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

MetaD-DT: A Reference Architecture Enabling Digital Twin Development for Complex Engineering Equipment

Gao, H., Wang, F., Zhao, T., & Gu, Y. (2025) · Electronics · doi:10.3390/electronics15010038 · Cited by 1

Harnessing the Power of Simulation in Supply Chain Digital Twins

Köksalmış, E. (2025) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-032-08147-6_3 · Cited by 1

Digital Twin Framework for In-Service Crack Monitoring and Fatigue Prognosis in Metallic Aerospace Structures

Naderi, S., Pan, Y., Giannakeas, I. N., Khodaei, Z. S., & Aliabadi, M. H. (2026) · Procedia Structural Integrity · doi:10.1016/j.prostr.2026.02.008 · Cited by 1

Digital twin‐based error motion monitoring and prediction method for aerostatic spindle

Chen, G., Tang, S., Jiang, Y., Zhou, D., & Tan, D. (2026) · Chinese Journal of Mechanical Engineering · doi:10.1016/j.cjme.2025.100016 · Cited by 1

AI- and ML-driven intelligent design of digital twins

Manasa, R., Navya, K., Keshavamurthy, R., Madhura, R., & Kumar, N. M. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-27388-9.00011-8 · Cited by 1

Constructed by multiple on-machine inspection: intelligent machining system driven by digital twin

Zhang, Y., Wan, N., Zeng, Z., Li, X., Zheng, Z., Sun, H., & Zhou, X. (2026) · International Journal of Production Research · doi:10.1080/00207543.2026.2651391 · Cited by 1

Identifying and characterising uncertainty in digital twin engineering

Tiali, B. E. B., Creff, S., Kallel, A., & Anwer, N. (2026) · Digital Twin · doi:10.1080/27525783.2026.2668886 · Cited by 1

Digital Twin-Enabled Robust Parallel Control of Construction Engineering Equipment Under Uncertainty

Chen, R., Xu, H., Zhang, L., Rong, J., Wei, C., Chang, H., & Zhang, H. (2026) · Buildings · doi:10.3390/buildings16101982 · Cited by 1

Real-time sensing digital twin for aerospace structural health monitoring

Fiore, F. D., Ariyaratnam, S., Ermacora, M., & Mainini, L. (2026) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-026-04324-8 · Cited by 1

Digital Twins: A Computational Realization of the Scientific Method in Dynamical Systems

Emmert‐Streib, F. (2026) · Machine Learning and Knowledge Extraction · doi:10.3390/make8060159 · Cited by 1

OPERAND: An innovative multi-physics approach to individual aircraft tracking

Levinski, O., Carrese, R., Conser, D., Marzocca, P., & McDonald, M. (2019) · Cited by 1

Digital twin based computerized numerical control machine tool virtual prototype design

Hu, T., Kong, T., Ye, Y., Tao, F., & Nee, A. Y. C. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818918-4.00009-9 · Cited by 1

A Real-Time Digital Twin Model Dynamically Modifying Method Based on Consistency Measurement Model

Song, W., Li, T., Zhou, J., & Xu, L. H. (2021) · International Conference on Electronics Technology (ICET) · doi:10.1109/icet51757.2021.9450970 · Cited by 1

Application analysis of digital twin model in horizontal directional drilling

Bi, D., & Huo, Y. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2030/1/012066 · Cited by 1

Digital twin-driven cutting tool service

Sun, H., & Yao, Y. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91300-3.00010-3 · Cited by 1

Analysis of Geometric Deformations in Off-Road Vehicles Using Dynamic Reduction-Based Virtual Models

Maulik, S., Awasthi, A., Riordan, D., & Walsh, J. L. (2022) · Irish Signals and Systems Conference · doi:10.1109/issc55427.2022.9826165 · Cited by 1

Temperature Variation Modelling of an Assembled Three-Storey Structure

Bonney, M. S., & Wagg, D. (2022) · Conference proceedings of the Society for Experimental Mechanics · doi:10.1007/978-3-031-05449-5_3 · Cited by 1

Efficiency and Reliability Enhancement of High Pressure Die Casting Process Through a Digital Twin

Torres, P., Abio, A., Busqué, R., Brígido, A., Cruz, S., da Silva, M., & Bonada, F. (2022) · International Conference of the Catalan Association for Artificial Intelligence · doi:10.3233/faia220331 · Cited by 4

Research on Fund Management Mechanism Based on Digital Twin Technology

Wang, J., Liu, H., Li, J., Song, X., & Li, S. (2022) · International Conference on Education, Knowledge and Information Management (ICEKIM) · doi:10.1109/icekim55072.2022.00200 · Cited by 1

Digital Twin Lifecycle: Core Challenges and Open Issues

Abdoune, F., Nouiri, M., Cardin, O., & Castagna, P. (2023) · Studies in computational intelligence · doi:10.1007/978-3-031-24291-5_13 · Cited by 1

Digital Twins: Modelling Languages Comparison

Wahid, A., Zhu, J., Mauceri, S., Li, L., & Liu, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25891-6_13 · Cited by 1

Leveraging Full-Field Deformation Measurements in Computational Modeling of Damage

Schlenker, S., Tekerek, E., & Kontsos, A. (2023) · Journal of Nondestructive Evaluation Diagnostics and Prognostics of Engineering Systems · doi:10.1115/1.4062291 · Cited by 1

Digital twin

Agarwal, S., Singh, V. P., Ganguly, P., Munnangi, P., Collins, C., Sarker, S., Shenoi, J., Heston, S., Pandita, S., Pandita, T. K., et al. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-824010-6.00051-4 · Cited by 1

Digital Twin shop-floor: A Complex System-oriented Construction Method and Operation Mechanism

Liu, H., Zhang, J., Cheng, Y., Tao, F., & Qi, Q. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.03.083 · Cited by 1

Copula-Based Multi-structure Damage Co-diagnosis and Prognosis for the Fleet Maintenance Digital Twin

Zhou, X., Sbarufatti, C., Giglio, M., & Dong, L. (2023) · Mechanisms and machine science · doi:10.1007/978-3-031-42515-8_95 · Cited by 1

Industry 5.0 and National Development Plans

ALPASLAN, B., & Çelik, S. (2023) · The Eurasia Proceedings of Science Technology Engineering and Mathematics · doi:10.55549/epstem.1406267 · Cited by 1

How Visual Data Is Revolutionizing the Industry World

Nassif, J., Tekli, J., & Kamradt, M. (2024) · Springer eBooks · doi:10.1007/978-3-031-47560-3_4 · Cited by 1

Enhancing Digital Twins With Wireless Sensor Networks

Akila, T., Bilgaiyan, P., Subramaniam, S., & Venkateswaran, R. (2024) · Advances in business information systems and analytics book series · doi:10.4018/979-8-3693-1818-8.ch009 · Cited by 1

Digitale Zwillinge und Datenvernetzung als Grundlage für KI-Anwendungen im Bauwesen

Schimanski, C. P., Sandau, M., Zinke, T., & Schumann, R. (2024) · Springer eBooks · doi:10.1007/978-3-658-42796-2_3 · Cited by 1

A Review of Multi-source Heterogeneous Twin Data Processing Methods in Traffic Scenes

Yan, Y. (2024) · International Journal of Computer Science and Information Technology · doi:10.62051/ijcsit.v3n1.15 · Cited by 1

Research on The Development Trend of Digital Twin Industry Based on Multi-source Data

Nan, M., Yuxiong, Z., Cai, C., Ying, C., Xiaolin, L., Fan, Y., Liu, M., & Jingtao, Z. (2024) · IEEE International Conference on Electronics Information and Emergency Communication · doi:10.1109/iceiec61773.2024.10561799 · Cited by 1

Decision-Oriented Digital Twin Framework of Naval Battlefield and Key Technologies

Wang, B.-Y., Sun, Q., & Jiang, B. (2024) · International Symposium on Intelligent Unmanned Systems and Artificial Intelligence (SIUSAI) · doi:10.1145/3669721.3669729 · Cited by 1

Design and Implementation of the Regolith Sampling Digital Twin System for Operation and Analysis

An, L., Li, L., Miao, Y., Liu, X., Miao, Q., & Feng, X. (2024) · IEEE China Conference on System Simulation Technology and its Applications (CCSSTA) · doi:10.1109/ccssta62096.2024.10691861 · Cited by 1

Simulation Cloning for Digital Twins: A Scalable Approach

Yoginath, S. B., Shukla, P., Seal, S. K., & Nutaro, J. J. (2024) · Annual Modeling and Simulation Conference (ANNSIM) · doi:10.23919/annsim61499.2024.10732459 · Cited by 1

Demagnetization Prediction Method of Permanent Magnet Synchronous Motor Based on Digital Twin Model

Xu, S., Zhang, Z., Huang, Y., & Han, T. (2024) · China Automation Congress (CAC) · doi:10.1109/cac63892.2024.10865195 · Cited by 1

Artificial Intelligence Meets Digital Twin: The AI Asset Administration Shell

Reichardt, M., Gundall, M., Buch, D., Stricker, P. D., & Schotten, H. D. (2024) · IEEE Industrial Electronics Society Annual On-Line Conference (ONCON) · doi:10.1109/oncon62778.2024.10931277 · Cited by 1

Graphics and Data Visualisation

Chen, Y., & Huang, L. J. (2025) · Springer eBooks · doi:10.1007/978-981-97-8788-3_8 · Cited by 1

Underground Gas Storage Digital Twin for Depleted Reservoirs Based on Mechanistic Models and Digital Technologies

Wang, B., Liu, T., Liu, H., Ouyang, M., Guo, G., Wang, B., Pan, Y., Yue, C., Gogoi, U., Ravoof, A., et al. (2025) · Offshore Technology Conference · doi:10.4043/35539-ms · Cited by 1

Discussion on the Application of Digital Twins in the Wear of Parts

Xie, F., & Zhou, Z. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-981-15-3753-0_15 · Cited by 1

Research on Digital Twin for Building Structure Health Monitoring

Jincheng, S. (2021) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-030-92632-8_71 · Cited by 1

Registration of NDE Data to CAD

Holland, S. D., & Krishnamurthy, A. (2022) · Springer eBooks · doi:10.1007/978-3-030-73206-6_5 · Cited by 1

Prediction of Health Status and Fault of Electrical Equipment Based on the Concept of Digital Twin

Yu, X., Huang, J., Liu, S., Lü, G., & Yuan, J. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-1870-4_126 · Cited by 1

Practical Modeling and Simulation Techniques for Power Electronics

Ishikawa, H. (2022) · International Power Electronics Conference (IPEC) · doi:10.23919/ipec-himeji2022-ecce53331.2022.9806884 · Cited by 1

Novel Data Acquisition Utilising a Flask Python Digital Twin Operational Platform

Wang, R., & Bonney, M. S. (2012) · Conference proceedings of the Society for Experimental Mechanics · doi:10.1007/978-3-031-05405-1_2 · Cited by 1

A Temperature Monitoring Method for Press Pack IGBT Based on Digital Twin

Zhou, B., Li, H., Lai, W., & Yao, R. (2022) · IEEE International Power Electronics and Application Conference and Exposition (PEAC) · doi:10.1109/peac56338.2022.9959546 · Cited by 1

Second-Year Review of the NSF-DoD REU Site: HYPER

Gordon, A. P., & Kauffman, J. L. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--42076 · Cited by 1

Assessing and mitigating vulnerability chains in model-centric acquisition programs

Reid, J. B. (2018) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 1

Real time prediction of probabilistic crack growth in complex structures with reduced-order models: Towards a Digital Twin of a helicopter componentPreprint

Zhou, X., He, S., Dong, L., & Atluri, S. N. (2021) · arXiv (Cornell University) · Cited by 1

Digital twins for collaborative robots: a case studyPreprint

Malik, A. A., & Brem, A. (2020) · arXiv (Cornell University) · Cited by 1

Digital-twin Healthcare: A Gateway to Future Medicine (Preprint)Preprint

Li, Z. (2022) · doi:10.2196/preprints.36867 · Cited by 1

Multi-Level Interval Credible Model Updating Method for Complex Structures with Limited Experimental SamplesPreprint

Wang, X., & Cao, Y. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4504174 · Cited by 1

Digital Twins for Built Environment. A Review on Key EnablersPreprint

Piras, G., & Agostinelli, S. (2023) · Preprints.org · doi:10.20944/preprints202307.1183.v1 · Cited by 1

BASIC TECHNOLOGIES AND MODELS FOR IMPLEMENTATION OF INDUSTRY 4.0

(2023) · doi:10.5644/pi2023.209.00 · Cited by 1

Object motion tracking in the NDE laboratory by random sample iterative closest point

Radkowski, R., Wehr, D., Gregory, E. D., & Holland, S. D. (2016) · AIP conference proceedings · doi:10.1063/1.4940571

Tracking composite material damage evolution using Bayesian filtering and flash thermography data

Gregory, E. D., & Holland, S. D. (2016) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2222420

A Concept of Semantic Description for e-Production Systems in Manufacturing

Klein, M., Jazdi, N., & Weyrich, M. (2017) · Procedia CIRP · doi:10.1016/j.procir.2016.06.055

Remote and dynamic assessment of reliability in electromechanical actuator systems

Brim, M., & Cale, J. L. (2018) · IEEE International Systems Conference (SysCon) · doi:10.1109/syscon.2018.8369537

Uncertainty Quantification and Confidence Assessment in Time-Dependent, Multidisciplinary Simulations

DeCarlo, E. C. (2017)

PASSIVE OBJECT DETECTION VIA AN ARTIFICIAL LATERAL LINE AND A 2-D VISCOUS FLOW MODEL

Clark, J. H. (2018) · doi:10.23860/thesis-clark-jack-2018

A Practical Approach to Manufacturing Execution Systems at Bosch AvP

Lopes, M. J., Almeida, D., & Cardoso, F. J. A. (2018) · Advances in logistics, operations, and management science book series · doi:10.4018/978-1-5225-4936-9.ch010

Closure to “Discussion of ‘Dynamic Modeling and Projection-Based Reduction Methods for Bladed Disks With Nonlinear Frictional and Intermittent Contact Interfaces’” (Wallaschek, J., Willeke, S., and Panning-von Scheidt, L., ASME Appl. Mech. Rev., 2019, 71(5), p. 055502)

Mitra, M., & Epureanu, B. I. (2019) · Applied Mechanics Reviews · doi:10.1115/1.4044803

Test campaign design for model uncertainty reduction

McLemore, K. (2012)

Desenvolvendo uma plataforma com Gêmeo Digital baseada na web para análise de braço robótico

Oliveira, D. F. G. D., & Dantas, R. R. (2018) · Escola Potiguar de Computação e suas Aplicações (EPOCA) · doi:10.5753/epoca.2018.13450

Advance Estimate-based Traffic State Synchronization for Parallel Testing

Qiu, W., Shangguan, W., Cai, B., Chai, L., & Chen, J. (2020) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc45102.2020.9294748

General Boundary Identification Through Surface Pressure Measurements on a 2-D Foil

Clark, J. H., & Dahl, J. M. (2021) · Notes on numerical fluid mechanics and multidisciplinary design · doi:10.1007/978-3-030-55594-8_47

Toltén Bridge’s response under extreme conditions analysis through numerical models

Real, J. I., Union, A. G. K., Achurra, S., Ribes-Llario, F., & Silva, G. C. (2021) · Journal of Vibroengineering · doi:10.21595/jve.2020.21246

Real-time prediction of probabilistic crack growth with a reduced-order digital twin of a helicopter componentPreprint

Zhou, X., He, S., Dong, L., & Atluri, S. N. (2021) · arXiv (Cornell University)

Design of ABOM Reconfiguration System Based on Digital Twin

Zou, J., Liu, X., & Xu, S. (2021) · IEEE International Conference on Software Engineering and Service Science (ICSESS) · doi:10.1109/icsess52187.2021.9522304

Registration of NDE Data to CAD

Holland, S. D., & Krishnamurthy, A. (2021) · Springer eBooks · doi:10.1007/978-3-030-48200-8_5-1

Analysis, Quantification and Evaluation of Uncertainty

Schaeffner, M., Abele, E., Anderl, R., Bölling, C., Brötz, J., Dietrich, I., Feldmann, R., Gehb, C. M., Geßner, F., Hartig, J., et al. (2021) · Springer tracts in mechanical engineering · doi:10.1007/978-3-030-78354-9_4

Testing and Model Updating for Geometrically Nonlinear Hypersonic Vehicle Assemblies Using Nonlinear Normal Modes

Allen, M. S., Kwarta, M., & Damme, C. I. V. (2020)

Changing Manufacturing Landscape: From a Factory to a Network

Michelsen, K.-E., Collan, M., Savolainen, J., & Ritala, P. (2021) · Handbook of Smart Materials, Technologies, and Devices · doi:10.1007/978-3-030-58675-1_2-1 · Cited by 2

An Initial Concept for an Error-Based Digital Twin Framework for Dynamics Applications

Edington, L. J., Dervilis, N., Gardner, P. A., & Wagg, D. (2021) · Conference proceedings of the Society for Experimental Mechanics · doi:10.1007/978-3-030-77348-9_13

Field Programmable Gate Array (FPGA) Based Digital Twin of Discrete Dynamic System

Ganguli, R., & Prasad, V. D. (2022) · AIAA SciTech Forum · doi:10.2514/6.2022-0721

Power Grid Disaster Loss Information Fusion Analysis and Prediction Technology

Xu, M., Yang, J., Yang, J., Lin, P., Tang, S., Li, N., Hou, Z., He, Z., Wang, G., Wang, H., et al. (2021) · International Conference on Data Science and Business Analytics (ICDSBA) · doi:10.1109/icdsba53075.2021.00026

Issues of Using Digital Twins of Gas Turbine Units at Their Facilities

Блинов, В. Л., Богданец, С. В., & Zubkov, I. S. (2022) · Lecture notes in mechanical engineering · doi:10.1007/978-981-16-9376-2_15

Research on Engine Simulation and Assembly Based on Computer Digital Twin

Lin, M., He, W., & Shan, L. (2021) · International Conference on Artificial Intelligence and Advanced Manufacture (AIAM) · doi:10.1145/3495018.3495032

Digital Twins and Federated Learning for Smart Cities and Their Applications

Shanker, S. (2022) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-6684-3733-9.ch009

Methodology for Designing Embedded Real-Time Electrothermal Models in PYNQ Z1 System on Chip

Baron, J. M., García, A. J., Vergara, F., Arnaiz, P. J., & Vasić, M. (2022) · IEEE Design Methodologies Conference (DMC) · doi:10.1109/dmc55175.2022.9906475

Digital Twin Software Overview with Text Mining Techniques

Kolev, G., Lozeva, V., & Koleva, E. G. (2022) · International Conference Automatics and Informatics (ICAI) · doi:10.1109/icai55857.2022.9959990

Changing Manufacturing Landscape: From a Factory to a Network

Michelsen, K.-E., Collan, M., Savolainen, J., & Ritala, P. (2022) · Springer eBooks · doi:10.1007/978-3-030-84205-5_2

Research on the Construction Method of Digital Twins of Complex Products

Xia, K., Zhang, W., Gao, L., Fang, C., Jiang, X., & Hu, C. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-9198-1_12

Construction of the optical-mechanical installation and calibration process technology on the basis of the digital twin

Chou, X.-Q., Xiao-yan, L. I., Shi-fa, K. A. N. G., & Yang, F. (2023) · Advanced Optical Manufacturing Technologies and Applications and International Forum of Young Scientists on Advanced Optical Manufacturing (AOMTA and YSAOM) · doi:10.1117/12.2655281

Consistency Analysis of Digital Twin Model used for Typical Robotic Pick-and-Place Process

Tang, Y., Zhang, J., Xu, W., Liu, J., Ji, Z., & Hu, Y. (2022) · IEEE Conference on Industrial Electronics and Applications (ICIEA) · doi:10.1109/iciea54703.2022.10006101

Multi-Fidelity Data Aggregation for Information Fusion in Simulation and Experiment

Chen, J., Meng, C., Gao, Y., & Liu, Y. (2023) · AIAA SciTech Forum · doi:10.2514/6.2023-2545

Supporting Computer Domains

Santucci, J.-F., Capocchi, L., Ören, T. I., Mittal, S., Li, B. H., Li, Z., Lin, T. Y., Laili, Y., & Szabo, C. (2023) · Simulation foundations, methods and applications · doi:10.1007/978-3-031-11085-6_11

Trends, Desirable Features, and Challenges

Li, B. H., Fan, W., & Li, Z. (2023) · Simulation foundations, methods and applications · doi:10.1007/978-3-031-11085-6_19

Digital Twin Background

Viola, J., & Chen, Y. (2023) · Synthesis lectures on engineering, science, and technology · doi:10.1007/978-3-031-22140-8_1

Digital Twin of Micro-Milling Process for Micro-Tool Wear MonitoringPreprint

Christiand, C., Kiswanto, G., & Baskoro, A. S. (2023) · Research Square · doi:10.21203/rs.3.rs-2708150/v1

A product-level digital twin modelling approach for the full lifecyclePreprint

Jiang, L., Su, S., Chu, C., Chen, C., & Wang, W. (2023) · Research Square · doi:10.21203/rs.3.rs-3203699/v1

Application of Digital Twin Technology in Storage Management of Power Equipment

Wang, L., Hao, H., Wang, L., & Zhang, C. (2023) · International Conference on Information Economy, Data Modeling and Cloud Computing (ICIDC) · doi:10.4108/eai.2-6-2023.2334628

A digital twin-based analysis method to assess geometric variations for parts in batch production

Zhi, J., Cao, Y., Li, T., Anwer, N., Liu, F., Jiang, X., & Yang, J. (2023) · Digital Twin · doi:10.12688/digitaltwin.17863.1

Operationalizing digital twins in agriculture with machine learning

Pylianidis, C. (2023) · doi:10.18174/591164

Real-Time Monitoring System of Spray-Painting Robot Based on Five-Dimension Digital Twin Model

Wang, W., Zhao, J., Chen, Z., & Zi, B. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-6504-5_15

Digital twin-based quality inspection system for low-voltage current transformer

Chen, H., Tong, T., Zhen, H., Wu, Y., & Yu, L. (2023) · International Symposium on Sensor Technology and Control (ISSTC) · doi:10.1109/isstc59603.2023.10280961

Comment on wes-2023-143

(2023) · doi:10.5194/wes-2023-143-rc1

Comment on wes-2023-143

(2023) · doi:10.5194/wes-2023-143-rc2

Research on the Digital Twin System of the Centring Process for High-Precision Lens

Chen, Z., Li, Y., Ma, G., Wang, Y., & Qin, B. (2023) · Applied Sciences · doi:10.3390/app132412988

Life prediction for aircraft structure based on Bayesian inference: towards a digital twin ecosystem

Wang, T., Liu, Z., Liao, M., & Mrad, N. (2020) · Annual Conference of the PHM Society · doi:10.36001/phmconf.2020.v12i1.1261 · Cited by 13

The Airframe Digital Twin: Some Challenges to Realization

Tuegel, E. (2012) · 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA · doi:10.2514/6.2012-1812 · Cited by 255

Aircraft Structural Design and Life-Cycle Assessment through Digital Twins

Tavares, S. M. O., Ribeiro, J. A., Ribeiro, B. A., & de Castro, P. M. S. T. (2024) · Designs · doi:10.3390/designs8020029 · Cited by 36

Research on Real Time Prediction Method of Aircraft Flight Load Based on Digital Twin Technology

Lu, C., Zong, N., & Shi, X. (2024) · Lecture notes in electrical engineering · doi:10.1007/978-981-97-4010-9_50 · Cited by 1

Aircraft Lifecycle Digital Twin for Defects Prediction Accuracy Improvement

Tyncherov, T., & Rozkova, L. (2020) · Lecture notes in networks and systems · doi:10.1007/978-3-030-44610-9_6 · Cited by 9