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2018 | OriginalPaper | Buchkapitel

Building Information Modeling for Cultural Heritage: The Management of Generative Process for Complex Historical Buildings

verfasst von : F. Banfi, L. Chow, M. Reina Ortiz, C. Ouimet, S. Fai

Erschienen in: Digital Cultural Heritage

Verlag: Springer International Publishing

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Abstract

Building Information Modeling (BIM) enhances the sharing of information during the traditional process for new construction, but most of the time, it requires high levels of knowledge management for the historical digital model (H-BIM). The innovation in the Digital Cultural Heritage (DCH) domain is supported by the development of Information and Communications Technologies (ICT) and modern tools that are able to transmit morphological characteristics of the buildings in all their uniqueness. The latest research in the field of H-BIM shows a significant emergence of innovative methods and management initiatives for the generation of complex historical elements, leading to the confrontation of the paradigm of regularity (simple geometric shapes) with the new paradigm of complexity (historical building elements). This paper proves the benefits of the BIM for project management of the Centre Block of the Canadian Parliament in Ottawa, Ontario Canada, and shows the results obtained by the introduction of Advanced Modeling Techniques (AMT) during the generative process, reducing time and cost for the creation of the complex architectural and structural elements. The uniqueness of the forms of historical buildings is a real value to be transmitted throughout the building’s lifecycle with high Levels of Detail (LOD). Proper management of geometric primitives and Non-Uniform Rational Basis Spline (NURBS) models have guaranteed the conversion of spatial data (point clouds) from laser scanning and photogrammetry (geometric survey) into parametric applications. This paper explores the generative process of one of the most complex spaces within The Centre Block building of Parliament Hill—Confederation Hall.

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Literatur
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Zurück zum Zitat Banfi, F., Fai, S., Brumana, R.: BIM automation: advanced modeling generative process for complex structures. ISPRS Ann. Photogrammetry Remote Sensing Spat. Inf. Sci. 4 (2017) Banfi, F., Fai, S., Brumana, R.: BIM automation: advanced modeling generative process for complex structures. ISPRS Ann. Photogrammetry Remote Sensing Spat. Inf. Sci. 4 (2017)
5.
Zurück zum Zitat Barazzetti, L., Banfi, F., Brumana, R., Gusmeroli, G., Previtali, M., Schiantarelli, G.: Cloud-to-BIM-to-FEM: structural simulation with accurate historic BIM from laser scans. In: Simulation Modelling Practice and Theory, vol. 57, pp. 71–87 (2015)CrossRef Barazzetti, L., Banfi, F., Brumana, R., Gusmeroli, G., Previtali, M., Schiantarelli, G.: Cloud-to-BIM-to-FEM: structural simulation with accurate historic BIM from laser scans. In: Simulation Modelling Practice and Theory, vol. 57, pp. 71–87 (2015)CrossRef
7.
Zurück zum Zitat Chow, L., Fai, S.: Developing verification systems for building information models of heritage buildings with heterogeneous datasets. Int. Arch. Photogrammetry Remote Sensing Spatial Inf. Sci. 42, 125 (2017)CrossRef Chow, L., Fai, S.: Developing verification systems for building information models of heritage buildings with heterogeneous datasets. Int. Arch. Photogrammetry Remote Sensing Spatial Inf. Sci. 42, 125 (2017)CrossRef
8.
Zurück zum Zitat Della Torre, S.: Shaping tools for built heritage conservation: from architectural design to program and management: learning from ‘Distretti culturali’. In: Community Involvement in Heritage, pp. 93–102, Garant (2015) Della Torre, S.: Shaping tools for built heritage conservation: from architectural design to program and management: learning from ‘Distretti culturali’. In: Community Involvement in Heritage, pp. 93–102, Garant (2015)
Metadaten
Titel
Building Information Modeling for Cultural Heritage: The Management of Generative Process for Complex Historical Buildings
verfasst von
F. Banfi
L. Chow
M. Reina Ortiz
C. Ouimet
S. Fai
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-75826-8_10

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