Vortrag: Marcos Valdebenito

Some Recent Developments on Uncertainty Propagation in Structural Mechanics, December 17, 14:45, Room 3408 / 010 (MZ2)

Prof. Dr. Marcos A. Valdebenito

Alexander von Humboldt Research Fellow
Institute for Risk and Reliability
Leibniz Universität Hannover

Associate Professor
Department of Civil Engineering
Santa Maria University, Valparaíso, Chile

Monday, December 17, 2018, 14:45 - 15:30
Building 3408 (Appelstraße 9a), Room 010 (MZ2)

 

Some Recent Developments on Uncertainty Propagation in Structural Mechanics

Abstract

The engineering community has widely acknowledged the necessity of quantifying the unavoidable effects of uncertainties on the performance of structural systems. However, for cases of engineering interest, uncertainty quantification becomes a challenging task, as it demands numerical efforts which can exceed in orders of magnitude the efforts associated with a traditional deterministic analysis. Hence, the practical application of methods for uncertainty quantification requires numerical strategies which are both efficient and reliable. This presentation discusses three of such strategies, which take advantage of:

  • Approximation concepts.
  • Substructuring and resampling.
  • Advanced simulation.

The main features and performance of these strategies is discussed by means of a series of examples.

Biography

Marcos Valdebenito is an associate professor at the Department of Civil Engineering of Santa Maria University, Valparaíso, Chile. In 2016, he received the prestigious K.J. Bathe Award for the best paper published in Computers & Structures in the years 2014 and 2015 by an author below the age of 40. In 2018, he was awarded a “Fellowship for Experienced Researchers” from the Humboldt Foundation and currently, he is conducting research at the Institute for Risk and Uncertainty of Leibniz Universität Hannover. His main research interest is the development of strategies for uncertainty quantification in computational mechanics. Within this broad field, his particular research interests are reliability assessment by means of advanced simulation methods, stochastic finite elements, reliability-based optimization and fuzzy analysis.