Digital Twin Technology in Structural Engineering: Concept, Applications, and Role in Assessing Structural Performance Prepared by: Asst. Prof. Dr. Mayada Waheed Falah Head of the Department of Civil Engineering, Al-Mustaqbal University Introduction With the rapid advancement of digital transformation technologies, the Digital Twin has become a promising technology in structural engineering. It makes it possible to create a digital model that simulates the real structure and is continuously linked to its operational data. The importance of this technology lies in its ability to integrate engineering modeling with sensors and data analytics. This helps engineers monitor the condition of buildings, evaluate their structural performance, and predict potential problems before they develop into major damage. What Is a Digital Twin? A Digital Twin is a dynamic virtual representation of a real structure, updated using data collected from the building, such as vibrations, strains, displacements, and temperatures. It differs from a conventional three-dimensional model: it does not merely display the shape and dimensions of the building, but links the digital model to physical reality and allows the expected structural behavior to be compared with the behavior measured in the field. How Is It Used in Structural Performance Assessment? A digital twin system relies on a set of integrated technologies. Its workflow can be explained through the following stages: Creating the digital model: Preparing an engineering model of the building using Building Information Modeling (BIM) and linking it to the structural analysis model. Collecting field data: Installing vibration, strain, displacement, and temperature sensors at suitable locations on the structure. Transmitting data and updating the model: Using Internet of Things (IoT) technologies to transmit readings to the digital platform and update the state of the model. Analysis and evaluation: Comparing actual data with the numerical analysis results obtained from Finite Element Method (FEM) software, in order to detect abnormal changes in the structural response. Prediction and decision-making: Using artificial intelligence algorithms and data analytics to identify damage indicators and estimate the need for inspection, maintenance, or rehabilitation. Key Engineering Applications and Benefits Digital twins can be employed to monitor concrete buildings, bridges, and strategically important structures. Their main benefits include: Early detection of changes in structural behavior and potential cracking. Monitoring the response to vibrations and operational loads. Supporting the condition assessment of old and damaged structures. Improving maintenance planning and reducing unnecessary inspections. Supporting rehabilitation decisions and extending the service life of structures. Providing engineering information that helps manage structures more efficiently. Challenges and Implementation Requirements Despite the great potential of this technology, its application faces challenges related to the cost of sensors and digital infrastructure, data accuracy, calibration of numerical models, integration of BIM and structural analysis software, as well as information security and data protection. Moreover, the digital model is not a substitute for engineering inspection and field testing; its results must be continuously verified to ensure the reliability of the assessment and the decisions based on it. Conclusion The Digital Twin represents a qualitative leap in structure management and structural performance assessment by linking the real building, the virtual model, and field data. Integrating this technology with artificial intelligence and the Internet of Things is expected to contribute to developing more efficient systems for monitoring structures, predicting damage, and improving maintenance decisions, thereby enhancing the safety and sustainability of buildings in the long term.