Development of a digital twin operational platform using Python Flask



Bonney, Matthew S, de Angelis, Marco ORCID: 0000-0001-8851-023X, Dal Borgo, Mattia, Andrade, Luis, Beregi, Sandor, Jamia, Nidhal and Wagg, David J
(2022) Development of a digital twin operational platform using Python Flask. DATA-CENTRIC ENGINEERING, 3 (1).

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Abstract

<jats:title>Abstract</jats:title> <jats:p>The digital twin concept has developed as a method for extracting value from data, and is being developed as a new technique for the design and asset management of high-value engineering systems such as aircraft, energy generating plant, and wind turbines. In terms of implementation, many proprietary digital twin software solutions have been marketed in this domain. In contrast, this paper describes a recently released open-source software framework for digital twins, which provides a browser-based operational platform using Python and Flask. The new platform is intended to maximize connectivity between users and data obtained from the physical twin. This paper describes how this type of <jats:italic>digital twin operational platform</jats:italic> (DTOP) can be used to connect the physical twin and other Internet-of-Things devices to both users and cloud computing services. The current release of the software—DTOP-Cristallo—uses the example of a three-storey structure as the engineering asset to be managed. Within DTOP-Cristallo, specific engineering software tools have been developed for use in the digital twin, and these are used to demonstrate the concept. At this stage, the framework presented is a prototype. However, the potential for open-source digital twin software using network connectivity is a very large area for future research and development.</jats:p>

Item Type: Article
Uncontrolled Keywords: Digital twin, Flask, operational platform, open source, Python
Divisions: Faculty of Science and Engineering > School of Engineering
Depositing User: Symplectic Admin
Date Deposited: 31 Jan 2022 16:37
Last Modified: 14 Mar 2024 17:47
DOI: 10.1017/dce.2022.1
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3147903