PSAM 16 Conference Paper Overview
Welcome to the PSAM 16 Conference paper and speaker overview page.
Lead Author: Marius Bittner Co-author(s): Marco Behrendt behrendt@irz.uni-hannover.de
Jasper Behrensdorf behrensdorf@irz.uni-hannover.de
Michael Beer beer@irz.uni-hannover.de
| Epistemic uncertainty quantification of localised seismic power spectral densities |
|---|
| The modelling and quantification of seismic loadings such as earthquakes to improve the safe design of structures is a challenging task. In particular, the unpredictable nature of earthquake characteristics like amplitude, dominant frequencies, and duration pose a great risk especially for sensitive structures like power plants, oil rigs, high-rise buildings, or large-span structures. The analysis, understanding and evaluation of those seismic characteristics and their influence on safe structural design is especially important for regions prone to earthquakes. The tectonic mechanisms leading to seismic underground waves are complex but measurements of earthquakes and their mechanical causes on surfaces are available manifold. A new procedure is presented herein for describing uncertainties in the power spectral density (PSD) function of seismic loadings and utilises the novel approach of Sliced-Normal distributions to describe multivariate probability density functions over frequency and amplitude. This representation enables analysts of stochastic dynamic systems the usage of a compact description for PSD functions and to reduce epistemic uncertainties on specific regions. This newly formed PSD function can be used in the simulation of seismic loads via spectral representation or other spectral-based stochastic process generators and is a subsequent development of the already introduced relaxed PSD function. |
Paper BI52 Preview
Author and Presentation Info
Lead Author Name: Marius Bittner (bittner@irz.uni-hannover.de)
Bio: Graduated 2018 with a M.Sc. in “Computational Methods in Engineering” at the University of Hannover. During the master absolved a semester abroad at the International Joint Research Center for Engineering Reliability and Stochastic Mechanics, Tongji University, China. Since 2019 working at the Institute for Risk and Reliability at the University of Hannover as research assistant and pursuing a PhD in “Efficient reliability analysis for complex high dimensional stochastic dynamic systems”. Since 2021 joined the International Research Training Group 2657 “Computational Mechanics Techniques in High Dimensions” hosted by the University of Hannover and the ENS Paris-Saclay.
Country: Germany
Company: Institute of Risk and Reliability, Leibniz University Hannover
Job Title: Research assistant
Bio: Graduated 2018 with a M.Sc. in “Computational Methods in Engineering” at the University of Hannover. During the master absolved a semester abroad at the International Joint Research Center for Engineering Reliability and Stochastic Mechanics, Tongji University, China. Since 2019 working at the Institute for Risk and Reliability at the University of Hannover as research assistant and pursuing a PhD in “Efficient reliability analysis for complex high dimensional stochastic dynamic systems”. Since 2021 joined the International Research Training Group 2657 “Computational Mechanics Techniques in High Dimensions” hosted by the University of Hannover and the ENS Paris-Saclay.
Country: Germany
Company: Institute of Risk and Reliability, Leibniz University Hannover
Job Title: Research assistant