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Stone Pavement Analysis using Building Information Modeling

Auteur(s): ORCID
ORCID
ORCID

ORCID

Médium: article de revue
Langue(s): anglais
Publié dans: Transportation Research Record: Journal of the Transportation Research Board, , n. 1, v. 2676
Page(s): 105-117
DOI: 10.1177/03611981211035751
Abstrait:

The growing need to recover and digitally represent heritage infrastructure has led to the challenge of choosing different Building Information Modeling (BIM) platforms that will be used to manage the implementation of the semi-automatic design and reconstruction processes of reverse engineering modeling. The approach to the integrated management of information derived through Heritage-BIM (H-BIM) has been applied to Via del Duomo, one of the main roads in the old town of Naples, Italy. During preliminary inspections of the construction site it was possible to acquire geometric features and pavement/subgrade information, as well as to conduct a photographic survey, with 1,618 photographs collected. Subsequently, the acquired data were processed, using different BIM-based tools, to obtain the 3D mesh; objects were then converted from pure graphic solids into parametric entities by proposing a specific algorithm. Then a library, with the inclusion of all the possible stone paving package alternatives, including all the structural and stress-deforming characteristics such as Young Modulus (E), Poisson coefficient (n), and Safety factor (SF), was created. In this way, it is possible to associate to the generic element the optimal pavement package solution, depending on different construction contexts. As preliminary result, a dynamic model that updates its information package and modifies the output of the analysis every time the data worksheet is integrated with new collected results is proposed for further pavement management operations evaluation.

Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1177/03611981211035751.
  • Informations
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  • Reference-ID
    10777908
  • Publié(e) le:
    12.05.2024
  • Modifié(e) le:
    12.05.2024
 
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