Publicación:
ARTIFICIAL INTELLIGENCE-BASED MODELING OF EXTRUDED ALUMINUM BEAMS SUBJECTED TO PATCH LOADING

Vista sencilla de ítem
dc.creatorEURO LUIS CASANOVA MEDINA
dc.date2022
dc.date.accessioned2025-01-10T15:30:23Z
dc.date.available2025-01-10T15:30:23Z
dc.date.issued2022
dc.description.abstractARTIFICIAL INTELLIGENCE (AI) HAS BECOME A RELIABLE TOOL FOR THE SOLUTION OF STRUCTURAL ENGINEERING PROBLEMS. THIS PAPER AIMS AT DEVELOPING PREDICTION MODELS FOR THE BEHAVIOR OF EXTRUDED ALUMINUM BEAMS UNDER PATCH LOADING VIA SYMBOLIC REGRESSION (SR) AND ARTIFICIAL NEURAL NETWORKS (ANN). THE MODELS ARE CONSTRUCTED EMPLOYING AN EXTENSIVE DATASET CALCULATED NUMERICALLY THROUGH NONLINEAR FINITE ELEMENT ANALYSIS. THIS DATASET COVERS A WIDE RANGE OF GEOMETRIC PARAMETERS AND CONSIDERS ALUMINUM ALLOYS WITH DIFFERENT STRAIN HARDENING CHARACTERISTICS. EXPLICIT FORMULATIONS FOR THE RESISTANCE OF EXTRUDED ALUMINUM BEAMS TO PATCH LOADING ARE DEVELOPED BY FITTING THIS DATASET USING SR AND ANN, THE RESULTS ARE COMPARED WITH THOSE OF THE RESISTANCE MODEL IN THE EC9:1-1. FINALLY, THE PERFORMANCE OF THE PROPOSED AI MODELS IS ALSO EVALUATED. RESULTS CONFIRMED THE SUPERIOR ACCURACY OF THE PROPOSED MODELS.
dc.formatapplication/pdf
dc.identifier.doi10.1016/j.tws.2022.109673
dc.identifier.issn1879-3223
dc.identifier.issn0263-8231
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/12337
dc.languagespa
dc.publisherTHIN-WALLED STRUCTURES
dc.relation.uri10.1016/j.tws.2022.109673
dc.rightsPUBLICADA
dc.titleARTIFICIAL INTELLIGENCE-BASED MODELING OF EXTRUDED ALUMINUM BEAMS SUBJECTED TO PATCH LOADING
dc.title.alternativeMODELADO BASADO EN INTELIGENCIA ARTIFICIAL DE VIGAS DE ALUMINIO EXTRUIDO SOMETIDAS A CARGA DE PARCHES
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE INGENIERIA CIVIL Y AMBIENTAL
ubb.SedeCONCEPCIÓN
Archivos
Colecciones
Artículos científicos