Actual Prestress Force Detection of Tendons in Prestressed Beams Based on Static Responses Using Genetic Algorithm
نویسندگان
1 دانشجوی دکتری، دانشکده مهندسی عمران، دانشگاه تربیت دبیر شهید رجائئ، تهران، ایران
2 استاد، دانشکده مهندسی عمران، دانشگاه تربیت دبیر شهید رجائئ، تهران، ایران
3 دانشیار، دانشکده مهندسی عمران، دانشگاه تفرش، تفرش، ایران.
doi
10.22065/jsce.2025.502521.3639چکیده
Researchers' attention has recently been focused to the measurement and tracking of prestressing force in the tendons of prestressed concrete (PC) constructions. Older structures need non-destructive testing techniques to evaluate these forces, even if modern structures are fitted with sensors to monitor prestress losses. This work presents a new approach that uses static displacement data under experimental loads to determine the real prestress force in the tendons of a prestressed concrete beam. This approach offers a more economical alternative by doing away with the requirement for destructive tests or pre-installed sensors. A genetic algorithm (GA) is created to precisely calculate the prestress force of tendons. Laboratory testing shows that the proposed method can detect prestress losses with excellent accuracy, even in the presence of intentional measurement mistakes of up to 10%.Researchers' attention has recently been focused to the measurement and tracking of prestressing force in the tendons of prestressed concrete (PC) constructions. Older structures need non-destructive testing techniques to evaluate these forces, even if modern structures are fitted with sensors to monitor prestress losses. This work presents a new approach that uses static displacement data under experimental loads to determine the real prestress force in the tendons of a prestressed concrete beam. This approach offers a more economical alternative by doing away with the requirement for destructive tests or pre-installed sensors. A genetic algorithm (GA) is created to precisely calculate the prestress force of tendons. Laboratory testing shows that the proposed method can detect prestress losses with excellent accuracy, even in the presence of intentional measurement mistakes of up to 10%.