Existing road and railway systems often incorporate bridges, part of the historical heritage, that need careful attention not only for their operational safety and safeguard. For this reason, the approach to the inspection and to the constructional knowledge requires the integration and coordination of phases like the analysis of primary sources to the in-situ characterization of the local and global performance of components and materials. The management of infrastructures has to exploit digital technologies, both in the data collection phase and in the decision-making process. The paper deals with the econservation paradigm and discusses the results of an investigation on the potentialities offered by parametric models of historic bridges. It also checks and validates the introduction of the approach advised by recent National regulations in the framework of the Historic Bridge Information Modelling (HBrIM) combining safety and conservation knowledge instances.

Digital models for e-conservation: the HBrIM of a bridge along the Aterno river

Marra A.;
2021-01-01

Abstract

Existing road and railway systems often incorporate bridges, part of the historical heritage, that need careful attention not only for their operational safety and safeguard. For this reason, the approach to the inspection and to the constructional knowledge requires the integration and coordination of phases like the analysis of primary sources to the in-situ characterization of the local and global performance of components and materials. The management of infrastructures has to exploit digital technologies, both in the data collection phase and in the decision-making process. The paper deals with the econservation paradigm and discusses the results of an investigation on the potentialities offered by parametric models of historic bridges. It also checks and validates the introduction of the approach advised by recent National regulations in the framework of the Historic Bridge Information Modelling (HBrIM) combining safety and conservation knowledge instances.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/199603
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