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Digital Twin: Values, Challenges and Enablers

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arxiv 1910.01719 v1 pith:OJJVN2HJ submitted 2019-10-03 eess.SP

classification eess.SP
keywords digitaltwinchallengescomputationalcurrentdatarecentsystem
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A digital twin can be defined as an adaptive model of a complex physical system. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 75 citations worldwide. Full citation record

  1. Trans-Domain Digital Twin: Conceptual Foundations, Architecture, and Research Outlook

    cs.SE 2026-07 conditional novelty 5.0 of 10

    TDDT defines a composite/federated digital twin system-of-systems that requires shared state, operational coupling, temporal coordination, and feedback, and details a seven-layer architecture.

  2. Electronic Health Records: Towards Digital Twins in Healthcare

    cs.AI 2025-01 unverdicted novelty 1.0 of 10

    A review chapter explaining EHR history, ICD coding, and MIMIC-III querying, with no new scientific findings.

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