BRIDGE DIGITAL TWINS AND THE ROLE OF LOAD TESTING IN LIFECYCLE MANAGEMENT

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Bridge digital twins represent a transformative approach in bridge engineering, enabling the creation of virtual replicas that mirror the physical structure throughout its lifecycle. Originating from advancements in other industries, digital twin technology integrates real-world data with computational models to support monitoring, analysis, and decision-making. In bridge applications, digital twins promise enhanced safety, predictive maintenance, and optimized asset management, making them a critical component of next-generation infrastructure systems.

Concept of Digital Twins in Bridge Engineering

A bridge digital twin combines geometric information, material properties, sensor data, and operational conditions into a unified virtual model. By linking physical bridges with Building Information Modeling (BIM) and Finite Element (FE) models, engineers can simulate structural behavior under varying loads and environmental influences. This integration enables continuous assessment of performance, allowing infrastructure owners to move from reactive maintenance toward proactive management strategies.

Load Testing as the Birth of the Digital Twin

The study emphasizes that bridge load testing marks the “birth” of the digital twin. During this phase, controlled loads are applied to the actual bridge to measure structural responses such as deflection, strain, and vibration. This process provides high-quality empirical data that cannot be obtained at later stages with the same reliability. Consequently, load testing offers a unique opportunity to calibrate digital models so that they accurately represent real structural behavior.

Updating BIM and Finite Element Models

Accurate digital twins depend on well-calibrated BIM and FE models. Load test data enables engineers to validate assumptions regarding stiffness, boundary conditions, and material properties. By updating these models with measured responses, discrepancies between theoretical predictions and actual performance can be minimized. This calibration ensures that the digital twin remains a trustworthy tool for structural analysis, safety evaluation, and performance forecasting.

Application During the Operational Phase

Once established, the digital twin supports the bridge throughout its service life. During operation, it can be continuously updated with monitoring data to detect anomalies, assess damage, and evaluate the effects of aging or environmental changes. This capability allows engineers to predict future performance, schedule maintenance efficiently, and extend service life while maintaining safety standards. Thus, the digital twin becomes an active management system rather than a static model.

Case Study of a Post-Tensioned Concrete Bridge

The concept is demonstrated through modeling and load testing of a real post-tensioned concrete bridge. Post-tensioning introduces complex stress distributions and structural behavior, making accurate modeling particularly important. The case study illustrates how field measurements obtained during testing can refine computational models and establish a reliable digital twin. This example confirms the feasibility and practical value of integrating testing, modeling, and digital technologies in modern bridge engineering.

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