TY - CONF A1 - Abraham, O. A1 - Niederleithinger, Ernst A1 - Schmidt, F. A1 - Sörensen, J.D. A1 - Thöns, S. A1 - Chapeleau, X. A1 - Ferria, H. T1 - Infrastar Training School on Fatigue and Reliability Analysis of Structures - Training for Assessment of Risk N2 - The Infrastar training school provides lectures and hands-on training to Master and PhD students, early-stage researchers and (young) professionals on all aspects of asset management of civil infrastructures with respect to fatigue of materials. It is organized yearly since 2019 and up to 20 profiles are selected to attend the 3.5-day training. A team of 7 teachers provides insight in multi-disciplinary and intersectoral basic concepts in three core fields, ranging from the design to the dismantling of the structures (bridges and wind turbines): 1. Monitoring and auscultation, 2. Structural and action models, 3. Reliability, risk and decision analyses. Each year, a recognized expert is invited to deliver a keynote lecture to raise interest in a specific aspect of one of the fields covered. The presentation is recorded and published on the training school website. T2 - NDT-CE 2022 CY - Zurich, Switzerland DA - 16.08.2022 KW - Doctoral School KW - Multidisciplinary KW - Fatigue KW - Reliability PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-563253 UR - https://www.ndt.net/article/ndtce2022/paper/61021_manuscript.pdf SP - 1 EP - 3 PB - NDT.net AN - OPUS4-56325 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Berchtold, Florian A1 - Knaust, Christian A1 - Thöns, S. A1 - Rogge, Andreas T1 - Risk analysis in road tunnels – most important risk indicators N2 - Methodologies on fire risk analysis in road tunnels consider numerous factors affecting risks (risk indicators) and express the results by risk measures. But only few comprehensive studies on effects of risk indicators on risk measures are available. For this reason, this study quantifies the effects and highlights the most important risk indicators with the aim to Support further developments in risk analysis. Therefore, a system model of a road tunnel was developed to determine the risk measures. The system model can be divided into three parts: the fire part connected to the fire model Fire Dynamics Simulator (FDS); the evacuation part connected to the evacuation model FDS+Evac; and the frequency part connected to a model to calculate the frequency of fires. This study shows that the parts of the system model (and their most important risk indicators) affect the risk measures in the following order: first, fire part (maximum heat release rate); second, evacuation part (maximum preevacuation time); and, third, frequency part (specific frequency of fire). The plausibility of These results is discussed with view to experiences from experimental studies and past fire incidents. Conclusively, further research can focus on these most important risk indicators with the aim to optimise risk analysis. T2 - Seventh International Symposium on Tunnel Safety and Security CY - Boras, Sweden DA - 16.03.2016 KW - Fire KW - Risk KW - Road KW - Tunnel KW - Analysis PY - 2016 SN - 978-91-88349-11-8 SN - 0284-5172 SP - 637 EP - 648 CY - Boras, Sweden AN - OPUS4-37689 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -