Künstliche Intelligenz und Maschinelles Lernen im Kontext der Forschung im Konstruktiven Glasbau

Artificial Intelligence and Machine Learning in the Context of Research in Constructive Glass Construction. The use of artificial intelligence (AI) is becoming increasingly widespread due to increasing data acquisition and processing possibilities. A social and economic change is predicted by numerous company managers, politicians and researchers. Machine Learning (ML) is a subcategory of AI, which is already used worldwide in numerous applications. In this article, the background of AI and ML will be presented, with emphasis is given to the specifics of the application of ML to engineering problems. Furthermore, the potentials of ML for the material parameter identification and uncertainty quantification of hyper- and viscoelastic constitutive laws of polymers of structural glass engineering are shown. Besides that, the application of ML for the evaluation and statistical prediction of fracture patterns of thermally pre-stressed glass is investigated. Finally, a first evaluation of the possible applicability of ML techniques to research questions in structural glass engineering is conducted. © 2019 Ernst & Sohn Verlag für Architektur und technische Wissenschaften GmbH & Co. KG, Berlin.