UMR CNRS/MC 3495 MAP, Modèles et Simulations pour l'Architecture et le Patrimoine, 13402, Marseille, France.
Laboratoire de Recherche des Monuments Historiques, 77420, Champs-sur-Marne, France.
Sci Rep. 2023 Apr 12;13(1):5981. doi: 10.1038/s41598-023-32504-9.
April 15th, 2019: Notre-Dame Cathedral in Paris was burning, the spire collapsed on the nave, vaults crumbled and most of the timber roof was gone. In the post-disaster context, the authenticity and the monitoring of the archaeological remains are crucial for their potential reuse during reconstruction. This paper analyzes the collapsed transverse arch from the nave of Notre-Dame as a case study of reconstruction, using the digital twin framework. We propose four facets for the digital twin experiment-physical anastylosis, reverse engineering, spatio-temporal tracking of assets, and operational research-that are described in detail, while being assembled to support a hybrid reconstruction hypothesis. The digital twin can realize the parallel unfolding of physical-native and digital-native processes, while acquiring and storing heterogeneous information as semantically structured data. The results demonstrate that the proposed modeling method facilitates the formalization and validation of the reconstruction problem and increases solutions performances. As result, we present a digital twin framework application ranging from acquisition to data processing that informs a successful hybrid reconstruction hypothesis.
2019 年 4 月 15 日：巴黎圣母院大教堂发生火灾，尖顶倒塌在中殿，拱顶坍塌，大部分木屋顶都不见了。在灾后背景下，考古遗迹的真实性和监测对于它们在重建过程中的潜在再利用至关重要。本文以圣母院中殿倒塌的横向拱为案例研究，使用数字孪生框架进行分析。我们提出了数字孪生实验的四个方面——物理修复、逆向工程、资产的时空跟踪和运筹学，并详细描述了它们，同时将它们组合起来以支持混合重建假设。数字孪生可以实现物理原生和数字原生过程的并行展开，同时获取和存储作为语义结构化数据的异构信息。结果表明，所提出的建模方法有助于对重建问题进行形式化和验证，并提高解决方案的性能。因此，我们提出了一种从采集到数据处理的数字孪生框架应用，为成功的混合重建假设提供信息。
