Digital twin modeling

TensorFlow: A system for large-scale machine learningPreprint

Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., et al. (2016) · arXiv (Cornell University) · doi:10.5555/3026877.3026899 · Cited by 16,369 · see citing works

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 · see citing works

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 · see citing works

Digital twin: values, challenges and enablers from a modeling perspective

Rasheed, A., San, O., & Kvamsdal, T. (2020) · IEEE Access · doi:10.1109/access.2020.2970143 · Cited by 1,952 · see citing works

Data-driven smart manufacturing

Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2018.01.006 · Cited by 1,934 · see citing works

Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues

Lu, Y., Liu, C., Wang, K. I., Huang, H., & Xu, X. W. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.101837 · Cited by 1,753 · see citing works

Enabling technologies and tools for digital twin

Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., & Nee, A. Y. C. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2019.10.001 · Cited by 1,579 · see citing works

A survey on digital twin: definitions, characteristics, applications, and design implications

Barricelli, B. R., Casiraghi, E., & Fogli, D. (2019) · IEEE Access · doi:10.1109/access.2019.2953499 · Cited by 1,480 · see citing works

The ‘Digital Twin’ to enable the vision of precision cardiology

Acero, J. C., Margara, F., Marciniak, M., Rodero, C., Lončarić, F., Feng, Y., Gilbert, A., Fernandes, J. F., Bukhari, S. H. A., Wajdan, A., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehaa159 · Cited by 987 · see citing works

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 · see citing works

Digital twins-based smart manufacturing system design in Industry 4.0: A review

Leng, J., Wang, D., Shen, W., Li, X., Liu, Q., & Chen, X. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.05.011 · Cited by 801 · see citing works

Make more digital twins

Tao, F., & Qi, Q. (2019) · Nature · doi:10.1038/d41586-019-02849-1 · Cited by 799 · see citing works

A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives

Lim, K. Y. H., Zheng, P., & Chen, C.-H. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01512-w · Cited by 700 · see citing works

How to tell the difference between a model and a digital twin

Wright, L., & Davidson, S. (2020) · Advanced Modeling and Simulation in Engineering Sciences · doi:10.1186/s40323-020-00147-4 · Cited by 601 · see citing works

Transdisciplinary Perspectives on Complex Systems

Alves, A., Flumerfelt, S., & Kahlen, F.-J. (2016) · Springer eBooks · doi:10.1007/978-3-319-38756-7 · Cited by 545 · see citing works

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 · see citing works

Digital twin, physics-based model, and machine learning applied to damage detection in structures

Ritto, T. G., & Rochinha, F. A. (2021) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2021.107614 · Cited by 374 · see citing works

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 · see citing works

The modelling and operations for the digital twin in the context of manufacturing

Bao, J., Guo, D., Li, J., & Zhang, J. (2019) · Enterprise Information Systems · doi:10.1080/17517575.2018.1526324 · Cited by 347 · see citing works

Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications

Wagg, D. J., Worden, K., Barthorpe, R., & Gardner, P. (2020) · ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg · doi:10.1115/1.4046739 · Cited by 321 · see citing works

Digital twin-based designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system

Liu, Q., Leng, J., Yan, D., Zhang, D., Wei, L., Yu, A., Zhao, R., Zhang, H., & Chen, X. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.012 · Cited by 315 · see citing works

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 · see citing works

Digital twin modeling method based on biomimicry for machining aerospace components

Liu, S., Bao, J., Lu, Y., Li, J., Lu, S., & Sun, X. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.014 · Cited by 310 · see citing works

Development of the simulation model for Digital Twin applications in historical masonry buildings: The integration between numerical and experimental reality

Angjeliu, G., Coronelli, D., & Cardani, G. (2020) · Computers & Structures · doi:10.1016/j.compstruc.2020.106282 · Cited by 251 · see citing works

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 · see citing works

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 · see citing works

A Methodology for Digital Twin Modeling and Deployment for Industry 4.0

Schroeder, G. N., Steinmetz, C., Rodrigues, R. N., Henriques, R. V. B., Rettberg, A., & Pereira, C. E. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2020.3032444 · Cited by 213 · see citing works

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 · see citing works

Participatory sensing and digital twin city: updating virtual city models for enhanced risk-informed decision-making

Ham, Y., & Kim, J. (2020) · Journal of Management in Engineering · doi:10.1061/(asce)me.1943-5479.0000748 · Cited by 182 · see citing works

Digital Twin Models in Industrial Operations: A Systematic Literature Review

Melesse, T. Y., Pasquale, V., & Riemma, S. (2020) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.02.084 · Cited by 180 · see citing works

Architecting Smart City Digital Twins: Combined Semantic Model and Machine Learning Approach

Austin, M. A., Delgoshaei, P., Coelho, M., & Heidarinejad, M. (2020) · Journal of Management in Engineering · doi:10.1061/(asce)me.1943-5479.0000774 · Cited by 180 · see citing works

Building a right digital twin with model engineering

Zhang, L., Zhou, L., & Horn, B. K. P. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.02.009 · Cited by 166 · see citing works

An Adapted Model of Cognitive Digital Twins for Building Lifecycle Management

Yitmen, I., Alizadehsalehi, S., Akıner, İ., & Akıner, M. E. (2021) · Applied Sciences · doi:10.3390/app11094276 · Cited by 165 · see citing works

Digital twins: Understanding the added value of integrated models for through-life engineering services

Vrabič, R., Erkoyuncu, J. A., Butala, P., & Roy, R. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.10.167 · Cited by 151 · see citing works

Consistency retention method for CNC machine tool digital twin model

Wei, Y., Hu, T., Zhou, T., Ye, Y., & Luo, W. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.002 · Cited by 134 · see citing works

Toward predictive digital twins via component-based reduced-order models and interpretable machine learning

Kapteyn, M. G., Knezevic, D. J., & Willcox, K. E. (2020) · AIAA SciTech Forum · doi:10.2514/6.2020-0418 · Cited by 131 · see citing works

On the Effects of Modeling As-Manufactured Geometry: Toward Digital Twin

Cerrone, A., Hochhalter, J. D., Heber, G., & Ingraffea, A. R. (2014) · International Journal of Aerospace Engineering · doi:10.1155/2014/439278 · Cited by 130 · see citing works

Digital Twin-driven framework for fatigue life prediction of steel bridges using a probabilistic multiscale model: Application to segmental orthotropic steel deck specimen

Jiang, F., Ding, Y., Song, Y., Geng, F., & Wang, Z. (2021) · Engineering Structures · doi:10.1016/j.engstruct.2021.112461 · Cited by 124 · see citing works

Designing a Shape–Performance Integrated Digital Twin Based on Multiple Models and Dynamic Data: A Boom Crane Example

Lai, X., Wang, S., Guo, Z., Zhang, C., Sun, W. F., & Song, X. (2021) · Journal of Mechanical Design · doi:10.1115/1.4049861 · Cited by 120 · see citing works

Towards Model-Driven Digital Twin Engineering: Current Opportunities and Future Challenges

Bordeleau, F., Combemale, B., Eramo, R., van den Brand, M., & Wimmer, M. (2020) · International Conferences on Systems Modelling and Management · doi:10.1007/978-3-030-58167-1_4 · Cited by 103 · see citing works

Data management for developing digital twin ontology model

Singh, S. K., Shehab, E., Higgins, N., Fowler, K., Reynolds, D., Erkoyuncu, J. A., & Gadd, P. (2020) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/0954405420978117 · Cited by 103 · see citing works

Digital twin of a combustion furnace operating in flameless conditions: reduced-order model development from CFD simulations

Aversano, G., Ferrarotti, M., & Parente, A. (2020) · Proceedings of the Combustion Institute · doi:10.1016/j.proci.2020.06.045 · Cited by 101 · see citing works

Model Order Reduction a Key Technology for Digital Twins

Hartmann, D., Herz, M., & Wever, U. (2018) · Springer eBooks · doi:10.1007/978-3-319-75319-5_8 · Cited by 95 · see citing works

Feature-preserving 3D mesh simplification for urban buildings

Li, M., & Nan, L. (2021) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2021.01.006 · Cited by 94 · see citing works

An assembly precision analysis method based on a general part digital twin model

Wang, K., Liu, D., Liu, Z., Wang, Q., & Tan, J. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.102089 · Cited by 91 · see citing works

Micro Manufacturing Unit and the Corresponding 3D-Model for the Digital Twin

Lohtander, M., Ahonen, N., Lanz, M., Ratava, J., & Kaakkunen, J. J. J. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.06.057 · Cited by 90 · see citing works

Proceedings of the 24th international conference on Computers and industrial engineering

Dessouky, M. I., Hindi, K. S., & Eid, M. (1999) · Annual Conference on Computers · Cited by 89 · see citing works

Multi-scale evolution mechanism and knowledge construction of a digital twin mimic model

Liu, S., Lu, Y., Li, J., Song, D., Sun, X., & Bao, J. (2021) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2021.102123 · Cited by 89 · see citing works

Advancing digital twin implementation: a toolbox for modelling and simulation

Singh, S., Weeber, M., & Birke, K.-P. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.03.078 · Cited by 86 · see citing works

Digital twin modeling method for CNC machine tool

Luo, W., Hu, T., Zhu, W., & Tao, F. (2018) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc.2018.8361285 · Cited by 83 · see citing works

Experimentable digital twins for model-based systems engineering and simulation-based development

Schluse, M., Atorf, L., & Roßmann, J. (2017) · 2020 IEEE International Systems Conference (SysCon) · doi:10.1109/syscon.2017.7934796 · Cited by 81 · see citing works

Multisource Model-Driven Digital Twin System of Robotic Assembly

Li, X., He, B., Zhou, Y., & Li, G. (2020) · IEEE Systems Journal · doi:10.1109/jsyst.2019.2958874 · Cited by 78 · see citing works

Ontology-based information modeling method for digital twin creation of as-fabricated machining parts

Dai, S. L., Zhao, G. L., Yu, Y., Zheng, P., Bao, Q., & Wang, W. (2021) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2021.102173 · Cited by 77 · see citing works

Multi‐fidelity digital twin structural model for a sub‐scale downwind wind turbine rotor blade

Chetan, M., Yao, S., & Griffith, D. T. (2021) · Wind Energy · doi:10.1002/we.2636 · Cited by 76 · see citing works

Hidden Markov model-based digital twin construction for futuristic manufacturing systems

Ghosh, A. K., Ullah, A., & Kubo, A. (2019) · Artificial intelligence for engineering design, analysis and manufacturing · doi:10.1017/s089006041900012x · Cited by 72 · see citing works

Data Super-Network Fault Prediction Model and Maintenance Strategy for Mechanical Product Based on Digital Twin

Liu, Z., Chen, W., Zhang, C., Yang, C., & Chu, H. (2019) · IEEE Access · doi:10.1109/access.2019.2957202 · Cited by 72 · see citing works

Composition and Application of Power System Digital Twins Based on Ontological Modeling

Андрюшкевич, С. К., Kovalyov, S. P., & Nefedov, E. I. (2019) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin41052.2019.8972267 · Cited by 71 · see citing works

Digital Twin Modelling of Ship Power and Propulsion Systems: Application of the Open Simulation Platform (OSP)

Perabo, F., Park, D., Zadeh, M., Smogeli, Ø. R., & Jamt, L. (2020) · IEEE International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie45063.2020.9152218 · Cited by 67 · see citing works

Synthetic PPG generation from haemodynamic model with baroreflex autoregulation: a Digital twin of cardiovascular system

Mazumder, O., Roy, D., Bhattacharya, S., Sinha, A., & Pal, A. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856691 · Cited by 66 · see citing works

Developing the Physical Distribution Digital Twin Model within the Trade Network

Barykin, S., Kapustina, I., Sergeev, S. M., Kalinina, O., Vilken, V. V., de la Poza, E., Putikhin, Y., & Volkova, L. V. (2021) · RiuNet (Universitat Politècnica de València) · Cited by 63 · see citing works

Automated fault detection for additive manufacturing using vibration sensors

Scheffel, R. M., Fröhlich, A. A., & Silvestri, M. (2021) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2021.1901316 · Cited by 61 · see citing works

Towards a Digital Twin model for Building Energy Management: Case of Morocco

Agouzoul, A., Tabaa, M., Chegari, B., Simeu, E., Dandache, A., & Alami, K. (2021) · Procedia Computer Science · doi:10.1016/j.procs.2021.03.051 · Cited by 59 · see citing works

The Development and use of a Digital Twin Model for Tire Touchdown Health Monitoring

Zakrajsek, A. J., & Mall, S. (2017) · AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (SDM) · doi:10.2514/6.2017-0863 · Cited by 53 · see citing works

A Digital Twin Approach to Study Additive Manufacturing Processing Using Embedded Optical Fiber Sensors and Numerical Modeling

Zou, R., Liang, X. Y., Chen, Q., Wang, M., Zaghloul, M., Lan, H., Buric, M., Ohodnicki, P. R., Chorpening, B., To, A. C., et al. (2020) · Journal of Lightwave Technology · doi:10.1109/jlt.2020.3010722 · Cited by 52 · see citing works

Modeling of Digital Twin Workshop Based on Perception Data

Zhang, Q., Zhang, X., Xu, W., Liu, A.-M., Zhou, Z.-D., & Pham, D. (2017) · International Conference on Intelligent Robotics and Applications · doi:10.1007/978-3-319-65298-6_1 · Cited by 47 · see citing works

Introduction of a comprehensive Structure Model for the Digital Twin in Manufacturing

Lechler, T., Fuchs, J., Sjarov, M., Brossog, M., Selmaier, A., Faltus, F., Donhauser, T., & Franke, J. E. (2020) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa46521.2020.9212030 · Cited by 47 · see citing works

Time series behavior modeling with digital twin for Internet of Vehicles

Zhang, T., Liu, X., Luo, Z., Dong, F., & Jiang, Y. (2019) · EURASIP Journal on Wireless Communications and Networking · doi:10.1186/s13638-019-1589-8 · Cited by 46 · see citing works

INTEGRATION OF 3D OBJECTS AND TERRAIN FOR 3D MODELLING SUPPORTING THE DIGITAL TWIN

Yan, J., Sisi Zlatanova, B., Aleksandrov, M., Diakité, A., & Pettit, C. J. (2019) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-iv-4-w8-147-2019 · Cited by 45 · see citing works

A Hierarchical Digital Twin Model Framework for Dynamic Cyber-Physical System Design

Shangguan, D., Chen, L., & Ding, J. (2019) · International Conference on Mechatronics and Robotics Engineering (ICMRE) · doi:10.1145/3314493.3314504 · Cited by 43 · see citing works

Multi-modelling and Co-simulation in the Engineering of Cyber-Physical Systems: Towards the Digital Twin

Fitzgerald, J. S., Larsen, P. G., & Pierce, K. G. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-30985-5_4 · Cited by 43 · see citing works

Towards digital twins through object-oriented modelling: a machine tool case study

Scaglioni, B., & Ferretti, G. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.03.104 · Cited by 42 · see citing works

Permeability prediction for porous sandstone using digital twin modeling technology and Lattice Boltzmann method

Xiao, H., He, L., Li, J., Zou, C., & Shao, C. (2021) · International Journal of Rock Mechanics and Mining Sciences · doi:10.1016/j.ijrmms.2021.104695 · Cited by 42 · see citing works

Digital Twin of an Electrical Motor Based on Empirical Performance Model

Rassõlkin, A., Rjabtšikov, V., Vaimann, T., Kallaste, A., Kuts, V., & Partyshev, A. (2020) · International Conference on Electrical Power Drive Systems (ICEPDS) · doi:10.1109/icepds47235.2020.9249366 · Cited by 41 · see citing works

Reduced-Order Modeling (ROM) for Simulation and Optimization

Keiper, W., Milde, A., & Volkwein, S. (2018) · Springer eBooks · doi:10.1007/978-3-319-75319-5 · Cited by 38 · see citing works

Digital Twin: Industrial Robot Kinematic Model Integration to the Virtual Reality Environment

Kuts, V., Cherezova, N., Sarkans, M., & Otto, T. (2020) · Journal of Machine Engineering · doi:10.36897/jme/120182 · Cited by 36 · see citing works

A Product Quality Monitor Model With the Digital Twin Model and the Stacked Auto Encoder

Zhang, S.-Z., Kang, C.-F., Liu, Z., Wu, J., & Ma, C.-M. (2020) · IEEE Access · doi:10.1109/access.2020.3003723 · Cited by 35 · see citing works

On modelling and handling of flexible materials: A review on Digital Twins and planning systems

Andronas, D., Kokotinis, G., & Makris, S. (2021) · Procedia CIRP · doi:10.1016/j.procir.2020.08.005 · Cited by 35 · see citing works

Tool Wear Online Monitoring Method Based on DT and SSAE-PHMM

Zhang, X., Liu, L., Wan, X., & Feng, B. (2021) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4050531 · Cited by 35 · see citing works

Asset Information Model to support the adoption of a Digital Twin: West Cambridge case study

Heaton, J., & Parlikad, A. K. (2020) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2020.11.059 · Cited by 33 · see citing works

Bridge assessment for PSC Girder Bridge using Digital Twins Model

Dang, N.-S., & Shim, C.-S. (2019) · Lecture notes in civil engineering · doi:10.1007/978-981-15-0802-8_199 · Cited by 30 · see citing works

Digital Twin-Based Energy Modeling of Industrial Robots

Yan, K. K., Xu, W., Yao, B., Zhou, Z., & Pham, D. T. (2018) · Communications in computer and information science · doi:10.1007/978-981-13-2853-4_26 · Cited by 29 · see citing works

A Visionary Model on Blockchain-based Accountability for Secure and Collaborative Digital Twin Environments

Kanak, A., Ugur, N., & Ergün, S. (2019) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2019.8914304 · Cited by 29 · see citing works

Tool Condition Prognostic Model Based on Digital Twin System

Xie, N., Rui, K., & Yao, Y. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.03.045 · Cited by 29 · see citing works

Multiscale Modelling and Analysis for Design and Development of a High-Precision Aerostatic Bearing Slideway and Its Digital Twin

Gou, N., Cheng, K., & Huo, D. (2021) · Machines · doi:10.3390/machines9050085 · Cited by 29 · see citing works

Human Interaction, Emerging Technologies and Future Applications III

Ahram, T., Taïar, R., Langlois, K., & Choplin, A. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-55307-4 · Cited by 28 · see citing works

A construction method of digital twin model for contact characteristics of assembly interface

Zhang, C., Sun, Q., We, S., Mu, X., & Wang, Y. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-06751-x · Cited by 28 · see citing works

Mapping Local Vulnerabilities into a 3D City Model through Social Sensing and the CAVE System toward Digital Twin City

Kim, J., Kim, H., & Ham, Y. (2019) · ASCE International Conference on Computing in Civil Engineering (i3CE) · doi:10.1061/9780784482445.058 · Cited by 26 · see citing works

Process Modelling of Geothermal Drilling System Using Digital Twin for Real-Time Monitoring and Control

Osinde, N. O., Byiringiro, J. B., Gichane, M. M., & Smajić, H. (2019) · Designs · doi:10.3390/designs3030045 · Cited by 26 · see citing works

The Potential of Digital Twin Model Integrated With Artificial Intelligence Systems

Agostinelli, S., Cumo, F., Guidi, G., & Tomazzoli, C. (2020) · IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) · doi:10.1109/eeeic/icpseurope49358.2020.9160810 · Cited by 26 · see citing works

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 · see citing works

Kalibre

Wang, R., Zhou, X., Dong, L., Wen, Y., Tan, R., Chen, L., Wang, G., & Zeng, F. (2020) · ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys) · doi:10.1145/3408308.3427982 · Cited by 24 · see citing works

Design and Implementation of Universal Cyber-Physical Model for Testing Logistic Control Algorithms of Production Line’s Digital Twin by Using Color Sensor

Vachálek, J., Šišmišová, D., Vasek, P., Fitka, I., Slovak, J., & Simovec, M. (2021) · Italian National Conference on Sensors · doi:10.3390/s21051842 · Cited by 24 · see citing works

Towards Automated 3D reconstruction in SME factories and Digital Twin Model generation

Minos-Stensrud, M., Haakstad, O. H., Sakseid, O., Westby, B., & Alcocer, A. (2018) · International Conference on Control, Automation and Systems (ICCAS) · Cited by 22 · see citing works

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 · see citing works

Creation of Digital Twins by Combining Fuzzy Rules with Artificial Neural Networks

Lermer, M., & Reich, C. (2019) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2019.8926914 · Cited by 21 · see citing works

Modeling as the Foundation of Digital Twins

Брылина, О. Г., Kuzmina, N. N., & Осинцев, К. В. (2020) · Global Smart Industry Conference (GloSIC) · doi:10.1109/glosic50886.2020.9267812 · Cited by 21 · see citing works

Modelling stochastic behaviour in simulation digital twins through neural nets

Reed, S., Löfstrand, M., & Andrews, J. (2021) · Journal of Simulation · doi:10.1080/17477778.2021.1874844 · Cited by 21 · see citing works

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 · see citing works

From Software Engineering to Formal Methods and Tools, and Back

ter Beek, M. H., ter Beek, M. H., Fantechi, A., & Semini, L. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-30985-5 · Cited by 20 · see citing works

Enabling the digital twin: a review of the modelling of measurement uncertainty on data transfer standards and its relationship with data from tests

Ríos, J., Staudter, G. A., Weber, M., & Anderl, R. (2020) · International Journal of Product Lifecycle Management · doi:10.1504/ijplm.2020.109801 · Cited by 19 · see citing works

Anomaly detection for aircraft electrical generator using machine learning in a functional data framework

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A Digital Twin-Oriented Lightweight Approach for 3D Assemblies

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Digital Twin: Multi-dimensional Model Reduction Method for Performance Optimization of the Virtual Entity

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Improved Analytical Model of Induction Machine for Digital Twin Application

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Automated Construction of Neural Network Potential Energy Surface: The Enhanced Self-Organizing Incremental Neural Network Deep Potential Method

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Towards a Reference Architecture for Leveraging Model Repositories for Digital Twins

Lehner, D., Wolny, S., Mazak‐Huemer, A., & Wimmer, M. (2020) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa46521.2020.9212109 · Cited by 16 · see citing works

Predictive Digital Twins: Where Dynamic Data-Driven Learning Meets Physics-Based Modeling

Kapteyn, M. G., & Willcox, K. E. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-61725-7_1 · Cited by 15 · see citing works

Neural network modelling methods for creating digital twins of real objects

Tarkhov, D. A., & Malykhina, G. F. (2019) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1236/1/012056 · Cited by 13 · see citing works

A review of simplified servovalve models for digital twins of electrohydraulic actuators

Berri, P. C., & Vedova, M. D. L. D. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1603/1/012016 · Cited by 13 · see citing works

A Digital Twin Modeling Method for Turbofan Engine Real-time Test Data Analysis and Performance Monitoring

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Construction of Digital Twin Geotechnical Resistance Model for Liquefaction Risk Evaluation

Song, S.-J., & Jang, Y.-G. (2018) · International Symposium on Computer Science and Intelligent Control (ISCSIC) · doi:10.1145/3284557.3284739 · Cited by 12 · see citing works

Vision-Based Analysis of Utility Poles Using Drones and Digital Twin Modeling in the Context of Power Distribution Infrastructure Systems

Kim, J., & Ham, Y. (2020) · ASCE Construction Research Congress (CRC) · doi:10.1061/9780784482865.101 · Cited by 12 · see citing works

Prediction Study of the Heavy Vehicle Driving State Based on Digital Twin Model

Liu, J., Dong, Y., Liu, Y., Li, P., Liu, S., & Wang, T. (2021) · 2021 IEEE International Conference on Power Electronics, Computer Applications (ICPECA) · doi:10.1109/icpeca51329.2021.9362618 · Cited by 12 · see citing works

Digital twin based comfort scenario modeling of ATO controlled train

Meng, Z., Tang, T., Wei, G., & Yuan, L. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1654/1/012071 · Cited by 11 · see citing works

Generating digital twins of mesoporous silica by graph-based stochastic microstructure modeling

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Product Information Units Modeling Oriented to Digital Twin

Bao, Q., Zhao, G. L., Yu, Y., & Dai, S. L. (2021) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/726/1/012014 · Cited by 9 · see citing works

CFD MODEL AS A DIGITAL TWIN OF THE RADIATION STATE OF THE NEW SAFE CONFINEMENT OF THE CHERNOBYL NPP

Krukovskyi, P. G., Diadiushko, Y. V., Garin, V., Tryfonov, O., & Kabanov, Y. Y. (2020) · doi:10.46813/2020-128-054 · Cited by 9 · see citing works

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 · see citing works

Information model and software architecture for the implementation of the digital twin of the turbine rotor

Bolotov, M. A., Pechenin, V. A., Ruzanov, N. V., & Grachev, I. A. (2019) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1368/5/052013 · Cited by 8 · see citing works

Fundamentals Of Digital Twins Applied To A Plastic Toy Boat And A Ship Scale Model

Fonseca, Í. A., & Gaspar, H. M. (2020) · doi:10.7148/2020-0207 · Cited by 8 · see citing works

Adaptive Modification of Digital Twin Model of CNC Machine Tools Coordinately Driven by Mechanism Model and Data Model

Zhao, P., & Sun, B. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1875/1/012003 · Cited by 7 · see citing works

Tree Species Modelling for Digital Twin Cities

Gobeawan, L., Wise, D. J., Wong, S. T., Yee, A. T. K., Lim, C. W., & Su, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-662-63170-6_2 · Cited by 7 · see citing works

Rocket Engine Digital Twin – Modeling and Simulation Benefits

Mena, D. J., Pluchart, S., Mouvand, S., & Broca, O. (2019) · AIAA Propulsion and Energy Forum · doi:10.2514/6.2019-4114 · Cited by 6 · see citing works

Investigation of inventive Tuning Algorithm for the realization of Digital Twins of Inverter Model in Inverter-dominated Power Distribution Grid

Song, X.-Y., Jiang, T., Schlegel, S., & Westermann, D. (2019) · IEEE PES Innovative Smart Grid Technologies Conference Europe · doi:10.1109/isgteurope.2019.8905551 · Cited by 6 · see citing works

Construction and Optimization of Digital Twin Model for Hardware Production Line

Wang, B., Yuan, L., Yu, X., & Ou, L. (2020) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon43393.2020.9254967 · Cited by 6 · see citing works

A Note on Leakage Jet Forces: Application in the Modelling of Digital Twins of Hydraulic Valves

Bare, Z., Gaertig, E., Krebs, J., Arndt, C., Sleziona, C., & Gensel, A. (2021) · International Journal of Fluid Power · doi:10.13052/ijfp1439-9776.2214 · Cited by 6 · see citing works

Transactions on Computational Science XXXVIII

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Development and creation a model of a digital twin of the cubepart rectification installation for the separation of a binary water-alcohol mixture

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A Visual Particle System Based on Mechanism Model Data in Digital Twin

Gu, Z., & Gao, T.-H. (2020) · International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing · doi:10.1007/978-3-030-50399-4_18 · Cited by 4 · see citing works

Optimizing Machining Time and Oscillation based on Digital Twin Model of Tool Center Point

Yu, B.-F., & Chen, J.-S. (2020) · IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE) · doi:10.1109/ecice50847.2020.9301988 · Cited by 4 · see citing works

Creation of a Digital Twin Model, Redesign of Plant Structure and New Fuzzy Logic Controller for the Cooling System of a Railway Locomotive

Poce, M., Casiello, G., Ferrari, L., Dei, L. F. N., & Saponara, S. (2021) · Lecture notes in electrical engineering · doi:10.1007/978-3-030-66729-0_15 · Cited by 4 · see citing works

Technological Transformation: A New Role For Human, Machines And Management

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Analysis of CFD Modeling Accuracy in Centrifugal Compressor Stages Digital Twins

Aksenov, A. A., Gileva, L., Danilishin, A. M., & Kozhukhov, Y. V. (2020) · International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon) · doi:10.1109/fareastcon50210.2020.9271363 · Cited by 3 · see citing works

Modeling of Digital Twins of Historical Fashionable Bodies

Kuzmichev, V. E., Moskvin, A., & Moskvina, M. V. (2021) · Proceedings of Higher Education Institutions Textile Industry Technology · doi:10.47367/0021-3497_2021_1_144 · Cited by 3 · see citing works

Towards Modelling a Diphasic Flow Using the CFD Technique to Achieve a Digital Twin of a Phosphate Slurry Piping Process

Elkarii, M., Bouallou, C., & Ratnani, A. (2020) · Chemical engineering transactions · doi:10.3303/cet2081127 · Cited by 3 · see citing works

Informationsmodelle mit intelligenter Auswertung für den Digitalen Zwilling

Müller, M., Talkhestani, B. A., Jazdi, N., Weyrich, M., Rosen, R., & Wehrstedt, J. C. (2020) · VDI Verlag eBooks · doi:10.51202/9783181023754-659 · Cited by 3 · see citing works

Digital Twin of Continuously Variable Transmission for Predictive Modeling of Dynamics and Performance Optimization

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Meta-Information driven Modeling of Services for Experimentable Digital Twins

Priggemeyer, M., & Roßmann, J. (2020) · IEEE International Systems Conference (SysCon) · doi:10.1109/syscon47679.2020.9275877 · Cited by 1 · see citing works

Creating a Digital Twin to Investigate AV Block: In-sights From a Validated Electromechanical Full-Heart Model

Sack, K. L., Blauer, J. J. E., Campbell, M., & Swenson, D. J. (2020) · Computing in cardiology · doi:10.22489/cinc.2020.238 · Cited by 1 · see citing works

Digital twin in healthcare: Recent updates and challenges

Sun, T., He, X., & Li, Z. (2023) · Digital Health · doi:10.1177/20552076221149651 · Cited by 421 · see citing works

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 · see citing works

Advancements and challenges of digital twins in industry

Tao, F., Zhang, H., & Zhang, C. (2024) · Nature Computational Science · doi:10.1038/s43588-024-00603-w · Cited by 286 · see citing works

The Application of Artificial Intelligence and Big Data in the Food Industry

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Digital twin: Data exploration, architecture, implementation and future

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Big data, machine learning, and digital twin assisted additive manufacturing: A review

Jin, L., Zhai, X., Wang, K., Zhang, K., Wu, D., Nazir, A., Jiang, J., & Liao, W. (2024) · Materials & Design · doi:10.1016/j.matdes.2024.113086 · Cited by 220 · see citing works

The advance of digital twin for predictive maintenance: The role and function of machine learning

Chen, C., Fu, H., Zheng, Y., Tao, F., & Liu, Y. (2023) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2023.10.010 · Cited by 233 · see citing works

Digital Twins in Healthcare: An Architectural Proposal and Its Application in a Social Distancing Case Study

Benedictis, A. D., Mazzocca, N., Somma, A., & Strigaro, C. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3205506 · Cited by 158 · see citing works

Digital Twins and Enabling Technologies in Museums and Cultural Heritage: An Overview

Luther, W. J., Baloian, N. A., Biella, D., & Sacher, D. (2023) · Sensors · doi:10.3390/s23031583 · Cited by 156 · see citing works

How Simulation Helps Autonomous Driving: A Survey of Sim2real, Digital Twins, and Parallel Intelligence

Hu, X.-M., Li, S., Huang, T., Tang, B., Huai, R., & Chen, L. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3312777 · Cited by 173 · see citing works

A review of digital twins and their application in cybersecurity based on artificial intelligence

Homaei, M., Gutiérrez, Ó. M., Núñez, J. C. S., Ávila, M., & Lindo, A. C. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10805-3 · Cited by 172 · see citing works

Digital twin-based structural health monitoring by combining measurement and computational data: An aircraft wing example

Lai, X., Yang, L., He, X., Pang, Y. J., Song, X., & Sun, W. F. (2023) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2023.06.006 · Cited by 132 · see citing works

Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy

Tahmasebinia, F., Lin, L., Wu, S., Kang, Y., & Sepasgozar, S. M. E. (2023) · Applied Sciences · doi:10.3390/app13158814 · Cited by 127 · see citing works

Digital twin for credit card fraud detection: opportunities, challenges, and fraud detection advancements

Chatterjee, P., Das, D., & Rawat, D. B. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.04.057 · Cited by 127 · see citing works

Developing a Skilled Workforce for Future Industry Demand: The Potential of Digital Twin-Based Teaching and Learning Practices in Engineering Education

Hazrat, M. A., Hassan, N. M. S., Chowdhury, A. A., Rasul, M. G., & Taylor, B. A. (2023) · Sustainability · doi:10.3390/su152316433 · Cited by 141 · see citing works

A review of digital twin capabilities, technologies, and applications based on the maturity model

Liu, Y., Feng, J., Lu, J., & Zhou, S. (2024) · Advanced Engineering Informatics · doi:10.1016/j.aei.2024.102592 · Cited by 123 · see citing works

Blockchain and its derived technologies shape the future generation of digital businesses: a focus on decentralized finance and the Metaverse

Far, S. B., Rad, A. I., & Asaar, M. R. (2023) · Data Science and Management · doi:10.1016/j.dsm.2023.06.002 · Cited by 110 · see citing works

Advanced informatic technologies for intelligent construction: A review

Zhang, L., Li, Y., Pan, Y., & Ding, L. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109104 · Cited by 115 · see citing works

Operation and maintenance optimization of offshore wind farms based on digital twin: A review

Xia, J., & Zou, G. (2022) · Ocean Engineering · doi:10.1016/j.oceaneng.2022.113322 · Cited by 112 · see citing works

Digital Twin Technology in Built Environment: A Review of Applications, Capabilities and Challenges

Mousavi, Y., Gharineiat, Z., Karimi, A. A., McDougall, K., Rossi, A., & Barsanti, S. G. (2024) · Smart Cities · doi:10.3390/smartcities7050101 · Cited by 117 · see citing works

Assessing the influence of artificial intelligence on the energy efficiency for sustainable ecological products value

Song, M., Pan, H., Shen, Z., & Tamayo‐Verleene, K. (2024) · Energy Economics · doi:10.1016/j.eneco.2024.107392 · Cited by 97 · see citing works

Digital twin in power system research and development: Principle, scope, and challenges

Yassin, M. A. M., Shrestha, A., & Rabie, S. (2023) · Energy Reviews · doi:10.1016/j.enrev.2023.100039 · Cited by 102 · see citing works

Digital Twins in Agriculture and Forestry: A Review

Tagarakis, A., Benos, L., Kyriakarakos, G., Pearson, S., Sørensen, C. G., & Bochtis, D. (2024) · Italian National Conference on Sensors · doi:10.3390/s24103117 · Cited by 92 · see citing works

From Simulation to Autonomy: Reviews of the Integration of Artificial Intelligence and Digital Twins

Sajadieh, S. M. M., & Noh, S. D. (2025) · International Journal of Precision Engineering and Manufacturing-Green Technology · doi:10.1007/s40684-025-00750-z · Cited by 114 · see citing works

Building digital twinning: Data, information, and models

Yoon, S. (2023) · Journal of Building Engineering · doi:10.1016/j.jobe.2023.107021 · Cited by 92 · see citing works

Task incremental learning-driven Digital-Twin predictive modeling for customized metal forming product manufacturing process

Li, J., Wang, Z., Zhang, S., Lin, Y., Jiang, L., & Tan, J. (2023) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2023.102647 · Cited by 94 · see citing works

Cybersecurity of Satellite Communications Systems: A Comprehensive Survey of the Space, Ground, and Links Segments

Salim, S., Moustafa, N., & Martin Reisslein, B. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3408277 · Cited by 95 · see citing works

Digital twin-inspired methods for rotating machinery intelligent fault diagnosis and remaining useful life prediction: A state-of-the-art review and future challenges

Ma, H., Fan, C., Zhang, Y., Wang, Q., Yu, K., & Ma, Z. (2025) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2025.112770 · Cited by 92 · see citing works

A 3D functional plant modelling framework for agricultural digital twins

Mitsanis, C., Hurst, W., & Teki̇nerdoğan, B. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.108733 · Cited by 86 · see citing works

Developing a digital twin model for monitoring building structural health by combining a building information model and a real-scene 3D model

Xu, J., Shu, X., Qiao, P., Li, S.-S., & Jigang, X. (2023) · Measurement · doi:10.1016/j.measurement.2023.112955 · Cited by 76 · see citing works

Digital twin for personalized medicine development

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Production logistics digital twins: Research profiling, application, challenges and opportunities

Zhu, Y., Cheng, J., Liu, Z., Cheng, Q., Zou, X., Xu, H., Wang, Y., & Tao, F. (2023) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2023.102592 · Cited by 79 · see citing works

Pipeline condition monitoring towards digital twin system: A case study

Wang, T., Feng, K., Ling, J., Liao, M., Yang, C., Neubeck, R., & Liu, Z. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.02.006 · Cited by 73 · see citing works

Towards the application of machine learning in digital twin technology: a multi-scale review

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Digital Twin Models: Functions, Challenges, and Industry Applications

Rayhana, R., Bai, L., Xiao, G. G., Liao, M., & Liu, Z. (2024) · IEEE Journal of Radio Frequency Identification · doi:10.1109/jrfid.2024.3387996 · Cited by 68 · see citing works

Digital Twin in Industries: A Comprehensive Survey

Zami, M. B. A., Shaon, S., Khanh, Q. V., & Nguyen, D. C. (2025) · IEEE Access · doi:10.1109/access.2025.3551532 · Cited by 83 · see citing works

Digital Twin of Space Environment: Development, Challenges, Applications, and Future Outlook

Liu, W., Wu, M., Wan, G., & Xu, M. (2024) · Remote Sensing · doi:10.3390/rs16163023 · Cited by 71 · see citing works

A unified framework for digital twin development in manufacturing

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A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review

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A systematic review on the current research of digital twin in automotive application

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Advancements in digital twin modeling for underground spaces and lightweight geometric modeling technologies

Gong, H., Su, D., Zeng, S., & Chen, X. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105578 · Cited by 63 · see citing works

Vehicle giga-casting Al alloys technologies, applications, and beyond

Yang, J. L., Liu, B., Shu, D., Qin, Y., & Hu, T. (2025) · Journal of Alloys and Compounds · doi:10.1016/j.jallcom.2025.178552 · Cited by 62 · see citing works

Remaining useful life prediction combined dynamic model with transfer learning under insufficient degradation data

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Application status and prospects of digital twin technology in distribution grid

Zhang, Z.-Y., & Lv, L.-J. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.10.410 · Cited by 53 · see citing works

Faceting the post-disaster built heritage reconstruction process within the digital twin framework for Notre-Dame de Paris

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Meta-model-based shop-floor digital twin architecture, modeling and application

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How to build a Digital Twin for operating PEM-Electrolyser system – A reference approach

Monopoli, D., Semeraro, C., Abdelkareem, M. A., Alami, A. H., Olabi, A. G., & Dassisti, M. (2024) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2024.100943 · Cited by 58 · see citing works

Digital twin technology in modern machining: A comprehensive review of research on machining errors

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Developing and leveraging digital twins in engineering design

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Digital Twins for Power Systems: Review of Current Practices, Requirements, Enabling Technologies, Data Federation, and Challenges

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Transforming the maintenance of underground infrastructure through Digital Twins: State of the art and outlook

Zhu, H., Huang, M., Ji, P.-Q., Xiao, F., & Zhang, Q. (2025) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2025.106508 · Cited by 61 · see citing works

Survey on open‐source digital twin frameworks–A case study approach

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Current status of digital twin architecture and application in nuclear energy field

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Digital-Twins-Based Internet of Robotic Things for Remote Health Monitoring of COVID-19 Patients

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A digital twin-based machining motion simulation and visualization monitoring system for milling robot

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Survey and insights on digital twins design and smart grid’s applications

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Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy

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Robot digital twin systems in manufacturing: Technologies, applications, trends and challenges

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Computational Architectures for Precision Dairy Nutrition Digital Twins: A Technical Review and Implementation Framework

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Digital Twin for Aquaponics Factory: Analysis, Opportunities, and Research Challenges

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Digital Twin as a Service (DTaaS): A Platform for Digital Twin Developers and Users

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Digital Twin Methodology in Food Processing: Basic Concepts and Applications

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Enhancing internal supply chain management in manufacturing through a simulation-based digital twin platform

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Application of Digital Twins and Metaverse in the Field of Fluid Machinery Pumps and Fans: A Review

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Governance and sustainability of distributed continuum systems: a big data approach

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Exploring human-machine collaboration in industry: a systematic literature review of digital twin and robotics interfaced with extended reality technologies

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Probing an LSTM-PPO-Based reinforcement learning algorithm to solve dynamic job shop scheduling problem

Chen, W., Zhang, Z., Tang, D., Liu, C., Gui, Y., Nie, Q., & Zhao, Z. M. (2024) · Computers & Industrial Engineering · doi:10.1016/j.cie.2024.110633 · Cited by 46 · see citing works

Digital twin based deep learning framework for personalized thermal comfort prediction and energy efficient operation in smart buildings

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Digital twin perception and modeling method for feeding behavior of dairy cows

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Digital Twin Smart Water Conservancy: Status, Challenges, and Prospects

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Measurement Informed Models and Digital Twins for Optical Fiber Communication Systems

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Digital twin for smart manufacturing equipment: modeling and applications

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Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

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Research on Rolling Bearing Fault Diagnosis Based on Digital Twin Data and Improved ConvNext

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Finite element analysis, machine learning, and digital twins for soft robots: state-of-arts and perspectives

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Digital twin-driven prognostics and health management for industrial assets

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IoT-based framework for digital twins in steel production: A case study of key parameter prediction and optimization for CSR

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Digital twin-enabled entropy regularized wavelet attention domain adaptation network for gearboxes fault diagnosis without fault data

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Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

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Proactiveness, knowledge management capability and innovation ambidexterity: an empirical examination of digital supply chain adoption

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An online monitoring method of milling cutter wear condition driven by digital twin

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Towards discrete manufacturing workshop-oriented digital twin model: Modeling, verification and evolution

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The philosophical foundations of digital twinning

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Research and Prospects of Digital Twin-Based Fault Diagnosis of Electric Machines

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Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure

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Digital Twin System of Pest Management Driven by Data and Model Fusion

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Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

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Digital Twin-Driven Stability Optimization Framework for Large Underground Caverns

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Interaction with Industrial Digital Twin Using Neuro-Symbolic Reasoning

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Digital twins in healthcare: Applications, technologies, simulations, and future trends

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A study on the development of digital model of digital twin in nuclear power plant based on a hybrid physics and data-driven approach

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Application of Digital Twin in Electric Vehicle Powertrain: A Review

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Model-driven engineering for digital twins: a systematic mapping study

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Research on coal mine safety management based on digital twin

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Digital twin designs with generative AI: crafting a comprehensive framework for manufacturing systems

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DT-CEPA: A digital twin-driven contour error prediction approach for machine tools based on hybrid modeling and sparse time series

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TWIN-ADAPT: Continuous Learning for Digital Twin-Enabled Online Anomaly Classification in IoT-Driven Smart Labs

Gupta, R., Tian, B., Wang, Y., & Nahrstedt, K. (2024) · Future Internet · doi:10.3390/fi16070239 · Cited by 33 · see citing works

Iterative updating of digital twin for equipment: Progress, challenges, and trends

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Digital Twins of Business Processes: A Research Manifesto

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A review of SCADA-based condition monitoring for wind turbines via artificial neural networks

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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 · see citing works

Digital Twins: Modeling Hierarchy and Basic Approaches

Liu, X., Liu, J., & Yin, S. (2025) · Springer eBooks · doi:10.1007/978-981-96-9108-1_2

Industry application of digital twin: from concept to implementation

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A Comprehensive Review of Digital Twin from the Perspective of Total Process: Data, Models, Networks and Applications

Wu, H., Ji, P., Ma, H., & Xing, L. (2023) · Sensors · doi:10.3390/s23198306 · Cited by 119 · see citing works

On the Notion of Digital Twins: A Modeling Perspective

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