P075 Scientific Computing and Visualization

Faculty of Informatics
Spring 2002
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Stanislav Bartoň, CSc. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Stanislav Bartoň, CSc.
Timetable
Mon 16:00–17:50 B117
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Syllabus
  • The goal of this course is the brief overview of the applications of higher mathematics in the technical and nature sciences. The mathematical basis of the technical problems, technological computations and nontrivial problems of the nature sciences are accented. No special knowledge are necessary to pass throw this course, the necessary theory is explained at the beginning of the problems solution, only the secondary - high school knowledge are required. The knowledge of the differential calculus of more variables and the symbolic algebra ere welcomed, (Maple, Derive).
  • The problems, (for example optimization of the heat insulation of the reservoir, the free compression of the metals, the bodies kinematics and dynamics, the optimization of the surfaces illumination, the classical celestial mechanics and others) are selected so, that it is possible to demonstrate how to use the symbolic algebra to solve nontrivial problems. The solving strategy is following: The definition of the problem, its physical model, the possibilities of its simplification, the initial and border conditions, the mathematical model, its symbolic algebra model (Maple, Derive), the possibility of its solution, the analytical solution (Maple, Derive) and its numerical solution (Maple, Matlab), the discussion about the results, the affect of the simplifications onto result, the visualization and animation of the solution (Maple, Matlab).
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 1997, Spring 1998, Spring 1999, Spring 2000, Spring 2001.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2002/P075