Structural assessment of rehabilitated culverts under momentary loads using vision-based measurements and model calibration

Abstract

This study leverages visualization techniques and model updating to evaluate previously unknown in-situ conditions, both before and after rehabilitation using a cementitious spray-applied pipe liner (SAPL) on a culvert. Full-scale field load tests are conducting using non-contact, vision-based measurements to accurately quantify deformations due to static and dynamic loads for the two conditions: 1) unlined (before rehabilitation) and 2) lined (after rehabilitation) to characterize the in-situ structural response of the culvert before and after the SAPL application. Using digital image correlation (DIC) techniques, field measurements captured deformations along the culvert and were used to calibrate a finite element (FE) model to account for the existing state of material properties and soil conditions, often unknown when evaluating existing structures. The vision-based approach coupled with model updating enables the visualization and calibration of multiple points, minimizing unintended consequences of assumptions in modeling structures. Field tests and calibrated FE analyses confirmed that the lined culvert exhibited increased ring stiffness, improved resistance to dynamic load effects, and enhanced structural integrity. These improvements resulted in reduced deflections, beam-on-elastic-foundation behavior with dampened responses to varying load magnitudes, and more uniform strain distribution under both static and dynamic loads. The integration of DIC with model updating establishes a robust methodology for evaluating structures and refining numerical models. This study highlights the importance of combining advanced DIC techniques and FE modeling to better understand in-situ behavior, especially at full-scale, that can inform rehabilitation strategies, especially for deteriorated infrastructure