Course Details
Theory of Structures Reliability
Academic Year 2023/24
NDA029 course is part of 1 study plan
NPC-SIK Summer Semester 1st year
Introduction of reliability theory, reliability background of standards for structural design (Eurocodes), Structural resistance and load action as two independent random variables, limit state and philosophy of design according to standards, theoretical failure probability, reliability conditions, reliability reserve, reliability index, numerical simulation methods of Monte Carlo type, Latin Hypercube Sampling, Importace Sampling, basic methods for failure probability analysis of structures designed by standards for design, basic methods for statistics, sensitivity and probabilistic analysis application to steel structures design. Introduction into risk engineering.
Course Guarantor
Institute
Objective
Students will get basic knowledge from theory of structural reliability: Stochastic model creation, reliability condition, numerical simulation methods of Monte Carlo type, limit states, risk engineering. Present reliability software will be introduced.
Knowledge
Student will learn basic knowledge from theory of structural reliability: Stochastic model creation, reliability condition, numerical simulation methods of Monte Carlo type, limit states, risk engineering. Present reliability software will be introduced.
Syllabus
1. Introduction of reliability theory, reliability background of standards for structural design (Eurocodes), structural resistance and load action as two independent random variables, reliability condition, reserve of reliability.
2. Limit state and philosophy of design by standards.
3. Reliability standards: theoretical failure probability, reliability index.
4. Aproximation methods FORM a SORM.
5. Numerical simulation method Monte Carlo in applications.
6. Computation model, model uncertainty, grosses errors.
7. Numerical simulation methods Latine Hypercube Sampling, Importace Sampling in applications.
8. Random process and random fields – Stochastic finite element methods and these applications.
9. Probabilistic optimization, problems of live-time of structures.
10. Weibull theory.
11. Unbalanced levels of the failure probability of the structures designed by standards, option of input variability modelling.
l2. Introduction of Risk engineering.
13. Reliability software – summary and conclusion.
2. Limit state and philosophy of design by standards.
3. Reliability standards: theoretical failure probability, reliability index.
4. Aproximation methods FORM a SORM.
5. Numerical simulation method Monte Carlo in applications.
6. Computation model, model uncertainty, grosses errors.
7. Numerical simulation methods Latine Hypercube Sampling, Importace Sampling in applications.
8. Random process and random fields – Stochastic finite element methods and these applications.
9. Probabilistic optimization, problems of live-time of structures.
10. Weibull theory.
11. Unbalanced levels of the failure probability of the structures designed by standards, option of input variability modelling.
l2. Introduction of Risk engineering.
13. Reliability software – summary and conclusion.
Prerequisites
Knowledge from Elasticity and plasticity, Structural mechanics, Probability and statistics.
Language of instruction
Czech
Credits
4 credits
Semester
summer
Forms and criteria of assessment
course-unit credit and examination
Specification of controlled instruction, the form of instruction, and the form of compensation of the absences
Extent and forms are specified by guarantor’s regulation updated for every academic year.
Offered to foreign students
Not to offer
Course on BUT site
Lecture
13 weeks, 2 hours/week, elective
Syllabus
1. Introduction of reliability theory, reliability background of standards for structural design (Eurocodes), structural resistance and load action as two independent random variables, reliability condition, reserve of reliability.
2. Limit state and philosophy of design by standards.
3. Reliability standards: theoretical failure probability, reliability index.
4. Aproximation methods FORM a SORM.
5. Numerical simulation method Monte Carlo in applications.
6. Computation model, model uncertainty, grosses errors.
7. Numerical simulation methods Latine Hypercube Sampling, Importace Sampling in applications.
8. Random process and random fields – Stochastic finite element methods and these applications.
9. Probabilistic optimization, problems of live-time of structures.
10. Weibull theory.
11. Unbalanced levels of the failure probability of the structures designed by standards, option of input variability modelling.
l2. Introduction of Risk engineering.
13. Reliability software – summary and conclusion.
Exercise
13 weeks, 2 hours/week, compulsory
Syllabus
1. Statistical evaluation of random variable.
2. Recapitulation of probability and statistics using simple examples.
3. Examples on usage of Cornell reliability index.
4. Simple example to learn Monte Carlo simulation method using Excel.
5. Calculations of failure probability via Latin Hypercube Sampling in Excel.
6. More complex examples on simulation methods using Excel.
7. Evaluation of previous examples in Freet.
8. Failure probability estimation using FORM method (First Order reliability Method).
9. Calculation of failure probability using Importance Sampling.
10. Introduction to individual semestral project.
11.–13. Work on individual semestral projects.