Research in Engineering Risk Analysis
We perform research in the broad area of optimized decision-making in engineering systems under uncertainty. In particular, we work on reliability analysis, predictive modeling and sensitivity analysis, risk assessment and management methods.
Key research areas of the group include:
- Reliability analysis methods
- Risk assessment
- Bayesian predictive modeling
- Decision analysis
- Predictive maintenance & value of information
- Natural hazards
- Reliability of structures
- Reliability of sensing systems
Ongoing research projects
- Assessment and optimization of monitoring and inspection in aging structures. 2016-2019, funded by DFG
- BAYES - Bayesian updating of engineering models with spatially variable properties. 2016 - 2019, in collaboration with TUM Chair of Numerical Mathemathics, funded by IGGSE / DFG
- Reliability of hydraulic structures considering spatial variability. 2017-2020, funded by BAW
- Reliability and sensitivity assessment with data assimilation for improved decision support. 2016-2019, funded by DFG
- Grusibau 2.0 - Structural codes for the 21st century. 2017 - 2020, funded by DIBt
- RIESGOS - Multirisk analysis and information system components for the Andes region. 2017-2020, with DLR, GfZ Potsdam and others, funded by BMBF
- Validation of sensor systems for automated vehicles. 2015-2018, funded by AUDI