The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles

By E. Glaessgen, D. Stargel. 2012

2,282 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/733d40c04be482d38dbd21f82b81e0fc890b6669

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In Control and Systems Engineering

In Statistics and Probability

Citations in the corpus

Digital Twin for rotating machinery fault diagnosis in smart manufacturing (2018, background): “The idea of Digital Twin as a paradigm shift is proposed for on-board integrated vehicle health management system to enable ﬂight safety and reliability (Glaessgen and Stargel 2012).”
Digital twins for health: a scoping review (2024, methodology): “Around 2010,NASA and John Vickers utilizedthe DT as a virtual model of a physical system 5,6 .”
Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020, methodology): “There are ongoing technological trends for creating DTs in several fields: smart cities [138], [196] or specific issues of the cities, like traffic [197], aerospace [187], aircraft fleet management [198], innovative factory [2], [199]–[201], environmental management [202], logistics [203], [204], th”
The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities (2021, background): “For instance, Glaessgen and Stargel [18] deﬁned it from the perspective of vehicles as ‘‘A digital twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, ﬂeet history, etc., to mirror the”
Digital Twin: Enabling Technologies, Challenges and Open Research (2020, background): “’’ [10] Definition a) is an ambiguous definition specific for NASA’s interplanetary vehicle development [5] and is one of the early papers that defines Digital Twins.”
A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications (2019, background): “Precisely, ten years after Grieves’ definition, NASA researchers, in their roadmap [22], which is now considered by aerospace researchers [23], [24] as the seminal work about DTs, suggested that DT would improve performance in the field of aviation.”
Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues (2020, positive): “A year later, NASA defined Digital Twin as (cid:147)an integrated multi-physics, multi-scale, probabilistic simulation of a vehicle or system that uses the best available physical models, sensor updates, fleet history, and so forth, to mirror the life of its flying twin [2].”
Digital twin for CNC machine tool: modeling and using strategy (2018, background): “In recent years, with the requirement of smart manufacturing mode, developed from CPS concept, the appearance of digital twin (DT) (Grieves and Vickers 2017; Glaessgen and Stargel 2012) technology provides an effective resolution to integrate the physical world and the information world.”
A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies (2022, methodology): “Amongst the many definitions of digital twin, the one specified in Glaessgen and Stargel (2012) is considered one of the most broadly accepted definitions, even though the definition may vary from application to application.”
Digital twin-driven product design framework (2019, methodology): “Digital twin (DT) consists of three parts: physical product, virtual product and the linkage between physical and virtual product (Glaessgen and Stargel 2012).”
Industrial applications of digital twins (2021, background): “, to mirror the life of its corresponding twin [19].”
An application framework of digital twin and its case study (2018, methodology): “…phase, NASA and US Air Force apply the DT technology in vehicles development, so they can predict the future performance and status of vehicles by constructing ultra-high fidelity simulation models with the parameters of material properties and Manufacturing defects (Glaessgen and Stargel 2012).”