Cited by 2,404Digital Transformation in IndustryEngineering and Test SystemsReliability and Maintenance Optimization

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index; none of the 21 sources its claims cite is checked for support yet.

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

Open access

Glaessgen, Edward, Stargel, David·2012·53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA

DOI 10.2514/6.2012-1818

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Abstract

Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation. Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements. To address the shortcomings of conventional approaches, a fundamental paradigm shift is needed. This paradigm shift, the Digital Twin, integrates ultra-high fidelity simulation with the vehicle s on-board integrated vehicle health management system, maintenance history and all available historical and fleet data to mirror the life of its flying twin and enable unprecedented levels of safety and reliability.

AI snapshot

Written from the paper’s full text.

TL;DR

The paper proposes the Digital Twin paradigm—an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle using best physical models, sensor updates, fleet history, and IVHM data—to mirror the life of its flying twin and improve certification, fleet management, and sustainment. It argues conventional factor-of-safety, similitude, and inspection approaches are inadequate for future NASA and U.S. Air Force vehicles with lighter mass, higher loads, and longer extreme service.

Key findings

Conventional certification and sustainment rely on factors-of-safety, similitude, worst-case scenarios, and fleet leaders; factors can be as large as 2.0 depending on material and configuration, a service life factor of 4.0 is applied to well-characterized spaceflight structures, and known flaws must show a safety factor of 1.5 against fracture.
The Digital Twin integrates ultra-high fidelity physical models, on-board IVHM sensor data, maintenance history, and historical/fleet data via data mining and text mining; it continuously forecasts vehicle health, remaining useful life, and probability of mission success, and can recommend mission profile changes or activate self-healing mechanisms.
Near-term opportunities include the AFRL Digital Twin: Spiral 1 using the F-15 as a testbed, and a NASA approach focused on a small highly critical non-redundant component such as a MEMS.
Expected advantages include decreased system weight by reducing reliance on statistical distributions, heuristic design philosophies, physical testing, and assumed similitude, plus increased reliability through continuous monitoring and mitigation of degradation and anomalous events.

Methods

Conceptual/vision paper, not an experimental study; it presents the Digital Twin paradigm and requirements, with examples drawn from NASA standards and handbooks including NASA-STD-5001A, NASA-STD-5019, and NASA-HDBK-5010.
No sample, dataset, or statistical analysis is reported; the paper discusses conventional approaches, Digital Twin attributes, near-term opportunities, advantages, and influence on national goals.
Illustrative figures and tables are used to motivate the paradigm, such as an STS payload launch/landing spectrum and upper-bound fatigue crack growth rate curves estimated as three standard deviations above mean values.

Limitations

The paper states the Digital Twin is an ambitious concept “unlikely to attain maturity for many decades,” so a series of intermediate steps is required.
The paper states future vehicles may encounter conditions that cannot be foreseen, and long-duration space missions may make conventional inspection and maintenance impossible.
Evident from the text: no quantitative validation, implementation results, or performance metrics for a Digital Twin are reported; the work is a concept and roadmap paper.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.2514/6.2012-1818

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 21 cited sources checked · 0 supported · 0 flagged

The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements.”
- Also stated in: § Introduction · plain
  “Existing methodologies for vehicle certification, fleet management and sustainment are largely based on similitude and a heuristic understanding of the effects of operational and anomalous conditions on the structural health, safety and performance of a vehicle.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Abstract
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes? Based: unclear
In the paper
“As discussed in the standard, the accepted practice for”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Conventional Approaches
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-STD-5001A
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes

Show all 7 claims

It may state two separate claims as one. 15
Probably not a substantial claim. 39

In the paper
“An extreme case of codified conservatism is discussed in NASA-HDBK-5010 10 , where separate conservatisms for crack size, applied loads, material properties, and analysis are discussed for”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-HDBK-5010
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“According to NASA-STD-5001A 1 , a service life factor of 4.0 is applied to”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-STD-5001A
Strength:plain· not yet calibratedCausal:conditional· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Known cracks in fracture critical hardware require special treatment wherein upper bounds for crack size estimate accounting for”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-HDBK-5010
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Finally, analyses of known flaws must show that the component has a service life factor of four and a safety factor of 1.5 against fracture.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-HDBK-5010
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Among these steps is the Air Force Research Laboratory (AFRL) Digital Twin: Spiral 1 17 , a plan to integrate existing state-of-the-art technologies, benchmark current capabilities and identify gaps using components from an existing U.S. Air Force vehicle, specifically, the F-15, as a testbed.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Identification of Near-Term Opportunities
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [17]
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Complex missions, particularly those where external support is difficult or impossible, will necessitate complete real-time management of complex materials, structures and systems that will ultimately lead to”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Concept
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: fails
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: The consequences of failure during a long-duration space mission, where the vehicle is far from home, will almost certainly be catastrophic.
In the paper
“In all of these cases,”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Conventional Approaches
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-STD-5001A
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As a result, demands on structural materials will be greatly increased and structural margins will necessarily be decreased.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Concept
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim. It may state two separate claims as one.
- Rests on an assumption: Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation.
In the paper
“Because the vehicles needed for future extreme missions are unlikely to be developed using existing material forms, the design and development of new enabling (e.g., multifunctional, nanostructured, ultra-durable) materials is required and is well aligned with the NRC's ICME roadmap.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Influence on National Goals
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [20]
Strength:boosted· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The application of continuum fracture mechanics analyses, including NASGRO fatigue crack growth analysis (see JSC 22267B 6 ), is the foundation of much of the codified fracture control methodology.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites JSC 22267B
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The ability to assess the evolution of defects is a critical element within the Digital Twin's on-board IVHM system and is well aligned with the NRC's advocacy for developments in Materials State Awareness.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Influence on National Goals
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [21]
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
It may state two separate claims as one.
In the paper
“The latter approach requires a factor-of-safety for yield that is higher than the factor-of-safety used for prototype testing.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Conventional Approaches
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-STD-5001A
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Fracture critical hardware requires the additional imposition of damage tolerance requirements (see, for example, NASA-STD-5019 2 ).”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-STD-5019
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, such an ambitious concept is unlikely to attain maturity for many decades, so a series of intermediate steps is required.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Identification of Near-Term Opportunities
Load-bearingStrength:hedged· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: fails
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
- Rests on an assumption: The Digital Twin concept is unlikely to attain maturity for many decades.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, the extensive legacy of historical flight information incorporated in the various standards and handbooks that were based on decades of aircraft and spacecraft design experience, will likely be insufficient to either certify future extreme vehicles or to guarantee mission success.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Concept
Load-bearingStrength:hedged· not yet calibrated
Tests✓ Asserted: passes? Checkable: unclear✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- Rests on an assumption: Future generations of vehicles will rely on increasingly complex, heterogeneous and multifunctional material forms with increasingly complex failure modes.
In the paper
“These factors vary widely depending on circumstance and can be as large as 2.0 depending on the material and local structural configuration.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-STD-5001A
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Additionally, worst-case limit loads for the mission must be used to compute the far field stress state at the location of the detected crack.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-HDBK-5010
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Because of the apparent scatter in material response under cyclic and creep loading, the corresponding factors are even larger.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-STD-5001A
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The handbook requires analysts to use material properties corresponding to the lower bound of fracture toughness and the upper bound of fatigue crack growth rate (da/dN vs. ΔK) as shown in Figure 2.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-HDBK-5010
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Upper bounds of fatigue crack growth rate curves are either visually estimated or statistically estimated as being three standard deviations above the mean values.”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-HDBK-5010
Strength:hedged· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“In addition to its prominence in the recently-published roadmaps of NASA's Office of Chief Technologist (OCT) [15][16] and plans of the Air Force Research Laboratory [17][18] , the Digital Twin paradigm can provide focus to the recent advocacy of the National Science Foundation (NSF) and the National Research Council (NRC) in the areas of Simulation Based Engineering Science (SBES) 19 , Integrated”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Influence on National Goals
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [19]
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [20]
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [21]
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Here, the crack size assumed for analysis (2c A ) is a combination of the NDE-detected crack dimensions (2c D ) and an adjustment based on the NDE detection capability (2c N ).”
§ The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles > Table 1: Sample of Publicly Available Standards and Handbooks
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites NASA-HDBK-5010
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.

43 of 43

The paper relies on this without support.
Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation.
“Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation.”
The paper relies on this without support.
Future vehicles will have little direct precedent to follow, and in some cases (e.g., long duration space missions) the vehicle may be impossible to inspect and maintain in the conventional sense.
“Unlike the methods used to insure safety and reliability of existing vehicles that have a clear and wellunderstood legacy, many future vehicles will have little direct precedent to follow, and in some cases (e.g., long duration space missions) the vehicle may be impossible to inspect and maintain in the conventional sense.”
The paper relies on this without support.
Future generations of vehicles will rely on increasingly complex, heterogeneous and multifunctional material forms with increasingly complex failure modes.
“Future generations of vehicles will rely on increasingly complex, heterogeneous and multifunctional material forms with increasingly complex failure modes.”
The paper relies on this without support.
The extensive physical testing that provided the confidence needed to assure the success of previous missions has become increasingly expensive to perform.
“Additionally, the extensive physical testing that provided the confidence needed to assure the success of previous missions has become increasingly expensive to perform.”
The paper relies on this without support.
The consequences of failure during a long-duration space mission, where the vehicle is far from home, will almost certainly be catastrophic.
“Moreover, the consequences of failure during a long-duration space mission, where the vehicle is far from home, will almost certainly be catastrophic.”
The paper relies on this without support.
The Digital Twin concept is unlikely to attain maturity for many decades.
“However, such an ambitious concept is unlikely to attain maturity for many decades, so a series of intermediate steps is required.”

6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

Handbook 5010 is identified as both HDBK and STD
Minor
The text cites document 5010 as NASA-HDBK-5010, but reference 10 identifies it as NASA-STD-5010.

1 of 1

Reengineering aircraft structural life prediction using a digital twin
Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M. (2011) · International Journal of Aerospace Engineering · doi:10.1155/2011/154798 · Cited by 1,119

Flagged first, then by citations

Show all 1 references

Research works printed but not linked: 9

Anon, 2008, NASA-STD-5019
Anon, 2008, NASA-STD-6016
Anon, 2001, Version 3, 0, 22267B
Anon, Fracture Control Implementation Handbook for Payloads, Experiments, and Similar Hardware,"NASA-STD-5010,May2005
Anon, 2004, Rules for Construction of Pressure Vessels
Kobryn P.A., 2011, USAF Air Force Research Laboratory, 88ABW-, 01428
Anon, 2006, Simulation-Based Engineering Science: Revolutionizing Engineering Science through Simulation
Anon, 2008, National Research Council, ISBN, 0, 12000
Anon, 2008, National Research Council,ISBN, 0, 12166

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“, increase of reliability, and timely assessment of mission parameters) [7].”
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BackgroundInfluential
Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models
Minerva, R., Lee, G. M., & Crespi, N. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2020.2998530 · Cited by 812
“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], the future of work or…”
BackgroundMethod
A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin
Liu, Y., Zhang, L., Yang, Y., Zhou, L., Ren, L., Wang, F., Liu, R., Pang, Z., & Deen, M. J. (2019) · IEEE Access · doi:10.1109/access.2019.2909828 · Cited by 763
“At present, one commonly used deﬁnition from NASA [28] is, ‘‘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 life of its corresponding…”
BackgroundMethod
Digital twins for health: a scoping review
Katsoulakis, E., Wang, Q., Wu, H., Shahriyari, L., Fletcher, R., Liu, J., Achenie, L. E. K., Liu, H., Jackson, P., Xiao, Y., et al. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01073-0 · Cited by 848
“Around 2010,NASA and John Vickers utilizedthe DT as a virtual model of a physical system 5,6 .”
Method
Digital Twin for maintenance: A literature review
Errandonea, I., Beltrán, S., & Arrizabalaga, S. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103316 · Cited by 819
Digital twins in smart farming
Verdouw, C., Tekinerdoğan, B., Beulens, A., & Wolfert, S. (2021) · Agricultural Systems · doi:10.1016/j.agsy.2020.103046 · Cited by 634
“Moreover, Digital Twins may consider multiple interdependent objects as well as sub systems at different levels of granularity (Glaessgen and Stargel, 2012; Verdouw et al., 2016b; Grieves and Vickers, 2017).”
Background
The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616
“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 life of its corres…”
Background
An application framework of digital twin and its case study
Zheng, Y., Yang, S., & Cheng, H. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0911-3 · Cited by 534
“…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).”
BackgroundMethod
Digital Twins: State of the art theory and practice, challenges, and open research questions
Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., & Calinescu, A. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2022.100383 · Cited by 587
“[26] discusses application of DT for NASA and U.S. Air Force vehicles.”
Method
Smart Manufacturing and Intelligent Manufacturing: A Comparative Review
Wang, B., Tao, F., Fang, X., Liu, C., Liu, Y., & Freiheit, T. I. (2020) · Engineering · doi:10.1016/j.eng.2020.07.017 · Cited by 571
Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus
Lu, Q., Parlikad, A. K., Woodall, P., Ranasinghe, G. D., Xie, X., Liang, Z., Konstantinou, E., Heaton, J., & Schooling, J. M. (2020) · Journal of Management in Engineering · doi:10.1061/(asce)me.1943-5479.0000763 · Cited by 532
Mechanistic models for additive manufacturing of metallic components
Wei, H., Mukherjee, T., Zhang, W., Zuback, J. S., Knapp, G., De, A., & DebRoy, T. (2020) · Progress in Materials Science · doi:10.1016/j.pmatsci.2020.100703 · Cited by 551
A systematic review of a digital twin city: A new pattern of urban governance toward smart cities
Deng, T., Zhang, K., & Shen, Z. M. (2021) · Journal of Management Science and Engineering · doi:10.1016/j.jmse.2021.03.003 · Cited by 560
Towards the future of smart electric vehicles: Digital twin technology
Bhatti, G., Mohan, H., & Singh, R. R. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.110801 · Cited by 547
Digital Twins: From Personalised Medicine to Precision Public Health
Kamel Boulos, M. N., & Zhang, P. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11080745 · Cited by 530
“However, the ﬁrst practical application that gave rise to the present name of this concept came later in 2010, during NASA’s (United States National Aeronautics and Space Administration) attempt to create digital simulations of spacecraft for testing [6].”
Background
A hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin
Luo, W., Hu, T., Ye, Y., Zhang, C., & Wei, Y. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.101974 · Cited by 525
A BIM-data mining integrated digital twin framework for advanced project management
Pan, Y., & Zhang, L. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103564 · Cited by 553
A Digital-Twin-Assisted Fault Diagnosis Using Deep Transfer Learning
Xu, Y., Sun, Y., Liu, X., & Zheng, Y. (2019) · IEEE Access · doi:10.1109/access.2018.2890566 · Cited by 533
Digital twin and its implementations in the civil engineering sector
Jiang, F., Ma, L., Broyd, T., & Chen, K. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103838 · Cited by 531
Digital Twin Service towards Smart Manufacturing
Qi, Q., Tao, F., Zuo, Y. N., & Zhao, D. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.103 · Cited by 504
A Digital Twin Approach for Fault Diagnosis in Distributed Photovoltaic Systems
Jain, P., Poon, J., Singh, J. P., Spanos, C. J., Sanders, S. R., & Panda, S. K. (2019) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2019.2911594 · Cited by 464
“of a physical system that analytically computes the measurable characteristic outputs in real time [26].”
Background
Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors
Ding, K., Chan, F. T. S., Zhang, X., Zhou, G., & Zhang, F. (2019) · International Journal of Production Research · doi:10.1080/00207543.2019.1566661 · Cited by 456
“…integrated technology roadmap deﬁned the Digital Twin as ‘an integrated multi-physics, multi-scale simulation of a vehicle or system that uses the best available physical models, sensor updates, ﬂeet history, etc., to mirror the life of its corresponding ﬂying twin’ (Glaessgen and Stargel 2012).”
A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies
Thelen, A., Zhang, X., Fink, O., Lu, Y., Ghosh, S., Youn, B. D., Todd, M. D., Mahadevan, S., Hu, C. K., & Hu, Z. Y. (2022) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-022-03425-4 · Cited by 511
“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.”
BackgroundMethodInfluential
Integrated digital twin and blockchain framework to support accountable information sharing in construction projects
Lee, D., Lee, S. H., Masoud, N., Krishnan, M. S., & Li, V. C. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103688 · Cited by 474
“The digital twin was first proposed in the product lifecycle management field [12] and studied in the aircraft and aerospace fields as a mirroring model for simulating an as-built vehicle, system, or process [13,14].”
Background
Model‐based systems engineering: Motivation, current status, and research opportunities
Madni, A. M., & Sievers, M. (2018) · Systems Engineering · doi:10.1002/sys.21438 · Cited by 424
Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing
Zhou, G., Zhang, C., Li, Z., Ding, K., & Wang, C. (2019) · International Journal of Production Research · doi:10.1080/00207543.2019.1607978 · Cited by 433
“The general acceptable deﬁnition of digital twin was developed by NASA (Glaessgen and Stargel 2012): an integrated multi-physics, multiscale, probabilistic simulation of an as-built product, system or process which can mirror the life of its corresponding twin using available physical models,…”
Method
Development of metaverse for intelligent healthcare
Wang, G., Badal, A., Jia, X., Maltz, J. S., Mueller, K. D., Myers, K. J., Niu, C., Vannier, M. W., Yan, P., Yu, Z., et al. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00549-6 · Cited by 442
A survey on AI-driven digital twins in Industry 4.0: smart manufacturing and advanced robotics
Huang, Z., Shen, Y., Li, J., Fey, M., & Brecher, C. (2021) · Sensors · doi:10.3390/s21196340 · Cited by 418
A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning
She, C., Sun, C., Gu, Z., Li, Y., Yang, C., Poor, H. V., & Vucetic, B. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2021.3053601 · Cited by 405
“According to the deﬁnition in [278], “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, and so on to mirror the life of its corresponding real system.””
Background
Digital twin in healthcare: Recent updates and challenges
Sun, T., He, X., & Li, Z. (2023) · Digital Health · doi:10.1177/20552076221149651 · Cited by 421
Industrial applications of digital twins
Jiang, Y., Yin, S., Li, K., Luo, H., & Kaynak, O. (2021) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2020.0360 · Cited by 414
“, to mirror the life of its corresponding twin [19].”
Background
Holistic Network Virtualization and Pervasive Network Intelligence for 6G
Shen, X., Gao, J., Wu, W. R., Li, M., Zhou, C., & Zhuang, W. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3135829 · Cited by 410
“Air Force Vehicles developed a digital twin paradigm for vehicles to forecast their remaining usable life and the mission success probability [76].”
Background
Deep learning in drug discovery: an integrative review and future challenges
Askr, H., Elgeldawi, E., Ella, H. A., Elshaier, Y. A. M. M., Gomaa, M. M., & Hassanien, A. E. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10306-1 · Cited by 428
“The synthesis of big molecule-based entities in various combinations that has applications in the treatment of inflammatory, microbial, and cancer issues, is the focus of biopharmaceutical manufacturing (Glaessgen and Stargel 2012; Narayanan et al.”
Background
Digital Twin for the Oil and Gas Industry: Overview, Research Trends, Opportunities, and Challenges
Wanasinghe, T. R., Wroblewski, L., Petersen, B. K., Gosine, R. G., James, L. A., Silva, O. D., Mann, G. K. I., & Warrian, P. J. (2020) · IEEE Access · doi:10.1109/access.2020.2998723 · Cited by 411
“There is a range of industries, such as manufacturing [9]–[12], automotive [13], [14], healthcare [15]–[20], aviation [21]–[25] and terrestrial exploration [21], [26], where the DT concept has been successfully deployed.”
Background
Dynamic Bayesian Network for Aircraft Wing Health Monitoring Digital Twin
Li, C., Mahadevan, S., Ling, Y., Choze, S., & Wang, L. (2017) · AIAA Journal · doi:10.2514/1.j055201 · Cited by 382
Co-Simulation
Gomes, C. Â. G., Thule, C., Broman, D., Larsen, P. G., & Vangheluwe, H. L. (2018) · ACM Computing Surveys · doi:10.1145/3179993 · Cited by 532
Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment
Sepasgozar, S. M. E. (2021) · Buildings · doi:10.3390/buildings11040151 · Cited by 414
Applications of Digital Twin across Industries: A Review
Singh, M., Srivastava, R., Fuenmayor, E. A., Kuts, V., Qiao, Y., Murray, N., & Devine, D. M. (2022) · Applied Sciences · doi:10.3390/app12115727 · Cited by 376
“Any damage detected by DT could be resolved by activating in situ repairs or recommending appropriate changes to the mission, resulting in a longer lifespan and a higher success rate of the mission [45].”
On the Integration of Agents and Digital Twins in Healthcare
Croatti, A., Gabellini, M., Montagna, S., & Ricci, A. (2020) · Journal of Medical Systems · doi:10.1007/s10916-020-01623-5 · Cited by 356
“There is not a common agreement on the definition of DTs, especially because the concept has been evolved over the years, since its initial formulation in the aerospace field by the National Aeronautics and Space Administration (NASA) [8, 10].”
Background
A systematic review of digital twin about physical entities, virtual models, twin data, and applications
Liu, X., Jiang, D., Tao, B., Xiang, F., Jiang, G., Sun, Y., Kong, J., & Li, G. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2023.101876 · Cited by 369
The role of data fusion in predictive maintenance using digital twin
Liu, Z., Meyendorf, N., & Mrad, N. (2018) · AIP conference proceedings · doi:10.1063/1.5031520 · Cited by 364
Digital twin for CNC machine tool: modeling and using strategy
Luo, W., Hu, T., Zhang, C., & Wei, Y. (2019) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0946-5 · Cited by 350
“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.”
Background
A probabilistic graphical model foundation for enabling predictive digital twins at scale
Kapteyn, M. G., Pretorius, J. V. R., & Willcox, K. E. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00069-0 · Cited by 363
Prototyping a Digital Twin for Real Time Remote Control Over Mobile Networks: Application of Remote Surgery
Laaki, H., Miché, Y., & Tammi, K. (2019) · IEEE Access · doi:10.1109/access.2019.2897018 · Cited by 273
“It includes physical products, digital products and the connectivity in between, as de(cid:28)ned in e.g. [4].”
Background
Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications
Wagg, D., Worden, K., Barthorpe, R. J., & Gardner, P. A. (2020) · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering · doi:10.1115/1.4046739 · Cited by 382
Digital Twin: A Comprehensive Survey of Security Threats
Alcaraz, C., & López, J. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3171465 · Cited by 364
“…or system that uses the best available physical models, sensor updates, ﬂeet history, etc., to mirror the life of its corresponding ﬂying twin ” [7], “ a computerized model of a physical device or system that represents all functional features and links with the working elements ” [3], and “ a…”
Background
Design, Modeling and Implementation of Digital Twins
Segovia, M., & García-Alfaro, J. (2022) · Sensors · doi:10.3390/s22145396 · Cited by 355
“This can be based on, e.g., historical data of the physical model [14,15].”
Digital Twins in Built Environments: An Investigation of the Characteristics, Applications, and Challenges
Shahzad, M., Shafiq, M. T., Douglas, D., & Kassem, M. (2022) · Buildings · doi:10.3390/buildings12020120 · Cited by 356
Mobility Digital Twin: Concept, Architecture, Case Study, and Future Challenges
Wang, Z.-R., Gupta, R., Han, K., Wang, H., Ganlath, A., Ammar, N., & Tiwari, P. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3156028 · Cited by 285
“Along with its rapid development in different domains during the past decade, including aeronautics and space [4], [7], robotics [8], [9], manufacturing [10], [11], and informatics [12], the Digital Twin also has a huge potential in the transportation domain.”
Background
Exploring the synergies between collaborative robotics, digital twins, augmentation, and industry 5.0 for smart manufacturing: A state-of-the-art review
Zafar, M. H., Langås, E. F., & Sanfilippo, F. (2024) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2024.102769 · Cited by 338
Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model
Shim, C.-S., Dang, N.-S., Lon, S., & Jeon, C.-H. (2019) · Structure and Infrastructure Engineering · doi:10.1080/15732479.2019.1620789 · Cited by 312
Recent advances on industrial data-driven energy savings: Digital twins and infrastructures
Teng, S. Y., Touš, M., Leong, W. D., How, B. S., Lam, H. L., & Máša, V. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110208 · Cited by 325
Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers
Perno, M., Hvam, L., & Haug, A. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103558 · Cited by 328
“The structure of the search strings was derived directly from the RQs to ensure they Glaessgen and Stargel (2012) “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…”
Method
Digital Twin in Aerospace Industry: A Gentle Introduction
Li, L., Aslam, S., Wileman, A., & Perinpanayagam, S. (2021) · IEEE Access · doi:10.1109/access.2021.3136458 · Cited by 316
Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks
Dai, Y., Zhang, K., Maharjan, S., & Zhang, Y. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3016320 · Cited by 298
“The concept of digital twin is first proposed in [2] and applied by NASA to comprehensive diagnosis and maintenance of flight systems.”
Method
A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools
Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3297395 · Cited by 304
From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry
Moleda, M., Małysiak-Mrozek, B., Ding, W.-P., Sunderam, V., & Mrozek, D. (2023) · Italian National Conference on Sensors · doi:10.3390/s23135970 · Cited by 317
A Simulation-Based Architecture for Smart Cyber-Physical Systems
Gabor, T., Belzner, L., Kiermeier, M., Beck, M. T., & Neitz, A. (2016) · 2016 IEEE International Conference on Autonomic Computing (ICAC) · doi:10.1109/icac.2016.29 · Cited by 298
“These ultra-high ﬁdelity simulations are commonly called a digital twin with respect to the system they model [4], [5], [6].”
Background
Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review
Chen, Y., Yang, O., Sampat, C., Bhalode, P., Ramachnadran, R., & Ierapetritou, M. (2020) · Processes · doi:10.3390/pr8091088 · Cited by 295
“Since the first definition of DT, interpretations from different perspectives have been proposed, with the most popular one given by Glaessegen and Stargel, noting that a DT is an integrated multiphysics, multiscale, probabilistic simulation of a complex product and uses the best available data, sensors, and models to…”
BackgroundMethodInfluential
Combustion machine learning: Principles, progress and prospects
Ihme, M., Chung, W. T., & Mishra, A. (2022) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2022.101010 · Cited by 300
Visualisation of the Digital Twin data in manufacturing by using Augmented Reality
Zhu, Z.-X., Liu, C., & Xu, X. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.223 · Cited by 241
Trusting artificial intelligence in cybersecurity is a double-edged sword
Taddeo, M., McCutcheon, T., & Floridi, L. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0109-1 · Cited by 299
“be considered a ‘digital twin’ [30] of the deployed system.”
Background
Digital Twins for the built environment: learning from conceptual and process models in manufacturing
Delgado, J. M. D., & Oyedele, L. O. (2021) · Advanced Engineering Informatics · doi:10.1016/j.aei.2021.101332 · Cited by 272
Blockchain for digital twins: recent advances and future research challenges
Yaqoob, I., Salah, K., Uddin, M., Jayaraman, R., Omar, M., & Imran, M. (2020) · IEEE Network · doi:10.1109/mnet.001.1900661 · Cited by 256
“DTs are expected to United States Air Force vehicles because of their striking features [1].”
Background
The Convergence of Digital Twin, IoT, and Machine Learning: Transforming Data into Action
Kaur, M., Mishra, V., & Maheshwari, P. (2019) · Internet of Things · doi:10.1007/978-3-030-18732-3_1 · Cited by 209
From simple digital twin to complex digital twin Part I: A novel modeling method for multi-scale and multi-scenario digital twin
Jia, W., Wang, W., & Zhang, Z. (2022) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101706 · Cited by 256
“NASA proposed the concept of the digital twin in 2012 [2].”
Background
Digital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems
Liu, C., Le Roux, L., Körner, C., Tabaste, O., Lacan, F., & Bigot, S. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.010 · Cited by 252
“, to mirror the life of its corresponding twin [50].”
Background
Methodology for enabling Digital Twin using advanced physics-based modelling in predictive maintenance
Aivaliotis, P., Georgoulias, K., Arkouli, Z., & Makris, S. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.072 · Cited by 204
Improving process safety: What roles for Digitalization and Industry 4.0?
Lee, J., Cameron, I., & Hassall, M. E. (2019) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2019.10.021 · Cited by 241
Intelligent Maintenance Systems and Predictive Manufacturing
Lee, J., Ni, J., Singh, J., Jiang, B., Azamfar, M., & Feng, J. (2020) · Journal of Manufacturing Science and Engineering · doi:10.1115/1.4047856 · Cited by 289
Data‐driven physics‐based digital twins via a library of component‐based reduced‐order models
Kapteyn, M. G., Knezevic, D. J., Huynh, D. B. P., Tran, M., & Willcox, K. E. (2020) · International Journal for Numerical Methods in Engineering · doi:10.1002/nme.6423 · Cited by 237
“The digital twin paradigm has garnered attention in a range of engineering applications, such as structural health monitoring and aircraft sustainment procedures [1, 2], simulation-based vehicle certification [1, 3], and fleet management [1, 4, 5].”
Background
Data-driven ship digital twin for estimating the speed loss caused by the marine fouling
Coraddu, A., Oneto, L., Baldi, F., Cipollini, F., Atlar, M., & Savio, S. (2019) · Ocean Engineering · doi:10.1016/j.oceaneng.2019.05.045 · Cited by 252
“In this work a data driven Digital Twin of the ship is built, leveraging on the large amount of information collected from the on-board sensors, and is used for estimating the speed loss due to marine fouling.”
MethodInfluential
A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect
Liu, C., Vengayil, H., Lu, Y.-Q., & Xu, X. (2019) · Journal of manufacturing systems · doi:10.1016/j.jmsy.2019.04.006 · Cited by 209
Scaling digital twins from the artisanal to the industrial
Niederer, S., Sacks, M. S., Girolami, M., & Willcox, K. E. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00072-5 · Cited by 231
“A great deal of attention has focused on digital twins to support structural health monitoring, sustainment and predictive maintenance 14,15 .”
Background
A Requirements Driven Digital Twin Framework: Specification and Opportunities
Moyne, J. R., Qamsane, Y., Balta, E. C., Kovalenko, I., Faris, J., Barton, K. L., & Tilbury, D. M. (2020) · IEEE Access · doi:10.1109/access.2020.3000437 · Cited by 230
“These include contributions from NASA and the US Air Force Research Laboratory [20], General Electric (GE) [8], the Industrial Internet Consortium [21], and a number of academic sources [22]–[25].”
Background
Is Human Digital Twin possible?
Shengli, W. (2021) · Computer Methods and Programs in Biomedicine Update · doi:10.1016/j.cmpbup.2021.100014 · Cited by 233
Digital twins: An analysis framework and open issues
Boyes, H. A., & Watson, T. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103763 · Cited by 241
“The concept of simulation as a core element of a digital twin was established by Glaessgen and Stargel (2012).”
Systematic review of digital twin technology and applications
Yao, J.-F., Yang, Y., Wang, X.-C., & Zhang, X.-P. (2023) · Visual Computing for Industry, Biomedicine, and Art · doi:10.1186/s42492-023-00137-4 · Cited by 201
“Reference Year DT definition 1 [9] 2012 DT is a multi‑scale integrated simulation of a physical equipment or system that makes full use of virtual models, real‑time sen‑ sor data, and historical data on the equipment or system to map the entire life cycle of the process 2 [8] 2012 DT models need to…”
BackgroundMethod
Digital twin and cloud-side-end collaboration for intelligent battery management system
Wang, Y., Xu, R., Zhou, C., Kang, X., & Chen, Z. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.11.006 · Cited by 222
Web-based digital twin modeling and remote control of cyber-physical production systems
Liu, C., Jiang, P., & Jiang, W. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.101956 · Cited by 223
Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
Sleiti, A. K., Kapat, J. S., & Veselý, L. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.02.305 · Cited by 245
Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review
Peladarinos, N., Piromalis, D. D., Cheimaras, V., Tserepas, E., Munteanu, R. A., & Papageorgas, P. G. (2023) · Sensors · doi:10.3390/s23167128 · Cited by 227
“[9], the concept of DTs emerged from NASA’s pioneering work in integrating physical models and simulations [10,11] to analyze intricate systems.”
Background
Digital Twin for Supply Chain Coordination in Modular Construction
Lee, D., & Lee, S. H. (2021) · Applied Sciences · doi:10.3390/app11135909 · Cited by 234
“A digital twin consists of three main components: the physical object, the virtual object, and the linkage between them [27].”
Background
Digital Twins in Healthcare: Is It the Beginning of a New Era of Evidence-Based Medicine? A Critical Review
Armeni, P., Polat, I., Rossi, L. M. D., Diaferia, L., Meregalli, S., & Gatti, A. M. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12081255 · Cited by 219
Real-time machining data application and service based on IMT digital twin
Tong, X., Liu, Q., Pi, S., & Xiao, Y. (2019) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01500-0 · Cited by 192
“A general definition of the digital twin was given by Glaessgen and Stargel (2012): digital twin is an integrated multi-physics, multi-scale, and probabilistic simulation of a complex product and use the best available physical models and sensor updates to mirror the life of its corresponding twin.”
Method
The concept of digital twin and digital shadow in manufacturing
Bergs, T., Gierlings, S., Auerbach, T., Klink, A., Schraknepper, D., & Augspurger, T. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.02.010 · Cited by 212

Authors: Glaessgen, E., & Stargel, D.
Affiliations: Langley Research Center (US)
United States Air Force Office of Scientific Research (US)
Venue: 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA
Publisher: American Institute of Aeronautics and Astronautics
Published: 2012-04-23
DOI: 10.2514/6.2012-1818
OpenAlex: W2046074714
Semantic Scholar: 733d40c04be482d38dbd21f82b81e0fc890b6669
Cited by: 2,404
References: 1
Citations by year: 2026: 214 · 2025: 332 · 2024: 451 · 2023: 381 · 2022: 342 · 2021: 278 · 2020: 211 · 2019: 108 · 2018: 48 · 2017: 13 · 2016: 11 · 2015: 4 · 2014: 6 · 2013: 4
FWCI: 11.20
Type: conference paper
Language: en
Open access: green
hdl.handle.net
Locations: NASA STI Repository (National Aeronautics and Space Administration) (submittedVersion)
Topics: Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
Physical Sciences › Engineering › Control and Systems Engineering › Engineering and Test Systems
Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
Keywords: digital twin, integrated vehicle health management, aircraft certification, fleet management, program sustainability, material property variation, maintenance history, safety and reliability

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

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