Subject Datasheet
PDF letöltéseI. Tantárgyleírás
1. Alapadatok
1.1 Tantárgy neve
Engineering Risk Assessment
1.2 Azonosító (tantárgykód)
BMEEOHSMSFST05-00
1.3 Tantárgy jellege
Kontaktórás tanegység
1.4 Óraszámok
| Típus | Óraszám / (nap) |
| Előadás (elmélet) | 1 |
| Gyakorlat | 1 |
1.5 Tanulmányi teljesítményértékelés (minőségi értékelés) típusa
Félévközi érdemjegy
1.6 Kreditszám
3
1.7 Tárgyfelelős
| név | Dr. Vigh László Gergely |
| beosztás | Egyetemi docens |
| vigh.laszlo.gergely@emk.bme.hu |
1.8 Tantárgyat gondozó oktatási szervezeti egység
Hidak és Szerkezetek Tanszék
1.9 A tantárgy weblapja
1.10 Az oktatás nyelve
magyar
1.11 Tantárgy típusa
Kötelező a Szerkezet-építőmérnök (MSc) szakon
1.12 Előkövetelmények
1.13 Tantárgyleírás érvényessége
2025. szeptember 1.
2. Célkitűzések és tanulási eredmények
2.1 Célkitűzések
The objective of the course is that the student shall understand and be aware of the principles and basis of practical methods of engineering risk assessment and analysis, and their application especially to extreme actions (earthquake, fire, extreme snow, blast load, tornado, etc.) It includes the fields of extreme effects, statistics, probability theory, reliability analysis, numerical methods, risk analysis and optimization. It also serves as the basis of the subsequent MSc subjects on modelling, design and programming.
The aim is that during the semester, students will acquire a complex knowledge of engineering risk assessment at a level that will allow them to present this competence as an element of their portfolio.
2.2 Tanulási eredmények
A tantárgy sikeres teljesítése utána a hallgató
A. Tudás
1. is aware of the principles and basic terms of statistics and probability theory, knows the basic statistical analysis and assessment methods,
2. is aware of the uncertainties in engineering problems, the distribution functions that are typical in civil engineering problems, and the model development methods,
3. is aware of the terms of failure probability and reliability index, the principles of basic reliability analysis methods (FORM, SORM and Monte Carlo analysis),
4. is aware of the definition of risk, principles of risk analysis and decision making analysis,
5. understands the objective function of optimization, can distinguish local and global optimum, and is aware of the principles of the most important classic optimization techniques,
6. is aware of extreme actions and the corresponding design methods,
7. is aware of the risk assessment methods applicable to extreme effects,
8. knows reliability background of Eurocode standards, and their provisions and design methods.
B. Képesség
1. applies the statistical and analysis methods for assessment of measuring results,
2. is able to develop models,
3. solves simple reliability problems by FORM and Monte Carlo methods using specific softwares,
4. computes risk on the basis simple logic tree,
5. applies provisions and design methods of Eurocode standards,
6. is able to complete optimization in practice,
7. applies risk analysis for extreme effects,
8. is able to present his/her results in proper written form,
C. Attitűd
1. follows the lectures, makes effort to understand the study material,
2. collaborates with the teacher in gaining knowledge,
3. is continuously gaining knowledge,
4. is open to the use of IT tools and equipments,
5. aims accuracy in his/her calculations/solutions,
D. Önállóság és felelősség
1. is independent in problem statements and solutions,
2. aims understanding the complexity, comprehensiveness of the problems and recognizing the synergies.
2.3 Oktatási módszertan
Theoretical lectures and practical seminars are basically not separated, but are held in hybrid way. Theoretical parts emphasize the principles; rigorous mathematical derivation is not addressed. Practical parts illustrate the practical application of the methods, incorporating the use of specific practical tools. Active involvement in and communication during the lectures are expected, helping the understanding of the study material. Homeworks help strenghtening the skills, while control tests support in deepen the knowledge. The subject uses elements if Research Based Learning methods.
2.4 Részletes tárgyprogram
1. Introduction.
2. Problem statement in engineering, model development.
3. Uncertainties in engineering problems.
4. Mechanical model, numerical analysis methods.
5-6. Basis of statistics and probability theory. Statistical analysis in practice.
7. Summary.
7-8. Methods of reliability analysis: practical use of FORM, SORM, Monte Carlo analysis.
9. Optimization. Basics of linear programming and gradient method.
10. Acceptable risk. Risk assessment, decision making.
11. Risk assessment methods.
12. Eurocode. Code evolution. Reliability background of Eurocodes.
13. Extreme effects. Earthquake. Extreme snow. Fire.
14. Extreme effects. Tornado. Blast load. Summary.
A félév közbeni munkaszüneti napok miatt a program csak tájékoztató jellegű, a pontos időpontokat a tárgy honlapján elérhető "Részletes féléves ütemterv" tartalmazza.
A félév közbeni munkaszüneti napok miatt a program csak tájékoztató jellegű, a pontos időpontokat a tárgy honlapján elérhető "Részletes féléves ütemterv" tartalmazza.
2.5 Tanulástámogató anyagok
a) Textbooks, literature:
Wilcox: Numerical methods for PDEs. Unit 2, 16.90 Computational Methods in Aerospace Engineering, MITOpenCourseware.
Hoffman – Frankel: Numerical methods for engineers and scientists. CRC Press, 2001.
Faber: Risk and safety in civil, environmental and geomatic engineering
Sorensen: Structural reliability theory and risk analysis
Lyons , R.G.: Understanding Digital Signal Processing . Prentice Hall, 2001.
Rao, S.R.: Engineering optimization – Theory and practice. Fourth Edition. Wiley, 2009.
b) Online materials:: materials uploaded to the web site of the subject, e.g.:
Lecture notes, electronic lecture notes,
slides of lectures and practices,
solved problems
midterm test samples with solution
2.6 Egyéb tudnivalók
0
2.7 Konzultációs lehetőségek
The instructors are available for consultation during their office hours, as advertised on the information system. Special appointments can be requested via e-mail. Consultation during lecture breaks is also available.
Jelen TAD az alábbi félévre érvényes:
2025/2026 semester II
II. Tárgykövetelmények
3. A tanulmányi teljesítmény ellenőrzése és értékelése
3.1 Általános szabályok
The achievements of this course will enable the student to demonstrate mastery of the structural engineering profession on completion of the full course, if the final mark is excellent (5).
The assessment of the learning outcomes specified in clause 2.2. above and the evaluation of student performance occurs via midterm stests, homework assignments and continuous performance assessments.
3.2 Teljesítményértékelési módszerek
| Assessment Name (Type) | Code | Assessed Learning Outcomes |
|---|---|---|
| Control Test #1 | of the progress presentations are accepted by the supervisor. | CT1 |
| Control Test #2 | CT2 | |
| Homework* | HW | |
| continuous performance assessment | A | |
| *Progress presentations are assigned to the homework; the actual schedule is announced on the web site of the subject. Criterion for final submission of the homework is that at least 50 |
A szorgalmi időszakban tartott értékelések pontos idejét, a házi feladatok ki- és beadási határidejét a "Részletes féléves ütemterv" tartalmazza, mely elérhető a tárgy honlapján.
3.3 Teljesítményértékelések részaránya a minősítésben
| Code | Weight |
|---|---|
| CT1 | 20% |
| CT2 | 20% |
| HW | 40% |
| A | 20% |
| Total | 100% |
3.4 Az aláírás megszerzésének feltétele, az aláírás érvényessége
No signature can be obtained.
3.5 Érdemjegy megállapítása
| Grade | Score (P) |
|---|---|
| excellent (5) | 85≤P |
| good (4) | 70≤P<85% |
| satisfactory (3) | 55≤P<70% |
| pass (2) | 40≤P<55% |
| fail (1) | P<40% |
3.6 Javítás és pótlás
1. Late submission of homeworks – with penalty fee applied – is normally possible two weeks after the normal deadline. In case the normal deadline of a homework falls on the last week of the study period, the late submission deadline is the last day of the supplementary week, at 12:00. Schedule and details on the homework submissions can be found on the web site of the subject.
2. Each CT can be repeated (2nd attempt) during the supplementary week; the exact date and time of the repetition is announced on the web site of the subject. The new result overwrites the result of the 1st attempt.
3. “Continuous performance assessment” A cannot be repeated, cannot be substituted with other forms of activity.
3.7 A tantárgy elvégzéséhez szükséges tanulmányi munka
| Activity | Hours/Semester |
|---|---|
| contact hours | 14×2=28 |
| preparation for the lectures and | 12×0,5+2×8=22 |
| for continuous performance assessments | |
| preparation for the tests | 5 |
| homework | 35 |
3.8 A tárgykövetelmények érvényessége
2025. szeptember 1.
Jelen TAD az alábbi félévre érvényes:
2025/2026 semester II