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Computation and verification of steel constructions using physics‐informed artificial intelligence

Computation and verification of steel constructions using physics‐informed artificial intelligence EDITOR’S RECOMMENDATIONS Computation and verification of steel constructions using physics-informed artificial intelligence This paper has been published in Ger- physics-informed neural nets (PINN) me- on and is therefore interesting for engi- man in Stahlbau 10/2020. Currently the thods, where the specific requirements neering research and practice. This paper technology of artificial intelligence (AI) for the formulation of the learning prob- eventually gives perspectives on future spreads into research and industry practi- lem are highlighted. PINN serves as an applications of AI for steel construction. ce of all branches in diverse forms. Given alternative to established computational that situation, this article serves to intro- methods for design of steel structures and Kraus, M. A.; Taras, A. (2020) Physik­ in­ duce the reader to theoretical back- its components using available experi- formierte Künstliche Intelligenz zur Be­ ground on AI in general as well as to the mental and simulation data. This enables rechnung und Bemessung im Stahlbau. specific case of physics-informed AI the interpretation and use of PINNs Stahlbau 89, No. 10, pp. 824–832. (PIKI). Selected examples from design being the digital twin of a steel structure https://doi.org/10.1002/stab.202000074 and verification practice of steel const- over its lifecycle. PIKI as presented here ruction then illustrate the application of does not per se cause a “big data” situati- Steel Construction 13 (2020), No. 4 293 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Steel Construction: Design and Research Wiley

Computation and verification of steel constructions using physics‐informed artificial intelligence

Steel Construction: Design and Research , Volume 13 (4) – Nov 1, 2020

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Publisher
Wiley
Copyright
© 2020 Ernst & Sohn Verlag für Architektur und technische Wissenschaften GmbH & Co. KG, Berlin
ISSN
1867-0520
eISSN
1867-0539
DOI
10.1002/stco.202070405
Publisher site
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Abstract

EDITOR’S RECOMMENDATIONS Computation and verification of steel constructions using physics-informed artificial intelligence This paper has been published in Ger- physics-informed neural nets (PINN) me- on and is therefore interesting for engi- man in Stahlbau 10/2020. Currently the thods, where the specific requirements neering research and practice. This paper technology of artificial intelligence (AI) for the formulation of the learning prob- eventually gives perspectives on future spreads into research and industry practi- lem are highlighted. PINN serves as an applications of AI for steel construction. ce of all branches in diverse forms. Given alternative to established computational that situation, this article serves to intro- methods for design of steel structures and Kraus, M. A.; Taras, A. (2020) Physik­ in­ duce the reader to theoretical back- its components using available experi- formierte Künstliche Intelligenz zur Be­ ground on AI in general as well as to the mental and simulation data. This enables rechnung und Bemessung im Stahlbau. specific case of physics-informed AI the interpretation and use of PINNs Stahlbau 89, No. 10, pp. 824–832. (PIKI). Selected examples from design being the digital twin of a steel structure https://doi.org/10.1002/stab.202000074 and verification practice of steel const- over its lifecycle. PIKI as presented here ruction then illustrate the application of does not per se cause a “big data” situati- Steel Construction 13 (2020), No. 4 293

Journal

Steel Construction: Design and ResearchWiley

Published: Nov 1, 2020

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