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 16,548

Digital Twin in Industry: State-of-the-Art

Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391

Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems

Grieves, M., & Vickers, J. (2017) · Transdisciplinary Perspectives on Complex Systems · doi:10.1007/978-3-319-38756-7_4 · Cited by 3,727

Digital twin: 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

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

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

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

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

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

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

Enhancing safety and resilience of ageing land-based LNG Tank structures through digital healthcare engineering: a feasibility assessment in seismic environments

Duan, W., Tan, P. J., & Paik, J. K. (2024) · Ships and Offshore Structures · doi:10.1080/17445302.2024.2428229 · Cited by 11

Premises for digital twins reporting on Atlantic salmon wellbeing

Giske, J., Dumitru, M. L., Enberg, K., Folkedal, O., Handeland, S. O., Higginson, A. D., Opdal, A. F., Rønnestad, I., Salvanes, A. G. V., Vollset, K. W., et al. (2025) · Behavioural Processes · doi:10.1016/j.beproc.2025.105163 · Cited by 11

How digital twin technology may improve safety management: A multi-industry perspective

Zou, P. X. W., & Ma, S. (2025) · Safety Science · doi:10.1016/j.ssci.2025.106837 · Cited by 13

AI-enabled consumer digital twins as a platform for research aimed at enhancing customer experience

Hornik, J., & Rachamim, M. (2025) · Management Review Quarterly · doi:10.1007/s11301-025-00527-3 · Cited by 14

Applications of artificial intelligence in the dairy Industry: From farm to product development

Khanashyam, A. C., Jagtap, S., Agrawal, T. K., Thorakkattu, P., Malav, O. P., Trollman, H., Hassoun, A., Ramesh, B., Manoj, V., Rathnakumar, K., et al. (2025) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2025.110879 · Cited by 13

A robust and scalable surrogate model for 3D crystal plasticity simulation under diverse loading conditions

Yu, G., Tang, X., Jiang, X. L., Deng, L. M., Fu, H., & Wang, X. (2025) · Acta Materialia · doi:10.1016/j.actamat.2025.121441 · Cited by 11

Digital twins for machine tools: a systematic mapping study

Chen, S., Ellwein, C., Klingel, L., Neumann, R., Zhang, J., Riedel, O., Verl, A. W., & Wortmann, A. (2025) · Digital Twin · doi:10.1080/27525783.2025.2538727 · Cited by 11

Digital twin connection model based on virtual sensor

Wang, C., Liu, X., Zhu, M., Zhu, C., Lv, F., & Ni, Z. (2023) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-023-12438-2 · Cited by 11

Leveraging a visual language for the awareness-based design of interaction requirements in digital twins

Duque, R., Bravo, C., Bringas, S., & Postigo, D. (2023) · Future Generation Computer Systems · doi:10.1016/j.future.2023.11.018 · Cited by 12

Feasibility of AI and Robotics in Indian Healthcare

Joshi, R., & Badola, R. (2024) · Wiley eBooks · doi:10.1002/9781394234196.ch18 · Cited by 11

Modular digital twin modelling method for 10 kV cable lines based on real‐time temperature field inversion

Huang, S., & Niu, H. (2024) · High Voltage · doi:10.1049/hve2.12465 · Cited by 10

Automatic response prediction in a digital twin framework for regional bridges group

Zhao, W., Wan, C., Zhang, X., Zhang, G., Ding, Y., Xie, L., Peng, H., & Xue, S. (2025) · Structures · doi:10.1016/j.istruc.2025.109052 · Cited by 10

Intelligent Manufacturing of a Bibliometric Review: From Frontier Hotspots to Key Technologies and Applications

Sun, X., Dong, L., Liu, Z., Qin, A., Liu, J., Zhou, Z., Yan, X., Wang, G., Liu, B., Zhou, Z., et al. (2025) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-025-01274-y · Cited by 10

Advancing intelligent transportation through digital twin: Challenges, models, and future prospects

XING, L. X., Li, B., Deng, K., Gao, J., Wu, H., Ma, H., & Zhang, X. (2025) · Ad Hoc Networks · doi:10.1016/j.adhoc.2025.104077 · Cited by 11

Digital twin–based dynamic prediction and simulation model of carbon efficiency in gear hobbing process

Hu, C., Yi, Q., Li, C., Luo, Y., & Yi, S. (2023) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-023-11385-2 · Cited by 10

Development of a Virtual Reality Model Using Digital Twin for Real-Time Data Analysis

Sahoo, S. K., Nalinipriya, G., Srinivasan, P. S., Ramesh, J. V. N., Ramamoorthy, K., & Soleti, N. (2023) · SN Computer Science · doi:10.1007/s42979-023-01928-5 · Cited by 10

Modeling of Digital Twin Workshop in Planning via a Graph Neural Network: The Case of an Ocean Engineering Manufacturing Intelligent Workshop

Li, J., Yin, W., Yang, B., Chen, L., Dong, R., Chen, Y., & Yang, H. (2023) · Applied Sciences · doi:10.3390/app131810134 · Cited by 11

An Educational Human Digital Twin Proposed Model for Personalized E-Learning

Aboulsafa, E. I., Khayat, G. A. E., & Elmorsy, S. A. (2023) · IEEE Afro-Mediterranean Conference on Artificial Intelligence (AMCAI) · doi:10.1109/amcai59331.2023.10431503 · Cited by 10

Review and Proposed Digital Twin Model for Sustainable Smart University Asset Management

Fashal, N. A., Khayat, G. A. E., & Elmorsy, S. A. (2023) · IEEE Afro-Mediterranean Conference on Artificial Intelligence (AMCAI) · doi:10.1109/amcai59331.2023.10431490 · Cited by 12

More than 10 years of industry 4.0 in the Netherlands: an opinion on promises, achievements, and emerging challenges

Martinetti, A., Nizamis, K., Chemweno, P. K., Goulas, C., van Dongen, L. A. M., Gibson, I., Thiede, S., Lutters, E., Vaneker, T., & Bonnema, G. M. (2024) · International Journal of Sustainable Engineering · doi:10.1080/19397038.2024.2327380 · Cited by 10

Fusion method for digital twin model of a production line

Liu, X.-J., Wang, C.-X., Huang, J.-S., Ni, Z.-H., Salam, M., Yan, Y., & Feng, J. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-13676-8 · Cited by 11

Overview of Digital Twins in Renewable Energy

Sharma, P., Bora, B. J., Deepanraj, B., & Jarin, T. (2024) · International Conference on Trends in Engineering Systems and Technologies (ICTEST) · doi:10.1109/ictest60614.2024.10576156 · Cited by 12

A bibliometric review on application of machine learning in additive manufacturing and practical justification

Ma, Q.-P., Nguyen, H.-S., Hajnyš, J., Měsíček, J., Pagáč, M., & Petrů, J. (2024) · Applied Materials Today · doi:10.1016/j.apmt.2024.102371 · Cited by 10

Promoting digital twin technology application for process industry: A novel generation modelling platform and its implementations

Zhang, Y. Z., Wang, W., Yang, Q., Tang, X., Ruan, W., Li, Y., Daoerji, S., Zhang, X., Ye, Y., Huang, J., et al. (2024) · Digital twins and applications. · doi:10.1049/dgt2.12010 · Cited by 10

Online optimization of adjustable settings for agricultural machinery assisted by digital twin

Guo, D., Wang, L., Du, Y., Wu, Z., Zhang, W., Qiao, Z. Q., & Ma, R. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.109504 · 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

Multimodal data visualization method for digital twin campus construction

Xie, Y., Zhan, N., Zhu, Q., Zhan, J., Guo, Z., Qiao, C., Zhu, J., & Xu, B. (2024) · International Journal of Digital Earth · doi:10.1080/17538947.2024.2431624 · Cited by 10

Automatic Data Generation and Optimization for Digital Twin Network

Li, M., Zhou, C., Lu, L., Zhang, Y., Sun, T., Chen, D., Yang, H., & Li, Z. (2024) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2024.3522504 · Cited by 13

Network Operation Constraints on the Path to Net Zero

Daví-Arderius, D., Jamasb, T., & Rosellón, J. (2025) · Applied Energy · doi:10.1016/j.apenergy.2024.125170 · Cited by 11

Artificial Intelligence-Driven Technologies for Environmental Sustainability in the Healthcare Industry

Dewasiri, N. J., Rathnasiri, M. S. H., & Karunarathne, K. S. S. N. (2024) · Approaches to global sustainability, markets, and governance · doi:10.1007/978-981-97-9555-0_4 · Cited by 11

A digital twin approach based method in civil engineering for classification of salt damage in building evaluation

Guzman-Torres, J. A., Domínguez-Mota, F. J., Guzmán, E. M. A., Tinoco-Guerrero, G., & Tinoco-Ruiz, J. G. (2025) · Mathematics and Computers in Simulation · doi:10.1016/j.matcom.2025.02.003 · Cited by 12

Real-Time Monitoring and Dynamic Interaction Methods Based on Digital Twin Workshop Theory

Yu, J., Chen, C., Zhang, C., & Ji, W. (2025) · Processes · doi:10.3390/pr13030685 · Cited by 10

A digital twin data management and process traceability method for the complex product assembly process

Cheng, X., Huang, F., Yang, Q., & Qiu, L. (2025) · Journal of the Brazilian Society of Mechanical Sciences and Engineering · doi:10.1007/s40430-025-05466-4 · Cited by 15

Exploring the concept of digital twins of wetlands for supporting ecosystem monitoring and management

Lu, B., Francescutto, L., Howie, S., Lin, H. Z., Wu, Q., Hedley, N., Jamali, A., & McDonald, I. (2025) · Big Earth Data · doi:10.1080/20964471.2025.2480446 · Cited by 10

Towards Universal Thermal Climate Index Prediction via machine learning approaches

Veisi, O., Tehrani, A. A., Gharaei, B., Du, D. K., & Shakibamanesh, A. (2025) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2025.115680 · Cited by 10

Metaverse for logistics and supply chain management: new framework and research advances

Zhang, Z., Wu, H., Qiu, Y., Liao, Z., & Song, M. (2025) · The International Journal of Logistics Management · doi:10.1108/ijlm-07-2024-0461 · Cited by 12

Behavioral model construction of architectural heritage for digital twin

Shang, X., Guo, M., Wang, G., Zhao, J., & Pan, D. (2025) · npj Heritage Science · doi:10.1038/s40494-025-01691-1 · Cited by 10

Mixed-model product disassembly sequence optimization based on cognitive digital twin

Qi, L., Xu, W., Wang, K., Liu, J., Ye, X., Yang, H., & Zhong, Y. (2025) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2025.07.004 · Cited by 10

Digital twin-driven reinforcement learning-based operational management for customized manufacturing

Tang, H., Cheng, M., Bhatti, U. A., Xu, B., Zhou, N., Guo, R., & Wei, B. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111754 · Cited by 10

Cyber-physical-human systems for mobile robots in energy asset management: Current practices and future opportunities

Mitchell, D., Baniqued, P. D. E., Kivrak, H., Blanche, J. R. D., Bremner, P., Harper, S., Jiang, Z., Pulgarín, E. J. L., Paterson, J., Carrasco, J., et al. (2025) · Energy and AI · doi:10.1016/j.egyai.2025.100570 · Cited by 9

Research Progress on Control Algorithms for Grain Combine Harvesters

Chen, Z., Qian, Z., Jin, C., & Yang, T. (2025) · Applied Sciences · doi:10.3390/app15169176 · Cited by 10

A Digital Twin-Empowered Framework for Interactive Consumers in Manufacturing Using Wearable Device

Nguyễn, T. P., Hung, N., Cao, H.-L., Bui, T. T., & Ngo, H. Q. T. (2025) · IEEE Access · doi:10.1109/access.2025.3598864 · Cited by 10

Data-driven digital twin for fault detection in compressed air energy storage systems: Design and experimental validation

Semeraro, C., Ababneh, R. F., Alkhatib, L. A., Saqallah, D., Koutoubi, R. A., Aljaghoub, H., Alami, A. H., Abdelkareem, M. A., & Olabi, A. G. (2025) · Energy · doi:10.1016/j.energy.2025.138401 · Cited by 10

Toward Smart Manufacturing Metaverse via Digital Twinning in Extended Reality

Yang, H. Y., Aqlan, F., & Zhao, R. (2025) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4070437 · Cited by 10

A comprehensive review on CFD simulations of left ventricle hemodynamics: numerical methods, experimental validation techniques, and emerging trends

Soni, P., Kumar, S., Kumar, B. V. R., Rai, S. K., Verma, A., & Shankar, O. (2024) · Journal of the Brazilian Society of Mechanical Sciences and Engineering · doi:10.1007/s40430-024-04875-1 · Cited by 9

An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning

Zhu, L., Tan, L., Li, B., & Tian, H. (2024) · IET Communications · doi:10.1049/cmu2.12800 · Cited by 9

PSDM: A parametrized structural dynamic modeling method based on digital twin for performance prediction

He, X., Yang, L., Pang, Y. J., Kan, Z., & Song, X. (2024) · Engineering Structures · doi:10.1016/j.engstruct.2024.118582 · Cited by 9

Digital Twins and E-Learning: Navigating Challenges and Opportunities

Jankovskis, D., Cīrule, I., & Carbone, A. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-67351-1_12 · Cited by 9

Concept and Six-Dimension Model of Digital Triplet

Wu, C., Cui, Z., Qian, X., & Yue, J. (2024) · International Conference on Control, Decision and Information Technologies (CoDIT) · doi:10.1109/codit62066.2024.10708594 · Cited by 9

A Novel Digital Twin Framework With Hardware-in-the-Loop for Engine Systems

Huang, S., Li, T., Ye, W., He, W., Xu, S., Cao, H., Li, S., Chen, R., Yi, P., & Wang, X. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3526204 · Cited by 9

Six-dimensional digital twin modeling and software platform design for complex industrial systems

Li, N., Xie, G., Zhang, X., Shi, H., Nie, X., Wang, Y., Wang, J.-A., & Wang, J. (2025) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-025-02567-8 · Cited by 10

Research on digital twin model for milling parameter optimization of thin-walled parts

Song, J., Jin, H., Wang, X., Hu, T., Zhen-yu, H., & Fu, H. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-15072-2 · Cited by 11

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

Digital-Twin-Based Modeling and Fault Prediction Method for Industrial Robots

Wang, Q., Yang, H., Zhang, H., Lu, J., Zhang, Y., Xiao, G., & Cheok, A. D. (2025) · IEEE Journal of Emerging and Selected Topics in Industrial Electronics · doi:10.1109/jestie.2025.3565106 · Cited by 9

Dendrite‐Inspired and 3D Printed Multidirectional Sensing Piezoresistive Metamaterials

Zhang, L., Bian, Y., Wei, W., Liao, Z., Cang, M., Yang, A., Hu, Z. H., Zhang, W., Chen, M., Cui, H., et al. (2025) · Advanced Functional Materials · doi:10.1002/adfm.202508987 · Cited by 9

Development of digital twin system for central air-conditioning based on BIM

Ma, N., Li, W., Jiang, C., Sun, X., & Zhang, J. (2025) · Journal of Building Engineering · doi:10.1016/j.jobe.2025.113171 · Cited by 9

Research Progress on Process Optimization of Thermal-Sprayed Iron-Based Amorphous Coatings

Zhang, E., Zhang, Z., Jing, Z., Yuan, J., Ma, C., Yan, S. Z., Zhang, S., & Liang, X. (2025) · Integrating materials and manufacturing innovation · doi:10.1007/s40192-025-00408-3 · Cited by 9

Digital transformation and wage distortion in R&D and innovation activities - Causal inference based on double machine learning

Ding, Y., Li, B., Ma, S., Yu, C., & Zhao, X. (2025) · International Review of Financial Analysis · doi:10.1016/j.irfa.2025.104541 · Cited by 9

GRU-based real-time scheduling method for production-logistics collaboration in digital twin workshop

Yang, W., Zhang, B., Luo, G., Li, L., Wen, X., Li, H., & Wang, H. (2025) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2025.08.013 · Cited by 9

Multi-source errors evaluation of machine tools: from research gaps to methodologies and applications

Sun, J., Zhang, Y., Ma, X., Li, B., Yang, M., Xu, L., Xin, H., An, Q., Zhu, L., Bie, Q., et al. (2025) · International Journal of Extreme Manufacturing · doi:10.1088/2631-7990/ae1be8 · Cited by 11

Power System Digital Twins in Action: What We Learnt and Where We Go Next

Islam, K., Aslam, U., Khan, M. Z. I., Ebrahimi, S., Ferdowsi, F., & Carbone, M. A. (2025) · Digital twins and applications. · doi:10.1049/dgt2.70015 · Cited by 9

Energy-efficient thermal management of air-liquid-cooled data centers via deep reinforcement learning

Wu, C., Huang, Z., Yu, T., Pan, Z., Wang, K., & Wu, Y. (2025) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2025.129626 · Cited by 9

The digital twin-enabled deformation prediction and control methodologies for thin-walled parts in intelligent manufacturing: a review

Wang, Y. Q., Zhao, Z., Qian, N., Ding, W., & Su, H. (2026) · Digital Twin · doi:10.1080/27525783.2026.2614885 · Cited by 9

Decentralised task planning and motion coordination for scalable multi-robot collaborative manufacturing

Yang, H., Xu, W., Pham, D. T., Qi, L., & Ba, M. (2026) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2026.103255 · Cited by 9

Empowering digital twins for wind energy operation and maintenance: A prospective framework and future directions

Li, M., Kikuchi, Y., Ringsberg, J. W., Gryllias, K., Baraldi, P., Zio, E., & Carroll, J. (2026) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2026.116970 · Cited by 10

Modeling, Analysis, and Optimization of Robotic Light Machining Tasks for Empowering Digital Twin: Generalized Impulse Model Approach

Imran, A., Kim, S., Woo, J.-H., & Yi, B. (2022) · IEEE Access · doi:10.1109/access.2022.3210247 · Cited by 8

9E analysis of a flat plate solar collector system implementation: A new approach based on digital twin model coupled with global sensitivity analysis and multi-objective optimization

Cetina-Quiñones, A. J., Sánchez, I., Casillas-Reyes, A., & Bassam, A. (2023) · Journal of Renewable and Sustainable Energy · doi:10.1063/5.0151617 · Cited by 9

Opportunities, Challenges, and Research Needs for Remote Microreactor Operations

Stevens, K., Oncken, J., Boring, R. L., Ulrich, T. A., Culler, M., Bryan, H. C., Browning, J. M., & Gutowska, I. (2024) · Nuclear Technology · doi:10.1080/00295450.2024.2344903 · Cited by 9

Feature-constrained automatic geometric deformation analysis method of bridge models toward digital twin

Zhu, J., Luo, N., Guo, Z., Lai, J., Li, Z., Zhang, C., Guo, Y., & Hu, Y. (2024) · International Journal of Digital Earth · doi:10.1080/17538947.2024.2312219 · Cited by 8

A Generative Shape Compositional Framework to Synthesize Populations of Virtual Chimeras

Dou, H., Virtanen, S., Ravikumar, N., & Frangi, A. F. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3374121 · Cited by 8

IoT-Inspired Smart Theft Control Framework for Logistic Industry

Alanazi, A., Alqahtani, A., Alsubai, S., & Bhatia, M. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3445884 · Cited by 8

Risk Analysis of Digital Twin Project Operation Based on Improved FMEA Method

Li, L., You, J., & Xu, T. (2025) · Systems · doi:10.3390/systems13010048 · Cited by 10

Research on digital twin based sealing mechanism of liquid swivel spring energized seal ring

Yang, Y., Gao, R., Baolei, Z., Jin, Z., Lin, S., & Zhang, H. (2025) · Geoenergy Science and Engineering · doi:10.1016/j.geoen.2025.213696 · Cited by 9

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

Virtual in-situ calibration for digital twin-synchronized building operations

Koo, J., & Yoon, S. (2025) · Energy and Buildings · doi:10.1016/j.enbuild.2025.115760 · Cited by 10

6G-DTFP: A Digital-Twin-Enabled Privacy-Preserving Federated User Prediction Framework for 6G Mobile Edge Computing

Li, C., Zheng, L., Ji, X., Liao, X., Wang, Z., & Mao, G. (2025) · IEEE Communications Magazine · doi:10.1109/mcom.001.2400536 · Cited by 8

Multi-fidelity digital twin based optimization for aircraft overhaul shop scheduling

Liu, M., Fang, S., & Dong, H. (2025) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2025.07.018 · Cited by 9

Maintenance planning using a digital twin: principles and case studies

Dwight, R. A., Li, W., van Rooij, F., & Scarf, P. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.111496 · Cited by 9

Multiple knowledge depiction of digital twin-driven circular economy: Concepts, integrated advanced technologies, triple bottom line of smart construction, and exploratory case studies

Ali, Z. A., Hasan, R., Alsanad, A., Alhogail, A. A., & Gumaei, A. (2025) · Journal of Engineering Research · doi:10.1016/j.jer.2025.08.018 · Cited by 13

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

Integrating human–machine systems and digital twin technologies: navigating trust, interoperability, and ethical challenges

Sabri, S., Aghaabbasi, M., Atkinson, S. R., Amon, M. J., Hancock, P. A., Azevedo, R., Wiedbusch, M. D., Maraj, C. S., Mondesire, S. C., Soykan, B., et al. (2025) · Cognitive Systems Research · doi:10.1016/j.cogsys.2025.101414 · Cited by 8

Shape sensing and strain field reconstruction of full-scale wind turbine blade in static tests based on the inverse finite element method

Sheng, F., Liang, X., Li, F. Y., Wang, B., Chen, Y., & Wang, Z. (2025) · Structures · doi:10.1016/j.istruc.2025.110366 · Cited by 8

A review on machine learning-based prognostics and health management for hydrogen fuel cells

Meng, H., Liang, J., Hu, M., Salehi, F., & Han, T. (2025) · Journal of Loss Prevention in the Process Industries · doi:10.1016/j.jlp.2025.105833 · Cited by 9

The Role of Digital Twin in Advancing Industrial Internet of Things: Insights, Applications, and Future Directions

Chen, J., Wang, Z. X., Gao, H., He, Q., Mou, J., & Wang, W. W. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3653640 · Cited by 8

From polygenic risk to digital twins: the future of personalised cardiovascular medicine

Antoun, I., Alkhayer, A., Abdelrazik, A., Eldesouky, M., Thu, K. M., Ibrahim, M. N., Dhutia, H., Somani, R., & Ng, G. A. (2026) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2026.1735094 · Cited by 8

Model-based digital twin engineering: insights, challenges, and future directions

Zech, P., Barat, S., Nast, B., Oakes, B., Michael, J., Zschaler, S., Barn, B., & Breu, R. (2026) · Software & Systems Modeling · doi:10.1007/s10270-026-01368-8 · Cited by 12

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 target-driven framework for assessing the effectiveness of product-service-system development approaches at System of Systems level

Abdoli, S., & Bahramimianrood, B. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.01.002 · Cited by 8

Container Terminal Digital Twin Yard System Construction

Du, X., Liang, C., Zhao, N., & Xuan, B. (2023) · Processes · doi:10.3390/pr11072223 · Cited by 10

Digital Twin Edge Services With Proximity-Aware Longitudinal Lane Changing Model for Connected Vehicles

Huang, Z., Yu, R., Ye, M., Zheng, S., Kang, J., & Zeng, W. (2024) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2024.3412119 · Cited by 8

Overview of the Research Status of Intelligent Water Conservancy Technology System

Li, Q., Ma, Z., Li, J., Li, W., Li, Y., & Yang, J. (2024) · Applied Sciences · doi:10.3390/app14177809 · Cited by 8

SurgEM: A Vision-Based Surgery Environment Modeling Framework for Constructing a Digital Twin Toward Autonomous Soft Tissue Manipulation

Chen, J., Kobayashi, E., Sakuma, I., & Tomii, N. (2024) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2024.3466074 · Cited by 8

A Case Study for Enhancing Maintenance of Cyber-Physical Systems With Digital Twin

Liu, J., Vatn, J., & Yin, S. (2024) · IEEE Transactions on Industrial Cyber-Physical Systems · doi:10.1109/ticps.2024.3485038 · Cited by 8

Fine-grained decomposition of complex digital twin systems driven by semantic-topological-dynamic associations

Wen, X., Sun, Y., Liu, S., Bao, J., & Zhang, D. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.10.023 · Cited by 8

A novel production execution logic model with directed service node pairs and encapsulated service cells for efficient scheduling and simulation in discrete manufacturing shops

Liu, M., Xie, J., Zhang, J., Qin, S., Ding, G., & Chen, H. (2025) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2025.103017 · Cited by 8

Research on data mapping and fusion method of ship production workshop based on digital twins

Wang, L., Chen, J., Zhang, Y., Tian, Y., Li, Z., & Wang, C. (2024) · Measurement and Control · doi:10.1177/00202940241236088 · Cited by 7

Virtual tomography as a novel method for segmenting machining process phases with the use of machine learning-supported measurement

Mazurkiewicz, D., Sobecki, P., Żabiński, T., & Piecuch, G. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.123945 · Cited by 7

Digital Twin Construction Method for Monitoring Operation Status of Building Machine Jacking Operation

Zou, Y., Wang, Z., Pan, H., Liao, F., Tu, W., & Sun, Z. (2024) · Buildings · doi:10.3390/buildings14082318 · Cited by 7

A prediction model of gear radial composite deviation based on digital twin mesh

Wang, Y., Wang, G., Xu, H., Liu, J., & Wang, Z. (2024) · Measurement · doi:10.1016/j.measurement.2024.115619 · Cited by 7

Evaluating the use of grey-box system identification for digital twins in manufacturing automation

Brennan, R. W., & Lesage, J. (2024) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2024.2386980 · Cited by 7

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

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

Fang, X., Wang, H., Liu, G., Tian, X., Ding, G., & Zhang, H. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-09632-z · Cited by 135

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

On the Notion of Digital Twins: A Modeling Perspective

Teki̇nerdoğan, B. (2022) · Systems · doi:10.3390/systems11010015 · Cited by 42