Hbim Generation: Extending Geometric Primitives and Bim Modelling Tools for Heritage Structures and Complex Vaulted Systems

Abstract

<p><strong>Abstract.</strong> Today, the generation of smart models and digital archives able to accompany the management of architectural assets through the integration of advanced 3D survey techniques and Historic Building Information Modelling (HBIM) becomes an irremissible added value for the management of building life cycle. New international BIM standards are trying to give some guidelines to this new digital tool, which has demonstrated a wide range of potential applications in digital heritage, structural simulation, generative design, site management, restoration and daily maintenance activities. To manage a proper 3D reconstruction from point clouds, also known as Scan-to-BIM process, BIM experts typically use 3D application developed for the management of new buildings, which make it difficult to generate complex objects such as historic vaults and irregular and damaged walls. For these reasons, this study places the heart of its research in the integration of generative modelling in BIM application, proposing new Scan-to-BIM modelling requirements for complex vaulted systems and a novel add-in (a set of new functionalities for Autodesk Revit) able to improve the generation of complex elements from point cloud data. In particular, new modelling requirements such as novel grades of generation (GOG) and accuracy (GOA) are integrated within the Revit’s structure in order to improve the level of information connected to HBIM and consequently to support the decision making of restoration and rehabilitation projects of complex heritage structures.</p>

From survey to semantic representation for Cultural Heritage: the 3D modeling of recurring architectural elements

“…This systematic and mathematical approach to digital heritage, based on the simplification of shapes and the reference to ideal geometries, presents an advantage in the parametric logic of H-BIM platforms, where series of smart objects, represented in 3D, are enriched with a large amount of technical information, related for example to geometry, materials, thickness, etc. [28], [40], [51]. The interoperability between NURBS modelling software and H-BIM platforms has also been verified [50], [52].…”

Computer Vision Meets Image Processing and UAS PhotoGrammetric Data Integration: From HBIM to the eXtended Reality Project of Arco della Pace in Milan and Its Decorative Complexity

“…Once the various NURBS objects were transformed into BIM parametric objects, thanks to the verification of the grade of accuracy (GOA), it was possible to communicate the reliability of each element created thanks to point set deviation analysis. In particular, thanks to an automatic verification system (AVS), the standard deviation between point clouds and BIM objects was calculated [ 23 , 56 , 57 ]. The value reached for every single element allowed us to define a GOA of about 1–2 mm.…”

Parametric Generation in Hbim Workflows for Slam-Based Data: Discussing Expectations on Suitability and Accuracy

“…Contrariwise, the so-called scan-to-BIM approach is characterized, as well known, by the possibility to involve the parametrization procedures rules in the generation of 3D objects and not only interpolated surfaces. The modelling is therefore constrained based on generative geometries and 3D transformation or combination of them, that are more or less complex and articulated in their hierarchy or Grade of Generation, as developed in (Banfi, 2019) and represented in Figure 2b. GOG are dependent on many variables but, first of all, the selection of a starting 3D data is one of the crucial factors affecting the result.…”

“…This phase begins with the metric analysis of the two initial point cloud data and then some specific geometric features are hierarchically considered according to a requirements sequence. Particularly the SLAM-based point clouds are analysed in order to support GOG modelling strategies, according to modelling choices and requirements conducted by the operator during the modelling: GOG 9 based on characterising polylines/break lines, belonging to the objects surfaces, and GOG 10, based on point cloud interpolation and external edge profiles (Banfi, 2019).…”