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101-0178-01L 3 Credits DR , MSC D-BSSE , D-BAUG , D-MAVT , D-ARCH , D-INFK , D-PHYS , D-MATH , D-ITET
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Uncertainty Quantification in Engineering

Lecturers & Examiners: Dr. Nora Lüthen
VVZ CR n/a

Last Updated: 2026-06-01 11:32:59

Abstract

Uncertainty quantification aims at studying the impact of aleatory and epistemic uncertainty onto computational models used in science and engineering. The course introduces the basic concepts of uncertainty quantification: probabilistic modelling of data (copula theory), uncertainty propagation techniques (Monte Carlo simulation, polynomial chaos expansions), and sensitivity analysis.

Objective

After this course students will be able to properly pose an uncertainty quantification problem, select the appropriate computational methods and interpret the results in meaningful statements for field scientists, engineers and decision makers. The course is suitable for any master/Ph.D. student in engineering or natural sciences, physics, mathematics, computer science with a basic knowledge of probability theory.

Content

The course introduces uncertainty quantification through a set of practical case studies that come from civil, mechanical, nuclear and electrical engineering, from which a general framework is introduced. The course in then divided into three blocks: probabilistic modelling (introduction to copula theory), uncertainty propagation (Monte Carlo simulation and polynomial chaos expansions) and sensitivity analysis (correlation measures, Sobol' indices). Each block contains lectures and tutorials using Matlab and the in-house software UQLab ( www.uqlab.com ).

Resources

Lecture Notes

Detailed slides are provided for each lecture. A printed script gathering all the lecture slides may be bought at the beginning of the semester.

Learning Materials (Links)

General Information

Language
English
Levels
DR , MSC
Frequency
Yearly recurring

Examination

Type
end-of-semester examination
Mode
written 120 minutes
Aids
All lecture notes (printed/handwritten) allowed. A calculator without possibility of external communication is needed (see DBAUG list). Other electronic devices are not allowed.
Final grade: 80% on final exam, compulsory continuous performance assessment task during semester (20% on mini-project) need not be passed on its own.

Course Components

Type Title Time & Place Hours
lecture with exercise Uncertainty Quantification in Engineering
  • Thu 15:45-17:30 (HCI J 7)
2 h weekly

Offered In