Condition assessment and long-term structural health monitoring of aging reinforced concrete water reservoirs
Date
2026
Authors
Nazari, Nasrin
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Abstract
Structural Health Monitoring (SHM) is increasingly required to ensure the safety, serviceability, and longevity of aging reinforced concrete (RC) infrastructure. According to the Canadian Infrastructure report card 2019, many municipal water reservoirs in Canada were constructed several decades ago and are approaching or exceeding their original design service life, while continuing to operate under changing environmental and loading conditions. Traditional condition assessment approaches, primarily based on visual inspection and occasional destructive testing, are limited in their ability to provide continuous, objective, and system-level insight into structural performance.
This thesis presents an integrated framework for condition assessment and long-term monitoring of reservoirs, with a specific focus on an in-service reinforced concrete potable water reservoir located at Mount Tolmie in Victoria, British Columbia. The proposed framework combines finite element modeling (FEM), non-destructive evaluation (NDE) methods, wireless sensor-based SHM, and Building Information Modeling (BIM) to develop an information-rich digital representation of the structure. Seismic response analysis with fluid–structure interaction is first conducted to identify structurally critical regions and guide sensor placement. A comprehensive, coring-free multi-NDE assessment which includes infrared thermography, rebound hammer, ultrasonic pulse velocity, ground penetrating radar, and non-invasive corrosion rate and electrical resistivity measurements, is then performed over multiple field campaigns to evaluate spatial patterns, repeatability, and temporal changes in material condition. Long-term sensor data, including linear displacement, tilt gauges, and acceleration measurements, are subsequently analyzed to characterize the structure’s behavior under operational conditions and to establish data-driven thresholds for anomaly detection. The novelty of this work lies in the first application of non-invasive corrosion rate and electrical resistivity measurements using the iCOR device for the condition assessment of an operating reinforced concrete potable water reservoir, together with the use of multi-year, coring-free NDE results to inform structural condition assessment and the development of a BIM-based digital twin framework in which long-term, low-frequency SHM sensor data are continuously linked to the 3D model to enable near real-time monitoring and automated anomaly alerts for stakeholders.
The outcomes of this research demonstrate the feasibility of integrating heterogeneous inspection, testing, and monitoring data into a unified digital twin model for reinforced concrete water reservoirs, supporting identification of critical zones and informed decision-making for maintenance and future monitoring of aging water infrastructure.
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Keywords
Structural Health Monitoring