A study on aged and cured behaviour of carbon based self-sensing concrete sensors for structural health monitoring purposes

Smart self-sensing concrete sensors (SSCSs) have been proposed as an alternative to conventional sensors for structural health monitoring (SHM) applications. However, their long-term reliability remains a major concern due to changes in electrical and mechanical properties caused by cement hydration and environmental aging. This study experimentally investigates the influence of curing and accelerated aging on the performance of SSCSs fabricated using carbon nanotubes (CNT), carbon nanofibers (CNF), and nano carbon black (NCB), applied individually and in hybrid combinations. A total of twenty-seven mix designs were developed and subjected to 28 days of standard curing followed by cyclic temperature and humidity exposure in an environmental chamber to simulate harsh aging conditions. The specimens were tested under cyclic compressive loading at stress levels of 10, 20, and 30 MPa. Electrical resistance (ER), electrical resistivity, piezoresistive response, gauge factor (GF), and compressive strength (CS) were evaluated and compared between cured and aged states. The results indicate that aging leads to a reduction in CS of up to 15%. Hybrid mixtures, particularly CNT–NCB systems, exhibited superior stability, with minimal resistivity variation of 4–7% after aging. These mixtures also demonstrated significantly enhanced strain sensitivity, achieving a maximum GF of 14.9, which is approximately 92% higher than that of corresponding single-filler systems. Linear regression analysis revealed a strong and statistically significant correlation between CS change and ER change (r = 0.83, p < 0.001), indicating that electrical response is highly sensitive to aging-induced mechanical degradation and highlighting the need for sensor recalibration in long-term applications. Finally, three mixtures achieve SNR values exceeding 20 dB, indicating high-quality signal clarity suitable for SHM applications as CNT1CNF2-Cured, CNT2CB2-Aged and CNT3CB3-Cured.