on Ordinary and Partial Differential Equations; by the end of the course students will be able to apply these for solving simple scientific problems.
The students will develop practical expertise, including experience in the process of abstracting real systems into models; by the end of the course students will be able to "translate" a true scientific question from the natural world into an appropriate framework.
The students will gain foundations in solving scientific problems through modelling and simulation; by the end of the course students will be able to logically choose an appropriate modelling framework for a particular scientific question and explain which level of detail they believe is appropriate to incorporate.
The hands-on modelling exercises will support expansion of the students’ ability to carry out critical and creative scientific research; by the end of the course students will be able to critically evaluate the approach of true scientific studies they are presented with.
Simulation and modelling in natural sciences require both skills (i.e., programming, developing algorithms, and solving equations) and techniques (i.e., the ability to recognise what is important and needs to be represented in the model, and what can and should be left out). Because this is a course designed for beginners, focus is given to both aspects— the technical side of constructing models and the ability to identify appropriate degrees of abstraction.
Because there is no absolute set of rules that can universally be prescribed for insuring successful modelling results; students will be confronted with realistic and concrete hands-on modelling exercises throughout the course through which they can gain proficiency in the process of abstracting real systems into models and other practical expertise relevant to modelling and simulation. This will also support the development of each student's personal understanding and intuition, providing them with foundations for critical and creative problem solving in the natural sciences through simulation and modelling.
|
Activity |
Number of hours |
|
Lecture |
14 |
|
Laptopcollege |
56 |
|
Exam |
3 |
|
Self study |
89.6 |
Aanwezigheidseisen opleiding (OER-B):
Aanvullende eisen voor dit vak:
| Onderdeel en weging | Details |
|
Eindcijfer | |
|
1 (100%) Tentamen |
Student final grade will be based on the score of the final exam and on the 6 assignments handed in by the students throughout the course. The final grade will be based on a weighted average between the assignments submitted throughout the course (1/3) and the final exam (2/3): the score of the exam cannot be less than 4.5, and the assignments will only be included in the final grade if: a) the exam mark falls between 4.5 and 5.5, and b), if the final grade after inclusion of the assignments is higher. In such cases the final grade will never be higher than 6.0.
| Learning objective: | Test 1: | Test item 2: |
|---|---|---|
| #1. | ||
| #2. | ||
| #3. | ||
| #4. | ||
| #5. | ||
| #6. | ||
For students that are enrolled in the course for the 2nd/3rd/etc. time, it is still mandatory to complete all components
Om een inzagemoment aan te vragen, kun je contact opnemen met de coördinator.
Up to 20 working days after the announcement of the result students have the right to inspect their work. Students can make an appointment with the course coordinator, Dr. Artzy-Randrup at Yael.Artzy@UvA.nl
The assignment has to be submitted individually, students are allowed to discuss with each other but they must not provide final solutions or scripts to each other.
The assignment has to be submitted individually, students are allowed to discuss with each other but they must not provide final solutions or scripts to each other.
The assignment has to be submitted individually, students are allowed to discuss with each other but they must not provide final solutions or scripts to each other.
The assignment has to be submitted individually, students are allowed to discuss with each other but they must not provide final solutions or scripts to each other.
The assignment has to be submitted individually, students are allowed to discuss with each other but they must not provide final solutions or scripts to each other.
The assignment has to be submitted individually, students are allowed to discuss with each other but they must not provide final solutions or scripts to each other.
|
Work assignment #1 (individually) |
Deadline |
Single ODE models |
|
Work assignment #2 |
Deadline |
Coupled ODE models |
|
Work assignment #3 |
Deadline |
Diffusion in space |
|
Work assignment #4 |
Deadline |
Reaction-Diffusion |
|
Work assignment #5 |
Deadline |
Groundwater flow |
|
Work assignment #6 |
Deadline |
Reaction-Advection-Diffusion |
Dit vak hanteert de algemene 'Fraude- en plagiaatregeling' van de UvA. Hier wordt nauwkeurig op gecontroleerd. Bij verdenking van fraude of plagiaat wordt de examencommissie van de opleiding ingeschakeld. Zie de Fraude- en plagiaatregeling van de UvA: http://student.uva.nl
Week 1 - Single ODE models (Feb 4th & 6th)
Week 2 - Coupled ODE models (Feb 11th & 13th)
→ Worksheet-1 submission deadline: Feb 13th at 13:00
Week 3 - Diffusion in space (Feb 18th & 20th)
→ Worksheet-2 submission deadline: Feb 20th at 13:00
Week 4 - Reaction-Diffusion (Feb 25th & 27th)
→ Worksheet-3 submission deadline: Feb 27th at 13:00
Week 5 - Groundwater flow (March 4th & 6th)
→ Worksheet-4 submission deadline: March 6th at 13:00
Week 6 - Advection I (March 11th & 13th)
→ Worksheet-5 submission deadline: March 13th at 13:00
Week 7 - Advection II (March 18th & 20th)
Week 8 - Final exam (March 27th)
→ Worksheet-6 submission deadline: March 25th at 13:00
* Note: Minor shifts in the schedule may take place during the course (with early notice). In any event, these will not have effect on the basic structure or design of the course.
Het rooster van dit vak is in te zien op DataNose.
1) Experience with basic programming in Matlab
2) Software and personal laptop: Students will need to bring their personal laptops to the lectures, practical’s and the exam. Matlab needs to be installed before the first meeting (for assistance see below).
FNWI offers licenses for MATLAB, including instructions for both Windows and Mac, as well as software support:
From 2013-2014, we have chosen to provide students with a better understanding of quality assurance by means of the table below. That is why we take a brief overview of the student evaluation and the resulting actions to improve the course.
Teacher's comment:
Some of the students felt they had fallen behind already in the early stages of the course and found it difficult to get back on track. To address this, I removed a two-week section of the course (the last two weeks of the course that were devoted to Cellular Automata). Instead I added two weeks to the beginning of the course as an extended introduction so students have more time to gain experience and confidence with the basic building blocks of the course are required for the later stages of the course. I also refreshed and reorganised all the remaining sections of the course accordingly, as well as replacing some of the earlier material that had not been from my area of expertise with case studies that are. The removal of the CA block should be helpful for the students in itself since this implies that student can focus on one type of modeling approach (i.e., based on differential equations), decreasing the risk of confused or overload by multiple modelling approaches.
Another addition is that at the end of each week students will have access to a self-assessment form with simple exercises and/or questions they can practice on.
Finally, some students felt they could use more 1-1 support from the TA's. The course this year is smaller in size that it was last year, while still maintaining the same number of TA's. Hopefully the students will feel they have sufficient support this year. They are always welcome to schedule an appointment with me outside of class hours, and I am also available during practicals to answer questions. Indeed, most students commented that I was easily approachable and always took time to explain patiently, I encourage the students to do so if for example they feel they are falling behind or for another reason.
Course coordinator:
Dr. Yael Artzy-Randrup (Yael.Artzy@UvA.nl)
Teaching assistants:
Emma Polman, Caper Borgman and Walter van Dijk