Semester projects
Project proposals Spring Semester 2026
The following is a list of proposals for semester projects offered at the Chair of Risk, Safety and Uncertainty Quantification. To enquire about conducting a project at the Chair, please directly contact the responsible supervisor.
Optimization of truss structures
Supervisor: M. Moustapha
Optimization is a major task in the design of structures where the analyst seeks to reduce the cost while ensuring that some performance criteria are met.
Many approaches have been developed in the literature depending on whether uncertainties are directly accounted for in the design process or not. The goal of this project is to perform a comparative study of various methods for deterministic and reliability-based design optimization (respectively DDO and RBDO).
In this project, students will design a truss structure using Abaqus as main case study. They will then proceed to optimize this structure in various configurations using UQLab, the Chair’s Matlab platform for uncertainty quantification.
Prerequisites: At least one of the following two courses
Additional information
- Group work: Yes (2)
Active learning reliability analysis
Supervisor: M. Moustapha
Structural reliability aims at assessing the reliability of a system by evaluating the probability of failure, i.e., the probability that the system fails to fulfil some performance requirements due to uncertainties in the system itself and its environment.
Active learning reliability is the most efficient method for assessing reliability. It relies on an inexpensive surrogate of the limit-state function built by evaluating the original limit-state over a carefully selected set of design points. The latter are sequentially identified using a so-called learning function.
In this project, the student(s) will benchmark recent learning functions in the literature and implement the most promising ones. They will then compare their performance against the ones currently available in UQLab, the chair's platform for uncertainty quantification.
Prerequisites (at least one)
Additional information
- Group work: Yes (2)
Leja sequences and experimental design for PCE
Supervisor: N. Lüthen
Polynomial chaos expansion (PCE) are a popular surrogate modelling method in the field of uncertainty quantification. The surrogate is constructed based on a limited number of evaluations of the original expensive model (experimental design). In order to construct a reliable surrogate, it is essential to use an informative set of training points.
The goal of this semester project is to implement the recently proposed experimental design method of Leja sequences using the UQ software UQLab, to investigate its potential for surrogate modeling, and to compare its performance to other established experimental design methods.
Prerequisites:
- Uncertainty Quantification in Engineering
- Basic knowledge of MATLAB programming
Additional information:
- Group work: No
Neural operators for civil engineering
Supervisor: S. Marelli
Neural operators are a recently proposed data-driven technique to emulate the behavior of complex, time-dependent models. While the body of literature on their properties is constantly growing, few applications exist to mechanical and civil engineering. The goal of this project is to benchmark their performance in Engineering scenarios.
This project will assess the usability and performance of the NeuralOperator pytorch package (https://github.com/neuraloperator/neuraloperator) on a multi-story building subject to seismic excitation.
Prerequisites:
- Uncertainty Quantification in Engineering
- Basic Python proficiency
Additional information:
- Group work: No
Completed projects
For a list of past semester projects conducted at our Chair, click here.