In recent decades, assessing the performance of existing structures has become increasingly crucial, especially as many post-war structures approach the end of their design lifespan. Among these, prestressed concrete bridges are particularly concerning because they are inherently vulnerable to deterioration caused by time-dependent prestress losses. Recent inspections of prestressed concrete bridges with internally grouted tendons have uncovered hidden defects beneath a seemingly intact and robust exterior, raising concerns about their structural integrity. Notable bridge collapses, including the Koror–Babeldaob Bridge (1996), Nanfang’ao Bridge (2019), the Polcevera Viaduct (Morandi bridge, 2018) and Carola Bridge (2024) highlight the critical need for accurately assessing the structural condition of aging bridges. These cases underscore vulnerabilities in prestressing systems and underline key gaps in understanding degradation mechanisms, long-term performance, and failure factors in prestressed concrete structures. Conventional investigation techniques and visual inspections often fail to capture the true condition of these structures, necessitating specialized evaluation methods. As a result, there is a pressing need for reliable, user-friendly, and nondestructive techniques to assess their structural performance throughout their life cycle. Such assessments play a vital role in early diagnostics, helping to prevent cracking and deflections that could jeopardize a bridge’s structural integrity and safety. A major challenge in evaluating the structural performance of existing prestressed concrete bridges is assessing the time-dependent loss of prestress. This loss serves as both an indicator and a warning sign of potential structural deterioration. However, accurately measuring prestress loss is difficult due to uncertainties in material properties, environmental conditions, and long-term degradation processes. Simplified code-conforming models fail to account for the combined effects of environmental wear and fatigue, leading to discrepancies between measured and predicted prestress losses.

This study examines various testing methods for estimating residual prestress, highlighting their features and experimental approaches through a case study of the Kalix Bridge, a 66-year-old prestressed box-girder bridge in northern Sweden. This bridge posed unique challenges due to the complexity of its prestress system, the non-homogenous concrete curing process induced by due to multiple construction stages and the long-term deformations at the pendulum joint associated with creep. A numerical model was developed and calibrated using proof-loading test data and material characterization from extracted concrete cores. This updated model was later used to calculate residual prestress, which was then compared with predictions from standard formulations. Advanced probabilistic methods, including Bayesian updating and time-dependent reliability analysis, were also employed to refine residual prestress estimations and improve longterm reliability assessments. These methods allowed for the probabilistic analysis of uncertainties in estimating the service life of bridges, particularly when updating prestress levels retrieved through testing. By incorporating uncertainties related to material properties, environmental conditions, and degradation processes, these approaches enhance the accuracy of predictions about how long a bridge can remain serviceable after prestress updates. This refined approach provided valuable insights for optimizing maintenance strategies and ensuring extended service life and durability of prestressed concrete structures.