TY - JOUR
T1 - Crack sensing in reinforced concrete beams and reinforced concrete pipes based on self-sensing cementitious sensors array
AU - Yu, Xianming
AU - Yao, Yao
N1 - Publisher Copyright:
© 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
PY - 2025/2
Y1 - 2025/2
N2 - To enable the smart monitoring of crack sensing in reinforced concrete structures using self-sensing cementitious sensors (SSCSs), this study quantified crack information based on changes in the electrical signals of SSCS. The location of cracks was evaluated based on changes in the electrical signals of SSCS. Following this, for the first time, a crack sensing was conducted by embedding an SSCS array into the reinforced concrete pipes. Based on external load tests, both failure tests and cyclic loading tests were conducted on reinforced concrete pipes. The empirical model for crack width was established based on the fractional change in peak electrical resistivity (FCRP) and the external load amplitude. The experimental results indicated: (1) the farther the crack was from the SSCS, the smaller the influence on the electrical signal changes of the SSCS. Therefore, the distance of the crack from the SSCS could be estimated by analyzing the changes in the fractional change in electrical resistivity (FCR); (2) for reinforced concrete pipes with existing cracks, both the FCRP and the residual FCR of the SSCS increased as the crack width and the amplitude of cyclic loading increased. These parameters could serve as indicators to determine whether a specific section of the concrete pipe has developed cracks; (3) an empirical model for crack width was developed based on the FCRP and the load amplitude. The proposed empirical model could effectively reflect the crack width in the concrete pipes by using the FCRP values from the SSCS array and the external load amplitude. This study presents a novel method for leakage monitoring in underground concrete pipes using an SSCS array, laying the foundation for their future application in underground concrete pipes.
AB - To enable the smart monitoring of crack sensing in reinforced concrete structures using self-sensing cementitious sensors (SSCSs), this study quantified crack information based on changes in the electrical signals of SSCS. The location of cracks was evaluated based on changes in the electrical signals of SSCS. Following this, for the first time, a crack sensing was conducted by embedding an SSCS array into the reinforced concrete pipes. Based on external load tests, both failure tests and cyclic loading tests were conducted on reinforced concrete pipes. The empirical model for crack width was established based on the fractional change in peak electrical resistivity (FCRP) and the external load amplitude. The experimental results indicated: (1) the farther the crack was from the SSCS, the smaller the influence on the electrical signal changes of the SSCS. Therefore, the distance of the crack from the SSCS could be estimated by analyzing the changes in the fractional change in electrical resistivity (FCR); (2) for reinforced concrete pipes with existing cracks, both the FCRP and the residual FCR of the SSCS increased as the crack width and the amplitude of cyclic loading increased. These parameters could serve as indicators to determine whether a specific section of the concrete pipe has developed cracks; (3) an empirical model for crack width was developed based on the FCRP and the load amplitude. The proposed empirical model could effectively reflect the crack width in the concrete pipes by using the FCRP values from the SSCS array and the external load amplitude. This study presents a novel method for leakage monitoring in underground concrete pipes using an SSCS array, laying the foundation for their future application in underground concrete pipes.
KW - crack sensing
KW - crack width
KW - external load amplitude
KW - fractional change in peak electrical resistivity
KW - self-sensing cementitious sensors
UR - http://www.scopus.com/inward/record.url?scp=85214678919&partnerID=8YFLogxK
U2 - 10.1088/1361-665X/ada3a9
DO - 10.1088/1361-665X/ada3a9
M3 - 文章
AN - SCOPUS:85214678919
SN - 0964-1726
VL - 34
JO - Smart Materials and Structures
JF - Smart Materials and Structures
IS - 2
M1 - 025014
ER -