PSI - Issue 64

Nicola Nisticò et al. / Procedia Structural Integrity 64 (2024) 2230–2237 Nicola Nisticò/ Structural Integrity Procedia 00 (2019) 000–000

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1. Introduction The work introduces a methodology for developing and deploying innovative tools and techniques to digitize both visible and non-visible attributes of cultural heritage items. According to Vrana and Sing (2021), digitization serves as the initial phase leading to digitalization, subsequently leading to Non-Destructive Evaluation (NDE). In this context, NDE (Bolton and Cora, 2021) represents a cyber-physical non-destructive assessment that utilizes Industry 4.0 digital technologies, alongside physical inspection methods and business models, to enhance inspection performance, integrity engineering, and decision-making processes. Moreover, it furnishes valuable insights to enhance the design, production, and maintenance throughout the useful lifespan of cultural heritage objects. The tools and methods are intended to be implemented within IMPIS 4 CH O D 2 (Nisticò, 2023), which stands for Intelligent Multi-Purpose System For Cultural Heritage Objects reproduced through Digital Twin. This concept was initially introduced by Grieves (2014) and later adopted by NASA (Glaessgen and Stargel, 2012) to aid in the production of their vehicles and systems. In this context, the acquisition and reconstruction of three-dimensional (3D) data play a crucial role. Specific technologies for augmented reality perception are essential for the widespread dissemination of Digital Twins to museums globally, including those in the Metaverse (Far and Rad, 2022) and cloud managed museums. Numerous methods and technologies for 3D digitalization can be identified, encompassing laser scanning, photogrammetry, satellite platforms, light pattern projection, spectroscopy techniques, infrared imaging, X-ray radiography, computer tomography, and various sensor technologies. These diverse tools facilitate the generation of precise 3D models and the acquisition of invaluable data for the preservation and analysis of cultural heritage. Geometrical models play a vital role in predicting how objects react to diverse external forces and environmental conditions. Multiscale modeling and analysis are pivotal for comprehending materials and structures across different levels, spanning nano-, micro-, and meso-scales. These principles find wide application across various disciplines. Furthermore, the integration of object digitization, geometric and mechanical modeling, and performance assessment can be greatly enhanced through the utilization of Artificial Intelligence (AI) technologies, which trace back to Turing's inquiry in 1950: "Can machines think?". Hence, the primary focus of the proposal revolves around designing a cloud infrastructure that achieves two key objectives. Firstly, it aims to integrate specific digitization solutions such as scanning and computer tomography scans. This integration is crucial for capturing both dynamic and hidden characteristics inherent in complex assemblies. Secondly, the proposal seeks to leverage Artificial Intelligence (AI) solutions to manage the substantial data within the cloud effectively. These AI solutions will play a pivotal role in developing geometric and mechanical models. To achieve these overarching goals, several specific objectives will be pursued. These include enhancing existing technologies and techniques for data acquisition and visualization; proposing and implementing a multi-scale approach; developing methodologies to estimate accuracy; implementing numerical methods to assess mechanical performance; creating physical scaled replicas; designing and implementing sound; deploying an AI-based methodology; establishing a DATA Storage and Navigation system; setting up a Metaverse museum; executing case studies; evaluating social implications. 2. Methodology The adopted methodology is centered around a series of activities aimed at achieving predefined objectives. These objectives are achieved through various tools categorized into three primary areas. Firstly, in Data Acquisition and Elaboration, efforts are focused on defining ontology, analyzing acquired data, conducting 2D and 3D geometrical model analyses, and assessing model fidelity for accuracy and reliability. Secondly, Data Divulgation involves visualizing and exploiting data, engaging multi-sensorial perception, employing game systems for social interaction, utilizing the Metaverse for dissemination and educational purposes, and creating virtual spaces for sharing results. Finally, Data Storage and Navigation play a crucial role in organizing and accessing the collected data. A holistic, multi-scale approach is required for data acquisition, integrating techniques like terrestrial laser scanning for external surfaces and precise 3D digitization technologies for finer details. Additionally, non-destructive testing