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Towards an automatic optimization framework for performance oriented precast concrete design

  • Concrete has a long history in the construction industry and is currently one of the most widely used building materials. Especially precast concrete elements are frequently utilized in construction projects for standardized applications, increasing the quality of the composite material, as well as reducing the required building time. Despite the accumulated knowledge, continuous research and development in this field is essential due to the complexity of the composite combined with the ever-growing number of applications and requirements. Especially in view of global climate change, design aspects as CO2 emissions and resource efficiency require new mix designs and optimization strategies. A result of the material’s high complexity and heterogeneity on multiple scales is that utilizing the full potential with changing demands is highly challenging, even for the established industry. We propose a framework based on an ontology, which automatically combines experimental data withConcrete has a long history in the construction industry and is currently one of the most widely used building materials. Especially precast concrete elements are frequently utilized in construction projects for standardized applications, increasing the quality of the composite material, as well as reducing the required building time. Despite the accumulated knowledge, continuous research and development in this field is essential due to the complexity of the composite combined with the ever-growing number of applications and requirements. Especially in view of global climate change, design aspects as CO2 emissions and resource efficiency require new mix designs and optimization strategies. A result of the material’s high complexity and heterogeneity on multiple scales is that utilizing the full potential with changing demands is highly challenging, even for the established industry. We propose a framework based on an ontology, which automatically combines experimental data with numerical simulations. This not only simplifies experimental knowledge transfer, but allows the model calibration and the resulting simulation predictions to be reproducible and interpretable. This research shows a way towards a more performance oriented material design. Within this talk we present our workflow for an automated simulation of a precast element, demonstrating the interaction of the ontology and the finite element simulation. We show the automatic calibration of our early-age concrete model [1, 2], to improve the prediction of the optimal time for the removal of the form work.zeige mehrzeige weniger

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Metadaten
Autor*innen:Erik Tamsen
Koautor*innen:Jörg F. Unger
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2022
Organisationseinheit der BAM:7 Bauwerkssicherheit
7 Bauwerkssicherheit / 7.7 Modellierung und Simulation
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten
Freie Schlagwörter:Early-age concrete; Ontology; Optimization workflow; Performance oriented concrete design; Precast concrete
Themenfelder/Aktivitätsfelder der BAM:Infrastruktur
Material
Material / Additive Fertigung
Veranstaltung:The 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) 2022
Veranstaltungsort:Oslo, Norway
Beginndatum der Veranstaltung:05.06.2022
Enddatum der Veranstaltung:09.06.2022
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:19.07.2022
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
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