Enabling Real-Time Mechanical Analysis in Digital Twin Systems: A Study on Multi-Source Heterogeneous Data Fusion via Midas Civil Integration

The Digital Twin (DT) model within a Digital Twin System (DTS) serves as a real-time digital representation of its corresponding physical entity. It is a dynamic, interconnected model that enables real-time optimization in its application environment, allowing for the simulation, monitoring, evaluation, and control of the physical counterpart’s state and behavior while facilitating data-driven decision-making. In engineering practice, most scholars focus on data visualization and twin system construction. However, a complete digital twin system not only requires numerical representation of the real-time state of the physical entity but also sometimes requires real-time mechanical behavior analysis of the physical entity. Thus, a robust mechanical analysis module becomes essential within the DTS framework. Integrating a general-purpose mechanical analysis platform into the DTS offers an effective solution, thereby necessitating the development of novel fusion techniques for multi-source heterogeneous data. This study takes the integration of the Midas Civil mechanical analysis platform with a digital twin system as an example. By utilizing the API provided by Midas Civil, we develop a synchronization technique for virtual-physical systems, capable of handling and modeling multi-source heterogeneous data. This enables real-time mechanical computation and analysis within the DTS, facilitating the dynamic updating and aggregation of both simulation data from mechanical analysis and monitoring data from the physical entity. Consequently, the digital twin system can predict mechanical behaviors in the virtual domain, providing a more accurate representation of the real-world physical system’s state and dynamics.

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Publication Details

Journal
Buildings
Published
2025-11-23
DOI
https://doi.org/10.3390/buildings15234228
Primary Topic
Digital Transformation in Industry
Type
article
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Enabling Real-Time Mechanical Analysis in Digital Twin Systems: A Study on Multi-Source Heterogeneous Data Fusion via Midas Civil Integration

Zhanghong Liu, Peng Hu, Dezhi Hong, M. Chen et al.
Buildings
Digital Transformation in Industry
article

Enabling Real-Time Mechanical Analysis in Digital Twin Systems: A Study on Multi-Source Heterogeneous Data Fusion via Midas Civil Integration

Zhanghong Liu, Peng Hu, Dezhi Hong, M. Chen, Guquan Song
article en

Abstract

The Digital Twin (DT) model within a Digital Twin System (DTS) serves as a real-time digital representation of its corresponding physical entity. It is a dynamic, interconnected model that enables real-time optimization in its application environment, allowing for the simulation, monitoring, evaluation, and control of the physical counterpart’s state and behavior while facilitating data-driven decision-making. In engineering practice, most scholars focus on data visualization and twin system construction. However, a complete digital twin system not only requires numerical representation of the real-time state of the physical entity but also sometimes requires real-time mechanical behavior analysis of the physical entity. Thus, a robust mechanical analysis module becomes essential within the DTS framework. Integrating a general-purpose mechanical analysis platform into the DTS offers an effective solution, thereby necessitating the development of novel fusion techniques for multi-source heterogeneous data. This study takes the integration of the Midas Civil mechanical analysis platform with a digital twin system as an example. By utilizing the API provided by Midas Civil, we develop a synchronization technique for virtual-physical systems, capable of handling and modeling multi-source heterogeneous data. This enables real-time mechanical computation and analysis within the DTS, facilitating the dynamic updating and aggregation of both simulation data from mechanical analysis and monitoring data from the physical entity. Consequently, the digital twin system can predict mechanical behaviors in the virtual domain, providing a more accurate representation of the real-world physical system’s state and dynamics.

BuildingsVol. 15(23)
Nanchang University (CN), Education Department of Jiangxi Province (CN), Detection Limit (United States) (US)
Openalex Percentile: Top 51%
Digital Transformation in Industry
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