|Lecturer||Prof. Petros Koumoutsakos
Dr. Michael Bergdorf
|Class Room||CAB G61 (Lecture)
CAB G59 (Exercise)
|Class Times||Wednesdays, 15.15 – 17.00 (Lecture)
Fridays, 13.15 – 14.00 (Exercise)
|CAB F 84 Office Hours: bergdorf_AT_inf.ethz.ch|
The course provides a unifying framework for particle simulations of discrete and continuum systems. Recent advances in molecular, mesoscopic and macroscale simulations using particles will be discussed and common computing paradigms and challenges across disciplines identified.The simulation of the motion of interacting particles is a deceivingly simple, yet powerful and natural, method for exploring physical systems as diverse as proteins and planetary dark matter, bluff body flows and cancer tumor growth.Particle methods have been developed in the last years independently in a number of disciplines ranging from computer graphics to polymer physics. The goal of this course if to provide a unifying framework for particle simulations of discrete and continuum systems. We will discuss recent advances in molecular, mesoscopic and macroscale simulations using particles and we will identify common computing paradigms and challenges across disciplines.
Class Topics will include : Discretizations and Representations using Particles, Fast Summation Algorithms, Time Integrators, Adaptive Particle Methods. The exercises will draw on problems simulated using particles from areas such as nanotechnology,computer graphics and fluid dynamics.
These Notes are tentative and aim to assisting your taking notes during the class. Your FEEDBACK is welcome !
|Exercise||Hand in date||Solution|
|02.04.08||Class Notes (From MD to Approximations Using Particles) (pdf)|
If you hand in your exercises by email put as subject: [SUP08]. Please document your results in detail. Provide plots of your solutions. If you hand in your code always with a Readme file that provides information on how to run it.
|Exercise||Hand in date||Remarks|
|Serie1||07.03.08||Note: The lift distribution in part 2o of exercise 2 is an initial value for the particles; the Gamma_p of the particles remains constant in time.|
D.-B. Wang et al. Algorithm optimization in molecular dynamics simulation. Comp. Phys. Comm., 177(7), 2007 (pdf).
J. H. Williamson. Low-storage runge-kutta schemes. J. Comput. Phys., 35, 1980 (pdf).
Download the horse here
Scaffolding for the inside/outside algorithm.
|Serie 7||09.05.08||Level set of a horse (zip)|
|Serie 8||16.05.08||Fishpack (g77/generic) (zip)
Fishpack (intel fortran) (zip)