INTEGRATION OF BIM AND ONTOLOGIES FOR DATA EFFICIENCY IN REINFORCED CONCRETE STRUCTURAL DESIGN: APPLICATION TO FRAME STABILITY

Abstract

This study investigates the integration of Building Information Building Information Modeling (BIM) and ontologies in reinforced concrete structural design, aiming to structure , enhance , and automated the management of technical information in response to the increasing complexity of the construction industry . The research adopts the Ontology Development 101 methodology (NOY; MCGUINNESS, 2001), adapted to the domain of reinforced concrete frame stability , encompassing the identification and systematization of technical requirements , the development of an ontology using the OWL language , and its integration with BIM models. Knowledge formalization was operationalized through a spreadsheet-based ontology constructor , from which the data were automatically converted into OWL and TTL formats and imported into Protect for logical validation , inference , and semantic query execution . The results demonstrate that ontological modeling enables the explicit representation of relationships among structural elements , properties , and code-based verifications , allowing SPARQL queries and automated inferences that support the comparative analysis of design alternatives regarding column slenderness , admissible displacements , and concrete and steel consumption . Thus, the proposed approach contributes to improving informational efficiency , technical reliability , and decision -making support in structural design, reinforcing BIM as a structured and semantically enriched information model rather than merely a geometric representation .