Reengineering Aircraft Structural Life Prediction Using a Digital Twin

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

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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

Analysis and applications of a generalized finite element method with global–local enrichment functions

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

Digital twinning for purpose-driven information management in production

Slot, M., & Lutters, E. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.05.141 · Cited by 11

Digital twin for component health- and stress-aware rotorcraft flight control

Sisson, W., Karve, P., & Mahadevan, S. (2022) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-022-03413-8 · Cited by 11

HIDT: A Digital Twin modeling approach through hierarchical integration for industrial internet

Zhang, H., Feng, Q., Wu, M., Xi, S., & Zhang, P. (2023) · Computers & Industrial Engineering · doi:10.1016/j.cie.2023.109306 · Cited by 11

A digital twin library of mechanical transmission system for the application of small sample fault diagnosis problem

Meng, X., Hu, T., Li, J., Zhang, Y., & Ma, S. (2024) · Measurement Science and Technology · doi:10.1088/1361-6501/ad34ef · Cited by 12

A Concept of Operations for an Integrated Vehicle Health Assurance System

Hunter, G. W., Ross, R., Berger, D. E., Lekki, J., Mah, R. W., Perey, D. F., Schuet, S., Simon, D. L., & Smith, S. W. (2013) · NASA Technical Reports Server (NASA) · Cited by 11

Improving Prediction Capability of Quadcopter Through Digital Twin

Jeon, H. Y., Justin, C. Y., & Mavris, D. N. (2019) · AIAA SciTech Forum · doi:10.2514/6.2019-1365 · Cited by 11

Digital Dices: Towards the Integration of Cyber-Physical Systems Merging the Web of Things and Microservices

Mena, M., Criado, J., Iribarne, L., & Corral, A. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-32065-2_14 · Cited by 11

A Review, Focused on Data Transfer Standards, of the Uncertainty Representation in the Digital Twin Context

Ríos, J., Staudter, G. A., Weber, M., & Anderl, R. (2019) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-42250-9_3 · Cited by 11

Thermo-mechanical-optical coupling within a digital twin development for automotive LiDAR

Tavakolibasti, M., Meszmer, P., Bottger, G. T., Kettelgerdes, M., Elger, G., Erdogan, H., Seshaditya, A., & Wunderle, B. (2022) · Microelectronics Reliability · doi:10.1016/j.microrel.2022.114871 · Cited by 11

Digital twin innovations for induction motor monitoring and predictive maintenance: A 2020–2025 review

Phutane, P. S., Chavan, S. L., Pawar, H., Mane, S., & Barde, V. (2025) · Next research. · doi:10.1016/j.nexres.2025.100969 · Cited by 10

Global Mechanical Response Sensing of Corrugated Compensators Based on Digital Twins

Zhou, R., Jiang, J., Qin, J., Du, N., Shi, H., & Wang, Y. (2023) · Applied Sciences · doi:10.3390/app13064048 · Cited by 10

Digital Twin in TIM

Wang, W., Zaheer, Q., Qiu, S., Wang, W., Ai, C., Wang, J., Wang, S., & Hu, W. (2023) · Springer eBooks · doi:10.1007/978-981-99-5804-7_4 · Cited by 10

Remote nuclear microreactors: a preliminary economic evaluation of digital twins and centralized offsite control

Bryan, H. C., Jesse, K., Miller, C. A., & Browning, J. M. (2023) · Frontiers in Nuclear Engineering · doi:10.3389/fnuen.2023.1293908 · Cited by 19

Towards Developing Reinforced Concrete Structures Digital Twins: A Multiscale Lattice Discrete Particle Model Approach

Zhu, Y., & Fascetti, A. (2024) · Advances in Structural Engineering · doi:10.1177/13694332241260866 · Cited by 10

Natural Language Interaction with a Household Electricity Knowledge-based Digital Twin

Fortuna, C., Hanžel, V., & Bertalanič, B. (2024) · IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) · doi:10.1109/smartgridcomm60555.2024.10738062 · Cited by 10

Concept and framework of digital twin human geographical environment

Xu, B., Xiao, X. P., Wang, Y. P., Kang, Y., Chen, Y., Wang, P., & Lin, H. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.123866 · Cited by 10

Multi-fidelity strength monitoring method for dynamic response of deep-sea pipelines based on digital-twin technology

Yu, J., Jin, Z., Yang, Y., Shao, Q., Su, Y., Li, Z., Gao, R., & Tian, H. (2025) · Applied Ocean Research · doi:10.1016/j.apor.2025.104414 · Cited by 11

Digital Twin’s Anatomy: A Cross-Sector Framework With Healthcare Validation

Araghi, S. N., Liu, Z., Sarkar, A., Louge, T., & Karray, M. H. (2025) · IEEE Access · doi:10.1109/access.2025.3528736 · Cited by 12

Condition-based fatigue life monitoring of a high-pressure hydrogen storage vessel using a reduced basis digital twin

Kang, D., Kang, S., Kim, B., & Lee, K. (2025) · Engineering Structures · doi:10.1016/j.engstruct.2025.120196 · Cited by 10

Research on Water Resources Intelligent Management of Thermal Power Plant Based on Digital Twins

Haihong, J., Li, J., Zhang, S., & Wu, Q. (2021) · International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) · doi:10.1109/icccbda51879.2021.9442503 · Cited by 10

Framework for remaining useful life prediction of casting roller in continuous casting machine based on digital twin

Han, Z., Shi, H., Liu, Y., Ba, L., Yuan, Q., Yang, M., & Gao, X. (2021) · IEEE International Conference on Software Engineering and Artificial Intelligence (SEAI) · doi:10.1109/seai52285.2021.9477527 · Cited by 10

Use of the digital twin concept to optimize the production process of engine blocks manufacturing

Sujová, E., Bambura, R., Vysloužilová, D., & Koleda, P. (2023) · Production Engineering Archives · doi:10.30657/pea.2023.29.20 · Cited by 10

How Can Digital Twins Support the Net Zero Vision?

Papadonikolaki, E., & Anumba, C. (2023) · Lecture notes in civil engineering · doi:10.1007/978-3-031-32515-1_7 · Cited by 13

Digital Twin-based Smart Building Management and Control Framework

Jian, N. I. E., Xu, W., CHENG, D.-Z., & Yu, Y. (2019) · DEStech Transactions on Computer Science and Engineering · doi:10.12783/dtcse/icaic2019/29395 · Cited by 12

Design and Development of Digital Twin System for Intelligent Motor

Jitong, X., Wang, L., & Yan, Z. (2020) · IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA) · doi:10.1109/aeeca49918.2020.9213679 · Cited by 10

A Generic DigitalTwin Model for Artificial Intelligence Applications

Niggemann, O., Diedrich, A., Kühnert, C., Pfannstiel, E., & Schraven, J. (2021) · IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) · doi:10.1109/icps49255.2021.9468243 · Cited by 10

On the alleviation of imminent technical and business challenges of long-lasting functional digital twins

Zeb, A., Kortelainen, J., Rantala, T., Saunila, M., & Ukko, J. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103701 · Cited by 11

Digital Twin-driven approach towards manufacturing processes support

Helman, J. (2022) · Journal of Physics, Conference Series · doi:10.1088/1742-6596/2198/1/012007 · Cited by 6

Development of Digital Twin-based WEEE Recycling Workshop: Initial Approaches and Future Challenges

Li, J., Zheng, H., & Bao, J. (2022) · International Conference on Robotics and Automation Sciences (ICRAS) · doi:10.1109/icras55217.2022.9842043 · Cited by 9

A digital twin modeling method based on multi-source crack growth prediction data fusion

Fang, X., Liu, G., Wang, H., & Tian, X. (2023) · Engineering Failure Analysis · doi:10.1016/j.engfailanal.2023.107645 · Cited by 9

Fatigue Crack and Residual Life Prediction Based on an Adaptive Dynamic Bayesian Network

Chen, S., Ma, Y., Wang, Z., Liu, M., & Wu, Z. (2024) · Applied Sciences · doi:10.3390/app14093808 · Cited by 9

Development and validation of graphics‐based digital twin framework for UAV‐aided post‐earthquake inspection of high‐rise buildings

Wang, J., Wu, Y., Wang, S., Narazaki, Y., Liu, H., & Spencer, B. F. (2024) · The Structural Design of Tall and Special Buildings · doi:10.1002/tal.2127 · Cited by 9

Mapping the Complexity of Net Zero Transition Through a System of Digital Twin Systems

Papadonikolaki, E., & Anumba, C. (2024) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2024.3428641 · Cited by 9

Digital twin–driven causal diagnosis mechanism for life health of high-speed spindle system

Feng, Y., & Fan, K. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-14200-8 · Cited by 9

Digital Twin for Smart Grid: A Survey

Xu, J., Li, Y., Zhang, X., Guan, P., Zhang, S., & Li, T. (2024) · International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) · doi:10.1109/iccsie61360.2024.10698570 · Cited by 9

Modeling of the blockchain-empowered cloud 4D printing services collaboration digital twin platform oriented on supply–demand

Liu, J., Zainudin, E. S., As’arry, A., Ismai, M. I. S. B., & Zhang, C. (2025) · Soft Computing · doi:10.1007/s00500-025-10461-x · Cited by 10

Augmented reality mobile digital twin for unmanned aerial vehicle wildfire prevention

Costa, C. S., Gomes, E., Rodrigues, N., Gonçalves, A., Ribeiro, R., Costa, P., & Pereira, A. M. D. J. (2025) · Virtual Reality · doi:10.1007/s10055-025-01145-w · Cited by 11

An inceptive approach for designing simple digital twins and industrial metaverse process frameworks for small manufacturing I5.0 environments using Node-RED

Kiangala, K. S., & Wang, Z. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-16434-6 · Cited by 9

The next-generation digital twin: from advanced sensing towards artificial intelligence-assisted physical-virtual system

Zhu, J., Yang, Y., Xi, M., Ji, S., Jia, L., & Hu, T. (2025) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2025.100942 · Cited by 10

Structural damage diagnosis and prognosis with fleet digital twin considering similarity of individual structural features

Xu, J., Dai, D., Zhou, X., Giglio, M., Sbarufatti, C., & Dong, L. (2025) · Aerospace Science and Technology · doi:10.1016/j.ast.2025.110983 · Cited by 9

Probabilistic Design and Management of Sustainable Concrete Infrastructure Using Multi-Physics Service Life Models

Lepech, M. D., Geiker, M. R., Michel, A., & Stang, H. (2016) · Cited by 9

Creep Rupture: From Physical Failure Mechanisms to Lifetime Prediction of Structures

Kangkang, W., Xiaowei, W., Jianfeng, W., Zhang, X., Jianming, G., & Shan-tung, T. (2021) · Journal of Mechanical Engineering · doi:10.3901/jme.2021.16.132 · Cited by 9

Damage Diagnostics on Post-buckled Stiffened Panels Utilizing the Digital-Twin Concept

Milanoski, D., Galanopoulos, G., Zarouchas, D. S., & Λούτας, Θ. (2022) · Lecture notes in civil engineering · doi:10.1007/978-3-031-07254-3_21 · Cited by 9

Digital Twins as Foundation for Augmented Reality Applications in Aerospace

Albuquerque, G., Fischer, P. M., Azeem, S. M., Bernstein, A.-C., Utzig, S., & Gerndt, A. (2023) · Springer handbooks · doi:10.1007/978-3-030-67822-7_35 · Cited by 9

Opportunities and Challenges of Digital Twins in Structural Health Monitoring

Tran, M. Q., Sousa, H. S., Nguyen, N. T. C., Nguyen, Q. H., & Matos, J. C. (2023) · Lecture notes in civil engineering · doi:10.1007/978-981-99-2345-8_69 · Cited by 9

Information gain-based inspection scheduling for fatigued aircraft components

Ling, Y., Asher, I., Wang, L., Viana, F. A. C., & Khan, G. (2017) · AIAA Non-Deterministic Approaches Conference · doi:10.2514/6.2017-1565 · Cited by 9

On the Effectiveness of Recurrent Neural Networks for Live Modeling of Cyber-Physical Systems

Yoginath, S. B., Tansakul, V., Chinthavali, S., Taylor, C. R., Hambrick, J. C., Irminger, P., & Perumalla, K. S. (2019) · IEEE International Conference on Industrial Internet (ICII) · doi:10.1109/icii.2019.00062 · Cited by 9

Gaps and Barriers to Successful Integration and Adoption of Practical Materials Informatics Tools and Workflows

McDowell, D. L. (2020) · JOM · doi:10.1007/s11837-020-04434-8 · Cited by 9

3D Digital Twin of Intelligent Transportation System based on Road-Side Sensing

Guo, Y., Zou, K., Chen, S., Yuan, F., & Fang, Y. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2083/3/032022 · Cited by 9

High-accuracy virtual testing of air conditioner’s digital twin focusing on key material’s deformation and fracture behavior prediction

Fu, S., Wan, Z., Lü, W., Liu, H., Zhang, P., Yu, B., Tan, M. J., Pan, F., & Liu, Z. (2022) · Scientific Reports · doi:10.1038/s41598-022-16511-w · Cited by 9

A modeling method of complex assembly based on digital twin

Zhi, J., Yang, J., Zhu, C., Liu, S., Anwer, N., & Cao, Y. (2022) · Procedia CIRP · doi:10.1016/j.procir.2022.10.035 · Cited by 10

Enhancing Interoperability of Digital Twin in the Maintenance phase of Lifecycle

Ariansyah, D., & Pardamean, B. (2022) · International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) · doi:10.1109/icitisee57756.2022.10057666 · Cited by 9

Experimental Validation of an Optically Measured Geometric Mistuning Model Using a System ID Approach

Kaszynski, A. A., Brown, J. M., & Beck, J. A. (2015) · AIAA Non-Deterministic Approaches Conference · doi:10.2514/6.2015-1371 · Cited by 9

An Ultrafast Crack Growth Lifing Model to Support Digital Twin, Virtual Testing, and Probabilistic Damage Tolerance Applications

Ocampo, J., Millwater, H. R., Crosby, N., Gamble, B., Hurst, C., Reyer, M., Mottaghi, S., & Nuss, M. (2019) · Lecture notes in mechanical engineering · doi:10.1007/978-3-030-21503-3_12 · Cited by 9

A framework to characterize, model, and optimize water-energy systems: case study of a novel HDH system

Elhashimi-Khalifa, M. A., & Abbasi, B. (2024) · Desalination · doi:10.1016/j.desal.2024.117735 · Cited by 8

Digital twin-driven lifecycle management for motorized spindle

Fan, K., & Liu, J. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-14538-z · Cited by 8

An augmented reality-enabled digital twin system for reconfigurable soft robots: Visualization, simulation and interaction

Liao, Z., Wei, W., Zhang, L., Gao, Y., & Cai, Y. (2025) · Computers in Industry · doi:10.1016/j.compind.2025.104285 · Cited by 9

Summary report from the mini-conference on Digital Twins for Fusion Research

Schissel, D. P., Nazikian, R., & Gibbs, T. (2025) · Physics of Plasmas · doi:10.1063/5.0273586 · Cited by 8

A digital twin-based multiscale framework for predicting full-scale TBM rock cutting performance from miniature point load tests

Zhao, G., Li, Z., Chen, Y., Gong, Q., Li, S., & Wei, X. (2025) · Smart Underground Engineering · doi:10.1016/j.sue.2025.05.001 · Cited by 8

The Role of Data Fusion in Predictive Maintenance Using Digital Twins

Liu, Z., Meyendorf, N., Blasch, E., Tsukada, K., Liao, M., & Mrad, N. (2025) · Springer eBooks · doi:10.1007/978-3-031-84477-5_65 · Cited by 8

Digital twin in railway industry: a bibliometric analysis and systematic review

Zhang, Z.-Y., Shang, D., & Su, S. (2025) · Digital Twin · doi:10.1080/27525783.2025.2533858 · Cited by 14

Evolution of Power System CIM to Digital Twins - A Comprehensive Review and Analysis

Balijepalli, V. S. K. M., Sielker, F., & Karmakar, G. (2021) · IEEE PES Innovative Smart Grid Technologies Europe · doi:10.1109/isgteurope52324.2021.9640174 · Cited by 8

Multimodal data augmentation for digital twining assisted by artificial intelligence in mechanics of materials

Aublet, A., N’Guyen, F., Proudhon, H., & Ryckelynck, D. (2022) · Frontiers in Materials · doi:10.3389/fmats.2022.971816 · Cited by 9

Towards Digital Twinning of Fabrication Lines in Shipyards

Hadžić, N., Lozar, V., Opetuk, T., & Keser, R. (2023) · Journal of Marine Science and Engineering · doi:10.3390/jmse11051053 · Cited by 9

Experimentable Digital Twin for Virtual Validation of Manufacturing Systems

Abdoli, S. (2023) · IEEE International Conference on Industrial Engineering and Applications (ICIEA) · doi:10.1145/3587889.3587904 · Cited by 8

A Novel Approach of Resource Allocation for Distributed Digital Twin Shop-Floor

Zhang, H., Yan, Q., Qin, Y., Chen, S., & Zhang, G. (2023) · Information · doi:10.3390/info14080458 · Cited by 8

A Dynamic Reliability Prognosis Method for Reusable Spacecraft Mission Planning Based on Digital Twin Framework

Gao, B., Ye, Y., Pan, X., Yang, Q., Xie, W., Meng, S., & Huo, Y. (2023) · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering · doi:10.1115/1.4063297 · Cited by 8

Digital-Twin-Driven PI Parameter Evaluation Method for Grid-Connected Converters

Cheng, X., Chen, J., Chen, Y., Zhao, X., Zhou, Z., Yang, Q., & Dai, N. (2023) · International Conference on Power Engineering (ICPE) · doi:10.1109/icpe59729.2023.10469163 · Cited by 8

Цифровые двойники в управлении производством: принципы создания, проблемы внедрения и перспективы развития

Жарасов, Б. С., & Абрамов, В. И. (2024) · Современная экономика проблемы и решения · doi:10.17308/meps/2078-9017/2024/6/80-94 · Cited by 8

Historical Perspective of the Development of Digital Twins

Bonney, M., & Wagg, D. J. (2021) · Special Topics in Structural Dynamics & Experimental Techniques, Volume 5 · doi:10.1007/978-3-030-75914-8_2 · Cited by 2

Acoustic digital twin for passive structural health monitoring

Sternini, S., Bottero, A., & Kuperman, W. A. (2022) · JASA Express Letters · doi:10.1121/10.0009610 · Cited by 8

Theory and Technology of Digital Twin Model for Geotechnical Engineering

Wu, J., Dai, L., Xue, G., & Chen, J. (2022) · Lecture notes in civil engineering · doi:10.1007/978-981-19-1260-3_37 · Cited by 8

Toward a Digital Twin for Monitoring In-Service Performance of Post-Tensioned Self-Centering Cross-Laminated Timber Shear Walls

Longman, R. P., Baas, E. J., Türkan, Y., & Riggio, M. (2022) · ASCE International Conference on Computing in Civil Engineering (i3CE) · doi:10.1061/9780784483893.069 · Cited by 8

Towards a Circular Rotating Blade Wear Assessment Digital Twin for Manufacturing Lines

de Calle-Etxabe, K. L., Eider, G. P., & Arnáiz, A. (2022) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2022.04.253 · Cited by 8

Digital Twin in Industry 4.0 A Real-Time Virtual Replica of Objects Improves Digital Health Monitoring System

Chaudhari, P., Gangane, C., & Lahe, A. D. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-031-13150-9_41 · Cited by 8

Language Support for Multi Agent Reinforcement Learning

Clark, T., Barn, B. S., Kulkarni, V., & Barat, S. (2020) · Innovations in Software Engineering Conference (ISEC) · doi:10.1145/3385032.3385041 · Cited by 8

A Conceptual Framework to Analyze Urban Digital Twins InteroperabilityPreprint

Traoré, M. K. (2024) · Preprints.org · doi:10.20944/preprints202402.0023.v1 · Cited by 8

Digital twin—The dream and the reality

Kortelainen, J., Minav, T. A., & Tammi, K. (2023) · Frontiers in the Internet of Things · doi:10.3389/friot.2023.1108777 · Cited by 7

Modeling & Validation of a Digital Twin Tracked Vehicle

Daly, N., Manvi, P., Chhatbar, T., Schmid, M., Castanier, M. P., & Wagner, J. R. (2024) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2024-01-2323 · Cited by 8

Digital twin technology for sewage sludge smoldering process and CO/NOx emissions based on back propagation neural network: A laboratory experimental study

Song, Q., Wang, X., Zhang, W., Qian, B., Yue, Y., Xu, K., & Wang, X. (2024) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2024.09.099 · Cited by 7

Aero-engines life cycle state assessment framework based on twin model mismatch

Luan, J., Li, S., & Cao, Y. (2025) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2024.112298 · Cited by 7

Digital twin of micro-milling process for micro-tool wear

Christiand, C., Kiswanto, G., Baskoro, A. S., & Ko, T. J. (2025) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2025.2461034 · Cited by 7

A novel wasserstein autoencoder-enhanced thermo-mechanical coupled reduced-order model for high pressure turbine blades life monitoring

Wang, R., Chen, R., Zhao, Y., Shen, T., Chen, G., Dianyin, H., Jiang, Z., & Wang, X. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110819 · Cited by 7

Real-Time Digital Twin-Driven Optimization of Industrial Machinery

Ali, A. R., & Kamal, H. (2025) · doi:10.1109/iceeng64546.2025.11031363 · Cited by 7

Virtual-physical collaborative intelligent fault diagnosis for marine rotating machinery under data scarcity towards digital twin

Lv, Y., Xiong, K., Yao, J., Zhao, S., & Li, Y. (2025) · Ocean Engineering · doi:10.1016/j.oceaneng.2025.122198 · Cited by 7

An Adaptive Scheduling Method Based on Cloud Technology: A Structural Steelwork Industry Case Study

Mourtzis, D., Gargallis, A., Angelopoulos, J., & Panopoulos, N. (2020) · Lecture notes in mechanical engineering · doi:10.1007/978-3-030-46212-3_1 · Cited by 7

Üretim Planlama ve Kontrol Süreçlerinde Dijital İkiz Teknolojisinin Kullanılması: Tekstil Sektöründe Bir Uygulama

KOÇAK, A., & Yıldız, A. (2022) · Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji · doi:10.29109/gujsc.1170021 · Cited by 7

Towards a Digital Twin Integrated DLT and IoT-Based Automated Healthcare Ecosystem

Mukherjee, P. P., Afroj, M., Hossain, S., & Biswas, M. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-23599-3_23 · Cited by 8

Maintenance architecture design of equipment operation and maintenance system based on digital twins

Lu, J., Ji, W., Chen, C., & Su, X. (2024) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/09544054231214011 · Cited by 7

A Two-Phase Lifetime Prediction Model of Generator Stator Main Wall Insulation Driven by Digital Twin

Zhang, Q., Wu, J., Wang, J., Huang, X., Fang, Y., Niu, F., & Zhang, J. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3436131 · Cited by 7

A structured digital twinning approach to improve decision-making in manufacturing SMEs

Slot, M., Damgrave, R., & Lutters, E. (2024) · CIRP journal of manufacturing science and technology · doi:10.1016/j.cirpj.2024.10.010 · Cited by 8

TwinExplainer: Explaining Predictions of an Automotive Digital Twin

Neupane, S., Fernandez, I., Patterson, W., Mittal, S., Parmar, M., & Rahimi, S. (2023) · Conference on Algebraic Informatics · doi:10.1109/cai64502.2025.00186 · Cited by 13

An Intelligent Maritime Scene Frame Prediction Based on Digital Twins Technology

Guo, Z., Wang, K., Qin, J., Li, X.-B., Ran, D., & Shen, Y. (2021) · IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI) · doi:10.1109/dtpi52967.2021.9540188 · Cited by 7

Digitaler Zwilling für die automatisierte Produktion von Betonfertigteilen

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