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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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Cites
The stochastic finite element method: Past, present and future
Stefanou, G. (2008) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/j.cma.2008.11.007 · Cited by 1,006
Partitioned analysis of coupled mechanical systems
Felippa, C. A., Park, K. C., & Farhat, C. (2001) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/s0045-7825(00)00391-1 · Cited by 822
Generalized finite element methods for three-dimensional structural mechanics problems
Duarte, C. A., Babuska, I. M., & Oden, J. T. (2000) · Computers & Structures · doi:10.1016/s0045-7949(99)00211-4 · Cited by 652
Studies on Fluid-Thermal-Structural Coupling for Aerothermoelasticity in Hypersonic Flow
Culler, A. J., & McNamara, J. J. (2010) · AIAA Journal · doi:10.2514/1.j050193 · Cited by 250
Duarte, C. A., & Kim, D. J. (2007) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/j.cma.2007.08.017 · Cited by 215
Nonlinear modal models for sonic fatigue response prediction: a comparison of methods
Hollkamp, J. J., Gordon, R. W., & Spottswood, S. M. (2004) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2004.08.036 · Cited by 190
A general theory of finite elements. II. Applications
Oden, J. T. (1969) · International Journal for Numerical Methods in Engineering · doi:10.1002/nme.1620010304 · Cited by 189
SUGGAR: A General Capability for Moving Body Overset Grid Assembly
Noack, R. W. (2005) · AIAA Computational Fluid Dynamics Conference · doi:10.2514/6.2005-5117 · Cited by 167
Some challenges of realistic flow simulations by unstructured grid CFD
Nakahashi, K., Ito, Y., & Togashi, F. (2003) · International Journal for Numerical Methods in Fluids · doi:10.1002/fld.559 · Cited by 154
Research directions in computational mechanics
Oden, J. T., Belytschko, T., Babuska, I. M., & Hughes, T. J. R. (2003) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/s0045-7825(02)00616-3 · Cited by 153
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Champaney, V., Amores, V. J., Garois, S., Irastorza-Valera, L., Ghnatios, C., Montáns, F. J., Cueto, E., & Chinesta, F. (2022) · Frontiers in Materials · doi:10.3389/fmats.2022.970970 · Cited by 9
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Wang, H., Zhang, P., Zhang, Z., Zhang, Y., & Wang, Y. (2022) · Applied Sciences · doi:10.3390/app122412990 · Cited by 6
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Yin, W.-M., Hu, Y.-F., Ding, G., Feng, L., & Chen, X.-F. (2024) · Measurement · doi:10.1016/j.measurement.2024.116235 · Cited by 8
Zhang, W., Chen, Y., He, X., Xue, F., Xu, P., & He, W. (2025) · International Journal of Fatigue · doi:10.1016/j.ijfatigue.2025.109475 · Cited by 6
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Loghin, A., & Ismonov, S. (2020) · AIAA SciTech Forum · doi:10.2514/6.2020-2295 · Cited by 6
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Mei, B., Yang, Y., & Zhu, W. (2021) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4052837 · Cited by 6
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Ghienne, M., & Limare, A. (2023) · Computers & Structures · doi:10.1016/j.compstruc.2023.107155 · Cited by 6
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Digital twins in the asset life cycle: are we there yet?
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A Critical Comparison of Shape Sensing Algorithms: The Calibration Matrix Method versus iFEM
de Mooij, C., & Martinez, M. J. (2024) · Sensors · doi:10.3390/s24113562 · Cited by 6
Zhang, L., He, S., Li, B., Mao, X., & Tan, X. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-13840-0 · Cited by 6
Emerging Opportunities in Distributed Manufacturing: Results and Analysis of an Expert Study
Daehn, G. S., Blue, C. A., Johnson-Bey, C., Lewandowski, J. J., Mahoney, T., Okwudire, C. E., Rossman, T., Schmitz, T. L., & Silveston, R. (2024) · Integrating materials and manufacturing innovation · doi:10.1007/s40192-024-00365-3 · Cited by 7
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Smith, H. (2024) · Information Communication & Society · doi:10.1080/1369118x.2024.2423346 · Cited by 6
Costa, G., Agostino Forestiero, A., Gentile, A. F., Macrì, D., Ortale, R., Bernardi, B., & Cerruto, E. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10826124 · Cited by 6
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Chaudhari, S., Bhole, K., & Rane, S. B. (2025) · Journal of the Institution of Engineers (India) Series C · doi:10.1007/s40032-025-01164-1 · Cited by 6
Sha, J., Leng, J.-C., Mao, H.-B., Pei, J., & Diao, K. (2025) · Journal of Marine Science and Application · doi:10.1007/s11804-025-00649-w · Cited by 6
Digital Twin Model and Platform Based on a Dual System for Control Rod Drive Mechanism Safety
Wan, C., Li, W., Yang, B., Ling, S., Fu, G., & Hong, Y. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.111075 · Cited by 6
Chen, S., Xu, H. G., Zhao, S., Tan, D., Dong, Z., Qu, X., Yang, L., & Wu, Z. (2025) · Measurement · doi:10.1016/j.measurement.2025.118070 · Cited by 6
State Tracking of Composite Delaminations with a Bayesian Filter
Gregory, E. D., & Holland, S. D. (2015) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2015.189 · Cited by 6
Analysis of Machine Learning Algorithms in Smart Manufacturing
Ratnayake, D., Lohit, P., Singh, B., & Mishra, V. (2020) · 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) · doi:10.1109/icrito48877.2020.9198017 · Cited by 3
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Yu, J., & Tang, D. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91300-3.00005-x · Cited by 6
Design of modified model of intelligent assembly digital twins based on optical fiber sensor network
Liu, Z., Yang, J., Wang, J., & Yue, L. (2022) · Digital Communications and Networks · doi:10.1016/j.dcan.2022.06.013 · Cited by 7
Discrete event-driven twin workshop modeling and simulation technology
Li, J., Zhang, N., Wang, A., Wang, S., & Shan, Q. (2022) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma54519.2022.9855939 · Cited by 6
Wang, S., Wang, Y., Liu, X., Wang, J., & Wang, Z. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/7324121 · Cited by 6
Deep learning for predicting frequency lock-in of a freely vibrating sphere
Chizfahm, A., & Jaiman, R. K. (2022) · Physics of Fluids · doi:10.1063/5.0121630 · Cited by 8
Lagartinho-Oliveira, C., Moutinho, F., & Gomes, L. (2022) · Computers · doi:10.3390/computers11110166 · Cited by 6
Jumeaux numériques : futur de la médecine personnalisée en cancérologie
Heudel, P., Renard, F., & Attyé, A. (2023) · Bulletin du Cancer · doi:10.1016/j.bulcan.2023.07.007 · Cited by 6
Architecture and Implementation of High-Fidelity Digital Twins for Industrial Robots
Liu, Y., Wang, X., Yang, K., Pan, Y., & Wang, Q. (2023) · International Conference on Frontiers of Robotics and Software Engineering (FRSE) · doi:10.1109/frse58934.2023.00036 · Cited by 6
Digital twins a digital transformation for management of the construction industry
Alvarenga, C. D. B. C. S., Aguilar, M. T. P., Sales, R. D. B. C., & Caldas, R. B. (2024) · Contribuciones a las Ciencias Sociales · doi:10.55905/revconv.17n.2-036 · Cited by 6
Advances in Virtual Factory Research and Applications
Bal, A., & Satoğlu, Ş. I. (2017) · Springer series in advanced manufacturing · doi:10.1007/978-3-319-57870-5_14 · Cited by 6
Digital Twin of Solid Rocket Motor, Problem and Challenge
Xiao, F., Fengchen, Q., Bing, S., & Yu-zhu, F. (2018) · International Symposium on Computational Intelligence and Design · doi:10.1109/iscid.2018.10103 · Cited by 6
Application of Artificial Intelligence to an Electrical Rewinding Factory Shop
Matenga, A., Murena, E., & Mpofu, K. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.04.135 · Cited by 6
Thermo-mechanical-optical coupling within a digital twin development for automotive LiDAR
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Dynamic Reduction-Based Virtual Models for Digital Twins—A Comparative Study
Maulik, S., Riordan, D., & Walsh, J. L. (2022) · Applied Sciences · doi:10.3390/app12147154 · Cited by 5
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Wang, H., Chen, S., Sami, M. S. U. I., Rahman, F., & Tehranipoor, M. M. (2020) · Springer eBooks · doi:10.1007/978-3-030-64448-2_2 · Cited by 6
Wang, D., Zhang, Z., Zhang, M., Fu, M., Li, J. C., Cai, S., Zhang, C., & Chen, X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.04877 · Cited by 6
A Formal Framework for Digital Twin Modeling, Verification, and Validation
Traoré, M. K., Gorecki, S., & Ducq, Y. (2024) · Simulation foundations, methods and applications · doi:10.1007/978-3-031-69107-2_6 · Cited by 5
Digital Twin for Health Monitoring of a Cantilever Beam Using Support Vector Machine
Harikumar, V., & Bijudas, C. R. (2025) · Journal of Vibration Engineering & Technologies · doi:10.1007/s42417-024-01608-5 · Cited by 5
Serratore, G., Borda, F., Cosma, A. M. I., Gagliardi, F., & Filice, L. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.02.038 · Cited by 5
Zhang, J. Z., Bakar, A., Humphry, A., Javid, F., Nadeau, P., Ebrahimi, M., Butscher, A., Tessier, A., Rodriguez, J., & Farhat, C. (2024) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/j.cma.2025.117863 · Cited by 5
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Li, L. (2025) · Intelligent and Converged Networks · doi:10.23919/icn.2025.0002 · Cited by 6
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Bae, C.-H., Choi, E.-T., Kang, S., Ahn, R., & Lee, S. (2025) · Future Generation Computer Systems · doi:10.1016/j.future.2025.108078 · Cited by 5
Bardiani, J., Poloni, D., Oboe, D., Giglio, M., Manes, A., & Sbarufatti, C. (2025) · Aerospace Science and Technology · doi:10.1016/j.ast.2025.111067 · Cited by 5
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Zhang, Y., Shi, K., & Li, B. (2025) · PET Clinics · doi:10.1016/j.cpet.2025.09.006 · Cited by 7
Peng, W., Hou, J., Guo, W., Li, J., & Duan, T. (2025) · npj Materials Degradation · doi:10.1038/s41529-025-00661-z · Cited by 5
Zhou, J., Liu, C., Ban, C., Shi, Z., Shang, H., Zhou, H., & Li, Z. (2026) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2026.107469 · Cited by 5
Exploiting Digital Twins in MBSE to Enhance System Modeling and Life Cycle Coverage
Madni, A. M., Purohit, S., & Madni, C. C. (2023) · Springer eBooks · doi:10.1007/978-3-030-93582-5_33 · Cited by 6
Omrany, H., Ghaffarianhoseini, A., GhaffarianHoseini, A., Dhawan, K., Almhafdy, A., & Oteng, D. (2024) · Urban sustainability · doi:10.1007/978-981-99-9014-6_11 · Cited by 6
Oke, A. E., Arowoiya, V. A., Chan, M., & Oyediran, A. O. (2024) · International Journal of Construction Management · doi:10.1080/15623599.2024.2411885 · Cited by 7
Crawford, B. R., Loader, C., Harrison, T. J., & Liu, Q. (2013) · Cited by 5
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Wang, J., Li, P., Li, X., & Zhu, H. (2021) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/861/7/072046 · Cited by 5
Zhou, X., Oboe, D., Poloni, D., Sbarufatti, C., Dong, L., & Giglio, M. (2022) · AIAA Journal · doi:10.2514/1.j062417 · Cited by 5
Aldabbas, L. J. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0140418 · Cited by 5
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Xin, X., Jianrong, T., Zhengyu, L., Yongfeng, S., & Ding, J. (2022) · Journal of Mechanical Engineering · doi:10.3901/jme.2022.17.191 · Cited by 5
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Sama, N. U., Jhanjhi, N. Z., Humayun, M., & Rahman, A. U. (2024) · AIP conference proceedings · doi:10.1063/5.0168361 · Cited by 5
Horvath, A.-S., & Pouliou, P. (2024) · CRC Press eBooks · doi:10.1201/9781003425724-46 · Cited by 7
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Song, L., Lu, Z., & Petsangsri, S. (2020) · International Conference on Dependable Systems and Their Applications (DSA) · doi:10.1109/dsa51864.2020.00070 · Cited by 5
Richstein, R., Schmid, S., & Schröder, K. (2022) · Lecture notes in civil engineering · doi:10.1007/978-3-031-07254-3_44 · Cited by 5
Rabe, M., & Kilic, E. (2022) · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice/itmc-iamot55089.2022.10033175 · Cited by 5
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Kapoor, G., & Sharma, P. (2024) · AIP conference proceedings · doi:10.1063/5.0184387 · Cited by 4
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Finan, A. E., Ritter, C., Suyderhoud, P. A., & Marshall, A. (2024) · Frontiers in Energy Research · doi:10.3389/fenrg.2024.1443896 · Cited by 4
He, Y., Guo, J., Liu, L., Liu, H., Zhang, X., Zhao, Q., Zheng, X., Jin, M., Wang, T., Liu, C., et al. (2018) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/3274783.3275179 · Cited by 4
Donoghue, I., Hannola, L., & Mikkola, A. (2019) · Portland International Conference on Management of Engineering and Technology (PICMET) · doi:10.23919/picmet.2019.8893904 · Cited by 4
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Suvorova, A. V. (2022) · Lecture notes in information systems and organisation · doi:10.1007/978-3-030-94617-3_10 · Cited by 5
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Oughton, E. J. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3141527 · Cited by 4
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Chen, X., Eder, M., & Shihavuddin, A. (2020) · doi:10.36227/techrxiv.13106108 · Cited by 4
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Kumar, S., Fred, A. L., Miriam, L. R. J., Christina, J. I., Kumar, H. A., Padmanabhan, P., & Gulyás, B. Z. (2022) · Wiley eBooks · doi:10.1002/9781119842316.ch5 · Cited by 4
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Traoré, M. K. (2023) · Preprints.org · doi:10.20944/preprints202310.0659.v1 · Cited by 4
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Shah, N., Nagar, J., Desai, K., Bhatt, N., Bhatt, N., & Mewada, H. K. (2024) · Wiley eBooks · doi:10.1002/9781394287420.ch5 · Cited by 4
IIoT and Digital Twin: A Systematic Literature Review and Looking Beyond the State
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Zhang, L., Li, R., Shao, C., Mei, Y., Song, H., Qiu, J., Li, J., Sun, C., & Liu, Y. (2026) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2026.114060 · Cited by 3
Kotecha, M. C., Staack, D., & McAdams, D. A. (2022) · Journal of Mechanical Design · doi:10.1115/1.4055136 · Cited by 3
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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