A machine learning enhanced structural response prediction strategy due to seismic excitation

PAMM, vol. 20

Abstract

Abstract In this contribution, we present a fast prediction approach to estimate response statistics of the crude Monte Carlo simulation using artificial neural networks. Hereby, the neural network is trained within an initial response subset, based on which a forecast can be evaluated in an early state of the Monte Carlo simulation.

Authors 3

1. Denny Thaler corresponding Aachen Institute of General Mechanics

   RWTH Aachen University

   Affiliation as printed

   Institute of General Mechanics RWTH Aachen University Eilfschornsteinstr. 18 52062 Aachen

   Denny Thaler

   Institute of General Mechanics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062 Aachen

   Telephone: +49 241 80 94601

2. Franz Bamer corresponding Aachen Institute of General Mechanics

   RWTH Aachen University

   Affiliation as printed

   Institute of General Mechanics RWTH Aachen University Eilfschornsteinstr. 18 52062 Aachen

   Denny Thaler

   Institute of General Mechanics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062 Aachen

   Telephone: +49 241 80 94601

3. Bernd A. Markert Aachen Institute of General Mechanics

   RWTH Aachen University

   Affiliation as printed

   Institute of General Mechanics RWTH Aachen University Eilfschornsteinstr. 18 52062 Aachen

   Institute of General Mechanics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062 Aachen