Robust estimation of axial loads sustained by tie-rods in historical structures using Artificial Neural Networks

Makoond, Nirvan ChandraPelà, LucaMolins, Climent2023-10-192023-10-192023-071475-9217https://riunet.upv.es/handle/10251/198421[EN] Widely used simplified analytical methods for estimating the tensile force in tie-rods are clearly not applicable when they contain significant discontinuities or irregularities. A common example for which this fact becomes relevant in practice is the use of connectors to unify historical ties consisting of several segments. To address this challenge, a robust hybrid methodology is proposed which can be applied to any historical tie by employing a data-driven approach to a dataset generated using the finite element method. The methodology is applied to a real case study involving two historical ties.Reserva de todos los derechosAxial force estimationVibration testingDynamic identificationModal analysisNatural frequencyMode shapesRobust estimation of axial loads sustained by tie-rods in historical structures using Artificial Neural NetworksArtículo10.1177/14759217221123326Abierto09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación11.- Conseguir que las ciudades y los asentamientos humanos sean inclusivos, seguros, resilientes y sostenibles