FEA-Assistenzsystem – Plausibilitätsprüfung für Finite-Elemente-Simulationen mittels sphärischen Detektorflächen

DFX 2016: Proceedings of the 27th Symposium Design for X, 5-6 October 2016, Jesteburg, Germany

Year: 2016
Editor: Dieter Krause, Kristin Paetzold, Sandro Wartzack
Author: Spruegel, Tobias C.; Kestel, Philipp; Wartzack, Sandro
Series: DfX
Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg
Section: Test und Simulation
Page(s): 027-038
ISBN: 978-3-946094-09-8

Abstract

Finite Element Analysis (FEA) is a very efficient tool for optimizing product performance and quality. Hence, more simulation engineers with a lot of experience are needed, but they are not available. Consequently other users, such as design engineers, should be able to perform valid, reliable FEA. One of the goals of the research cooperation FORPRO˛ is to create a knowledge-based FEA assistance system with an integrated plausibility check for structural mechanics. Within this paper a methodology for a plausibility check using spherical detector surfaces is presented. Thereby it is possible to reduce any FE simulation to matrices of fixed size for each boundary condition and each FEA result variable. The created matrices can then be combined to form a single larger image. These images can afterwards be classified as plausible or implausible by a Deep Learning Neural Network.

Keywords: FEA assistance system, plausibility check, neural network classification, deep learning