Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Numerical Methods
1.2 Code
BMEEOTMDT73
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 2 |
1.5 Evaluation
Exam
1.6 Credits
3
1.7 Coordinator
| name | Dr. Németh Róbert |
| academic rank | Associate professor |
| nemeth.robert@emk.bme.hu |
1.8 Department
Department of Structural Mechanics
1.9 Website
1.10 Language of instruction
hungarian and english
1.11 Curriculum requirements
Ph.D.
1.12 Prerequisites
1.13 Effective date
5 February 2020
2. Objectives and learning outcomes
2.1 Objectives
Extend the knowledge of linear algebra by understanding the algorithmic properties of typical numerical methods
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
- knows the basic methods for the solution of typical civil engineering problems
B. Skills
- is able to formulate the basic algorithms
C. Attitudes
- ready to learn
D. Autonomy and Responsibility
- is autonomous
2.3 Methods
Lecture presentation of the deivation of algorithms
2.4 Course outline
| Week | Topics of lectures and/or exercise classes |
| 1. | Review of linear algebra 1. |
| 2. | Review of linear algebra 2. |
| 3. | Non-homogeneous linear equations - Factorization methods 1. |
| 4. | Non-homogeneous linear equations - Factorization methods 2. |
| 5. | Non-homogeneous linear equations - iterative methods 1. |
| 6. | Non-homogeneous linear equations - iterative methods 2. |
| 7. | Eigenvalue problems - manual solution, power iteration |
| 8. | Eigenvalue problems - inverse iteration, subspace iteration |
| 9. | Eigenvalue problems - Rayleigh-Ritz method, polynomial iteration |
| 10. | Eigenvalue problems - transformation methods |
| 11. | Nonlinear equations - minimization in 1D, Newton-type methods |
| 12. | Nonlinear equations - gradient-type methods |
| 13. | Nonlinear equations - Gaussian section, Quasi-Newton methods, Implicit Function Theorem |
| 14. | Summary |
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials
- Gene H. Golub - Charles F. Van Loan: Matrix Computations, The Johns Hopkins University Press, Baltimore, 2013
2.6 Other information
2.7 Consultation
The instructors are available for consultation during their office hours, as advertised on the department website. Special appointments can be requested via e-mail: nemeth.robert@epito.bme.hu.
This Subject Datasheet is valid for:
Inactive courses
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
There is an oral exam, where the student presents the solution of a numerical problem from his/her research, then related questions must be answered.
3.2 Assessment methods
| Evaluation form | Abbreviation | Assessed learning outcomes |
| Oral exam | E | A.1; B.1; C.1; D.1 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Abbreviation | Score |
| E | 100% |
| Sum | 100% |
3.4 Requirements and validity of signature
Presence on the lectures
3.5 Grading system
| Grade | Points (P) |
| excellent (5) | 90=P |
| good (4) | 75<=P<90 |
| satisfactory (3) | 65<=P<75 |
| passed (2) | 50<=P<65 |
| failed (1) | P<50 |
3.6 Retake and repeat
There is no retake
3.7 Estimated workload
| Activity | Hours/semester |
| participation on the lectures | 14×2=28 |
| homeworks | 14×0.5=7 |
| preparation for the exam | 55 |
| Sum | 90 |
3.8 Effective date
5 February 2020
This Subject Datasheet is valid for:
Inactive courses