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

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

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

Analyzing the Scholarly Literature of Digital Twin Research: Trends, Topics and Structure

Emmert‐Streib, F., Tripathi, S., & Dehmer, M. (2023) · IEEE Access · doi:10.1109/access.2023.3290488 · Cited by 27

A New Era of Mobility: Exploring Digital Twin Applications in Autonomous Vehicular Systems

Hossain, S., Saha, S. K., Banik, S., & Banik, T. (2023) · IEEE World AI IoT Congress (AIIoT) · doi:10.1109/aiiot58121.2023.10174376 · Cited by 27

An accuracy and performance-oriented accurate digital twin modeling method for precision microstructures

Saren, Q., Zhang, Z., Xiong, J., Chen, X. D., Zhu, D., Wu, W., Jin, X., & Shang, K. (2023) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-023-02169-2 · Cited by 28

Toward parallel intelligence: An interdisciplinary solution for complex systems

Zhao, Y., Zhu, Z., Chen, B., Qiu, S., Huang, J., Lu, X., Yang, W., Ai, C., Huang, K., He, C., et al. (2023) · The Innovation · doi:10.1016/j.xinn.2023.100521 · Cited by 31

Machine Learning-Based Surrogate Model for Press Hardening Process of 22MnB5 Sheet Steel Simulation in Industry 4.0

Abio, A., Bonada, F., Pujante, J., Grané, M., Nievas, N., Lange, D., & Pujol, O. (2022) · Materials · doi:10.3390/ma15103647 · Cited by 27

Digital Twins in 3D Printing Processes Using Artificial Intelligence

Rojek, I., Marciniak, T., & Mikołajewski, D. (2024) · Electronics · doi:10.3390/electronics13173550 · Cited by 34

Model-Based Feature Information Network (MFIN): A Digital Twin Framework to Integrate Location-Specific Material Behavior Within Component Design, Manufacturing, and Performance Analysis

Gopalakrishnan, S., Hartman, N. W., & Sangid, M. D. (2020) · Integrating materials and manufacturing innovation · doi:10.1007/s40192-020-00190-4 · Cited by 26

Aircraft turbulence and gust identification using simulated in-flight data

Balatti, D., Khodaparast, H. H., Friswell, M. I., Μανωλέσος, Μ., & Castrichini, A. (2021) · Aerospace Science and Technology · doi:10.1016/j.ast.2021.106805 · Cited by 26

The development of standardized models of digital twin

Duan, H., & Tian, F. (2020) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.04.164 · Cited by 26

Digital twins of product families in aviation based on an MBSE-assisted approach

Laukotka, F. N., Hanna, M., & Krause, D. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.05.144 · Cited by 26

Implementation of digital twin-enabled virtually monitored data in inspection planning

Li, S., & Brennan, F. (2024) · Applied Ocean Research · doi:10.1016/j.apor.2024.103903 · Cited by 24

Data‐Driven Urban Digital Twins and Critical Infrastructure Under Climate Change: A Review of Frameworks and Applications

Zhu, M., & Jin, J. (2025) · Urban Planning · doi:10.17645/up.10109 · Cited by 33

Diagnostics and prognostics of multi-mode failure scenarios in miter gates using multiple data sources and a dynamic Bayesian network

Wu, Z., Fillmore, T. B., Vega, M. A., Hu, Z. Y., & Todd, M. D. (2022) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-022-03381-z · Cited by 25

The Sociotechnical Digital Twin: On the Gap Between Social and Technical Feasibility

Barn, B. S. (2022) · IEEE Conference on Business Informatics · doi:10.1109/cbi54897.2022.00009 · Cited by 25

Setting Adaptive Inspection Intervals in Helicopter Components, Based on a Digital Twin

Zhao, F., Zhou, X., Wang, C., Dong, L., & Atluri, S. N. (2023) · AIAA Journal · doi:10.2514/1.j062222 · Cited by 25

Physic-based vs data-based digital twins for bush bearing wear diagnostic

Regis, A., Arroyave-Tobón, S., Linares, J., & Mermoz, E. (2023) · Wear · doi:10.1016/j.wear.2023.204888 · Cited by 21

Digitale Zwillinge – Eine explorative Fallstudie zur Untersuchung von Geschäftsmodellen

Klostermeier, R., Haag, S., & Benlian, A. (2018) · HMD Praxis der Wirtschaftsinformatik · doi:10.1365/s40702-018-0406-x · Cited by 25

Development of self-adaptive digital twin for battery monitoring and management system

Fu, K., Hamacher, T., & Perić, V. S. (2024) · Electric Power Systems Research · doi:10.1016/j.epsr.2024.110698 · Cited by 24

Digital twin–driven optimization of laser powder bed fusion processes: a focus on lack-of-fusion defects

Malik, A., Mahmood, M. A., & Liou, F. (2024) · Rapid prototyping journal · doi:10.1108/rpj-02-2024-0091 · Cited by 16

Digital twin development towards integration into blue economy: A bibliometric analysis

Bhati, M., Goerlandt, F., & Pelot, R. P. (2024) · Ocean Engineering · doi:10.1016/j.oceaneng.2024.119781 · Cited by 31

A review of digital twins in smart industries: Concepts, milestones, trends, applications, opportunities and challenges

Ding, P.-P., Liu, S., Chiong, R., Dhakal, S., Chen, D., Li, D.-B., Ma, H.-L., & Chung, S.-H. (2026) · Computers in industry (Print) · doi:10.1016/j.compind.2025.104398 · Cited by 27

Micro Manufacturing Unit – Creating Digital Twin Objects with Common Engineering Software

Lohtander, M., Garcia, E., Lanz, M., Volotinen, J., Ratava, J., & Kaakkunen, J. J. J. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.10.071 · Cited by 24

A Universal Methodology to Create Digital Twins for Serial and Parallel Manipulators

Huynh, B. H., Akhtar, H., & Sett, M. K. (2019) · IEEE International Conference on Systems, Man and Cybernetics · doi:10.1109/smc.2019.8914195 · Cited by 15

Predictive Maintenance on Aircraft and Applications with Digital Twin

Heim, S., Clemens, J., Steck, J. E., Basic, C., Timmons, D., & Zwiener, K. (2020) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata50022.2020.9378433 · Cited by 24

A method for developing and validating simulation models for automated storage and retrieval system digital twins

Ferrari, A., Carlin, A., Rafele, C., & Zenezini, G. (2023) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-023-12660-y · Cited by 22

Softwarized Resource Allocation in Digital Twins-Empowered Networks for Future Quantum-Enabled Consumer Applications

Cao, H., Garg, S., Mumtaz, S., Alrashoud, M. R., Yang, L., & Kaddoum, G. (2024) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2024.3370052 · Cited by 24

A Digital Twin Method for Automated Behavior Analysis of Large-Scale Distributed IoT Systems

Sleuters, J., Li, Y., Verriet, J., Velikova, M., & Doornbos, R. M. P. (2019) · International Conference on System of Systems Engineering · doi:10.1109/sysose.2019.8753845 · Cited by 25

On Digital Twins, Mirrors and Virtualisations

Keith Worden, B., Cross, E. J., Gardner, P. A., Barthorpe, R. J., & Wagg, D. (2019) · Conference proceedings of the Society for Experimental Mechanics · doi:10.1007/978-3-030-12075-7_34 · Cited by 24

Application of Digital Twin Assistant-System in State Estimation for Inverter Dominated Grid

Song, X.-Y., Cai, H., Kircheis, J., Jiang, T., Schlegel, S., & Westermann, D. (2020) · International Universities Power Engineering Conference · doi:10.1109/upec49904.2020.9209876 · Cited by 16

Application of a surrogate model for condition monitoring of a digital twin gas turbine

Luan, J., Li, S., Cao, Y., & Gu, C. (2024) · Applied Mathematical Modelling · doi:10.1016/j.apm.2024.115683 · Cited by 23

The Future of Digital Twin Research and Development

Bossuyt, D. L. V., Allaire, D., Bickford, J. F., Bozada, T. A., Chen, W., Cutitta, R. P., Cuzner, R. M., Fletcher, K. M., Giachetti, R. E., Hale, B., et al. (2025) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4068082 · Cited by 27

Multi-level damage diagnosis on stiffened composite panels based on a damage-uninformative digital twin

Milanoski, D., Galanopoulos, G., Zarouchas, D. S., & Λούτας, Θ. (2022) · Structural Health Monitoring · doi:10.1177/14759217221108676 · Cited by 23

Digital Twin Modeling of Power Electronic Converters

Sado, K. A., Hannum, J., & Booth, K. (2023) · IEEE Electric Ship Technologies Symposium (ESTS) · doi:10.1109/ests56571.2023.10220465 · Cited by 23

A multi-dimensional evolution modeling method for digital twin process model

Liu, J., Ji, Q., Zhou, H., Du, C., Liu, X., & Li, M. (2023) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2023.102667 · Cited by 22

Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0

Mon, B. F., Hayajneh, M., Ali, N. A., Ullah, F., Ullah, H., & Alkobaisi, S. (2025) · Computers, Materials & Continua · doi:10.32604/cmc.2025.061411 · Cited by 26

Autonomous control of heat pipes through digital twins: Application to fission batteries

Wilsdon, K. N., Hansel, J., Kunz, M. R., & Browning, J. M. (2023) · Progress in Nuclear Energy · doi:10.1016/j.pnucene.2023.104813 · Cited by 21

A transferable diagnosis method with incipient fault detection for a digital twin of wind turbine

Hu, W., Jiao, Q., Liu, H., Wang, K., Jiang, Z., Wu, J., Cong, F., & Hao, G. (2024) · Digital engineering. · doi:10.1016/j.dte.2024.100001 · Cited by 22

Digital twin technology in electric and self-navigating vehicles: Readiness, convergence, and future directions

Yalavarthy, U. R. S., Kumar, N. B., Babu, A. R. V., Narasipuram, R. P., & Padmanaban, S. (2025) · Energy Conversion and Management X · doi:10.1016/j.ecmx.2025.100949 · Cited by 23

Monitoring and Warning for Digital Twin-driven Mountain Geological Disaster

Zhang, H., Wang, R., & Wang, C. (2019) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma.2019.8816292 · Cited by 22

Digital Twin (DT) in Smart Energy Systems - Systematic Literature Review of DT as a growing solution for Energy Internet of the Things (EIoT)

Ardebili, A. A., Longo, A., & Ficarella, A. (2021) · E3S Web of Conferences · doi:10.1051/e3sconf/202131209002 · Cited by 23

Digital twin-driven complexity management in intelligent manufacturing

Wang, Y., Wang, X., Tao, F., & Liu, A. (2021) · Digital Twin · doi:10.12688/digitaltwin.17489.1 · Cited by 21

Design of Digital Twin Sensing Strategies Via Predictive Modeling and Interpretable Machine Learning

Kapteyn, M. G., & Willcox, K. E. (2022) · Journal of Mechanical Design · doi:10.1115/1.4054907 · Cited by 22

Design of a Digital Twin for an Industrial Vacuum Process: A Predictive Maintenance Approach

Yakhni, M., Hosni, H., Cauet, S., Sakout, A., Etien, E., Rambault, L., Assoum, H., & Elgohary, M. (2022) · Machines · doi:10.3390/machines10080686 · Cited by 21

Shaping the role of the digital twins for human‐robot dyad: Connotations, scenarios, and future perspectives

Elbasheer, M., Longo, F., Mirabelli, G., Nicoletti, L., Padovano, A., & Solina, V. (2022) · IET Collaborative Intelligent Manufacturing · doi:10.1049/cim2.12066 · Cited by 18

Multi-fidelity neural optimization machine for Digital Twins

Chen, J., Meng, C., Gao, Y., & Liu, Y. (2022) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-022-03443-2 · Cited by 22

Methodology for the Development of Virtual Representations within the Process Development Framework of Energy Plants: From Digital Model to Digital Predictive Twin—A Review

Hammerschmid, M., Rosenfeld, D. C., Bartik, A., Benedikt, F., Fuchs, J., & Müller, S. (2023) · Energies · doi:10.3390/en16062641 · Cited by 21

Product Lifecycle Management Challenges of CPPS

Gerhard, D. (2017) · Springer eBooks · doi:10.1007/978-3-319-56345-9_4 · Cited by 22

Updating Geometrically Nonlinear Reduced-Order Models Using Nonlinear Modes and Harmonic Balance

Damme, C. I. V., Allen, M. S., & Hollkamp, J. J. (2020) · AIAA Journal · doi:10.2514/1.j058698 · Cited by 22

Role of smart materials and digital twin (DT) for the adoption of electric vehicles in India

Kamran, S. S., Haleem, A., Bahl, S., Javaid, M., Nandan, D., & Verma, A. S. (2021) · Materials Today: Proceedings · doi:10.1016/j.matpr.2021.09.249 · Cited by 14

Numerical investigation of stress states in buckled laminated composite plates under dynamic loading

Kim, H.-G., & Wiebe, R. (2019) · Composite Structures · doi:10.1016/j.compstruct.2019.111743 · Cited by 21

The Role of Digital Twins in Collaborative Cyber-Physical Systems

Nazarenko, A., & Camarinha-Matos, L. (2020) · Doctoral Conference on Computing, Electrical and Industrial Systems · doi:10.1007/978-3-030-45124-0_18 · Cited by 21

Digital-Twin-Aided Product Design Framework For IoT Platforms

Wang, C., & Li, Y. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3100796 · Cited by 24

Unifying Digital Twin Framework: Simulation-Based Proof-of-Concept

Traoré, M. (2021) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.08.105 · Cited by 15

Digital-Twins-Driven Semi-Physical Simulation for Testing and Evaluation of Industrial Software in a Smart Manufacturing System

Cheng, K., Wang, Q., Yang, D., Dai, Q., & Wang, M. (2022) · Machines · doi:10.3390/machines10050388 · Cited by 22

M-LFM: a multi-level fusion modeling method for shape-performance integrated digital twin of complex structure

He, X., Lai, X., Yang, L., Zhang, F., Zhou, D., Song, X., & Sun, W. (2022) · Frontiers of Mechanical Engineering · doi:10.1007/s11465-022-0708-0 · Cited by 21

Fine-Grained Detection of Pavement Distress Based on Integrated Data Using Digital Twin

Wang, W., Xu, X., Peng, J., Hu, W., & Wu, D. (2023) · Applied Sciences · doi:10.3390/app13074549 · Cited by 24

Copula-Based Collaborative Multistructure Damage Diagnosis and Prognosis for Fleet Maintenance Digital Twins

Zhou, X., Sbarufatti, C., Giglio, M., Dong, L., & Atluri, S. N. (2023) · AIAA Journal · doi:10.2514/1.j063105 · Cited by 21

Development and Verification of a Simulation Model of an Automated Assembly Line

Bendowska, K., & Zawadzki, P. (2023) · Applied Sciences · doi:10.3390/app131810142 · Cited by 21

Methods of computational modeling of coronary heart vessels for its digital twin

Naplekov, I., Zheleznikov, I., Pashchenko, D., Kobysheva, P., Moskvitina, A., Mustafin, R. M., Gnutikova, M., Mullagalieva, A., & Uzlov, P. (2018) · MATEC Web of Conferences · doi:10.1051/matecconf/201817201009 · Cited by 21

Digital twin-driven system for roller conveyor line: design and control

Wang, P., Liu, W., Liu, N., & You, Y. (2020) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-020-01898-z · Cited by 21

The Research of Ontology-based Digital Twin Machine Tool Modeling

Liu, J., Yu, D., Bi, X., Hu, Y., Yu, H., & Li, B. (2020) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/iccc51575.2020.9344997 · Cited by 21

The Application and challenge of Digital Twin technology in Ship equipment

Wu, W., Chen, G., & Zi-chun, Y. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1939/1/012068 · Cited by 21

Enhanced multi-fidelity modeling for digital twin and uncertainty quantification

Desai, A. S., Navaneeth, N., Adhikari, S., & Chakraborty, S. (2023) · Probabilistic Engineering Mechanics · doi:10.1016/j.probengmech.2023.103525 · Cited by 20

Digital Twins and Civil Engineering Phases: Reorienting Adoption Strategies

Adebiyi, T. A., Ajenifuja, N. A., & Zhang, R. (2024) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4066181 · Cited by 26

Digital twin-driven CNC spindle performance assessment

Xue, R., Zhou, X., Huang, Z., Zhang, F., Tao, F., & Wang, J. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-08403-6 · Cited by 20

Digital Twin Assisted Economic Dispatch for Energy Internet With Information Entropy

Ren, R., Li, Y., Sun, Q., Xie, X., Liu, L., & Gao, W. (2024) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2024.3386358 · Cited by 20

Internet of Digital Twin: Framework, Applications, and Enabling Technologies

Liu, R., Luan, T. H., Qu, Y., Xiang, Y., Gao, L., & Zhao, D. (2025) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2025.3554579 · Cited by 21

DEMONSTRATED BENEFITS OF A NASCENT DIGITAL TWIN

West, T. D., & Blackburn, M. (2018) · Insight · doi:10.1002/inst.12189 · Cited by 20

Micro-Workflows: Kafka and Kepler Fusion to Support Digital Twins of Industrial Processes

Radchenko, G., Alaasam, A. B. A., & Tchernykh, A. N. (2018) · IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion) · doi:10.1109/ucc-companion.2018.00039 · Cited by 20

Applications of Digital Twin

Tao, F., Zhang, M., & Nee, A. Y. C. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-817630-6.00002-3 · Cited by 21

A Development Strategy for Structural Health Monitoring Applications

Cawley, P. (2021) · Journal of Nondestructive Evaluation Diagnostics and Prognostics of Engineering Systems · doi:10.1115/1.4051974 · Cited by 20

Digital twins in the minerals industry – a comprehensive review

Qu, J., Kizil, M. S., Yahyaei, M., & Knights, P. F. (2023) · Mining Technology Transactions of the Institutions of Mining and Metallurgy · doi:10.1080/25726668.2023.2257479 · Cited by 25

Characterizing the Digital Twin in Structural Mechanics

Richstein, R., & Schröder, K. (2024) · Designs · doi:10.3390/designs8010008 · Cited by 19

Lifecycle Management of Optical Networks With Dynamic-Updating Digital Twin: A Hybrid Data-Driven and Physics-Informed Approach

Song, Y., Zhang, M., Zhang, Y., Shi, Y., Shen, S., Tang, X., Huang, S., & Wang, D. (2025) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2025.3543489 · Cited by 19

Transformative roles of digital twins from drug discovery to continuous manufacturing: pharmaceutical and biopharmaceutical perspectives

Maharjan, R., Kim, N. A., Kim, K. H., & Jeong, S. H. (2025) · International Journal of Pharmaceutics X · doi:10.1016/j.ijpx.2025.100409 · Cited by 30

A Digital Twin Modular Framework for Reconfigurable Manufacturing Systems

Benderbal, H. H., Yelles-Chaouche, A. R., & Dolgui, A. B. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-57997-5_57 · Cited by 19

Displacement field reconstruction of structures under thermal and mechanical loading environment

Wang, X., Si, C.-Y., Wang, Z., & Li, Y. (2021) · Aerospace Science and Technology · doi:10.1016/j.ast.2021.106914 · Cited by 19

Predicting failure progressions of structural materials via deep learning based on void topology

Tiong, L. C. O., Lee, G., Yi, G. H., Sohn, S. S., & Kim, D.-H. (2023) · Acta Materialia · doi:10.1016/j.actamat.2023.118862 · Cited by 19

Surrogate-Based Time-Dependent Reliability Analysis for a Digital Twin

Hu, W., Yan, J., Zhao, F., Jiang, C., Liu, H., Cho, H., & Lee, I. (2023) · Journal of Mechanical Design · doi:10.1115/1.4062668 · Cited by 19

Digital twin-driven intelligent operation and maintenance platform for large-scale hydro-steel structures

Li, H., Zhang, R., Zheng, S., Shen, Y., Fu, C., & Zhao, H. (2024) · Advanced Engineering Informatics · doi:10.1016/j.aei.2024.102661 · Cited by 22

Fault diagnosis of reducers based on digital twins and deep learning

Liu, W., Han, B., Zheng, A., Zheng, Z., Chen, S., & Jia, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-75112-x · Cited by 20

Simulation Models of Production Plants as a Tool for Implementation of the Digital Twin Concept into Production

Sujová, E., Vysloužilová, D., Čierna, H., & Bambura, R. (2020) · MANUFACTURING TECHNOLOGY · doi:10.21062/mft.2020.064 · Cited by 17

Towards Digital Twins Driven Breast Cancer Detection

Meraghni, S., Benaggoune, K., Masry, Z. A., Terrissa, L. S., Devalland, C., & Noureddine Zerhouni, A. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-80129-8_7 · Cited by 21

Digital twin design requirements in downgraded situations management

Pinto, S. C. D., Villeneuve, É., Masson, D., Boy, G., Baron, T., & Urfels, L. (2021) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.08.102 · Cited by 16

On the dimension of complex responses in nonlinear structural vibrations

Wiebe, R., & Spottswood, S. M. (2016) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2016.03.009 · Cited by 19

Wearable Devices and Health Monitoring

Kanakaprabha, S., Kumar, G. G., Reddy, B. P., Raju, Y. R., & Rai, P. C. M. (2024) · Wiley eBooks · doi:10.1002/9781394270910.ch12 · Cited by 18

Discrete event simulation and Digital Twins in warehouse logistics: a bibliometric and content analysis-based systematic literature review

Aretoulaki, E., Ponis, S. T., Plakas, G., & Tzanetou, D. (2024) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2024.2314772 · Cited by 21

Digital twin–enabled model predictive control in additive manufacturing: critical review, research challenges, and future directions

Kolate, V. D., Chaudhary, M. K., Mane, S., & Devadhe, M. (2025) · Materials and Manufacturing Processes · doi:10.1080/10426914.2025.2586498 · Cited by 23

Digital Twins for Industry 4.0 and Beyond

Hsu, Y., Chiu, J., & Liu, J. S. (2019) · doi:10.1109/ieem44572.2019.8978614 · Cited by 18

Implementation of a holistic digital twin solution for design prototyping and virtual commissioning

Ugarte, M., Illarramendi, M., Unamuno, G., Bellanco, J. L., Ugalde, E., & Valor, A. V. (2022) · IET Collaborative Intelligent Manufacturing · doi:10.1049/cim2.12058 · Cited by 18

A Foundation Model for Building Digital Twins: A Case Study of a Chiller

Li, S., Yang, Q., Xing, J., Chen, W., & Zou, R. (2022) · Buildings · doi:10.3390/buildings12081079 · Cited by 20

Comprehensive Survey of the Landscape of Digital Twin Technologies and Their Diverse Applications

Chen, H., Shao, H., Deng, X., Wang, L., & Wang, X. (2023) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2023.027834 · Cited by 20

Research on digital twin framework for customized product manual assembly systems

Ren, X., & Zhao, N. (2023) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2023.08.018 · Cited by 20

Digital twin enabled structural integrity management: Critical review and framework development

Shen, L., & Brennan, F. (2024) · Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment · doi:10.1177/14750902241227254 · Cited by 28

A Systematic Review of Additive Manufacturing Solutions Using Machine Learning, Internet of Things, Big Data, Digital Twins and Blockchain Technologies: A Technological Perspective Towards Sustainability

Pant, R., Singh, R., Gehlot, A., Akram, S. V., Gupta, L. R., & Thakur, A. K. (2024) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-024-10116-4 · Cited by 22

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