The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Reengineering Aircraft Structural Life Prediction Using a Digital Twin
Open accessAbstract
Reengineering of the aircraft structural life prediction process to fully exploit advances in very high performance digital computing is proposed. The proposed process utilizes an ultrahigh fidelity model of individual aircraft by tail number, a Digital Twin, to integrate computation of structural deflections and temperatures in response to flight conditions, with resulting local damage and material state evolution. A conceptual model of how the Digital Twin can be used for predicting the life of aircraft structure and assuring its structural integrity is presented. The technical challenges to developing and deploying a Digital Twin are discussed in detail.
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“Subsequently, following NASA's footsteps, the US Air Force Research Laboratory (AFRL) adopted DT technology for aircraft design, maintenance, and prediction [20].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [20]
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Citations
Cites
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SUGGAR: A General Capability for Moving Body Overset Grid Assembly
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Some challenges of realistic flow simulations by unstructured grid CFD
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Research directions in computational mechanics
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Cited by
Sorted by citations
High-performance medicine: the convergence of human and artificial intelligence
Topol, E. J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0300-7 · Cited by 10,450
Digital Twin in Industry: State-of-the-Art
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391
Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems
Grieves, M., & Vickers, J. (2017) · Transdisciplinary Perspectives on Complex Systems · doi:10.1007/978-3-319-38756-7_4 · Cited by 3,727
Digital twin-driven product design, manufacturing and service with big data
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0233-1 · Cited by 2,920
The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles
Glaessgen, E., & Stargel, D. (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 · Cited by 2,404
Metadata
- Authors
- Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M.
- Affiliations
- United States Air Force Research Laboratory (US)
- Cornell University (US)
- Corresponding author
- Tuegel, Eric J.
- Venue
- International Journal of Aerospace Engineering
- Publisher
- Wiley
- Published
- 2011
- Volume
- 2011
- Pages
- 1-14
- ISSN
- 1687-5966 (ISSN-L)
- 1687-5974
- OpenAlex
- W2108366027
- Cited by
- 1,119
- References
- 45
- Citations by year
- 2026: 75 · 2025: 119 · 2024: 173 · 2023: 158 · 2022: 179 · 2021: 129 · 2020: 110 · 2019: 77 · 2018: 50 · 2017: 20 · 2016: 12 · 2015: 6 · 2014: 4 · 2013: 3 · 2012: 4
- FWCI
- 10.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- International Journal of Aerospace Engineering (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Mechanics of Materials › Fatigue and fracture mechanics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Keywords
- digital twin, structural integrity, structural deflection, temperature prediction, local damage, flight conditions, aircraft structural health monitoring
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