A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies Article Swipe
Adam Thelen
,
Xiaoge Zhang
,
Olga Fink
,
Yan Lu
,
Sayan Ghosh
,
Byeng D. Youn
,
Michael D. Todd
,
Sankaran Mahadevan
,
Chao Hu
,
Zhen‐Zhong Hu
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2208.14197
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2208.14197
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively modeling the physical world as a group of interconnected digital models. In a two-part series of papers, we examine the fundamental role of different modeling techniques, twinning enabling technologies, and uncertainty quantification and optimization methods commonly used in digital twins. This first paper presents a thorough literature review of digital twin trends across many disciplines currently pursuing this area of research. Then, digital twin modeling and twinning enabling technologies are further analyzed by classifying them into two main categories: physical-to-virtual, and virtual-to-physical, based on the direction in which data flows. Finally, this paper provides perspectives on the trajectory of digital twin technology over the next decade, and introduces a few emerging areas of research which will likely be of great use in future digital twin research. In part two of this review, the role of uncertainty quantification and optimization are discussed, a battery digital twin is demonstrated, and more perspectives on the future of digital twin are shared.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- http://arxiv.org/abs/2208.14197
- https://arxiv.org/pdf/2208.14197
- OA Status
- green
- Cited By
- 15
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4293999519
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4293999519Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2208.14197Digital Object Identifier
- Title
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A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling TechnologiesWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-08-26Full publication date if available
- Authors
-
Adam Thelen, Xiaoge Zhang, Olga Fink, Yan Lu, Sayan Ghosh, Byeng D. Youn, Michael D. Todd, Sankaran Mahadevan, Chao Hu, Zhen‐Zhong HuList of authors in order
- Landing page
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https://arxiv.org/abs/2208.14197Publisher landing page
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https://arxiv.org/pdf/2208.14197Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2208.14197Direct OA link when available
- Concepts
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Computer science, Data science, Emerging technologies, Process (computing), Crystal twinning, Artificial intelligence, Microstructure, Metallurgy, Operating system, Materials scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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15Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 9, 2023: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.unprecedented | 14 |
| abstract_inverted_index.interconnected | 45 |
| abstract_inverted_index.quantification | 68, 173 |
| abstract_inverted_index.comprehensively | 36 |
| abstract_inverted_index.physical-to-virtual, | 116 |
| abstract_inverted_index.virtual-to-physical, | 118 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 10 |
| citation_normalized_percentile |